A morphometric analysis of vegetation patterns in dryland ecosystems

NASA Astrophysics Data System (ADS)

Mander, Luke; Dekker, Stefan C.; Li, Mao; Mio, Washington; Punyasena, Surangi W.; Lenton, Timothy M.

2017-02-01

Vegetation in dryland ecosystems often forms remarkable spatial patterns. These range from regular bands of vegetation alternating with bare ground, to vegetated spots and labyrinths, to regular gaps of bare ground within an otherwise continuous expanse of vegetation. It has been suggested that spotted vegetation patterns could indicate that collapse into a bare ground state is imminent, and the morphology of spatial vegetation patterns, therefore, represents a potentially valuable source of information on the proximity of regime shifts in dryland ecosystems. In this paper, we have developed quantitative methods to characterize the morphology of spatial patterns in dryland vegetation. Our approach is based on algorithmic techniques that have been used to classify pollen grains on the basis of textural patterning, and involves constructing feature vectors to quantify the shapes formed by vegetation patterns. We have analysed images of patterned vegetation produced by a computational model and a small set of satellite images from South Kordofan (South Sudan), which illustrates that our methods are applicable to both simulated and real-world data. Our approach provides a means of quantifying patterns that are frequently described using qualitative terminology, and could be used to classify vegetation patterns in large-scale satellite surveys of dryland ecosystems.

Inhomogeneity Based Characterization of Distribution Patterns on the Plasma Membrane

PubMed Central

Paparelli, Laura; Corthout, Nikky; Wakefield, Devin L.; Sannerud, Ragna; Jovanovic-Talisman, Tijana; Annaert, Wim; Munck, Sebastian

2016-01-01

Cell surface protein and lipid molecules are organized in various patterns: randomly, along gradients, or clustered when segregated into discrete micro- and nano-domains. Their distribution is tightly coupled to events such as polarization, endocytosis, and intracellular signaling, but challenging to quantify using traditional techniques. Here we present a novel approach to quantify the distribution of plasma membrane proteins and lipids. This approach describes spatial patterns in degrees of inhomogeneity and incorporates an intensity-based correction to analyze images with a wide range of resolutions; we have termed it Quantitative Analysis of the Spatial distributions in Images using Mosaic segmentation and Dual parameter Optimization in Histograms (QuASIMoDOH). We tested its applicability using simulated microscopy images and images acquired by widefield microscopy, total internal reflection microscopy, structured illumination microscopy, and photoactivated localization microscopy. We validated QuASIMoDOH, successfully quantifying the distribution of protein and lipid molecules detected with several labeling techniques, in different cell model systems. We also used this method to characterize the reorganization of cell surface lipids in response to disrupted endosomal trafficking and to detect dynamic changes in the global and local organization of epidermal growth factor receptors across the cell surface. Our findings demonstrate that QuASIMoDOH can be used to assess protein and lipid patterns, quantifying distribution changes and spatial reorganization at the cell surface. An ImageJ/Fiji plugin of this analysis tool is provided. PMID:27603951

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

ERIC Educational Resources Information Center

Riby, Leigh M.; Orme, Elizabeth

2013-01-01

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

Spatial patterns of ergot and quantification of sclerotia in perennial ryegrass seed fields

USDA-ARS?s Scientific Manuscript database

Ergot, caused by Claviceps purpurea, is a major disease of perennial ryegrass grass grown for seed in eastern Oregon. The objective of this research was to quantify and describe the spatial patterns of ergot severity in each of three 50 ha commercial fields of perennial ryegrass grown for seed in 20...

Spatial patterns of development drive water use

USGS Publications Warehouse

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

2018-01-01

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

Spatial Patterns of Development Drive Water Use

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

Historical forest structure, composition, and spatial pattern in dry conifer forests of the western Blue Mountains, Oregon

Treesearch

Derek J. Churchill; Gunnar C. Carnwath; Andrew J. Larson; Sean A. Jeronimo

2017-01-01

In frequent-fire forests of the interior Western United States, historical (prefire suppression) conditions are often used as a reference to set management objectives, guide prescriptions, and monitor treatment effectiveness. We quantified the historical size, density, composition, and spatial patterns of dry mixed-conifer forests in the Blue Mountains of Oregon to...

Range and variation in landscape patch dynamics: Implications for ecosystem management

Treesearch

Robert E. Keane; Janice L. Garner; Casey Teske; Cathy Stewart; Paul Hessburg

2001-01-01

Northern Rocky Mountain landscape patterns are shaped primarily by fire and succession, and conversely, these vegetation patterns influence burning patterns and plant colonization processes. Historical range and variability (HRV) of landscape pattern can be quantified from three sources: (1) historical chronosequences, (2) spatial series, and (3) simulated...

Processing and statistical analysis of soil-root images

NASA Astrophysics Data System (ADS)

Razavi, Bahar S.; Hoang, Duyen; Kuzyakov, Yakov

2016-04-01

Importance of the hotspots such as rhizosphere, the small soil volume that surrounds and is influenced by plant roots, calls for spatially explicit methods to visualize distribution of microbial activities in this active site (Kuzyakov and Blagodatskaya, 2015). Zymography technique has previously been adapted to visualize the spatial dynamics of enzyme activities in rhizosphere (Spohn and Kuzyakov, 2014). Following further developing of soil zymography -to obtain a higher resolution of enzyme activities - we aimed to 1) quantify the images, 2) determine whether the pattern (e.g. distribution of hotspots in space) is clumped (aggregated) or regular (dispersed). To this end, we incubated soil-filled rhizoboxes with maize Zea mays L. and without maize (control box) for two weeks. In situ soil zymography was applied to visualize enzymatic activity of β-glucosidase and phosphatase at soil-root interface. Spatial resolution of fluorescent images was improved by direct application of a substrate saturated membrane to the soil-root system. Furthermore, we applied "spatial point pattern analysis" to determine whether the pattern (e.g. distribution of hotspots in space) is clumped (aggregated) or regular (dispersed). Our results demonstrated that distribution of hotspots at rhizosphere is clumped (aggregated) compare to control box without plant which showed regular (dispersed) pattern. These patterns were similar in all three replicates and for both enzymes. We conclude that improved zymography is promising in situ technique to identify, analyze, visualize and quantify spatial distribution of enzyme activities in the rhizosphere. Moreover, such different patterns should be considered in assessments and modeling of rhizosphere extension and the corresponding effects on soil properties and functions. Key words: rhizosphere, spatial point pattern, enzyme activity, zymography, maize.

Environmental drivers and spatial dependency in wildfire ignition patterns of northwestern Patagonia.

PubMed

Mundo, Ignacio A; Wiegand, Thorsten; Kanagaraj, Rajapandian; Kitzberger, Thomas

2013-07-15

Fire management requires an understanding of the spatial characteristics of fire ignition patterns and how anthropogenic and natural factors influence ignition patterns across space. In this study we take advantage of a recent fire ignition database (855 points) to conduct a comprehensive analysis of the spatial pattern of fire ignitions in the western area of Neuquén province (57,649 km(2)), Argentina, for the 1992-2008 period. The objectives of our study were to better understand the spatial pattern and the environmental drivers of the fire ignitions, with the ultimate aim of supporting fire management. We conducted our analyses on three different levels: statistical "habitat" modelling of fire ignition (natural, anthropogenic, and all causes) based on an information theoretic approach to test several competing hypotheses on environmental drivers (i.e. topographic, climatic, anthropogenic, land cover, and their combinations); spatial point pattern analysis to quantify additional spatial autocorrelation in the ignition patterns; and quantification of potential spatial associations between fires of different causes relative to towns using a novel implementation of the independence null model. Anthropogenic fire ignitions were best predicted by the most complex habitat model including all groups of variables, whereas natural ignitions were best predicted by topographic, climatic and land-cover variables. The spatial pattern of all ignitions showed considerable clustering at intermediate distances (<40 km) not captured by the probability of fire ignitions predicted by the habitat model. There was a strong (linear) and highly significant increase in the density of fire ignitions with decreasing distance to towns (<5 km), but fire ignitions of natural and anthropogenic causes were statistically independent. A two-dimensional habitat model that quantifies differences between ignition probabilities of natural and anthropogenic causes allows fire managers to delineate target areas for consideration of major preventive treatments, strategic placement of fuel treatments, and forecasting of fire ignition. The techniques presented here can be widely applied to situations where a spatial point pattern is jointly influenced by extrinsic environmental factors and intrinsic point interactions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Describing spatial pattern in stream networks: A practical approach

USGS Publications Warehouse

Ganio, L.M.; Torgersen, C.E.; Gresswell, R.E.

2005-01-01

The shape and configuration of branched networks influence ecological patterns and processes. Recent investigations of network influences in riverine ecology stress the need to quantify spatial structure not only in a two-dimensional plane, but also in networks. An initial step in understanding data from stream networks is discerning non-random patterns along the network. On the other hand, data collected in the network may be spatially autocorrelated and thus not suitable for traditional statistical analyses. Here we provide a method that uses commercially available software to construct an empirical variogram to describe spatial pattern in the relative abundance of coastal cutthroat trout in headwater stream networks. We describe the mathematical and practical considerations involved in calculating a variogram using a non-Euclidean distance metric to incorporate the network pathway structure in the analysis of spatial variability, and use a non-parametric technique to ascertain if the pattern in the empirical variogram is non-random.

A geostatistical approach for describing spatial pattern in stream networks

USGS Publications Warehouse

Ganio, L.M.; Torgersen, C.E.; Gresswell, R.E.

2005-01-01

The shape and configuration of branched networks influence ecological patterns and processes. Recent investigations of network influences in riverine ecology stress the need to quantify spatial structure not only in a two-dimensional plane, but also in networks. An initial step in understanding data from stream networks is discerning non-random patterns along the network. On the other hand, data collected in the network may be spatially autocorrelated and thus not suitable for traditional statistical analyses. Here we provide a method that uses commercially available software to construct an empirical variogram to describe spatial pattern in the relative abundance of coastal cutthroat trout in headwater stream networks. We describe the mathematical and practical considerations involved in calculating a variogram using a non-Euclidean distance metric to incorporate the network pathway structure in the analysis of spatial variability, and use a non-parametric technique to ascertain if the pattern in the empirical variogram is non-random.

FracPaQ: a MATLAB™ Toolbox for the Quantification of Fracture Patterns

NASA Astrophysics Data System (ADS)

Healy, D.; Rizzo, R. E.; Cornwell, D. G.; Timms, N.; Farrell, N. J.; Watkins, H.; Gomez-Rivas, E.; Smith, M.

2016-12-01

The patterns of fractures in deformed rocks are rarely uniform or random. Fracture orientations, sizes, shapes and spatial distributions often exhibit some kind of order. In detail, there may be relationships among the different fracture attributes e.g. small fractures dominated by one orientation, larger fractures by another. These relationships are important because the mechanical (e.g. strength, anisotropy) and transport (e.g. fluids, heat) properties of rock depend on these fracture patterns and fracture attributes. This presentation describes an open source toolbox to quantify fracture patterns, including distributions in fracture attributes and their spatial variation. Software has been developed to quantify fracture patterns from 2-D digital images, such as thin section micrographs, geological maps, outcrop or aerial photographs or satellite images. The toolbox comprises a suite of MATLAB™ scripts based on published quantitative methods for the analysis of fracture attributes: orientations, lengths, intensity, density and connectivity. An estimate of permeability in 2-D is made using a parallel plate model. The software provides an objective and consistent methodology for quantifying fracture patterns and their variations in 2-D across a wide range of length scales. Our current focus for the application of the software is on quantifying the fracture patterns in and around fault zones. There is a large body of published work on the quantification of relatively simple joint patterns, but fault zones present a bigger, and arguably more important, challenge. The method presented is inherently scale independent, and a key task will be to analyse and integrate quantitative fracture pattern data from micro- to macro-scales. Planned future releases will incorporate multi-scale analyses based on a wavelet method to look for scale transitions, and combining fracture traces from multiple 2-D images to derive the statistically equivalent 3-D fracture pattern.

Habitat history improves prediction of biodiversity in rainforest fauna

PubMed Central

Graham, Catherine H.; Moritz, Craig; Williams, Stephen E.

2006-01-01

Patterns of biological diversity should be interpreted in light of both contemporary and historical influences; however, to date, most attempts to explain diversity patterns have largely ignored history or have been unable to quantify the influence of historical processes. The historical effects on patterns of diversity have been hypothesized to be most important for taxonomic groups with poor dispersal abilities. We quantified the relative stability of rainforests over the late Quaternary period by modeling rainforest expansion and contraction in 21 biogeographic subregions in northeast Australia across four time periods. We demonstrate that historical habitat stability can be as important, and in endemic low-dispersal taxa even more important, than current habitat area in explaining spatial patterns of species richness. In contrast, patterns of endemic species richness for taxa with high dispersal capacity are best predicted by using current environmental parameters. We also show that contemporary patterns of species turnover across the region are best explained by historical patterns of habitat connectivity. These results clearly demonstrate that spatially explicit analyses of the historical processes of persistence and colonization are both effective and necessary for understanding observed patterns of biodiversity. PMID:16407139

Characterizing forest fragments in boreal, temperate, and tropical ecosystems

Treesearch

Arjan J. H. Meddens; Andrew T. Hudak; Jeffrey S. Evans; William A. Gould; Grizelle Gonzalez

2008-01-01

An increased ability to analyze landscapes in a spatial manner through the use of remote sensing leads to improved capabilities for quantifying human-induced forest fragmentation. Developments of spatially explicit methods in landscape analyses are emerging. In this paper, the image delineation software program eCognition and the spatial pattern analysis program...

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

Treesearch

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

2015-01-01

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

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.

ESTUARINE AND SCALAR PATTERNS OF INVASION IN THE SOFT-BOTTOM BENTHIC COMMUNITIES OF THE SAN FRANCISCO ESTUARY

EPA Science Inventory

The spatial patterns of nonindigenous species in seven subtidal soft-bottom communities in the San Francisco Estuary were quantified. Sixty nonindigenous species were found out of the 533 taxa enumerated (11%). Patterns of invasion across the communities were evaluated using a ...

Measuring forest landscape patterns in the Cascade Range of Oregon, USA

NASA Technical Reports Server (NTRS)

Ripple, William J.; Bradshaw, G. A.; Spies, Thomas A.

1995-01-01

This paper describes the use of a set of spatial statistics to quantify the landscape pattern caused by the patchwork of clearcuts made over a 15-year period in the western Cascades of Oregon. Fifteen areas were selected at random to represent a diversity of landscape fragmentation patterns. Managed forest stands (patches) were digitized and analyzed to produce both tabular and mapped information describing patch size, shape, abundance and spacing, and matrix characteristics of a given area. In addition, a GIS fragmentation index was developed which was found to be sensitive to patch abundance and to the spatial distribution of patches. Use of the GIS-derived index provides an automated method of determining the level of forest fragmentation and can be used to facilitate spatial analysis of the landscape for later coordination with field and remotely sensed data. A comparison of the spatial statistics calculated for the two years indicates an increase in forest fragmentation as characterized by an increase in mean patch abundance and a decrease in interpatch distance, amount of interior natural forest habitat, and the GIS fragmentation index. Such statistics capable of quantifying patch shape and spatial distribution may prove important in the evaluation of the changing character of interior and edge habitats for wildlife.

Quantifying Spatial Genetic Structuring in Mesophotic Populations of the Precious Coral Corallium rubrum

PubMed Central

Costantini, Federica; Carlesi, Lorenzo; Abbiati, Marco

2013-01-01

While shallow water red coral populations have been overharvested in the past, nowadays, commercial harvesting shifted its pressure on mesophotic organisms. An understanding of red coral population structure, particularly larval dispersal patterns and connectivity among harvested populations is paramount to the viability of the species. In order to determine patterns of genetic spatial structuring of deep water Corallium rubrum populations, for the first time, colonies found between 58–118 m depth within the Tyrrhenian Sea were collected and analyzed. Ten microsatellite loci and two regions of mitochondrial DNA (mtMSH and mtC) were used to quantify patterns of genetic diversity within populations and to define population structuring at spatial scales from tens of metres to hundreds of kilometres. Microsatellites showed heterozygote deficiencies in all populations. Significant levels of genetic differentiation were observed at all investigated spatial scales, suggesting that populations are likely to be isolated. This differentiation may by the results of biological interactions, occurring within a small spatial scale and/or abiotic factors acting at a larger scale. Mitochondrial markers revealed significant genetic structuring at spatial scales greater then 100 km showing the occurrence of a barrier to gene flow between northern and southern Tyrrhenian populations. These findings provide support for the establishment of marine protected areas in the deep sea and off-shore reefs, in order to effectively maintain genetic diversity of mesophotic red coral populations. PMID:23646109

Quantifying spatial genetic structuring in mesophotic populations of the precious coral Corallium rubrum.

PubMed

Costantini, Federica; Carlesi, Lorenzo; Abbiati, Marco

2013-01-01

While shallow water red coral populations have been overharvested in the past, nowadays, commercial harvesting shifted its pressure on mesophotic organisms. An understanding of red coral population structure, particularly larval dispersal patterns and connectivity among harvested populations is paramount to the viability of the species. In order to determine patterns of genetic spatial structuring of deep water Corallium rubrum populations, for the first time, colonies found between 58-118 m depth within the Tyrrhenian Sea were collected and analyzed. Ten microsatellite loci and two regions of mitochondrial DNA (mtMSH and mtC) were used to quantify patterns of genetic diversity within populations and to define population structuring at spatial scales from tens of metres to hundreds of kilometres. Microsatellites showed heterozygote deficiencies in all populations. Significant levels of genetic differentiation were observed at all investigated spatial scales, suggesting that populations are likely to be isolated. This differentiation may by the results of biological interactions, occurring within a small spatial scale and/or abiotic factors acting at a larger scale. Mitochondrial markers revealed significant genetic structuring at spatial scales greater then 100 km showing the occurrence of a barrier to gene flow between northern and southern Tyrrhenian populations. These findings provide support for the establishment of marine protected areas in the deep sea and off-shore reefs, in order to effectively maintain genetic diversity of mesophotic red coral populations.

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

PubMed

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

2016-01-01

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

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

Treesearch

Bernard R. Parresol

2011-01-01

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

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

PubMed Central

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

2018-01-01

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

Monitoring urbanization and its implications in a mega city from space: spatiotemporal patterns and its indicators.

PubMed

Ramachandra, T V; Bharath, A H; Sowmyashree, M V

2015-01-15

Rapid and invasive urbanization has been associated with depletion of natural resources (vegetation and water resources), which in turn deteriorates the landscape structure and conditions in the local environment. Rapid increase in population due to the migration from rural areas is one of the critical issues of the urban growth. Urbanisation in India is drastically changing the land cover and often resulting in the sprawl. The sprawl regions often lack basic amenities such as treated water supply, sanitation, etc. This necessitates regular monitoring and understanding of the rate of urban development in order to ensure the sustenance of natural resources .Urban sprawl is the extent of urbanization which leads to the development of urban forms with the destruction of ecology and natural landforms. The rate of change of land use and extent of urban sprawl can be efficiently visualized and modelled with the help of geoinformatics. The knowledge of urban area, especially the growth magnitude, shape geometry, and spatial pattern is essential to understand the growth and characteristics of urbanization process. Urban pattern, shape and growth can be quantified using spatial metrics. This communication quantifies the urbanisation and associated growth pattern in Delhi. Spatial data of four decades were analysed to understand land over and land use dynamics. Further the region was divided into 4 zones and into circles of 1 km incrementing radius to understand and quantify the local spatial changes. Results of the landscape metrics indicate that the urban center was highly aggregated and the outskirts and the buffer regions were in the verge of aggregating urban patches. Shannon's Entropy index clearly depicted the outgrowth of sprawl areas in different zones of Delhi. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cross-scale analysis of fire regimes

Treesearch

Donald A. Falk; Carol Miller; Donald McKenzie; Anne E. Black

2007-01-01

Cross-scale spatial and temporal perspectives are important for studying contagious landscape disturbances such as fire, which are controlled by myriad processes operating at different scales. We examine fire regimes in forests of western North America, focusing on how observed patterns of fire frequency change across spatial scales. To quantify changes in fire...

FRAGSTATS: spatial pattern analysis program for quantifying landscape structure.

Treesearch

Kevin McGarigal; Barbara J. Marks

1995-01-01

This report describes a program, FRAGSTATS, developed to quantify landscape structure. FRAGSTATS offers a comprehensive choice of landscape metrics and was designed to be as versatile as possible. The program is almost completely automated and thus requires little technical training. Two separate versions of FRAGSTATS exist: one for vector images and one for raster...

FracPaQ: a MATLAB™ toolbox for the quantification of fracture patterns

NASA Astrophysics Data System (ADS)

Healy, David; Rizzo, Roberto; Farrell, Natalie; Watkins, Hannah; Cornwell, David; Gomez-Rivas, Enrique; Timms, Nick

2017-04-01

The patterns of fractures in deformed rocks are rarely uniform or random. Fracture orientations, sizes, shapes and spatial distributions often exhibit some kind of order. In detail, there may be relationships among the different fracture attributes e.g. small fractures dominated by one orientation, larger fractures by another. These relationships are important because the mechanical (e.g. strength, anisotropy) and transport (e.g. fluids, heat) properties of rock depend on these fracture patterns and fracture attributes. This presentation describes an open source toolbox to quantify fracture patterns, including distributions in fracture attributes and their spatial variation. Software has been developed to quantify fracture patterns from 2-D digital images, such as thin section micrographs, geological maps, outcrop or aerial photographs or satellite images. The toolbox comprises a suite of MATLAB™ scripts based on published quantitative methods for the analysis of fracture attributes: orientations, lengths, intensity, density and connectivity. An estimate of permeability in 2-D is made using a parallel plate model. The software provides an objective and consistent methodology for quantifying fracture patterns and their variations in 2-D across a wide range of length scales. Our current focus for the application of the software is on quantifying crack and fracture patterns in and around fault zones. There is a large body of published work on the quantification of relatively simple joint patterns, but fault zones present a bigger, and arguably more important, challenge. The methods presented are inherently scale independent, and a key task will be to analyse and integrate quantitative fracture pattern data from micro- to macro-scales. New features in this release include multi-scale analyses based on a wavelet method to look for scale transitions, support for multi-colour traces in the input file processed as separate fracture sets, and combining fracture traces from multiple 2-D images to derive the statistically equivalent 3-D fracture pattern expressed as a 2nd rank crack tensor.

Spatial Uncertainty Modeling of Fuzzy Information in Images for Pattern Classification

PubMed Central

Pham, Tuan D.

2014-01-01

The modeling of the spatial distribution of image properties is important for many pattern recognition problems in science and engineering. Mathematical methods are needed to quantify the variability of this spatial distribution based on which a decision of classification can be made in an optimal sense. However, image properties are often subject to uncertainty due to both incomplete and imprecise information. This paper presents an integrated approach for estimating the spatial uncertainty of vagueness in images using the theory of geostatistics and the calculus of probability measures of fuzzy events. Such a model for the quantification of spatial uncertainty is utilized as a new image feature extraction method, based on which classifiers can be trained to perform the task of pattern recognition. Applications of the proposed algorithm to the classification of various types of image data suggest the usefulness of the proposed uncertainty modeling technique for texture feature extraction. PMID:25157744

HYDRAULIC REDISTRIBUTION OF SOIL WATER IN TWO OLD-GROWTH CONIFEROUS FORESTS: QUANTIFYING PATTERNS AND CONTROLS

EPA Science Inventory

Although hydraulic redistribution of soil water (HR) by roots is a widespread phenomenon, the processes governing spatial and temporal patterns of HR are not well understood. We incorporated soil/plant biophysical properties into a simple model based on Darcy's law to predict sea...

RipleyGUI: software for analyzing spatial patterns in 3D cell distributions

PubMed Central

Hansson, Kristin; Jafari-Mamaghani, Mehrdad; Krieger, Patrik

2013-01-01

The true revolution in the age of digital neuroanatomy is the ability to extensively quantify anatomical structures and thus investigate structure-function relationships in great detail. To facilitate the quantification of neuronal cell patterns we have developed RipleyGUI, a MATLAB-based software that can be used to detect patterns in the 3D distribution of cells. RipleyGUI uses Ripley's K-function to analyze spatial distributions. In addition the software contains statistical tools to determine quantitative statistical differences, and tools for spatial transformations that are useful for analyzing non-stationary point patterns. The software has a graphical user interface making it easy to use without programming experience, and an extensive user manual explaining the basic concepts underlying the different statistical tools used to analyze spatial point patterns. The described analysis tool can be used for determining the spatial organization of neurons that is important for a detailed study of structure-function relationships. For example, neocortex that can be subdivided into six layers based on cell density and cell types can also be analyzed in terms of organizational principles distinguishing the layers. PMID:23658544

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders.

PubMed

Tapia-McClung, Horacio; Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology.

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders

PubMed Central

Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology. PMID:27902724

Quantifying dispersal rates and distances in North American martens: a test of enriched isotope labeling

Treesearch

Jonathan N. Pauli; Winston P. Smith; Merav Ben-David

2012-01-01

Advances in the application of stable isotopes have allowed the quantitative evaluation of previously cryptic ecological processes. In particular, researchers have utilized the predictable spatial patterning in natural abundance of isotopes to better understand animal dispersal and migration. However, quantifying dispersal via natural abundance alone has proven to be...

Neural Representation of Spatial Topology in the Rodent Hippocampus

PubMed Central

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

2014-01-01

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

Measuring floodplain spatial patterns using continuous surface metrics at multiple scales

USGS Publications Warehouse

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

2015-01-01

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

Quantifying urban growth patterns in Hanoi using landscape expansion modes and time series spatial metrics.

PubMed

Nong, Duong H; Lepczyk, Christopher A; Miura, Tomoaki; Fox, Jefferson M

2018-01-01

Urbanization has been driven by various social, economic, and political factors around the world for centuries. Because urbanization continues unabated in many places, it is crucial to understand patterns of urbanization and their potential ecological and environmental impacts. Given this need, the objectives of our study were to quantify urban growth rates, growth modes, and resultant changes in the landscape pattern of urbanization in Hanoi, Vietnam from 1993 to 2010 and to evaluate the extent to which the process of urban growth in Hanoi conformed to the diffusion-coalescence theory. We analyzed the spatiotemporal patterns and dynamics of the built-up land in Hanoi using landscape expansion modes, spatial metrics, and a gradient approach. Urbanization was most pronounced in the periods of 2001-2006 and 2006-2010 at a distance of 10 to 35 km around the urban center. Over the 17 year period urban expansion in Hanoi was dominated by infilling and edge expansion growth modes. Our findings support the diffusion-coalescence theory of urbanization. The shift of the urban growth areas over time and the dynamic nature of the spatial metrics revealed important information about our understanding of the urban growth process and cycle. Furthermore, our findings can be used to evaluate urban planning policies and aid in urbanization issues in rapidly urbanizing countries.

Evidence for self-organization in determining spatial patterns of stream nutrients, despite primacy of the geomorphic template

PubMed Central

Dong, Xiaoli; Grimm, Nancy B.

2017-01-01

Nutrients in freshwater ecosystems are highly variable in space and time. Nevertheless, the variety of processes contributing to nutrient patchiness, and the wide range of spatial and temporal scales at which these processes operate, obfuscate how this spatial heterogeneity is generated. Here, we describe the spatial structure of stream nutrient concentration, quantify the relative importance of the physical template and biological processes, and detect and evaluate the role of self-organization in driving such patterns. We examined nutrient spatial patterns in Sycamore Creek, an intermittent desert stream in Arizona that experienced an ecosystem regime shift [from a gravel/algae-dominated to a vascular plant-dominated (hereafter, “wetland”) system] in 2000 when cattle grazing ceased. We conducted high-resolution nutrient surveys in surface water along a 10-km stream reach over four visits spanning 18 y (1995–2013) that represent different successional stages and prewetland stage vs. postwetland state. As expected, groundwater upwelling had a major influence on nutrient spatial patterns. However, self-organization realized by the mechanism of spatial feedbacks also was significant and intensified over ecosystem succession, as a resource (nitrogen) became increasingly limiting. By late succession, the effects of internal spatial feedbacks and groundwater upwelling were approximately equal in magnitude. Wetland establishment influenced nutrient spatial patterns only indirectly, by modifying the extent of surface water/groundwater exchange. This study illustrates that multiple mechanisms interact in a dynamic way to create spatial heterogeneity in riverine ecosystems, and provides a means to detect spatial self-organization against physical template heterogeneity as a dominant driver of spatial patterns. PMID:28559326

Evidence for self-organization in determining spatial patterns of stream nutrients, despite primacy of the geomorphic template.

PubMed

Dong, Xiaoli; Ruhí, Albert; Grimm, Nancy B

2017-06-13

Nutrients in freshwater ecosystems are highly variable in space and time. Nevertheless, the variety of processes contributing to nutrient patchiness, and the wide range of spatial and temporal scales at which these processes operate, obfuscate how this spatial heterogeneity is generated. Here, we describe the spatial structure of stream nutrient concentration, quantify the relative importance of the physical template and biological processes, and detect and evaluate the role of self-organization in driving such patterns. We examined nutrient spatial patterns in Sycamore Creek, an intermittent desert stream in Arizona that experienced an ecosystem regime shift [from a gravel/algae-dominated to a vascular plant-dominated (hereafter, "wetland") system] in 2000 when cattle grazing ceased. We conducted high-resolution nutrient surveys in surface water along a 10-km stream reach over four visits spanning 18 y (1995-2013) that represent different successional stages and prewetland stage vs. postwetland state. As expected, groundwater upwelling had a major influence on nutrient spatial patterns. However, self-organization realized by the mechanism of spatial feedbacks also was significant and intensified over ecosystem succession, as a resource (nitrogen) became increasingly limiting. By late succession, the effects of internal spatial feedbacks and groundwater upwelling were approximately equal in magnitude. Wetland establishment influenced nutrient spatial patterns only indirectly, by modifying the extent of surface water/groundwater exchange. This study illustrates that multiple mechanisms interact in a dynamic way to create spatial heterogeneity in riverine ecosystems, and provides a means to detect spatial self-organization against physical template heterogeneity as a dominant driver of spatial patterns.

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

USGS Publications Warehouse

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

2016-01-01

Floodplains can be viewed as complex adaptive systems (Levin, 1998) because they are comprised of many different biophysical components, such as morphological features, soil groups and vegetation communities as well as being sites of key biogeochemical processing (Stanford et al., 2005). Interactions and feedbacks among the biophysical components often result in additional phenomena occuring over a range of scales, often in the absence of any controlling factors (sensu Hallet, 1990). This emergence of new biophysical features and rates of processing can lead to alternative stable states which feed back into floodplain adaptive cycles (cf. Hughes, 1997; Stanford et al., 2005). Interactions between different biophysical components, feedbacks, self emergence and scale are all key properties of complex adaptive systems (Levin, 1998; Phillips, 2003; Murray et al., 2014) and therefore will influence the manner in which we study and view spatial patterns. Measuring the spatial patterns of floodplain biophysical components is a prerequisite to examining and understanding these ecosystems as complex adaptive systems. Elucidating relationships between pattern and process, which are intrinsically linked within floodplains (Ward et al., 2002), is dependent upon an understanding of spatial pattern. This knowledge can help river scientists determine the major drivers, controllers and responses of floodplain structure and function, as well as the consequences of altering those drivers and controllers (Hughes and Cass, 1997; Whited et al., 2007). Interactions and feedbacks between physical, chemical and biological components of floodplain ecosystems create and maintain a structurally diverse and dynamic template (Stanford et al., 2005). This template influences subsequent interactions between components that consequently affect system trajectories within floodplains (sensu Bak et al., 1988). Constructing and evaluating models used to predict floodplain ecosystem responses to natural and anthropogenic disturbances therefore require quantification of spatial pattern (Asselman and Middelkoop, 1995; Walling and He, 1998). Quantifying these patterns also provides insights into the spatial and temporal domains of structuring processes as well as enabling the detection of self-emergent phenomena, environmental constraints or anthropogenic interference (Turner et al., 1990; Holling, 1992; De Jager and Rohweder, 2012). Thus, quantifying spatial pattern is an important building block on which to examine floodplains as complex adaptive systems (Levin, 1998). Approaches to measuring spatial pattern in floodplains must be cognisant of scale, self-emergent phenomena, spatial organisation, and location. Fundamental problems may arise when patterns observed at a site or transect scale are scaled-up to infer processes and patterns over entire floodplain surfaces (Wiens, 2002; Thorp et al., 2008). Likewise, patterns observed over the entire spatial extent of a landscape can mask important variation and detail at finer scales (Riitters et al., 2002). Indeed, different patterns often emerge at different scales (Turner et al., 1990) because of hierarchical structuring processes (O'Neill et al., 1991). Categorising data into discrete, homogeneous and predefined spatial units at a particular scale (e.g. polygons) creates issues and errors associated with scale and subjective classification (McGarigal et al., 2009; Cushman et al., 2010). These include, loss of information within classified ‘patches’, as well as the ability to detect the emergence of new features that do not fit the original classification scheme. Many of these issues arise because floodplains are highly heterogeneous and have complex spatial organizations (Carbonneau et al., 2012; Legleiter, 2013). As a result, the scale and location at which measurements are made can influence the observed spatial patterns; and patterns may not be scale independent or applicable in different geomorp

Analysis of Alaskan burn severity patterns using remotely sensed data

USGS Publications Warehouse

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

2007-01-01

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

Evaluating methods to quantify spatial variation in the velocity of biological invasions

Treesearch

Clement Tisseuil; Aiko Gryspeirt; Renaud Lancelot; Maryline Pioz; Andrew Liebhold; Marius Gilbert

2016-01-01

Invading species rarely spread homogeneously through a landscape and invasion patterns typically display irregular frontal boundaries as the invasion progresses through space. Those irregular patterns are generally produced by local environmental factors that may slow or accelerate movement of the frontal boundary. While there is an abundant literature on species...

Space--time patterns during the establishmentof a nonindigenous species

Treesearch

Patrick C. Tobin

2007-01-01

Increasing rates of global trade and travel have the invariable consequence of an increase in the likelihood of nonindigenous species arrival, and some new arrivals are successful in establishing themselves. Quantifying the pattern of establishment of nonindigenous species across both spatial and temporal scales is paramount in early detection efforts, yet very...

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

PubMed Central

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

2016-01-01

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

Spatial arrangement of faults and opening-mode fractures

NASA Astrophysics Data System (ADS)

Laubach, S. E.; Lamarche, J.; Gauthier, B. D. M.; Dunne, W. M.; Sanderson, David J.

2018-03-01

Spatial arrangement is a fundamental characteristic of fracture arrays. The pattern of fault and opening-mode fracture positions in space defines structural heterogeneity and anisotropy in a rock volume, governs how faults and fractures affect fluid flow, and impacts our understanding of the initiation, propagation and interactions during the formation of fracture patterns. This special issue highlights recent progress with respect to characterizing and understanding the spatial arrangements of fault and fracture patterns, providing examples over a wide range of scales and structural settings. Five papers describe new methods and improvements of existing techniques to quantify spatial arrangement. One study unravels the time evolution of opening-mode fracture spatial arrangement, which are data needed to compare natural patterns with progressive fracture growth in kinematic and mechanical models. Three papers investigate the role of evolving diagenesis in localizing fractures by mechanical stratigraphy and nine discuss opening-mode fracture spatial arrangement. Two papers show the relevance of complex cluster patterns to unconventional reservoirs through examples of fractures in tight gas sandstone horizontal wells, and a study of fracture arrangement in shale. Four papers demonstrate the roles of folds in fracture localization and the development spatial patterns. One paper models along-fault friction and fluid pressure and their effects on fault-related fracture arrangement. Contributions address deformation band patterns in carbonate rocks and fault size and arrangement above a detachment fault. Three papers describe fault and fracture arrangements in basement terrains, and three document fracture patterns in shale. This collection of papers points toward improvement in field methods, continuing improvements in computer-based data analysis and creation of synthetic fracture patterns, and opportunities for further understanding fault and fracture attributes in the subsurface through coupled spatial, size, and pattern analysis.

Spatial uncertainty analysis: Propagation of interpolation errors in spatially distributed models

USGS Publications Warehouse

Phillips, D.L.; Marks, D.G.

1996-01-01

In simulation modelling, it is desirable to quantify model uncertainties and provide not only point estimates for output variables but confidence intervals as well. Spatially distributed physical and ecological process models are becoming widely used, with runs being made over a grid of points that represent the landscape. This requires input values at each grid point, which often have to be interpolated from irregularly scattered measurement sites, e.g., weather stations. Interpolation introduces spatially varying errors which propagate through the model We extended established uncertainty analysis methods to a spatial domain for quantifying spatial patterns of input variable interpolation errors and how they propagate through a model to affect the uncertainty of the model output. We applied this to a model of potential evapotranspiration (PET) as a demonstration. We modelled PET for three time periods in 1990 as a function of temperature, humidity, and wind on a 10-km grid across the U.S. portion of the Columbia River Basin. Temperature, humidity, and wind speed were interpolated using kriging from 700- 1000 supporting data points. Kriging standard deviations (SD) were used to quantify the spatially varying interpolation uncertainties. For each of 5693 grid points, 100 Monte Carlo simulations were done, using the kriged values of temperature, humidity, and wind, plus random error terms determined by the kriging SDs and the correlations of interpolation errors among the three variables. For the spring season example, kriging SDs averaged 2.6??C for temperature, 8.7% for relative humidity, and 0.38 m s-1 for wind. The resultant PET estimates had coefficients of variation (CVs) ranging from 14% to 27% for the 10-km grid cells. Maps of PET means and CVs showed the spatial patterns of PET with a measure of its uncertainty due to interpolation of the input variables. This methodology should be applicable to a variety of spatially distributed models using interpolated inputs.

Extended generalized recurrence plot quantification of complex circular patterns

NASA Astrophysics Data System (ADS)

Riedl, Maik; Marwan, Norbert; Kurths, Jürgen

2017-03-01

The generalized recurrence plot is a modern tool for quantification of complex spatial patterns. Its application spans the analysis of trabecular bone structures, Turing patterns, turbulent spatial plankton patterns, and fractals. Determinism is a central measure in this framework quantifying the level of regularity of spatial structures. We show by basic examples of fully regular patterns of different symmetries that this measure underestimates the orderliness of circular patterns resulting from rotational symmetries. We overcome this crucial problem by checking additional structural elements of the generalized recurrence plot which is demonstrated with the examples. Furthermore, we show the potential of the extended quantity of determinism applying it to more irregular circular patterns which are generated by the complex Ginzburg-Landau-equation and which can be often observed in real spatially extended dynamical systems. So, we are able to reconstruct the main separations of the system's parameter space analyzing single snapshots of the real part only, in contrast to the use of the original quantity. This ability of the proposed method promises also an improved description of other systems with complicated spatio-temporal dynamics typically occurring in fluid dynamics, climatology, biology, ecology, social sciences, etc.

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

USGS Publications Warehouse

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

2016-01-01

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

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.

Step selection techniques uncover the environmental predictors of space use patterns in flocks of Amazonian birds.

PubMed

Potts, Jonathan R; Mokross, Karl; Stouffer, Philip C; Lewis, Mark A

2014-12-01

Understanding the behavioral decisions behind animal movement and space use patterns is a key challenge for behavioral ecology. Tools to quantify these patterns from movement and animal-habitat interactions are vital for transforming ecology into a predictive science. This is particularly important in environments undergoing rapid anthropogenic changes, such as the Amazon rainforest, where animals face novel landscapes. Insectivorous bird flocks are key elements of avian biodiversity in the Amazonian ecosystem. Therefore, disentangling and quantifying the drivers behind their movement and space use patterns is of great importance for Amazonian conservation. We use a step selection function (SSF) approach to uncover environmental drivers behind movement choices. This is used to construct a mechanistic model, from which we derive predicted utilization distributions (home ranges) of flocks. We show that movement decisions are significantly influenced by canopy height and topography, but depletion and renewal of resources do not appear to affect movement significantly. We quantify the magnitude of these effects and demonstrate that they are helpful for understanding various heterogeneous aspects of space use. We compare our results to recent analytic derivations of space use, demonstrating that the analytic approximation is only accurate when assuming that there is no persistence in the animals' movement. Our model can be translated into other environments or hypothetical scenarios, such as those given by proposed future anthropogenic actions, to make predictions of spatial patterns in bird flocks. Furthermore, our approach is quite general, so could potentially be used to understand the drivers of movement and spatial patterns for a wide variety of animal communities.

Step selection techniques uncover the environmental predictors of space use patterns in flocks of Amazonian birds

PubMed Central

Potts, Jonathan R; Mokross, Karl; Stouffer, Philip C; Lewis, Mark A

2014-01-01

Understanding the behavioral decisions behind animal movement and space use patterns is a key challenge for behavioral ecology. Tools to quantify these patterns from movement and animal–habitat interactions are vital for transforming ecology into a predictive science. This is particularly important in environments undergoing rapid anthropogenic changes, such as the Amazon rainforest, where animals face novel landscapes. Insectivorous bird flocks are key elements of avian biodiversity in the Amazonian ecosystem. Therefore, disentangling and quantifying the drivers behind their movement and space use patterns is of great importance for Amazonian conservation. We use a step selection function (SSF) approach to uncover environmental drivers behind movement choices. This is used to construct a mechanistic model, from which we derive predicted utilization distributions (home ranges) of flocks. We show that movement decisions are significantly influenced by canopy height and topography, but depletion and renewal of resources do not appear to affect movement significantly. We quantify the magnitude of these effects and demonstrate that they are helpful for understanding various heterogeneous aspects of space use. We compare our results to recent analytic derivations of space use, demonstrating that the analytic approximation is only accurate when assuming that there is no persistence in the animals' movement. Our model can be translated into other environments or hypothetical scenarios, such as those given by proposed future anthropogenic actions, to make predictions of spatial patterns in bird flocks. Furthermore, our approach is quite general, so could potentially be used to understand the drivers of movement and spatial patterns for a wide variety of animal communities. PMID:25558353

Quantifying cross-border movements and migrations for guiding the strategic planning of malaria control and elimination

PubMed Central

2014-01-01

Background Identifying human and malaria parasite movements is important for control planning across all transmission intensities. Imported infections can reintroduce infections into areas previously free of infection, maintain ‘hotspots’ of transmission and import drug resistant strains, challenging national control programmes at a variety of temporal and spatial scales. Recent analyses based on mobile phone usage data have provided valuable insights into population and likely parasite movements within countries, but these data are restricted to sub-national analyses, leaving important cross-border movements neglected. Methods National census data were used to analyse and model cross-border migration and movement, using East Africa as an example. ‘Hotspots’ of origin-specific immigrants from neighbouring countries were identified for Kenya, Tanzania and Uganda. Populations of origin-specific migrants were compared to distance from origin country borders and population size at destination, and regression models were developed to quantify and compare differences in migration patterns. Migration data were then combined with existing spatially-referenced malaria data to compare the relative propensity for cross-border malaria movement in the region. Results The spatial patterns and processes for immigration were different between each origin and destination country pair. Hotspots of immigration, for example, were concentrated close to origin country borders for most immigrants to Tanzania, but for Kenya, a similar pattern was only seen for Tanzanian and Ugandan immigrants. Regression model fits also differed between specific migrant groups, with some migration patterns more dependent on population size at destination and distance travelled than others. With these differences between immigration patterns and processes, and heterogeneous transmission risk in East Africa and the surrounding region, propensities to import malaria infections also likely show substantial variations. Conclusion This was a first attempt to quantify and model cross-border movements relevant to malaria transmission and control. With national census available worldwide, this approach can be translated to construct a cross-border human and malaria movement evidence base for other malaria endemic countries. The outcomes of this study will feed into wider efforts to quantify and model human and malaria movements in endemic regions to facilitate improved intervention planning, resource allocation and collaborative policy decisions. PMID:24886389

Regional gradient analysis and spatial pattern of woody plant communities in Oregon forests.

Treesearch

J.L. Ohmann; T.A. Spies

1998-01-01

Knowledge of regional-scale patterns of ecological community structure, and of factors that control them, is largely conceptual. Regional- and local-scale factors associated with regional variation in community composition have not been quantified. We analyzed data on woody plant species abundance from 2443 field plots across natural and seminatural forests and...

Usability and potential of geostatistics for spatial discrimination of multiple sclerosis lesion patterns.

PubMed

Marschallinger, Robert; Golaszewski, Stefan M; Kunz, Alexander B; Kronbichler, Martin; Ladurner, Gunther; Hofmann, Peter; Trinka, Eugen; McCoy, Mark; Kraus, Jörg

2014-01-01

In multiple sclerosis (MS) the individual disease courses are very heterogeneous among patients and biomarkers for setting the diagnosis and the estimation of the prognosis for individual patients would be very helpful. For this purpose, we are developing a multidisciplinary method and workflow for the quantitative, spatial, and spatiotemporal analysis and characterization of MS lesion patterns from MRI with geostatistics. We worked on a small data set involving three synthetic and three real-world MS lesion patterns, covering a wide range of possible MS lesion configurations. After brain normalization, MS lesions were extracted and the resulting binary 3-dimensional models of MS lesion patterns were subject to geostatistical indicator variography in three orthogonal directions. By applying geostatistical indicator variography, we were able to describe the 3-dimensional spatial structure of MS lesion patterns in a standardized manner. Fitting a model function to the empirical variograms, spatial characteristics of the MS lesion patterns could be expressed and quantified by two parameters. An orthogonal plot of these parameters enabled a well-arranged comparison of the involved MS lesion patterns. This method in development is a promising candidate to complement standard image-based statistics by incorporating spatial quantification. The work flow is generic and not limited to analyzing MS lesion patterns. It can be completely automated for the screening of radiological archives. Copyright © 2013 by the American Society of Neuroimaging.

Quantifying urban growth patterns in Hanoi using landscape expansion modes and time series spatial metrics

PubMed Central

Lepczyk, Christopher A.; Miura, Tomoaki; Fox, Jefferson M.

2018-01-01

Urbanization has been driven by various social, economic, and political factors around the world for centuries. Because urbanization continues unabated in many places, it is crucial to understand patterns of urbanization and their potential ecological and environmental impacts. Given this need, the objectives of our study were to quantify urban growth rates, growth modes, and resultant changes in the landscape pattern of urbanization in Hanoi, Vietnam from 1993 to 2010 and to evaluate the extent to which the process of urban growth in Hanoi conformed to the diffusion-coalescence theory. We analyzed the spatiotemporal patterns and dynamics of the built-up land in Hanoi using landscape expansion modes, spatial metrics, and a gradient approach. Urbanization was most pronounced in the periods of 2001–2006 and 2006–2010 at a distance of 10 to 35 km around the urban center. Over the 17 year period urban expansion in Hanoi was dominated by infilling and edge expansion growth modes. Our findings support the diffusion-coalescence theory of urbanization. The shift of the urban growth areas over time and the dynamic nature of the spatial metrics revealed important information about our understanding of the urban growth process and cycle. Furthermore, our findings can be used to evaluate urban planning policies and aid in urbanization issues in rapidly urbanizing countries. PMID:29734346

Contrasting Role of Temperature in Structuring Regional Patterns of Invasive and Native Pestilential Stink Bugs

PubMed Central

Venugopal, P. Dilip; Dively, Galen P.; Herbert, Ames; Malone, Sean; Whalen, Joanne; Lamp, William O.

2016-01-01

Objectives Assessment and identification of spatial structures in the distribution and abundance of invasive species is important for unraveling the underlying ecological processes. The invasive agricultural insect pest Halyomorpha halys that causes severe economic losses in the United States is currently expanding both within United States and across Europe. We examined the drivers of H. halys invasion by characterizing the distribution and abundance patterns of H. halys and native stink bugs (Chinavia hilaris and Euschistus servus) across eight different spatial scales. We then quantified the interactive and individual influences of temperature, and measures of resource availability and distance from source populations, and their relevant spatial scales. We used Moran’s Eigenvector Maps based on Gabriel graph framework to quantify spatial relationships among the soybean fields in mid-Atlantic Unites States surveyed for stink bugs. Findings Results from the multi-spatial scale, multivariate analyses showed that temperature and its interaction with resource availability and distance from source populations structures the patterns in H. halys at very broad spatial scale. H. halys abundance decreased with increasing average June temperature and distance from source population. H. halys were not recorded at fields with average June temperature higher than 23.5°C. In parts with suitable climate, high H. halys abundance was positively associated with percentage developed open area and percentage deciduous forests at 250m scale. Broad scale patterns in native stink bugs were positively associated with increasing forest cover and, in contrast to the invasive H. halys, increasing mean July temperature. Our results identify the contrasting role of temperature in structuring regional patterns in H. halys and native stink bugs, while demonstrating its interaction with resource availability and distance from source populations for structuring H. halys patterns. Conclusion These results help predicting the pest potential of H. halys and vulnerability of agricultural systems at various regions, given the climatic conditions, and its interaction with resource availability and distance from source populations. Monitoring and control efforts within parts of the United States and Europe with more suitable climate could focus in areas of peri-urban developments with deciduous forests and other host plants, along with efforts to reduce propagule pressure. PMID:26928562

Spatial and temporal statistical analysis of bycatch data: Patterns of sea turtle bycatch in the North Atlantic

USGS Publications Warehouse

Gardner, B.; Sullivan, P.J.; Morreale, S.J.; Epperly, S.P.

2008-01-01

Loggerhead (Caretta caretta) and leatherback (Dermochelys coriacea) sea turtle distributions and movements in offshore waters of the western North Atlantic are not well understood despite continued efforts to monitor, survey, and observe them. Loggerhead and leatherback sea turtles are listed as endangered by the World Conservation Union, and thus anthropogenic mortality of these species, including fishing, is of elevated interest. This study quantifies spatial and temporal patterns of sea turtle bycatch distributions to identify potential processes influencing their locations. A Ripley's K function analysis was employed on the NOAA Fisheries Atlantic Pelagic Longline Observer Program data to determine spatial, temporal, and spatio-temporal patterns of sea turtle bycatch distributions within the pattern of the pelagic fishery distribution. Results indicate that loggerhead and leatherback sea turtle catch distributions change seasonally, with patterns of spatial clustering appearing from July through October. The results from the space-time analysis indicate that sea turtle catch distributions are related on a relatively fine scale (30-200 km and 1-5 days). The use of spatial and temporal point pattern analysis, particularly K function analysis, is a novel way to examine bycatch data and can be used to inform fishing practices such that fishing could still occur while minimizing sea turtle bycatch. ?? 2008 NRC.

Spatial controls of occurrence and spread of wildfires in the Missouri Ozark Highlands.

PubMed

Yang, Jian; He, Hong S; Shifley, Stephen R

2008-07-01

Understanding spatial controls on wildfires is important when designing adaptive fire management plans and optimizing fuel treatment locations on a forest landscape. Previous research about this topic focused primarily on spatial controls for fire origin locations alone. Fire spread and behavior were largely overlooked. This paper contrasts the relative importance of biotic, abiotic, and anthropogenic constraints on the spatial pattern of fire occurrence with that on burn probability (i.e., the probability that fire will spread to a particular location). Spatial point pattern analysis and landscape succession fire model (LANDIS) were used to create maps to show the contrast. We quantified spatial controls on both fire occurrence and fire spread in the Midwest Ozark Highlands region, USA. This area exhibits a typical anthropogenic surface fire regime. We found that (1) human accessibility and land ownership were primary limiting factors in shaping clustered fire origin locations; (2) vegetation and topography had a negligible influence on fire occurrence in this anthropogenic regime; (3) burn probability was higher in grassland and open woodland than in closed-canopy forest, even though fire occurrence density was less in these vegetation types; and (4) biotic and abiotic factors were secondary descriptive ingredients for determining the spatial patterns of burn probability. This study demonstrates how fire occurrence and spread interact with landscape patterns to affect the spatial distribution of wildfire risk. The application of spatial point pattern data analysis would also be valuable to researchers working on landscape forest fire models to integrate historical ignition location patterns in fire simulation.

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Shifting Patterns of Aedes aegypti Fine Scale Spatial Clustering in Iquitos, Peru

PubMed Central

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

2014-01-01

Background Empiric evidence shows that Aedes aegypti abundance is spatially heterogeneous and that some areas and larval habitats produce more mosquitoes than others. There is a knowledge gap, however, with regards to the temporal persistence of such Ae. aegypti abundance hotspots. In this study, we used a longitudinal entomologic dataset from the city of Iquitos, Peru, to (1) quantify the spatial clustering patterns of adult Ae. aegypti and pupae counts per house, (2) determine overlap between clusters, (3) quantify the temporal stability of clusters over nine entomologic surveys spaced four months apart, and (4) quantify the extent of clustering at the household and neighborhood levels. Methodologies/Principal Findings Data from 13,662 household entomological visits performed in two Iquitos neighborhoods differing in Ae. aegypti abundance and dengue virus transmission was analyzed using global and local spatial statistics. The location and extent of Ae. aegypti pupae and adult hotspots (i.e., small groups of houses with significantly [p<0.05] high mosquito abundance) were calculated for each of the 9 entomologic surveys. The extent of clustering was used to quantify the probability of finding spatially correlated populations. Our analyses indicate that Ae. aegypti distribution was highly focal (most clusters do not extend beyond 30 meters) and that hotspots of high vector abundance were common on every survey date, but they were temporally unstable over the period of study. Conclusions/Significance Our findings have implications for understanding Ae. aegypti distribution and for the design of surveillance and control activities relying on household-level data. In settings like Iquitos, where there is a relatively low percentage of Ae. aegypti in permanent water-holding containers, identifying and targeting key premises will be significantly challenged by shifting hotspots of Ae. aegypti infestation. Focusing efforts in large geographic areas with historically high levels of transmission may be more effective than targeting Ae. aegypti hotspots. PMID:25102062

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

PubMed

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

2014-08-01

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

Shifts in controls on the temporal coherence of throughfall chemical flux in Acadia National Park, Maine, USA

USGS Publications Warehouse

Nelson, Sarah J.; Webster, Katherine E.; Loftin, Cynthia S.; Weathers, Kathleen C.

2013-01-01

Major ion and mercury (Hg) inputs to terrestrial ecosystems include both wet and dry deposition (total deposition). Estimating total deposition to sensitive receptor sites is hampered by limited information regarding its spatial heterogeneity and seasonality. We used measurements of throughfall flux, which includes atmospheric inputs to forests and the net effects of canopy leaching or uptake, for ten major ions and Hg collected during 35 time periods in 1999–2005 at over 70 sites within Acadia National Park, Maine to (1) quantify coherence in temporal dynamics of seasonal throughfall deposition and (2) examine controls on these patterns at multiple scales. We quantified temporal coherence as the correlation between all possible site pairs for each solute on a seasonal basis. In the summer growing season and autumn, coherence among pairs of sites with similar vegetation was stronger than for site-pairs that differed in vegetation suggesting that interaction with the canopy and leaching of solutes differed in coniferous, deciduous, mixed, and shrub or open canopy sites. The spatial pattern in throughfall hydrologic inputs across Acadia National Park was more variable during the winter snow season, suggesting that snow re-distribution affects net hydrologic input, which consequently affects chemical flux. Sea-salt corrected calcium concentrations identified a shift in air mass sources from maritime in winter to the continental industrial corridor in summer. Our results suggest that the spatial pattern of throughfall hydrologic flux, dominant seasonal air mass source, and relationship with vegetation in winter differ from the spatial pattern of throughfall flux in these solutes in summer and autumn. The coherence approach applied here made clear the strong influence of spatial heterogeneity in throughfall hydrologic inputs and a maritime air mass source on winter patterns of throughfall flux. By contrast, vegetation type was the most important influence on throughfall chemical flux in summer and autumn.

Spatial distribution of tree species governs the spatio-temporal interaction of leaf area index and soil moisture across a forested landscape.

PubMed

Naithani, Kusum J; Baldwin, Doug C; Gaines, Katie P; Lin, Henry; Eissenstat, David M

2013-01-01

Quantifying coupled spatio-temporal dynamics of phenology and hydrology and understanding underlying processes is a fundamental challenge in ecohydrology. While variation in phenology and factors influencing it have attracted the attention of ecologists for a long time, the influence of biodiversity on coupled dynamics of phenology and hydrology across a landscape is largely untested. We measured leaf area index (L) and volumetric soil water content (θ) on a co-located spatial grid to characterize forest phenology and hydrology across a forested catchment in central Pennsylvania during 2010. We used hierarchical Bayesian modeling to quantify spatio-temporal patterns of L and θ. Our results suggest that the spatial distribution of tree species across the landscape created unique spatio-temporal patterns of L, which created patterns of water demand reflected in variable soil moisture across space and time. We found a lag of about 11 days between increase in L and decline in θ. Vegetation and soil moisture become increasingly homogenized and coupled from leaf-onset to maturity but heterogeneous and uncoupled from leaf maturity to senescence. Our results provide insight into spatio-temporal coupling between biodiversity and soil hydrology that is useful to enhance ecohydrological modeling in humid temperate forests.

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

Treesearch

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

2015-01-01

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

Evidence of territoriality and species interactions from spatial point-pattern analyses of subarctic-nesting geese

USGS Publications Warehouse

Reiter, Matthew E.; Andersen, David E.

2013-01-01

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

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.

Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China.

PubMed

Yu, Gui-Rui; Zhu, Xian-Jin; Fu, Yu-Ling; He, Hong-Lin; Wang, Qiu-Feng; Wen, Xue-Fa; Li, Xuan-Ran; Zhang, Lei-Ming; Zhang, Li; Su, Wen; Li, Sheng-Gong; Sun, Xiao-Min; Zhang, Yi-Ping; Zhang, Jun-Hui; Yan, Jun-Hua; Wang, Hui-Min; Zhou, Guang-Sheng; Jia, Bing-Rui; Xiang, Wen-Hua; Li, Ying-Nian; Zhao, Liang; Wang, Yan-Fen; Shi, Pei-Li; Chen, Shi-Ping; Xin, Xiao-Ping; Zhao, Feng-Hua; Wang, Yu-Ying; Tong, Cheng-Li

2013-03-01

Understanding the dynamics and underlying mechanism of carbon exchange between terrestrial ecosystems and the atmosphere is one of the key issues in global change research. In this study, we quantified the carbon fluxes in different terrestrial ecosystems in China, and analyzed their spatial variation and environmental drivers based on the long-term observation data of ChinaFLUX sites and the published data from other flux sites in China. The results indicate that gross ecosystem productivity (GEP), ecosystem respiration (ER), and net ecosystem productivity (NEP) of terrestrial ecosystems in China showed a significantly latitudinal pattern, declining linearly with the increase of latitude. However, GEP, ER, and NEP did not present a clear longitudinal pattern. The carbon sink functional areas of terrestrial ecosystems in China were mainly located in the subtropical and temperate forests, coastal wetlands in eastern China, the temperate meadow steppe in the northeast China, and the alpine meadow in eastern edge of Qinghai-Tibetan Plateau. The forest ecosystems had stronger carbon sink than grassland ecosystems. The spatial patterns of GEP and ER in China were mainly determined by mean annual precipitation (MAP) and mean annual temperature (MAT), whereas the spatial variation in NEP was largely explained by MAT. The combined effects of MAT and MAP explained 79%, 62%, and 66% of the spatial variations in GEP, ER, and NEP, respectively. The GEP, ER, and NEP in different ecosystems in China exhibited 'positive coupling correlation' in their spatial patterns. Both ER and NEP were significantly correlated with GEP, with 68% of the per-unit GEP contributed to ER and 29% to NEP. MAT and MAP affected the spatial patterns of ER and NEP mainly by their direct effects on the spatial pattern of GEP. © 2012 Blackwell Publishing Ltd.

Spatial statistical analysis of tree deaths using airborne digital imagery

NASA Astrophysics Data System (ADS)

Chang, Ya-Mei; Baddeley, Adrian; Wallace, Jeremy; Canci, Michael

2013-04-01

High resolution digital airborne imagery offers unprecedented opportunities for observation and monitoring of vegetation, providing the potential to identify, locate and track individual vegetation objects over time. Analytical tools are required to quantify relevant information. In this paper, locations of trees over a large area of native woodland vegetation were identified using morphological image analysis techniques. Methods of spatial point process statistics were then applied to estimate the spatially-varying tree death risk, and to show that it is significantly non-uniform. [Tree deaths over the area were detected in our previous work (Wallace et al., 2008).] The study area is a major source of ground water for the city of Perth, and the work was motivated by the need to understand and quantify vegetation changes in the context of water extraction and drying climate. The influence of hydrological variables on tree death risk was investigated using spatial statistics (graphical exploratory methods, spatial point pattern modelling and diagnostics).

Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang; Yin, Runsheng; Li, Zhengpeng; Deng, Yulin; Tan, Kun; Deng, Xiangzheng; Rothstein, David; Qi, Jiaguo

2010-01-01

Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon budgets. Here we use the General Ensemble biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China’s upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to a lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sink/source patterns showed a high degree of spatial heterogeneity. Carbon sinks were associated with forest areas without disturbances, whereas carbon sources were primarily caused by stand-replacing disturbances. It is critical to adequately represent the detailed fast-changing dynamics of land use activities in regional biogeochemical models to determine the spatial and temporal evolution of regional carbon sink/source patterns.

Bioaccumulation of perfluoroalkyl substances in exploited fish and crustaceans: Spatial trends across two estuarine systems.

PubMed

Taylor, Matthew D; Beyer-Robson, Janina; Johnson, Daniel D; Knott, Nathan A; Bowles, Karl C

2018-06-01

Spatial patterns in perfluoroalkyl substances were quantified for exploited fish and crustaceans across two contrasting Australian estuaries (Port Stephens and Hunter River). Perfluorooctane sulfonate (PFOS) was detected in 77% of composites from Port Stephens and 100% of composites from Hunter River. Most species from Port Stephens showed a clear trend with distance to source. In contrast, only a subset of species showed this trend in the Hunter River, potentially due to species movement patterns and differing hydrology. Spatial modelling showed that PFOS concentrations were expected to exceed the relevant trigger value up to ~13,500 m from the main point source for Port Stephens and ~9000 m for the Hunter River. These results represent the first major investigation of bioaccumulation of PFASs in exploited species in Australian estuaries, and highlight various factors that can contribute to spatial patterns in bioaccumulation. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

Watching grass grow: Successes and limitations of image-based methods for monitoring grassland phenology

USDA-ARS?s Scientific Manuscript database

Seasonal changes in aboveground primary production (i.e. phenology) are influenced by environmental conditions with implications for land-atmosphere interactions, carbon cycling, and agricultural production. Monitoring phenology and quantifying seasonal patterns across spatially extensive grasslands...

On Expression Patterns and Developmental Origin of Human Brain Regions.

PubMed

Kirsch, Lior; Chechik, Gal

2016-08-01

Anatomical substructures of the human brain have characteristic cell-types, connectivity and local circuitry, which are reflected in area-specific transcriptome signatures, but the principles governing area-specific transcription and their relation to brain development are still being studied. In adult rodents, areal transcriptome patterns agree with the embryonic origin of brain regions, but the processes and genes that preserve an embryonic signature in regional expression profiles were not quantified. Furthermore, it is not clear how embryonic-origin signatures of adult-brain expression interplay with changes in expression patterns during development. Here we first quantify which genes have regional expression-patterns related to the developmental origin of brain regions, using genome-wide mRNA expression from post-mortem adult human brains. We find that almost all human genes (92%) exhibit an expression pattern that agrees with developmental brain-region ontology, but that this agreement changes at multiple phases during development. Agreement is particularly strong in neuron-specific genes, but also in genes that are not spatially correlated with neuron-specific or glia-specific markers. Surprisingly, agreement is also stronger in early-evolved genes. We further find that pairs of similar genes having high agreement to developmental region ontology tend to be more strongly correlated or anti-correlated, and that the strength of spatial correlation changes more strongly in gene pairs with stronger embryonic signatures. These results suggest that transcription regulation of most genes in the adult human brain is spatially tuned in a way that changes through life, but in agreement with development-determined brain regions.

On Expression Patterns and Developmental Origin of Human Brain Regions

PubMed Central

Kirsch, Lior; Chechik, Gal

2016-01-01

Anatomical substructures of the human brain have characteristic cell-types, connectivity and local circuitry, which are reflected in area-specific transcriptome signatures, but the principles governing area-specific transcription and their relation to brain development are still being studied. In adult rodents, areal transcriptome patterns agree with the embryonic origin of brain regions, but the processes and genes that preserve an embryonic signature in regional expression profiles were not quantified. Furthermore, it is not clear how embryonic-origin signatures of adult-brain expression interplay with changes in expression patterns during development. Here we first quantify which genes have regional expression-patterns related to the developmental origin of brain regions, using genome-wide mRNA expression from post-mortem adult human brains. We find that almost all human genes (92%) exhibit an expression pattern that agrees with developmental brain-region ontology, but that this agreement changes at multiple phases during development. Agreement is particularly strong in neuron-specific genes, but also in genes that are not spatially correlated with neuron-specific or glia-specific markers. Surprisingly, agreement is also stronger in early-evolved genes. We further find that pairs of similar genes having high agreement to developmental region ontology tend to be more strongly correlated or anti-correlated, and that the strength of spatial correlation changes more strongly in gene pairs with stronger embryonic signatures. These results suggest that transcription regulation of most genes in the adult human brain is spatially tuned in a way that changes through life, but in agreement with development-determined brain regions. PMID:27564987

Factors influencing the spatial and temporal dynamics of engelmann spruce mortality during a spruce beetle outbreak on the Markagunt Plateau, Utah

Treesearch

R. Justin DeRose; James N. Long

2012-01-01

Host conditions are known to influence spruce beetle population levels, but whether they influence the spatial and temporal patterns of beetle-caused mortality during an outbreak is unknown. Using dendrochronological techniques, we quantified the spatiotemporal dynamics of a modern (late 1980s through the early 2000s) spruce beetle outbreak in Engelmann spruce on the...

Spatial patterns of land cover in the United States: a technical document supporting the Forest Service 2010 RPA Assessment

Treesearch

Kurt H. Riitters

2011-01-01

Land cover patterns inventoried from a national land cover map provide information about the landscape context and fragmentation of the Nation’s forests, grasslands, and shrublands. This inventory is required to quantify, map, and evaluate the capacities of landscapes to provide ecological goods and services sustainably. This report documents the procedures to...

Hydraulic redistribution of soil water in two old-growth coniferous forests: quantifying patterns and controls.

Treesearch

J.M. Warren; F.C. Meinzer; J.R. Brooks; J.-C. Domec; R. Coulombe

2006-01-01

We incorporated soil/plant biophysical properties into a simple model to predict seasonal trajectories of hydraulic redistribution (HR). We measured soil water content, water potential root conductivity, and climate across multiple years in two old-growth coniferous forests. The HR variability within sites (0 to 0.5 mm/d) was linked to spatial patterns of roots, soil...

Quantifying bushfire penetration into urban areas in Australia

NASA Astrophysics Data System (ADS)

Chen, Keping; McAneney, John

2004-06-01

The extent and trajectory of bushfire penetration at the bushland-urban interface are quantified using data from major historical fires in Australia. We find that the maximum distance at which homes are destroyed is typically less than 700 m. The probability of home destruction emerges as a simple linear and decreasing function of distance from the bushland-urban boundary but with a variable slope that presumably depends upon fire regime and human intervention. The collective data suggest that the probability of home destruction at the forest edge is around 60%. Spatial patterns of destroyed homes display significant neighbourhood clustering. Our results provide revealing spatial evidence for estimating fire risk to properties and suggest an ember-attack model.

Extended quantification of the generalized recurrence plot

NASA Astrophysics Data System (ADS)

Riedl, Maik; Marwan, Norbert; Kurths, Jürgen

2016-04-01

The generalized recurrence plot is a modern tool for quantification of complex spatial patterns. Its application spans the analysis of trabecular bone structures, Turing structures, turbulent spatial plankton patterns, and fractals. But, it is also successfully applied to the description of spatio-temporal dynamics and the detection of regime shifts, such as in the complex Ginzburg-Landau- equation. The recurrence plot based determinism is a central measure in this framework quantifying the level of regularities in temporal and spatial structures. We extend this measure for the generalized recurrence plot considering additional operations of symmetry than the simple translation. It is tested not only on two-dimensional regular patterns and noise but also on complex spatial patterns reconstructing the parameter space of the complex Ginzburg-Landau-equation. The extended version of the determinism resulted in values which are consistent to the original recurrence plot approach. Furthermore, the proposed method allows a split of the determinism into parts which based on laminar and non-laminar regions of the two-dimensional pattern of the complex Ginzburg-Landau-equation. A comparison of these parts with a standard method of image classification, the co-occurrence matrix approach, shows differences especially in the description of patterns associated with turbulence. In that case, it seems that the extended version of the determinism allows a distinction of phase turbulence and defect turbulence by means of their spatial patterns. This ability of the proposed method promise new insights in other systems with turbulent dynamics coming from climatology, biology, ecology, and social sciences, for example.

Quantifying spatial habitat loss from hydrocarbon development through assessing habitat selection patterns of mule deer.

PubMed

Northrup, Joseph M; Anderson, Charles R; Wittemyer, George

2015-11-01

Extraction of oil and natural gas (hydrocarbons) from shale is increasing rapidly in North America, with documented impacts to native species and ecosystems. With shale oil and gas resources on nearly every continent, this development is set to become a major driver of global land-use change. It is increasingly critical to quantify spatial habitat loss driven by this development to implement effective mitigation strategies and develop habitat offsets. Habitat selection is a fundamental ecological process, influencing both individual fitness and population-level distribution on the landscape. Examinations of habitat selection provide a natural means for understanding spatial impacts. We examined the impact of natural gas development on habitat selection patterns of mule deer on their winter range in Colorado. We fit resource selection functions in a Bayesian hierarchical framework, with habitat availability defined using a movement-based modeling approach. Energy development drove considerable alterations to deer habitat selection patterns, with the most substantial impacts manifested as avoidance of well pads with active drilling to a distance of at least 800 m. Deer displayed more nuanced responses to other infrastructure, avoiding pads with active production and roads to a greater degree during the day than night. In aggregate, these responses equate to alteration of behavior by human development in over 50% of the critical winter range in our study area during the day and over 25% at night. Compared to other regions, the topographic and vegetative diversity in the study area appear to provide refugia that allow deer to behaviorally mediate some of the impacts of development. This study, and the methods we employed, provides a template for quantifying spatial take by industrial activities in natural areas and the results offer guidance for policy makers, mangers, and industry when attempting to mitigate habitat loss due to energy development. © 2015 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Normalized burn ratios link fire severity with patterns of avian occurrence

USGS Publications Warehouse

Rose, Eli T.; Simons, Theodore R.; Klein, Rob; McKerrow, Alexa

2016-01-01

ContextRemotely sensed differenced normalized burn ratios (DNBR) provide an index of fire severity across the footprint of a fire. We asked whether this index was useful for explaining patterns of bird occurrence within fire adapted xeric pine-oak forests of the southern Appalachian Mountains.ObjectivesWe evaluated the use of DNBR indices for linking ecosystem process with patterns of bird occurrence. We compared field-based and remotely sensed fire severity indices and used each to develop occupancy models for six bird species to identify patterns of bird occurrence following fire.MethodsWe identified and sampled 228 points within fires that recently burned within Great Smoky Mountains National Park. We performed avian point counts and field-assessed fire severity at each bird census point. We also used Landsat™ imagery acquired before and after each fire to quantify fire severity using DNBR. We used non-parametric methods to quantify agreement between fire severity indices, and evaluated single season occupancy models incorporating fire severity summarized at different spatial scales.ResultsAgreement between field-derived and remotely sensed measures of fire severity was influenced by vegetation type. Although occurrence models using field-derived indices of fire severity outperformed those using DNBR, summarizing DNBR at multiple spatial scales provided additional insights into patterns of occurrence associated with different sized patches of high severity fire.ConclusionsDNBR is useful for linking the effects of fire severity to patterns of bird occurrence, and informing how high severity fire shapes patterns of bird species occurrence on the landscape.

A Secondary Spatial Analysis of Gun Violence near Boston Schools: a Public Health Approach.

PubMed

Barboza, Gia

2018-06-01

School neighborhood violence continues to be a major public health problem among urban students. A large body of research addresses violence at school; however, fewer studies have explored concentrations of violence in areas proximal to schools. This study aimed to quantify the concentration of shootings near schools to elucidate the place-based dynamics that may be focal points for violence prevention. Geocoded databases of shooting and school locations were used to examine locational patterns of firearm shootings and elementary, middle, and high schools in Boston, Massachusetts. Analyses utilized spatial statistics for point pattern data including distance matrix and K function methodology to quantify the degree of spatial dependence of shootings around schools. Results suggested that between 2012 and 2015, there were 678 shooting incidents in Boston; the average density was 5.1 per square kilometer. The nearest neighbor index (NNI = 0.335 km, p < .001, O = 0.95 km, E = 0.28 km) and G function analysis revealed a clustered pattern of gun shooting incidents indicative of a spatially non-random process. The mean and median distance from any school to the nearest shooting location was 0.35 and 0.33 km, respectively. A majority (56%, 74/133) of schools in Boston had at least one shooting incident within 400 m, a distance that would take about 5 min to walk if traveling by foot. The bivariate K function indicated that a significantly greater number of shootings were clustered within short distances from schools than would be expected under a null hypothesis of no spatial dependence. Implications for students attending schools in racially homogenous neighborhoods across all income levels are discussed.

High-speed spatial frequency domain imaging of rat cortex detects dynamic optical and physiological properties following cardiac arrest and resuscitation.

PubMed

Wilson, Robert H; Crouzet, Christian; Torabzadeh, Mohammad; Bazrafkan, Afsheen; Farahabadi, Maryam H; Jamasian, Babak; Donga, Dishant; Alcocer, Juan; Zaher, Shuhab M; Choi, Bernard; Akbari, Yama; Tromberg, Bruce J

2017-10-01

Quantifying rapidly varying perturbations in cerebral tissue absorption and scattering can potentially help to characterize changes in brain function caused by ischemic trauma. We have developed a platform for rapid intrinsic signal brain optical imaging using macroscopically structured light. The device performs fast, multispectral, spatial frequency domain imaging (SFDI), detecting backscattered light from three-phase binary square-wave projected patterns, which have a much higher refresh rate than sinusoidal patterns used in conventional SFDI. Although not as fast as "single-snapshot" spatial frequency methods that do not require three-phase projection, square-wave patterns allow accurate image demodulation in applications such as small animal imaging where the limited field of view does not allow single-phase demodulation. By using 655, 730, and 850 nm light-emitting diodes, two spatial frequencies ([Formula: see text] and [Formula: see text]), three spatial phases (120 deg, 240 deg, and 360 deg), and an overall camera acquisition rate of 167 Hz, we map changes in tissue absorption and reduced scattering parameters ([Formula: see text] and [Formula: see text]) and oxy- and deoxyhemoglobin concentration at [Formula: see text]. We apply this method to a rat model of cardiac arrest (CA) and cardiopulmonary resuscitation (CPR) to quantify hemodynamics and scattering on temporal scales ([Formula: see text]) ranging from tens of milliseconds to minutes. We observe rapid concurrent spatiotemporal changes in tissue oxygenation and scattering during CA and following CPR, even when the cerebral electrical signal is absent. We conclude that square-wave SFDI provides an effective technical strategy for assessing cortical optical and physiological properties by balancing competing performance demands for fast signal acquisition, small fields of view, and quantitative information content.

Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang; Yin, Runsheng; Li, Zhengpeng; Deng, Yulin; Tan, Kun; Deng, Xiangzheng; Rothstein, David; Qi, Jiaguo; Yin, Runsheng

2009-01-01

Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon storage and loss. Here we use the General Ensemble Biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China's upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sinks/source pattern showed a high degree of spatial heterogeneity, Carbon sinks were associated with forest areas without disturbances, whereas carbon Sources were primarily caused by stand-replacing disturbances. This highlights the importance of land-use history in determining the regional carbon sinks/source pattern.

Quantifying Fast and Slow Responses of Terrestrial Carbon Exchange across a Water Availability Gradient in North American Flux Sites

NASA Astrophysics Data System (ADS)

Biederman, J. A.; Scott, R. L.; Goulden, M.

2014-12-01

Climate change is predicted to increase the frequency and severity of water limitation, altering terrestrial ecosystems and their carbon exchange with the atmosphere. Here we compare site-level temporal sensitivity of annual carbon fluxes to interannual variations in water availability against cross-site spatial patterns over a network of 19 eddy covariance flux sites. This network represents one order of magnitude in mean annual productivity and includes western North American desert shrublands and grasslands, savannahs, woodlands, and forests with continuous records of 4 to 12 years. Our analysis reveals site-specific patterns not identifiable in prior syntheses that pooled sites. We interpret temporal variability as an indicator of ecosystem response to annual water availability due to fast-changing factors such as leaf stomatal response and microbial activity, while cross-site spatial patterns are used to infer ecosystem adjustment to climatic water availability through slow-changing factors such as plant community and organic carbon pools. Using variance decomposition, we directly quantify how terrestrial carbon balance depends on slow- and fast-changing components of gross ecosystem production (GEP) and total ecosystem respiration (TER). Slow factors explain the majority of variance in annual net ecosystem production (NEP) across the dataset, and their relative importance is greater at wetter, forest sites than desert ecosystems. Site-specific offsets from spatial patterns of GEP and TER explain one third of NEP variance, likely due to slow-changing factors not directly linked to water, such as disturbance. TER and GEP are correlated across sites as previously shown, but our site-level analysis reveals surprisingly consistent linear relationships between these fluxes in deserts and savannahs, indicating fast coupling of TER and GEP in more arid ecosystems. Based on the uncertainty associated with slow and fast factors, we suggest a framework for improved prediction of terrestrial carbon balance. We will also present results of ongoing work to quantify fast and slow contributions to the relationship between evapotranspiration and precipitation across a precipitation gradient.

Neutral processes contribute to patterns of spatial variation for flower colour in the Mediterranean Iris lutescens (Iridaceae)

PubMed Central

Wang, Hui; Talavera, María; Min, Ya; Flaven, Elodie; Imbert, Eric

2016-01-01

Background and Aims Flower colour polymorphism in plants has been used as a classic model for understanding the importance of neutral processes vs. natural selection in population differentiation. However, current explanations for the maintenance of flower colour polymorphism mainly rely on balancing selection, while neutral processes have seldom been championed. Iris lutescens (Iridaceae) is a widespread species in the northern Mediterranean basin, which shows a stable and striking purple–yellow flower colour polymorphism. To evaluate the roles of neutral processes in the spatial variation for flower colour in this species, patterns of neutral genetic variation across its distribution range were quantified, and phenotypic differentiation was compared with neutral genetic differentiation. Methods Genetic diversity levels and population genetic structure were investigated through the genotyping of a collection of 1120 individuals in 41 populations ranging from Spain to France, using a set of eight newly developed microsatellite markers. In addition, phenotypic differentiation for flower colour was also quantified by counting colour morph frequency in each population, and measuring the reflectance spectra of sampled individuals. Key Results Populations in Spain present a sharp colour transition from solely purple to solely yellow. The results provide evidence that genetic drift through limited gene flow is important in the evolution of monomorphic populations. In contrast, most populations in France are polymorphic with both phenotypes, and the colour frequencies vary geographically without any spatial gradients observed. A pattern of isolation by distance is detected in France, and gene flow between adjacent populations seems to be an important factor maintaining populations polymorphic. Conclusions Overall, neutral processes contribute to patterns of spatial variation for flower colour in I. lutescens, but it cannot be excluded that natural selection is also operating. An interaction between neutral processes and natural selection is suggested to explain the spatial variation for flower colour in I. lutescens. PMID:27084922

Neutral processes contribute to patterns of spatial variation for flower colour in the Mediterranean Iris lutescens (Iridaceae).

PubMed

Wang, Hui; Talavera, María; Min, Ya; Flaven, Elodie; Imbert, Eric

2016-05-01

Flower colour polymorphism in plants has been used as a classic model for understanding the importance of neutral processes vs. natural selection in population differentiation. However, current explanations for the maintenance of flower colour polymorphism mainly rely on balancing selection, while neutral processes have seldom been championed. Iris lutescens (Iridaceae) is a widespread species in the northern Mediterranean basin, which shows a stable and striking purple-yellow flower colour polymorphism. To evaluate the roles of neutral processes in the spatial variation for flower colour in this species, patterns of neutral genetic variation across its distribution range were quantified, and phenotypic differentiation was compared with neutral genetic differentiation. Genetic diversity levels and population genetic structure were investigated through the genotyping of a collection of 1120 individuals in 41 populations ranging from Spain to France, using a set of eight newly developed microsatellite markers. In addition, phenotypic differentiation for flower colour was also quantified by counting colour morph frequency in each population, and measuring the reflectance spectra of sampled individuals. Populations in Spain present a sharp colour transition from solely purple to solely yellow. The results provide evidence that genetic drift through limited gene flow is important in the evolution of monomorphic populations. In contrast, most populations in France are polymorphic with both phenotypes, and the colour frequencies vary geographically without any spatial gradients observed. A pattern of isolation by distance is detected in France, and gene flow between adjacent populations seems to be an important factor maintaining populations polymorphic. Overall, neutral processes contribute to patterns of spatial variation for flower colour in I. lutescens, but it cannot be excluded that natural selection is also operating. An interaction between neutral processes and natural selection is suggested to explain the spatial variation for flower colour in I. lutescens. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

AIRWAY IDENTIFICATION WITHIN PLANAR GAMMA CAMERA IMAGES USING COMPUTER MODELS OF LUNG MORPHOLOGY

EPA Science Inventory

The quantification of inhaled aerosols could be improved if a more comprehensive assessment of their spatial distribution patterns among lung airways were obtained. A common technique for quantifying particle deposition in human lungs is with planar gamma scintigraphy. However, t...

Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones

PubMed Central

Wesolowski, Amy; Stresman, Gillian; Eagle, Nathan; Stevenson, Jennifer; Owaga, Chrispin; Marube, Elizabeth; Bousema, Teun; Drakeley, Christopher; Cox, Jonathan; Buckee, Caroline O.

2014-01-01

Human travel impacts the spread of infectious diseases across spatial and temporal scales, with broad implications for the biological and social sciences. Individual data on travel patterns have been difficult to obtain, particularly in low-income countries. Travel survey data provide detailed demographic information, but sample sizes are often small and travel histories are hard to validate. Mobile phone records can provide vast quantities of spatio-temporal travel data but vary in spatial resolution and explicitly do not include individual information in order to protect the privacy of subscribers. Here we compare and contrast both sources of data over the same time period in a rural area of Kenya. Although both data sets are able to quantify broad travel patterns and distinguish regional differences in travel, each provides different insights that can be combined to form a more detailed picture of travel in low-income settings to understand the spread of infectious diseases. PMID:25022440

Quantifying travel behavior for infectious disease research: a comparison of data from surveys and mobile phones.

PubMed

Wesolowski, Amy; Stresman, Gillian; Eagle, Nathan; Stevenson, Jennifer; Owaga, Chrispin; Marube, Elizabeth; Bousema, Teun; Drakeley, Christopher; Cox, Jonathan; Buckee, Caroline O

2014-07-14

Human travel impacts the spread of infectious diseases across spatial and temporal scales, with broad implications for the biological and social sciences. Individual data on travel patterns have been difficult to obtain, particularly in low-income countries. Travel survey data provide detailed demographic information, but sample sizes are often small and travel histories are hard to validate. Mobile phone records can provide vast quantities of spatio-temporal travel data but vary in spatial resolution and explicitly do not include individual information in order to protect the privacy of subscribers. Here we compare and contrast both sources of data over the same time period in a rural area of Kenya. Although both data sets are able to quantify broad travel patterns and distinguish regional differences in travel, each provides different insights that can be combined to form a more detailed picture of travel in low-income settings to understand the spread of infectious diseases.

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

PubMed

Koch, Julian; Stisen, Simon

2017-01-01

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

Spatial Patterns in Herbivory on a Coral Reef Are Influenced by Structural Complexity but Not by Algal Traits

PubMed Central

Vergés, Adriana; Vanderklift, Mathew A.; Doropoulos, Christopher; Hyndes, Glenn A.

2011-01-01

Background Patterns of herbivory can alter the spatial structure of ecosystems, with important consequences for ecosystem functions and biodiversity. While the factors that drive spatial patterns in herbivory in terrestrial systems are well established, comparatively less is known about what influences the distribution of herbivory in coral reefs. Methodology and Principal Findings We quantified spatial patterns of macroalgal consumption in a cross-section of Ningaloo Reef (Western Australia). We used a combination of descriptive and experimental approaches to assess the influence of multiple macroalgal traits and structural complexity in establishing the observed spatial patterns in macroalgal herbivory, and to identify potential feedback mechanisms between herbivory and macroalgal nutritional quality. Spatial patterns in macroalgal consumption were best explained by differences in structural complexity among habitats. The biomass of herbivorous fish, and rates of herbivory were always greater in the structurally-complex coral-dominated outer reef and reef flat habitats, which were also characterised by high biomass of herbivorous fish, low cover and biomass of macroalgae and the presence of unpalatable algae species. Macroalgal consumption decreased to undetectable levels within 75 m of structurally-complex reef habitat, and algae were most abundant in the structurally-simple lagoon habitats, which were also characterised by the presence of the most palatable algae species. In contrast to terrestrial ecosystems, herbivory patterns were not influenced by the distribution, productivity or nutritional quality of resources (macroalgae), and we found no evidence of a positive feedback between macroalgal consumption and the nitrogen content of algae. Significance This study highlights the importance of seascape-scale patterns in structural complexity in determining spatial patterns of macroalgal consumption by fish. Given the importance of herbivory in maintaining the ability of coral reefs to reorganise and retain ecosystem functions following disturbance, structural complexity emerges as a critical feature that is essential for the healthy functioning of these ecosystems. PMID:21347254

Drought Patterns Forecasting using an Auto-Regressive Logistic Model

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Detecting fractal power-law long-range dependence in pre-sliced cooked pork ham surface intensity patterns using Detrended Fluctuation Analysis.

PubMed

Valous, Nektarios A; Drakakis, Konstantinos; Sun, Da-Wen

2010-10-01

The visual texture of pork ham slices reveals information about the different qualities and perceived image heterogeneity, which is encapsulated as spatial variations in geometry and spectral characteristics. Detrended Fluctuation Analysis (DFA) detects long-range correlations in nonstationary spatial sequences, by a self-similarity scaling exponent alpha. In the current work, the aim is to investigate the usefulness of alpha, using different colour channels (R, G, B, L*, a*, b*, H, S, V, and Grey), as a quantitative descriptor of visual texture in sliced ham surface patterns for the detection of long-range correlations in unidimensional spatial series of greyscale intensity pixel values at 0 degrees , 30 degrees , 45 degrees , 60 degrees , and 90 degrees rotations. Images were acquired from three qualities of pre-sliced pork ham, typically consumed in Ireland (200 slices per quality). Results indicated that the DFA approach can be used to characterize and quantify the textural appearance of the three ham qualities, for different image orientations, with a global scaling exponent. The spatial series extracted from the ham images display long-range dependence, indicating an average behaviour around 1/f-noise. Results indicate that alpha has a universal character in quantifying the visual texture of ham surface intensity patterns, with no considerable crossovers that alter the behaviour of the fluctuations. Fractal correlation properties can thus be a useful metric for capturing information embedded in the visual texture of hams. Copyright (c) 2010 The American Meat Science Association. Published by Elsevier Ltd. All rights reserved.

FracPaQ: A MATLAB™ toolbox for the quantification of fracture patterns

NASA Astrophysics Data System (ADS)

Healy, David; Rizzo, Roberto E.; Cornwell, David G.; Farrell, Natalie J. C.; Watkins, Hannah; Timms, Nick E.; Gomez-Rivas, Enrique; Smith, Michael

2017-02-01

The patterns of fractures in deformed rocks are rarely uniform or random. Fracture orientations, sizes, and spatial distributions often exhibit some kind of order. In detail, relationships may exist among the different fracture attributes, e.g. small fractures dominated by one orientation, larger fractures by another. These relationships are important because the mechanical (e.g. strength, anisotropy) and transport (e.g. fluids, heat) properties of rock depend on these fracture attributes and patterns. This paper describes FracPaQ, a new open source, cross-platform toolbox to quantify fracture patterns, including distributions in fracture attributes and their spatial variation. Software has been developed to quantify fracture patterns from 2-D digital images, such as thin section micrographs, geological maps, outcrop or aerial photographs or satellite images. The toolbox comprises a suite of MATLAB™ scripts based on previously published quantitative methods for the analysis of fracture attributes: orientations, lengths, intensity, density and connectivity. An estimate of permeability in 2-D is made using a parallel plate model. The software provides an objective and consistent methodology for quantifying fracture patterns and their variations in 2-D across a wide range of length scales, rock types and tectonic settings. The implemented methods presented are inherently scale independent, and a key task where applicable is analysing and integrating quantitative fracture pattern data from micro-to macro-scales. The toolbox was developed in MATLAB™ and the source code is publicly available on GitHub™ and the Mathworks™ FileExchange. The code runs on any computer with MATLAB installed, including PCs with Microsoft Windows, Apple Macs with Mac OS X, and machines running different flavours of Linux. The application, source code and sample input files are available in open repositories in the hope that other developers and researchers will optimise and extend the functionality for the benefit of the wider community.

Human movement data for malaria control and elimination strategic planning.

PubMed

Pindolia, Deepa K; Garcia, Andres J; Wesolowski, Amy; Smith, David L; Buckee, Caroline O; Noor, Abdisalan M; Snow, Robert W; Tatem, Andrew J

2012-06-18

Recent increases in funding for malaria control have led to the reduction in transmission in many malaria endemic countries, prompting the national control programmes of 36 malaria endemic countries to set elimination targets. Accounting for human population movement (HPM) in planning for control, elimination and post-elimination surveillance is important, as evidenced by previous elimination attempts that were undermined by the reintroduction of malaria through HPM. Strategic control and elimination planning, therefore, requires quantitative information on HPM patterns and the translation of these into parasite dispersion. HPM patterns and the risk of malaria vary substantially across spatial and temporal scales, demographic and socioeconomic sub-groups, and motivation for travel, so multiple data sets are likely required for quantification of movement. While existing studies based on mobile phone call record data combined with malaria transmission maps have begun to address within-country HPM patterns, other aspects remain poorly quantified despite their importance in accurately gauging malaria movement patterns and building control and detection strategies, such as cross-border HPM, demographic and socioeconomic stratification of HPM patterns, forms of transport, personal malaria protection and other factors that modify malaria risk. A wealth of data exist to aid filling these gaps, which, when combined with spatial data on transport infrastructure, traffic and malaria transmission, can answer relevant questions to guide strategic planning. This review aims to (i) discuss relevant types of HPM across spatial and temporal scales, (ii) document where datasets exist to quantify HPM, (iii) highlight where data gaps remain and (iv) briefly put forward methods for integrating these datasets in a Geographic Information System (GIS) framework for analysing and modelling human population and Plasmodium falciparum malaria infection movements.

Human movement data for malaria control and elimination strategic planning

PubMed Central

2012-01-01

Recent increases in funding for malaria control have led to the reduction in transmission in many malaria endemic countries, prompting the national control programmes of 36 malaria endemic countries to set elimination targets. Accounting for human population movement (HPM) in planning for control, elimination and post-elimination surveillance is important, as evidenced by previous elimination attempts that were undermined by the reintroduction of malaria through HPM. Strategic control and elimination planning, therefore, requires quantitative information on HPM patterns and the translation of these into parasite dispersion. HPM patterns and the risk of malaria vary substantially across spatial and temporal scales, demographic and socioeconomic sub-groups, and motivation for travel, so multiple data sets are likely required for quantification of movement. While existing studies based on mobile phone call record data combined with malaria transmission maps have begun to address within-country HPM patterns, other aspects remain poorly quantified despite their importance in accurately gauging malaria movement patterns and building control and detection strategies, such as cross-border HPM, demographic and socioeconomic stratification of HPM patterns, forms of transport, personal malaria protection and other factors that modify malaria risk. A wealth of data exist to aid filling these gaps, which, when combined with spatial data on transport infrastructure, traffic and malaria transmission, can answer relevant questions to guide strategic planning. This review aims to (i) discuss relevant types of HPM across spatial and temporal scales, (ii) document where datasets exist to quantify HPM, (iii) highlight where data gaps remain and (iv) briefly put forward methods for integrating these datasets in a Geographic Information System (GIS) framework for analysing and modelling human population and Plasmodium falciparum malaria infection movements. PMID:22703541

Urban sprawl and fragmentation in Latin America: a dynamic quantification and characterization of spatial patterns.

PubMed

Inostroza, Luis; Baur, Rolf; Csaplovics, Elmar

2013-01-30

South America is one of the most urbanized continents in the world, where almost 84% of the total population lives in cities, more urbanized than North America (82%) and Europe (73%). Spatial dynamics, their structure, main features, land consumption rates, spatial arrangement, fragmentation degrees and comparability, remain mostly unknown for most Latin American cities. Using satellite imagery the main parameters of sprawl are quantified for 10 Latin American cities over a period of 20 years by monitoring growth patterns and identifying spatial metrics to characterize urban development and sprawling features measured with GIS tools. This quantification contributes to a better understanding of urban form in Latin America. A pervasive spatial expansion has been observed, where most of the studied cities are expanding at fast rates with falling densities trend. Although important differences in the rates of land consumption and densities exist, there is an underlying fragmentation trend towards increasing sprawl. These trends of spatial discontinuity may eventually be intensified by further economic development. Urban Sprawl/Latin America/GIS metrics/spatial development. Copyright © 2012 Elsevier Ltd. All rights reserved.

Visualizing Zonation Patterns

ERIC Educational Resources Information Center

Baumgartner, Erin; Zabin, Chela J.

2006-01-01

The study of "zonation", the distribution of plants and animals into distinct spatial areas, is a great way to introduce students to basic ecological concepts. Students can conduct methodical, quantifying surveys of zones in areas as diverse as mudflats, beaches, forests, wetlands, and fields. Students collect data from these areas with field…

Analyzing Protein Clusters on the Plasma Membrane: Application of Spatial Statistical Analysis Methods on Super-Resolution Microscopy Images.

PubMed

Paparelli, Laura; Corthout, Nikky; Pavie, Benjamin; Annaert, Wim; Munck, Sebastian

2016-01-01

The spatial distribution of proteins within the cell affects their capability to interact with other molecules and directly influences cellular processes and signaling. At the plasma membrane, multiple factors drive protein compartmentalization into specialized functional domains, leading to the formation of clusters in which intermolecule interactions are facilitated. Therefore, quantifying protein distributions is a necessity for understanding their regulation and function. The recent advent of super-resolution microscopy has opened up the possibility of imaging protein distributions at the nanometer scale. In parallel, new spatial analysis methods have been developed to quantify distribution patterns in super-resolution images. In this chapter, we provide an overview of super-resolution microscopy and summarize the factors influencing protein arrangements on the plasma membrane. Finally, we highlight methods for analyzing clusterization of plasma membrane proteins, including examples of their applications.

Noise assisted pattern fabrication

NASA Astrophysics Data System (ADS)

Roy, Tanushree; Agarwal, V.; Singh, B. P.; Parmananda, P.

2018-04-01

Pre-selected patterns on an n-type Si surface are fabricated by electrochemical etching in the presence of a weak optical signal. The constructive role of noise, namely, stochastic resonance (SR), is exploited for these purposes. SR is a nonlinear phenomenon wherein at an optimal amplitude of noise, the information transfer from weak input sub-threshold signals to the system output is maximal. In the present work, the amplitude of internal noise was systematically regulated by varying the molar concentration of hydrofluoric acid (HF) in the electrolyte. Pattern formation on the substrate for two different amplitudes (25 ± 2 and 11 ± 1 mW) of the optical template (sub-threshold signal) was considered. To quantify the fidelity/quality of pattern formation, the spatial cross-correlation coefficient (CCC) between the constructed pattern and the template of the applied signal was calculated. The maximum CCC is obtained for the pattern formed at an optimal HF concentration, indicating SR. Simulations, albeit using external noise, on a spatial array of coupled FitzHugh-Nagumo oscillators revealed similar results.

Network analysis reveals multiscale controls on streamwater chemistry

USGS Publications Warehouse

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

2014-01-01

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

Network analysis reveals multiscale controls on streamwater chemistry

PubMed Central

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

2014-01-01

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

Network analysis reveals multiscale controls on streamwater chemistry.

PubMed

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

2014-05-13

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

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

PubMed

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

2018-05-30

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

Analysing the spatial patterns of erosion scars using point process theory at the coastal chalk cliff of Mesnil-Val, (Normandy, Northern France)

NASA Astrophysics Data System (ADS)

Rohmer, J.; Dewez, D.

2014-09-01

Over the last decade, many cliff erosion studies have focused on frequency-size statistics using inventories of sea cliff retreat sizes. By comparison, only a few paid attention to quantifying the spatial and temporal organisation of erosion scars over a cliff face. Yet, this spatial organisation carries essential information about the external processes and the environmental conditions that promote or initiate sea-cliff instabilities. In this article, we use summary statistics of spatial point process theory as a tool to examine the spatial and temporal pattern of a rockfall inventory recorded with repeated terrestrial laser scanning surveys at the chalk coastal cliff site of Mesnil-Val (Normandy, France). Results show that: (1) the spatial density of erosion scars is specifically conditioned alongshore by the distance to an engineered concrete groin, with an exponential-like decreasing trend, and vertically focused both at wave breaker height and on strong lithological contrasts; (2) small erosion scars (10-3-10-2 m3) aggregate in clusters within a radius of 5 to 10 m, which suggests some sort of attraction or focused causative process, and disperse above this critical distance; (3) on the contrary, larger erosion scars (10-2-101 m3) tend to disperse above a radius of 1 to 5 m, possibly due to the spreading of successive failures across the cliff face; (4) large scars significantly occur albeit moderately, where previous large rockfalls have occurred during preceeding winter; (5) this temporal trend is not apparent for small events. In conclusion, this study shows, with a worked example, how spatial point process summary statistics are a tool to test and quantify the significance of geomorphological observation organisation.

Analysing the spatial patterns of erosion scars using point process theory at the coastal chalk cliff of Mesnil-Val, Normandy, northern France

NASA Astrophysics Data System (ADS)

Rohmer, J.; Dewez, T.

2015-02-01

Over the last decade, many cliff erosion studies have focused on frequency-size statistics using inventories of sea cliff retreat sizes. By comparison, only a few paid attention to quantifying the spatial and temporal organisation of erosion scars over a cliff face. Yet, this spatial organisation carries essential information about the external processes and the environmental conditions that promote or initiate sea-cliff instabilities. In this article, we use summary statistics of spatial point process theory as a tool to examine the spatial and temporal pattern of a rockfall inventory recorded with repeated terrestrial laser scanning surveys at the chalk coastal cliff site of Mesnil-Val (Normandy, France). Results show that: (1) the spatial density of erosion scars is specifically conditioned alongshore by the distance to an engineered concrete groyne, with an exponential-like decreasing trend, and vertically focused both at wave breaker height and on strong lithological contrasts; (2) small erosion scars (10-3 to 10-2 m3) aggregate in clusters within a radius of 5 to 10 m, which suggests some sort of attraction or focused causative process, and disperse above this critical distance; (3) on the contrary, larger erosion scars (10-2 to 101 m3) tend to disperse above a radius of 1 to 5 m, possibly due to the spreading of successive failures across the cliff face; (4) large scars significantly occur albeit moderately, where previous large rockfalls have occurred during preceding winter; (5) this temporal trend is not apparent for small events. In conclusion, this study shows, with a worked example, how spatial point process summary statistics are a tool to test and quantify the significance of geomorphological observation organisation.

A guide to calculating habitat-quality metrics to inform conservation of highly mobile species

USGS Publications Warehouse

Bieri, Joanna A.; Sample, Christine; Thogmartin, Wayne E.; Diffendorfer, James E.; Earl, Julia E.; Erickson, Richard A.; Federico, Paula; Flockhart, D. T. Tyler; Nicol, Sam; Semmens, Darius J.; Skraber, T.; Wiederholt, Ruscena; Mattsson, Brady J.

2018-01-01

Many metrics exist for quantifying the relative value of habitats and pathways used by highly mobile species. Properly selecting and applying such metrics requires substantial background in mathematics and understanding the relevant management arena. To address this multidimensional challenge, we demonstrate and compare three measurements of habitat quality: graph-, occupancy-, and demographic-based metrics. Each metric provides insights into system dynamics, at the expense of increasing amounts and complexity of data and models. Our descriptions and comparisons of diverse habitat-quality metrics provide means for practitioners to overcome the modeling challenges associated with management or conservation of such highly mobile species. Whereas previous guidance for applying habitat-quality metrics has been scattered in diversified tracks of literature, we have brought this information together into an approachable format including accessible descriptions and a modeling case study for a typical example that conservation professionals can adapt for their own decision contexts and focal populations.Considerations for Resource ManagersManagement objectives, proposed actions, data availability and quality, and model assumptions are all relevant considerations when applying and interpreting habitat-quality metrics.Graph-based metrics answer questions related to habitat centrality and connectivity, are suitable for populations with any movement pattern, quantify basic spatial and temporal patterns of occupancy and movement, and require the least data.Occupancy-based metrics answer questions about likelihood of persistence or colonization, are suitable for populations that undergo localized extinctions, quantify spatial and temporal patterns of occupancy and movement, and require a moderate amount of data.Demographic-based metrics answer questions about relative or absolute population size, are suitable for populations with any movement pattern, quantify demographic processes and population dynamics, and require the most data.More real-world examples applying occupancy-based, agent-based, and continuous-based metrics to seasonally migratory species are needed to better understand challenges and opportunities for applying these metrics more broadly.

The spatial and temporal variability of groundwater recharge in a forested basin in northern Wisconsin

USGS Publications Warehouse

Dripps, W.R.; Bradbury, K.R.

2010-01-01

Recharge varies spatially and temporally as it depends on a wide variety of factors (e.g. vegetation, precipitation, climate, topography, geology, and soil type), making it one of the most difficult, complex, and uncertain hydrologic parameters to quantify. Despite its inherent variability, groundwater modellers, planners, and policy makers often ignore recharge variability and assume a single average recharge value for an entire watershed. Relatively few attempts have been made to quantify or incorporate spatial and temporal recharge variability into water resource planning or groundwater modelling efforts. In this study, a simple, daily soil-water balance model was developed and used to estimate the spatial and temporal distribution of groundwater recharge of the Trout Lake basin of northern Wisconsin for 1996-2000 as a means to quantify recharge variability. For the 5 years of study, annual recharge varied spatially by as much as 18 cm across the basin; vegetation was the predominant control on this variability. Recharge also varied temporally with a threefold annual difference over the 5-year period. Intra-annually, recharge was limited to a few isolated events each year and exhibited a distinct seasonal pattern. The results suggest that ignoring recharge variability may not only be inappropriate, but also, depending on the application, may invalidate model results and predictions for regional and local water budget calculations, water resource management, nutrient cycling, and contaminant transport studies. Recharge is spatially and temporally variable, and should be modelled as such. Copyright ?? 2009 John Wiley & Sons, Ltd.

Monitoring air quality in mountains: Designing an effective network

USGS Publications Warehouse

Peterson, D.L.

2000-01-01

A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.

The Emergence of Regional Immigrant Concentrations in USA and Australia: A Spatial Relatedness Approach

PubMed Central

Novotny, Josef; Hasman, Jiri

2015-01-01

This paper examines the patterns of the US and Australian immigration geography and the process of regional population diversification and the emergence of new immigrant concentrations at the regional level. It presents a new approach in the context of human migration studies, focusing on spatial relatedness between individual foreign-born groups as revealed from the analysis of their joint spatial concentrations. The approach employs a simple assumption that the more frequently the members of two population groups concentrate in the same locations the higher is the probability that these two groups can be related. Based on detailed data on the spatial distribution of foreign-born groups in US counties (2000–2010) and Australian postal areas (2006–2011) we firstly quantify the spatial relatedness between all pairs of foreign-born groups and model the aggregate patterns of US and Australian immigration systems conceptualized as the undirected networks of foreign-born groups linked by their spatial relatedness. Secondly, adopting a more dynamic perspective, we assume that immigrant groups with higher spatial relatedness to those groups already concentrated in a region are also more likely to settle in this region in future. As the ultimate goal of the paper, we examine the power of spatial relatedness measures in projecting the emergence of new immigrant concentrations in the US and Australian regions. The results corroborate that the spatial relatedness measures can serve as useful instruments in the analysis of the patterns of population structure and prediction of regional population change. More generally, this paper demonstrates that information contained in spatial patterns (relatedness in space) of population composition has yet to be fully utilized in population forecasting. PMID:25966371

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

PubMed

Riby, Leigh M; Orme, Elizabeth

2013-03-01

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

Quantitative characterization of the regressive ecological succession by fractal analysis of plant spatial patterns

USGS Publications Warehouse

Alados, C.L.; Pueyo, Y.; Giner, M.L.; Navarro, T.; Escos, J.; Barroso, F.; Cabezudo, B.; Emlen, J.M.

2003-01-01

We studied the effect of grazing on the degree of regression of successional vegetation dynamic in a semi-arid Mediterranean matorral. We quantified the spatial distribution patterns of the vegetation by fractal analyses, using the fractal information dimension and spatial autocorrelation measured by detrended fluctuation analyses (DFA). It is the first time that fractal analysis of plant spatial patterns has been used to characterize the regressive ecological succession. Plant spatial patterns were compared over a long-term grazing gradient (low, medium and heavy grazing pressure) and on ungrazed sites for two different plant communities: A middle dense matorral of Chamaerops and Periploca at Sabinar-Romeral and a middle dense matorral of Chamaerops, Rhamnus and Ulex at Requena-Montano. The two communities differed also in the microclimatic characteristics (sea oriented at the Sabinar-Romeral site and inland oriented at the Requena-Montano site). The information fractal dimension increased as we moved from a middle dense matorral to discontinuous and scattered matorral and, finally to the late regressive succession, at Stipa steppe stage. At this stage a drastic change in the fractal dimension revealed a change in the vegetation structure, accurately indicating end successional vegetation stages. Long-term correlation analysis (DFA) revealed that an increase in grazing pressure leads to unpredictability (randomness) in species distributions, a reduction in diversity, and an increase in cover of the regressive successional species, e.g. Stipa tenacissima L. These comparisons provide a quantitative characterization of the successional dynamic of plant spatial patterns in response to grazing perturbation gradient. ?? 2002 Elsevier Science B.V. All rights reserved.

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

PubMed Central

Stisen, Simon

2017-01-01

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

Quantify Lateral Dispersion and Turbulent Mixing by Spatial Array of chi-EM-APEX Floats

DTIC Science & Technology

2013-09-30

pattern), 18-hour background field on the R/V Oceanus. ii) 10 km, 4-hour butterfly following dye on R/V Endeavor. iii) Dye following to track the...analysis of drogue observations, Deep- Sea Research, 23, 349-352. PUBLICATIONS (wholly or in part supported by this grant) Sanford, T.B. (2013...Spatial Structure of Thermocline and Abyssal Internal Waves, Deep- Sea Res. Part II. 85, 195-209. [published, refereed] Szuts, Z.B. and T. B. Sanford

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

PubMed

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

2017-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-01-01

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

A metric for quantifying El Niño pattern diversity with implications for ENSO-mean state interaction

NASA Astrophysics Data System (ADS)

Lemmon, Danielle E.; Karnauskas, Kristopher B.

2018-04-01

Recent research on the El Niño-Southern Oscillation (ENSO) phenomenon increasingly reveals the highly complex and diverse nature of ENSO variability. A method of quantifying ENSO spatial pattern uniqueness and diversity is presented, which enables (1) formally distinguishing between unique and "canonical" El Niño events, (2) testing whether historical model simulations aptly capture ENSO diversity by comparing with instrumental observations, (3) projecting future ENSO diversity using future model simulations, (4) understanding the dynamics that give rise to ENSO diversity, and (5) analyzing the associated diversity of ENSO-related atmospheric teleconnection patterns. Here we develop a framework for measuring El Niño spatial SST pattern uniqueness and diversity for a given set of El Niño events using two indices, the El Niño Pattern Uniqueness (EPU) index and El Niño Pattern Diversity (EPD) index, respectively. By applying this framework to instrumental records, we independently confirm a recent regime shift in El Niño pattern diversity with an increase in unique El Niño event sea surface temperature patterns. However, the same regime shift is not observed in historical CMIP5 model simulations; moreover, a comparison between historical and future CMIP5 model scenarios shows no robust change in future ENSO diversity. Finally, we support recent work that asserts a link between the background cooling of the eastern tropical Pacific and changes in ENSO diversity. This robust link between an eastern Pacific cooling mode and ENSO diversity is observed not only in instrumental reconstructions and reanalysis, but also in historical and future CMIP5 model simulations.

Using High Resolution Commercial Satellite Imagery to Quantify Spatial Features of Urban Areas and their Relationship to Quality of Life Indicators in Accra, Ghana

NASA Astrophysics Data System (ADS)

Sandborn, A.; Engstrom, R.; Yu, Q.

2014-12-01

Mapping urban areas via satellite imagery is an important task for detecting and anticipating land cover and land use change at multiple scales. As developing countries experience substantial urban growth and expansion, remotely sensed based estimates of population and quality of life indicators can provide timely and spatially explicit information to researchers and planners working to determine how cities are changing. In this study, we use commercial high spatial resolution satellite imagery in combination with fine resolution census data to determine the ability of using remotely sensed data to reveal the spatial patterns of quality of life in Accra, Ghana. Traditionally, spectral characteristics are used on a per-pixel basis to determine land cover; however, in this study, we test a new methodology that quantifies spatial characteristics using a variety of spatial features observed in the imagery to determine the properties of an urban area. The spatial characteristics used in this study include histograms of oriented gradients, PanTex, Fourier transform, and line support regions. These spatial features focus on extracting structural and textural patterns of built-up areas, such as homogeneous building orientations and straight line indices. Information derived from aggregating the descriptive statistics of the spatial features at both the fine-resolution census unit and the larger neighborhood level are then compared to census derived quality of life indicators including information about housing, education, and population estimates. Preliminary results indicate that there are correlations between straight line indices and census data including available electricity and literacy rates. Results from this study will be used to determine if this methodology provides a new and improved way to measure a city structure in developing cities and differentiate between residential and commercial land use zones, as well as formal versus informal housing areas.

Mistletoe effects on Scots pine decline following drought events: insights from within-tree spatial patterns, growth and carbohydrates.

PubMed

Sangüesa-Barreda, Gabriel; Linares, Juan Carlos; Camarero, J Julio

2012-05-01

Forest decline has been attributed to the interaction of several stressors including biotic factors such as mistletoes and climate-induced drought stress. However, few data exist on how mistletoes are spatially arranged within trees and how this spatial pattern is related to changes in radial growth, responses to drought stress and carbon use. We used dendrochronology to quantify how mistletoe (Viscum album L.) infestation and drought stress affected long-term growth patterns in Pinus sylvestris L. at different heights. Basal area increment (BAI) trends and comparisons between trees of three different infestation degrees (without mistletoe, ID1; moderately infested trees, ID2; and severely infested trees, ID3) were performed using linear mixed-effects models. To identify the main climatic drivers of tree growth tree-ring widths were converted into indexed chronologies and related to climate data using correlation functions. We performed spatial analyses of the 3D distribution of mistletoe individuals and their ages within the crowns of three severely infested pines to describe their patterns. Lastly, we quantified carbohydrate and nitrogen concentrations in needles and sapwood of branches from severely infested trees and from trees without mistletoe. Mistletoe individuals formed strongly clustered groups of similar age within tree crowns and their age increased towards the crown apex. Mistletoe infestation negatively impacted growth but this effect was stronger near the tree apex than in the rest of sampled heights, causing an average loss of 64% in BAI (loss of BAI was ∼51% at 1.3 m or near the tree base). We found that BAI of severely infested trees and moderately or non-infested trees diverged since 2001 and such divergence was magnified by drought. Infested trees had lower concentrations of soluble sugars in their needles than non-infested ones. We conclude that mistletoe infestation causes growth decline and increases the sensitivity of trees to drought stress.

Spatial analysis of ecosystem service relationships to improve targeting of payments for hydrological services

PubMed Central

Manson, Robert H.; Ricketts, Taylor H.; Geissert, Daniel

2018-01-01

Payment for hydrological services (PHS) are popular tools for conserving ecosystems and their water-related services. However, improving the spatial targeting and impacts of PHS, as well as their ability to foster synergies with other ecosystem services (ES), remain challenging. We aimed at using spatial analyses to evaluate the targeting performance of México’s National PHS program in central Veracruz. We quantified the effectiveness of areas targeted for PHS in actually covering areas of high HS provision and social priority during 2003–2013. First, we quantified provisioning and spatial distributions of two target (water yield and soil retention), and one non-target ES (carbon storage) using InVEST. Subsequently, pairwise relationships among ES were quantified by using spatial correlation and overlap analyses. Finally, we evaluated targeting by: (i) prioritizing areas of individual and overlapping ES; (ii) quantifying spatial co-occurrences of these priority areas with those targeted by PHS; (iii) evaluating the extent to which PHS directly contribute to HS delivery; and (iv), testing if PHS targeted areas disproportionately covered areas with high ecological and social priority. We found that modelled priority areas exhibited non-random distributions and distinct spatial patterns. Our results show significant pairwise correlations between all ES suggesting synergistic relationships. However, our analysis showed a significantly lower overlap than expected and thus significant mismatches between PHS targeted areas and all types of priority areas. These findings suggest that the targeting of areas with high HS provisioning and social priority by Mexico’s PHS program could be improved significantly. This study underscores: (1) the importance of using maps of HS provisioning as main targeting criteria in PHS design to channel payments towards areas that require future conservation, and (2) the need for future research that helps balance ecological and socioeconomic targeting criteria. PMID:29462205

Woodland type and spatial distribution of nymphal Ixodes scapularis (Acari: Ixodidae)

USGS Publications Warehouse

Ginsberg, Howard S.; Zhioua, Elyes; Mitra, Shaibal; Fischer, Jason L.; Buckley, P.A.; Verret, Frank; Underwood, H. Brian; Buckley, Francine G.

2004-01-01

Spatial distribution patterns of black-legged ticks, Ixodes scapularis, in deciduous and coniferous woodlands were studied by sampling ticks in different woodland types and at sites from which deer had been excluded and by quantifying movement patterns of tick host animals (mammals and birds) at the Lighthouse Tract, Fire Island, NY, from 1994 to 2000. Densities of nymphal ticks were greater in deciduous than coniferous woods in 3 of 7 yr. Only engorged ticks survived the winter, and overwintering survival of engorged larvae in experimental enclosures did not differ between deciduous and coniferous woods. Nymphs were not always most abundant in the same forest type as they had been as larvae, and the habitat shift between life stages differed in direction in different years. Therefore, forest type by itself did not account for tick distribution patterns. Nymphal densities were lower where deer had been excluded compared with areas with deer present for 3 yr after exclusion, suggesting that movement patterns of vertebrate hosts influenced tick distribution, but nymphal densities increased dramatically in one of the enclosures in the fourth year. Therefore, movements of ticks on animal hosts apparently contribute substantially to tick spatial distribution among woodland types, but the factor(s) that determine spatial distribution of nymphal I. scapularis shift from year to year.

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

PubMed

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

2014-01-01

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

Quantifying Patterns in Spatial and Temporal Distributions of Intertidal Native and Non-Indigenous Eelgrass in Yaquina Estuary, Oregon: 1997 – 2012

EPA Science Inventory

Intertidal native eelgrass Zostera marina and non-indigenous dwarf eelgrass Z. japonica in lower Yaquina estuary, Oregon were mapped between 1997 and 2012. Annual color infrared aerial photographs acquired annually between 1997 and 2007 were used to classify distributions of the...

Pattern analysis of eastern spruce budworm Choristoneura fumiferana dispersal

Treesearch

Dean P. Anderson; Brian R. Sturtevant

2011-01-01

Dispersal has been proposed as an important mechanism in the broad-scale synchronisation of insect outbreaks by linking spatially disjunct populations. Evidence suggests that dispersal is influenced by landscape structure, phenology, temperature, and air currents; however, the details remain unclear due to the difficulty of quantifying dispersal. In this study, we used...

Landscape patterns and soil organic carbon stocks in agricultural bocage landscapes

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Navigating the currents of seascape genomics: how spatial analyses can augment population genomic studies

PubMed Central

Crandall, Eric D.; Liggins, Libby; Bongaerts, Pim; Treml, Eric A.

2016-01-01

Population genomic approaches are making rapid inroads in the study of non-model organisms, including marine taxa. To date, these marine studies have predominantly focused on rudimentary metrics describing the spatial and environmental context of their study region (e.g., geographical distance, average sea surface temperature, average salinity). We contend that a more nuanced and considered approach to quantifying seascape dynamics and patterns can strengthen population genomic investigations and help identify spatial, temporal, and environmental factors associated with differing selective regimes or demographic histories. Nevertheless, approaches for quantifying marine landscapes are complicated. Characteristic features of the marine environment, including pelagic living in flowing water (experienced by most marine taxa at some point in their life cycle), require a well-designed spatial-temporal sampling strategy and analysis. Many genetic summary statistics used to describe populations may be inappropriate for marine species with large population sizes, large species ranges, stochastic recruitment, and asymmetrical gene flow. Finally, statistical approaches for testing associations between seascapes and population genomic patterns are still maturing with no single approach able to capture all relevant considerations. None of these issues are completely unique to marine systems and therefore similar issues and solutions will be shared for many organisms regardless of habitat. Here, we outline goals and spatial approaches for landscape genomics with an emphasis on marine systems and review the growing empirical literature on seascape genomics. We review established tools and approaches and highlight promising new strategies to overcome select issues including a strategy to spatially optimize sampling. Despite the many challenges, we argue that marine systems may be especially well suited for identifying candidate genomic regions under environmentally mediated selection and that seascape genomic approaches are especially useful for identifying robust locus-by-environment associations. PMID:29491947

Navigating the currents of seascape genomics: how spatial analyses can augment population genomic studies.

PubMed

Riginos, Cynthia; Crandall, Eric D; Liggins, Libby; Bongaerts, Pim; Treml, Eric A

2016-12-01

Population genomic approaches are making rapid inroads in the study of non-model organisms, including marine taxa. To date, these marine studies have predominantly focused on rudimentary metrics describing the spatial and environmental context of their study region (e.g., geographical distance, average sea surface temperature, average salinity). We contend that a more nuanced and considered approach to quantifying seascape dynamics and patterns can strengthen population genomic investigations and help identify spatial, temporal, and environmental factors associated with differing selective regimes or demographic histories. Nevertheless, approaches for quantifying marine landscapes are complicated. Characteristic features of the marine environment, including pelagic living in flowing water (experienced by most marine taxa at some point in their life cycle), require a well-designed spatial-temporal sampling strategy and analysis. Many genetic summary statistics used to describe populations may be inappropriate for marine species with large population sizes, large species ranges, stochastic recruitment, and asymmetrical gene flow. Finally, statistical approaches for testing associations between seascapes and population genomic patterns are still maturing with no single approach able to capture all relevant considerations. None of these issues are completely unique to marine systems and therefore similar issues and solutions will be shared for many organisms regardless of habitat. Here, we outline goals and spatial approaches for landscape genomics with an emphasis on marine systems and review the growing empirical literature on seascape genomics. We review established tools and approaches and highlight promising new strategies to overcome select issues including a strategy to spatially optimize sampling. Despite the many challenges, we argue that marine systems may be especially well suited for identifying candidate genomic regions under environmentally mediated selection and that seascape genomic approaches are especially useful for identifying robust locus-by-environment associations.

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

PubMed Central

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

2012-01-01

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

Spatially patterned matrix elasticity directs stem cell fate

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

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

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

Kuang, Wenhui; Liu, Yue; Dou, Yinyin

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

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

DOE PAGES

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

2014-12-06

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

Quantify spatial relations to discover handwritten graphical symbols

NASA Astrophysics Data System (ADS)

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

2012-01-01

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

Analysing the impact of urban areas patterns on the mean annual flow of 43 urbanized catchments

NASA Astrophysics Data System (ADS)

Salavati, B.; Oudin, L.; Furusho, C.; Ribstein, P.

2015-06-01

It is often argued that urban areas play a significant role in catchment hydrology, but previous studies reported disparate results of urbanization impacts on stream flow. This might stem either from the difficulty to quantify the historical flow changes attributed to urbanization only (and not climate variability) or from the inability to decipher what type of urban planning is more critical for flows. In this study, we applied a hydrological model on 43 urban catchments in the United States to quantify the flow changes attributable to urbanization. Then, we tried to relate these flow changes to the changes of urban/impervious areas of the catchments. We argue that these spatial changes of urban areas can be more precisely characterized by landscape metrics, which enable analysing the patterns of historical urban growth. Landscape metrics combine the richness (the number) and evenness (the spatial distribution) of patch types represented on the landscape. Urbanization patterns within the framework of patch analysis have been widely studied but, to our knowledge, previous research works had not linked them to catchments hydrological behaviours. Our results showed that the catchments with larger impervious areas and larger mean patch areas are likely to have larger increase of runoff yield.

Effects Of Spatial Variability In Marshes On Coastal Erosion Under Storm Conditions

NASA Astrophysics Data System (ADS)

Lunghino, B.; Suckale, J.; Fringer, O. B.; Maldonado, S.; Ferreira, C.; Marras, S.; Mandel, T.

2016-12-01

To quantify the contribution of marshes in protecting coastlines, engineers and planners need to evaluate how variability in marsh characteristics and storm conditions affect erosion in the inundation zone. Previous studies show that spatial patterns in marshes significantly affect flow and sediment transport under normal tidal conditions [1, 2]. This study investigates the effect of spatial variability on floodplain sediment transport under a range of extreme hydrodynamic conditions that occur during storm events. We model the hydrodynamics of storm surge conditions on an idealized coastal floodplain by solving the 2D shallow water equations. We approximate the effect of vegetation on hydrodynamics as a constant drag coefficient. The model calculates suspended sediment transport with the advection-diffusion equation and updates morphology with erosional and depositional fluxes. We conduct numerical experiments in which we vary both the scale of the storm event and the spatial patterns of vegetation and evaluate the impact on erosion and deposition on the floodplain. We find that the alongshore extent of the vegetation is the primary control on the net volume of sediment eroded. Scour occurs in narrow channels between vegetated areas, but this does not significantly alter the net volume of sediment transported. Deposition occurs in vegetated areas under the full range of flow velocities we test. These results suggest that resolving all variability in vegetation is not necessary to quantify net sediment transport volumes at the floodplain scale. Increasing the scale of the storm event does not alter the role of spatial variability. References [1] Meire, D. W., Kondziolka, J. M., and Nepf, H. M. Interaction between neighboring vegetation patches: Impact on flow and deposition. Water Resources Research 50, 5 (2014), 3809-3825. [2] Temmerman, S., Bouma, T., Govers, G., Wang, Z., De Vries, M., and Her- man, P. Impact of vegetation on flow routing and sedimentation patterns: Three-dimensional modeling for a tidal marsh. Journal of Geophysical Research: Earth Surface 110, F4 (2005).

Functional Nonlinear Mixed Effects Models For Longitudinal Image Data

PubMed Central

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

2015-01-01

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

Seed dispersal increases local species richness and reduces spatial turnover of tropical tree seedlings

PubMed Central

Dunham, Amy E.; Duncan, Richard P.; Rogers, Haldre S.

2017-01-01

Dispersal is thought to be a key process underlying the high spatial diversity of tropical forests. Just how important dispersal is in structuring plant communities is nevertheless an open question because it is very difficult to isolate dispersal from other processes, and thereby measure its effect. Using a unique situation, the loss of vertebrate seed dispersers on the island of Guam and their presence on the neighboring islands of Saipan and Rota, we quantify the contribution of vertebrate seed dispersal to spatial patterns of diversity of tree seedlings in treefall gaps. The presence of vertebrate seed dispersers approximately doubled seedling species richness within canopy gaps and halved species turnover among gaps. Our study demonstrates that dispersal plays a key role in maintaining local and regional patterns of diversity, and highlights the potential for ongoing declines in vertebrate seed dispersers to profoundly alter tropical forest composition. PMID:28847937

Seed dispersal increases local species richness and reduces spatial turnover of tropical tree seedlings.

PubMed

Wandrag, Elizabeth M; Dunham, Amy E; Duncan, Richard P; Rogers, Haldre S

2017-10-03

Dispersal is thought to be a key process underlying the high spatial diversity of tropical forests. Just how important dispersal is in structuring plant communities is nevertheless an open question because it is very difficult to isolate dispersal from other processes, and thereby measure its effect. Using a unique situation, the loss of vertebrate seed dispersers on the island of Guam and their presence on the neighboring islands of Saipan and Rota, we quantify the contribution of vertebrate seed dispersal to spatial patterns of diversity of tree seedlings in treefall gaps. The presence of vertebrate seed dispersers approximately doubled seedling species richness within canopy gaps and halved species turnover among gaps. Our study demonstrates that dispersal plays a key role in maintaining local and regional patterns of diversity, and highlights the potential for ongoing declines in vertebrate seed dispersers to profoundly alter tropical forest composition.

Spatial and Temporal Emergence Pattern of Lyme Disease in Virginia

PubMed Central

Li, Jie; Kolivras, Korine N.; Hong, Yili; Duan, Yuanyuan; Seukep, Sara E.; Prisley, Stephen P.; Campbell, James B.; Gaines, David N.

2014-01-01

The emergence of infectious diseases over the past several decades has highlighted the need to better understand epidemics and prepare for the spread of diseases into new areas. As these diseases expand their geographic range, cases are recorded at different geographic locations over time, making the analysis and prediction of this expansion complicated. In this study, we analyze spatial patterns of the disease using a statistical smoothing analysis based on areal (census tract level) count data of Lyme disease cases in Virginia from 1998 to 2011. We also use space and space–time scan statistics to reveal the presence of clusters in the spatial and spatiotemporal distribution of Lyme disease. Our results confirm and quantify the continued emergence of Lyme disease to the south and west in states along the eastern coast of the United States. The results also highlight areas where education and surveillance needs are highest. PMID:25331806

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

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.

Segmentation of fluorescence microscopy images for quantitative analysis of cell nuclear architecture.

PubMed

Russell, Richard A; Adams, Niall M; Stephens, David A; Batty, Elizabeth; Jensen, Kirsten; Freemont, Paul S

2009-04-22

Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments.

Segmentation of Fluorescence Microscopy Images for Quantitative Analysis of Cell Nuclear Architecture

PubMed Central

Russell, Richard A.; Adams, Niall M.; Stephens, David A.; Batty, Elizabeth; Jensen, Kirsten; Freemont, Paul S.

2009-01-01

Abstract Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments. PMID:19383481

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

USGS Publications Warehouse

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

2014-01-01

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

Locating Sensors for Detecting Source-to-Target Patterns of Special Nuclear Material Smuggling: A Spatial Information Theoretic Approach

PubMed Central

Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong

2010-01-01

In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy. PMID:22163641

Controlling the influence of elastic eigenmodes on nanomagnet dynamics through pattern geometry

NASA Astrophysics Data System (ADS)

Berk, C.; Yahagi, Y.; Dhuey, S.; Cabrini, S.; Schmidt, H.

2017-03-01

The effect of the nanoscale array geometry on the interaction between optically generated surface acoustic waves (SAWs) and nanomagnet dynamics is investigated using Time-Resolved Magneto-Optical Kerr Effect Microscopy (TR-MOKE). It is demonstrated that altering the nanomagnet geometry from a periodic to a randomized aperiodic pattern effectively removes the magneto-elastic effect of SAWs on the magnetization dynamics. The efficiency of this method depends on the extent of any residual spatial correlations and is quantified by spatial Fourier analysis of the two structures. Randomization allows observation and extraction of intrinsic magnetic parameters such as spin wave frequencies and damping to be resolvable using all-optical methods, enabling the conclusion that the fabrication process does not affect the damping.

Locating sensors for detecting source-to-target patterns of special nuclear material smuggling: a spatial information theoretic approach.

PubMed

Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong

2010-01-01

In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy.

Spatial analysis of factors influencing long-term stress in the grizzly bear (Ursus arctos) population of Alberta, Canada.

PubMed

Bourbonnais, Mathieu L; Nelson, Trisalyn A; Cattet, Marc R L; Darimont, Chris T; Stenhouse, Gordon B

2013-01-01

Non-invasive measures for assessing long-term stress in free ranging mammals are an increasingly important approach for understanding physiological responses to landscape conditions. Using a spatially and temporally expansive dataset of hair cortisol concentrations (HCC) generated from a threatened grizzly bear (Ursus arctos) population in Alberta, Canada, we quantified how variables representing habitat conditions and anthropogenic disturbance impact long-term stress in grizzly bears. We characterized spatial variability in male and female HCC point data using kernel density estimation and quantified variable influence on spatial patterns of male and female HCC stress surfaces using random forests. Separate models were developed for regions inside and outside of parks and protected areas to account for substantial differences in anthropogenic activity and disturbance within the study area. Variance explained in the random forest models ranged from 55.34% to 74.96% for males and 58.15% to 68.46% for females. Predicted HCC levels were higher for females compared to males. Generally, high spatially continuous female HCC levels were associated with parks and protected areas while low-to-moderate levels were associated with increased anthropogenic disturbance. In contrast, male HCC levels were low in parks and protected areas and low-to-moderate in areas with increased anthropogenic disturbance. Spatial variability in gender-specific HCC levels reveal that the type and intensity of external stressors are not uniform across the landscape and that male and female grizzly bears may be exposed to, or perceive, potential stressors differently. We suggest observed spatial patterns of long-term stress may be the result of the availability and distribution of foods related to disturbance features, potential sexual segregation in available habitat selection, and may not be influenced by sources of mortality which represent acute traumas. In this wildlife system and others, conservation and management efforts can benefit by understanding spatial- and gender-based stress responses to landscape conditions.

Spatial Analysis of Factors Influencing Long-Term Stress in the Grizzly Bear (Ursus arctos) Population of Alberta, Canada

PubMed Central

Bourbonnais, Mathieu L.; Nelson, Trisalyn A.; Cattet, Marc R. L.; Darimont, Chris T.; Stenhouse, Gordon B.

2013-01-01

Non-invasive measures for assessing long-term stress in free ranging mammals are an increasingly important approach for understanding physiological responses to landscape conditions. Using a spatially and temporally expansive dataset of hair cortisol concentrations (HCC) generated from a threatened grizzly bear (Ursus arctos) population in Alberta, Canada, we quantified how variables representing habitat conditions and anthropogenic disturbance impact long-term stress in grizzly bears. We characterized spatial variability in male and female HCC point data using kernel density estimation and quantified variable influence on spatial patterns of male and female HCC stress surfaces using random forests. Separate models were developed for regions inside and outside of parks and protected areas to account for substantial differences in anthropogenic activity and disturbance within the study area. Variance explained in the random forest models ranged from 55.34% to 74.96% for males and 58.15% to 68.46% for females. Predicted HCC levels were higher for females compared to males. Generally, high spatially continuous female HCC levels were associated with parks and protected areas while low-to-moderate levels were associated with increased anthropogenic disturbance. In contrast, male HCC levels were low in parks and protected areas and low-to-moderate in areas with increased anthropogenic disturbance. Spatial variability in gender-specific HCC levels reveal that the type and intensity of external stressors are not uniform across the landscape and that male and female grizzly bears may be exposed to, or perceive, potential stressors differently. We suggest observed spatial patterns of long-term stress may be the result of the availability and distribution of foods related to disturbance features, potential sexual segregation in available habitat selection, and may not be influenced by sources of mortality which represent acute traumas. In this wildlife system and others, conservation and management efforts can benefit by understanding spatial- and gender-based stress responses to landscape conditions. PMID:24386273

Environmental drivers of spatial variation in whole-tree transpiration in an aspen-dominated upland-to-wetland forest gradient

NASA Astrophysics Data System (ADS)

Loranty, Michael M.; Mackay, D. Scott; Ewers, Brent E.; Adelman, Jonathan D.; Kruger, Eric L.

2008-02-01

Assumed representative center-of-stand measurements are typical inputs to models that scale forest transpiration to stand and regional extents. These inputs do not consider gradients in transpiration at stand boundaries or along moisture gradients and therefore potentially bias the large-scale estimates. We measured half-hourly sap flux (JS) for 173 trees in a spatially explicit cyclic sampling design across a topographically controlled gradient between a forested wetland and upland forest in northern Wisconsin. Our analyses focused on three dominant species in the site: quaking aspen (Populus tremuloides Michx), speckled alder (Alnus incana (DuRoi) Spreng), and white cedar (Thuja occidentalis L.). Sapwood area (AS) was used to scale JS to whole tree transpiration (EC). Because spatial patterns imply underlying processes, geostatistical analyses were employed to quantify patterns of spatial autocorrelation across the site. A simple Jarvis type model parameterized using a Monte Carlo sampling approach was used to simulate EC (EC-SIM). EC-SIM was compared with observed EC(EC-OBS) and found to reproduce both the temporal trends and spatial variance of canopy transpiration. EC-SIM was then used to examine spatial autocorrelation as a function of environmental drivers. We found no spatial autocorrelation in JS across the gradient from forested wetland to forested upland. EC was spatially autocorrelated and this was attributed to spatial variation in AS which suggests species spatial patterns are important for understanding spatial estimates of transpiration. However, the range of autocorrelation in EC-SIM decreased linearly with increasing vapor pressure deficit, implying that consideration of spatial variation in the sensitivity of canopy stomatal conductance to D is also key to accurately scaling up transpiration in space.

Evaluation of Spatial Pattern of Altered Flow Regimes on a River Network Using a Distributed Hydrological Model

PubMed Central

Ryo, Masahiro; Iwasaki, Yuichi; Yoshimura, Chihiro; Saavedra V., Oliver C.

2015-01-01

Alteration of the spatial variability of natural flow regimes has been less studied than that of the temporal variability, despite its ecological importance for river ecosystems. Here, we aimed to quantify the spatial patterns of flow regime alterations along a river network in the Sagami River, Japan, by estimating river discharge under natural and altered flow conditions. We used a distributed hydrological model, which simulates hydrological processes spatiotemporally, to estimate 20-year daily river discharge along the river network. Then, 33 hydrologic indices (i.e., Indicators of Hydrologic Alteration) were calculated from the simulated discharge to estimate the spatial patterns of their alterations. Some hydrologic indices were relatively well estimated such as the magnitude and timing of maximum flows, monthly median flows, and the frequency of low and high flow pulses. The accuracy was evaluated with correlation analysis (r > 0.4) and the Kolmogorov–Smirnov test (α = 0.05) by comparing these indices calculated from both observed and simulated discharge. The spatial patterns of the flow regime alterations varied depending on the hydrologic indices. For example, both the median flow in August and the frequency of high flow pulses were reduced by the maximum of approximately 70%, but these strongest alterations were detected at different locations (i.e., on the mainstream and the tributary, respectively). These results are likely caused by different operational purposes of multiple water control facilities. The results imply that the evaluation only at discharge gauges is insufficient to capture the alteration of the flow regime. Our findings clearly emphasize the importance of evaluating the spatial pattern of flow regime alteration on a river network where its discharge is affected by multiple water control facilities. PMID:26207997

Complex Greenland outlet glacier flow captured

PubMed Central

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

2016-01-01

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

Detecting Spatial Patterns in Biological Array Experiments

PubMed Central

ROOT, DAVID E.; KELLEY, BRIAN P.; STOCKWELL, BRENT R.

2005-01-01

Chemical genetic screening and DNA and protein microarrays are among a number of increasingly important and widely used biological research tools that involve large numbers of parallel experiments arranged in a spatial array. It is often difficult to ensure that uniform experimental conditions are present throughout the entire array, and as a result, one often observes systematic spatially correlated errors, especially when array experiments are performed using robots. Here, the authors apply techniques based on the discrete Fourier transform to identify and quantify spatially correlated errors superimposed on a spatially random background. They demonstrate that these techniques are effective in identifying common spatially systematic errors in high-throughput 384-well microplate assay data. In addition, the authors employ a statistical test to allow for automatic detection of such errors. Software tools for using this approach are provided. PMID:14567791

Design and analysis for thematic map accuracy assessment: Fundamental principles

Treesearch

Stephen V. Stehman; Raymond L. Czaplewski

1998-01-01

Land-cover maps are used in numerous natural resource applications to describe the spatial distribution and pattern of land-cover, to estimate areal extent of various cover classes, or as input into habitat suitability models, land-cover change analyses, hydrological models, and risk analyses. Accuracy assessment quantifies data quality so that map users may evaluate...

Cordilleran forest scaling dynamics and disturbance regimes quantified by aerial LiDAR

Treesearch

Tyson L. Swetnam

2013-01-01

Semi-arid forests are in a period of rapid transition as a result of unprecedented landscape scale fires, insect outbreaks, drought, and anthropogenic land use practices. Understanding how historically episodic disturbances led to coherent forest structural and spatial patterns that promoted resilience and resistance is a critical part of addressing change. Here my...

Deep groundwater mediates streamflow response to climate warming in the Oregon Cascades

Treesearch

Christina Tague; Gordon Grant; Mike Farrell; Janet Choate; Anne Jefferson

2008-01-01

Recent studies predict that projected climate change will lead to significant reductions in summer streamflow in the mountainous regions of the Western United States. Hydrologic modeling directed at quantifying these potential changes has focused on the magnitude and timing of spring snowmelt as the key control on the spatial temporal pattern of summer streamflow. We...

Vegetation-environment relations of the Chisos Mountains, Big Bend National Park, Texas

Treesearch

Helen M. Poulos; Ann E. Camp

2005-01-01

The Sky Island Archipelagos of the Sierra Madre Oriental and Occidental contain a unique array of endemic flora and fauna. Plant species composition in these elevationally restricted forests is thought to vary in relation to environmental gradients. This study quantifies plant population abundance and spatial distribution patterns in pine-oak woodlands of Big Bend...

Patterns of houses and habitat loss from 1937 to 1999 in northern Wisconsin, USA.

PubMed

Gonzalez-Abraham, Charlotte E; Radeloff, Volker C; Hawbaker, Todd J; Hammer, Roger B; Stewart, Susan I; Clayton, Murray K

2007-10-01

Rural America is witnessing widespread housing development, which is to the detriment of the environment. It has been suggested to cluster houses so that their disturbance zones overlap and thus cause less habitat loss than is the case for dispersed development. Clustering houses makes intuitive sense, but few empirical studies have quantified the spatial pattern of houses in real landscapes, assessed changes in their patterns over time, and quantified the resulting habitat loss. We addressed three basic questions: (1) What are the spatial patterns of houses and how do they change over time; (2) How much habitat is lost due to houses, and how is this affected by spatial pattern of houses; and (3) What type of habitat is most affected by housing development. We mapped 27 419 houses from aerial photos for five time periods in 17 townships in northern Wisconsin and calculated the terrestrial land area remaining after buffering each house using 100- and 500-m disturbance zones. The number of houses increased by 353% between 1937 and 1999. Ripley's K test showed that houses were significantly clustered at all time periods and at all scales. Due to the clustering, the rate at which habitat was lost (176% and 55% for 100- and 500-m buffers, respectively) was substantially lower than housing growth rates, and most land area was undisturbed (95% and 61% for 100-m and 500-m buffers, respectively). Houses were strongly clustered within 100 m of lakes. Habitat loss was lowest in wetlands but reached up to 60% in deciduous forests. Our results are encouraging in that clustered development is common in northern Wisconsin, and habitat loss is thus limited. However, the concentration of development along lakeshores causes concern, because these may be critical habitats for many species. Conservation goals can only be met if policies promote clustered development and simultaneously steer development away from sensitive ecosystems.

Assessing exotic plant species invasions and associated soil characteristics: A case study in eastern Rocky Mountain National Park, Colorado, USA, using the pixel nested plot design

USGS Publications Warehouse

Kalkhan, M.A.; Stafford, E.J.; Woodly, P.J.; Stohlgren, T.J.

2007-01-01

Rocky Mountain National Park (RMNP), Colorado, USA, contains a diversity of plant species. However, many exotic plant species have become established, potentially impacting the structure and function of native plant communities. Our goal was to quantify patterns of exotic plant species in relation to native plant species, soil characteristics, and other abiotic factors that may indicate or predict their establishment and success. Our research approach for field data collection was based on a field plot design called the pixel nested plot. The pixel nested plot provides a link to multi-phase and multi-scale spatial modeling-mapping techniques that can be used to estimate total species richness and patterns of plant diversity at finer landscape scales. Within the eastern region of RMNP, in an area of approximately 35,000 ha, we established a total of 60 pixel nested plots in 9 vegetation types. We used canonical correspondence analysis (CCA) and multiple linear regressions to quantify relationships between soil characteristics and native and exotic plant species richness and cover. We also used linear correlation, spatial autocorrelation and cross correlation statistics to test for the spatial patterns of variables of interest. CCA showed that exotic species were significantly (P < 0.05) associated with photosynthetically active radiation (r = 0.55), soil nitrogen (r = 0.58) and bare ground (r = -0.66). Pearson's correlation statistic showed significant linear relationships between exotic species, organic carbon, soil nitrogen, and bare ground. While spatial autocorrelations indicated that our 60 pixel nested plots were spatially independent, the cross correlation statistics indicated that exotic plant species were spatially associated with bare ground, in general, exotic plant species were most abundant in areas of high native species richness. This indicates that resource managers should focus on the protection of relatively rare native rich sites with little canopy cover, and fertile soils. Using the pixel nested plot approach for data collection can facilitate the ecological monitoring of these vulnerable areas at the landscape scale in a time- and cost-effective manner. ?? 2006 Elsevier B.V. All rights reserved.

Thematic and spatial resolutions affect model-based predictions of tree species distribution.

PubMed

Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei

2013-01-01

Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.

Thematic and Spatial Resolutions Affect Model-Based Predictions of Tree Species Distribution

PubMed Central

Liang, Yu; He, Hong S.; Fraser, Jacob S.; Wu, ZhiWei

2013-01-01

Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution. PMID:23861828

Environmental risk of leptospirosis infections in the Netherlands: Spatial modelling of environmental risk factors of leptospirosis in the Netherlands.

PubMed

Rood, Ente J J; Goris, Marga G A; Pijnacker, Roan; Bakker, Mirjam I; Hartskeerl, Rudy A

2017-01-01

Leptospirosis is a globally emerging zoonotic disease, associated with various climatic, biotic and abiotic factors. Mapping and quantifying geographical variations in the occurrence of leptospirosis and the surrounding environment offer innovative methods to study disease transmission and to identify associations between the disease and the environment. This study aims to investigate geographic variations in leptospirosis incidence in the Netherlands and to identify associations with environmental factors driving the emergence of the disease. Individual case data derived over the period 1995-2012 in the Netherlands were geocoded and aggregated by municipality. Environmental covariate data were extracted for each municipality and stored in a spatial database. Spatial clusters were identified using kernel density estimations and quantified using local autocorrelation statistics. Associations between the incidence of leptospirosis and the local environment were determined using Simultaneous Autoregressive Models (SAR) explicitly modelling spatial dependence of the model residuals. Leptospirosis incidence rates were found to be spatially clustered, showing a marked spatial pattern. Fitting a spatial autoregressive model significantly improved model fit and revealed significant association between leptospirosis and the coverage of arable land, built up area, grassland and sabulous clay soils. The incidence of leptospirosis in the Netherlands could effectively be modelled using a combination of soil and land-use variables accounting for spatial dependence of incidence rates per municipality. The resulting spatially explicit risk predictions provide an important source of information which will benefit clinical awareness on potential leptospirosis infections in endemic areas.

Environmental risk of leptospirosis infections in the Netherlands: Spatial modelling of environmental risk factors of leptospirosis in the Netherlands

PubMed Central

Goris, Marga G. A.; Pijnacker, Roan; Bakker, Mirjam I.; Hartskeerl, Rudy A.

2017-01-01

Leptospirosis is a globally emerging zoonotic disease, associated with various climatic, biotic and abiotic factors. Mapping and quantifying geographical variations in the occurrence of leptospirosis and the surrounding environment offer innovative methods to study disease transmission and to identify associations between the disease and the environment. This study aims to investigate geographic variations in leptospirosis incidence in the Netherlands and to identify associations with environmental factors driving the emergence of the disease. Individual case data derived over the period 1995–2012 in the Netherlands were geocoded and aggregated by municipality. Environmental covariate data were extracted for each municipality and stored in a spatial database. Spatial clusters were identified using kernel density estimations and quantified using local autocorrelation statistics. Associations between the incidence of leptospirosis and the local environment were determined using Simultaneous Autoregressive Models (SAR) explicitly modelling spatial dependence of the model residuals. Leptospirosis incidence rates were found to be spatially clustered, showing a marked spatial pattern. Fitting a spatial autoregressive model significantly improved model fit and revealed significant association between leptospirosis and the coverage of arable land, built up area, grassland and sabulous clay soils. The incidence of leptospirosis in the Netherlands could effectively be modelled using a combination of soil and land-use variables accounting for spatial dependence of incidence rates per municipality. The resulting spatially explicit risk predictions provide an important source of information which will benefit clinical awareness on potential leptospirosis infections in endemic areas. PMID:29065186

The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach.

PubMed

Guo, Qiang; Xu, Pengpeng; Pei, Xin; Wong, S C; Yao, Danya

2017-02-01

Pedestrian safety is increasingly recognized as a major public health concern. Extensive safety studies have been conducted to examine the influence of multiple variables on the occurrence of pedestrian-vehicle crashes. However, the explicit relationship between pedestrian safety and road network characteristics remains unknown. This study particularly focused on the role of different road network patterns on the occurrence of crashes involving pedestrians. A global integration index via space syntax was introduced to quantify the topological structures of road networks. The Bayesian Poisson-lognormal (PLN) models with conditional autoregressive (CAR) prior were then developed via three different proximity structures: contiguity, geometry-centroid distance, and road network connectivity. The models were also compared with the PLN counterpart without spatial correlation effects. The analysis was based on a comprehensive crash dataset from 131 selected traffic analysis zones in Hong Kong. The results indicated that higher global integration was associated with more pedestrian-vehicle crashes; the irregular pattern network was proved to be safest in terms of pedestrian crash occurrences, whereas the grid pattern was the least safe; the CAR model with a neighborhood structure based on road network connectivity was found to outperform in model goodness-of-fit, implying the importance of accurately accounting for spatial correlation when modeling spatially aggregated crash data. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

A Spatial-frequency Method for Analyzing Antenna-to-Probe Interactions in Near-field Antenna Measurements.

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

Brock, Billy C.

The measurement of the radiation characteristics of an antenna on a near-field range requires that the antenna under test be located very close to the near-field probe. Although the direct coupling is utilized for characterizing the near field, this close proximity also presents the opportunity for significant undesired interactions (for example, reflections) to occur between the antenna and the near-field probe. When uncompensated, these additional interactions will introduce error into the measurement, increasing the uncertainty in the final gain pattern obtained through the near-field-to-far-field transformation. Quantifying this gain-uncertainty contribution requires quantifying the various additional interactions. A method incorporating spatial-frequency analysismore » is described which allows the dominant interaction contributions to be easily identified and quantified. In addition to identifying the additional antenna-to-probe interactions, the method also allows identification and quantification of interactions with other nearby objects within the measurement room. Because the method is a spatial-frequency method, wide-bandwidth data is not required, and it can be applied even when data is available at only a single temporal frequency. This feature ensures that the method can be applied to narrow-band antennas, where a similar time-domain analysis would not be possible. - 3 - - 4 -« less

Socio-ecological factors and hand, foot and mouth disease in dry climate regions: a Bayesian spatial approach in Gansu, China

NASA Astrophysics Data System (ADS)

Gou, Faxiang; Liu, Xinfeng; Ren, Xiaowei; Liu, Dongpeng; Liu, Haixia; Wei, Kongfu; Yang, Xiaoting; Cheng, Yao; Zheng, Yunhe; Jiang, Xiaojuan; Li, Juansheng; Meng, Lei; Hu, Wenbiao

2017-01-01

The influence of socio-ecological factors on hand, foot and mouth disease (HFMD) were explored in this study using Bayesian spatial modeling and spatial patterns identified in dry regions of Gansu, China. Notified HFMD cases and socio-ecological data were obtained from the China Information System for Disease Control and Prevention, Gansu Yearbook and Gansu Meteorological Bureau. A Bayesian spatial conditional autoregressive model was used to quantify the effects of socio-ecological factors on the HFMD and explore spatial patterns, with the consideration of its socio-ecological effects. Our non-spatial model suggests temperature (relative risk (RR) 1.15, 95 % CI 1.01-1.31), GDP per capita (RR 1.19, 95 % CI 1.01-1.39) and population density (RR 1.98, 95 % CI 1.19-3.17) to have a significant effect on HFMD transmission. However, after controlling for spatial random effects, only temperature (RR 1.25, 95 % CI 1.04-1.53) showed significant association with HFMD. The spatial model demonstrates temperature to play a major role in the transmission of HFMD in dry regions. Estimated residual variation after taking into account the socio-ecological variables indicated that high incidences of HFMD were mainly clustered in the northwest of Gansu. And, spatial structure showed a unique distribution after taking account of socio-ecological effects.

Quantifying site-specific physical heterogeneity within an estuarine seascape

USGS Publications Warehouse

Kennedy, Cristina G.; Mather, Martha E.; Smith, Joseph M.

2017-01-01

Quantifying physical heterogeneity is essential for meaningful ecological research and effective resource management. Spatial patterns of multiple, co-occurring physical features are rarely quantified across a seascape because of methodological challenges. Here, we identified approaches that measured total site-specific heterogeneity, an often overlooked aspect of estuarine ecosystems. Specifically, we examined 23 metrics that quantified four types of common physical features: (1) river and creek confluences, (2) bathymetric variation including underwater drop-offs, (3) land features such as islands/sandbars, and (4) major underwater channel networks. Our research at 40 sites throughout Plum Island Estuary (PIE) provided solutions to two problems. The first problem was that individual metrics that measured heterogeneity of a single physical feature showed different regional patterns. We solved this first problem by combining multiple metrics for a single feature using a within-physical feature cluster analysis. With this approach, we identified sites with four different types of confluences and three different types of underwater drop-offs. The second problem was that when multiple physical features co-occurred, new patterns of total site-specific heterogeneity were created across the seascape. This pattern of total heterogeneity has potential ecological relevance to structure-oriented predators. To address this second problem, we identified sites with similar types of total physical heterogeneity using an across-physical feature cluster analysis. Then, we calculated an additive heterogeneity index, which integrated all physical features at a site. Finally, we tested if site-specific additive heterogeneity index values differed for across-physical feature clusters. In PIE, the sites with the highest additive heterogeneity index values were clustered together and corresponded to sites where a fish predator, adult striped bass (Morone saxatilis), aggregated in a related acoustic tracking study. In summary, we have shown general approaches to quantifying site-specific heterogeneity.

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

PubMed

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

2018-02-01

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

Climate and weather influences on spatial temporal patterns of mountain pine beetle populations in Washington and Oregon

Treesearch

Haiganoush K. Preisler; Jeffrey A. Hicke; Alan A. Ager; Jane L. Hayes

2012-01-01

Widespread outbreaks of mountain pine beetle in North America have drawn the attention of scientists, forest managers, and the public. There is strong evidence that climate change has contributed to the extent and severity of recent outbreaks. Scientists are interested in quantifying relationships between bark beetle population dynamics and trends in climate. Process...

Development of a method using multispectral imagery and spatial pattern metrics to quantify stress to wheat fields caused by Diuraphis noxia

USDA-ARS?s Scientific Manuscript database

The Russian wheat aphid, Diuraphis noxia, is an important pest of winter wheat, Triticum aestivum, and barley, Hordeum vulgare that has caused an annual economic loss estimated at over 1 billion dollars since it first appeared in the United States. The objective of this study was to determine the p...

Quantifying agricultural drought in tallgrass prairie region in the U.S. Southern Great Plains through analysis of a water-related vegetation index from MODIS images

USDA-ARS?s Scientific Manuscript database

Severe droughts in the Southern Great Plains (SGP: Kansas, Oklahoma, and Texas) in recent years have reduced the productivity of tallgrass prairie and resulted in substantial economic losses to the beef cattle industry in this region. Understanding spatial and temporal patterns of agricultural droug...

Simulation modeling of forest landscape disturbances: Where do we go from here?

Treesearch

Ajith H. Perera; Brian R. Sturtevant; Lisa J. Buse

2015-01-01

It was nearly a quarter-century ago when Turner and Gardner (1991) drew attention to methods of quantifying landscape patterns and processes, including simulation modeling. The many authors who contributed to that seminal text collectively signaled the emergence of a new field—spatially explicit simulation modeling of broad-scale ecosystem dynamics. Of particular note...

Neural mechanisms underlying spatial realignment during adaptation to optical wedge prisms.

PubMed

Chapman, Heidi L; Eramudugolla, Ranmalee; Gavrilescu, Maria; Strudwick, Mark W; Loftus, Andrea; Cunnington, Ross; Mattingley, Jason B

2010-07-01

Visuomotor adaptation to a shift in visual input produced by prismatic lenses is an example of dynamic sensory-motor plasticity within the brain. Prism adaptation is readily induced in healthy individuals, and is thought to reflect the brain's ability to compensate for drifts in spatial calibration between different sensory systems. The neural correlate of this form of functional plasticity is largely unknown, although current models predict the involvement of parieto-cerebellar circuits. Recent studies that have employed event-related functional magnetic resonance imaging (fMRI) to identify brain regions associated with prism adaptation have discovered patterns of parietal and cerebellar modulation as participants corrected their visuomotor errors during the early part of adaptation. However, the role of these regions in the later stage of adaptation, when 'spatial realignment' or true adaptation is predicted to occur, remains unclear. Here, we used fMRI to quantify the distinctive patterns of parieto-cerebellar activity as visuomotor adaptation develops. We directly contrasted activation patterns during the initial error correction phase of visuomotor adaptation with that during the later spatial realignment phase, and found significant recruitment of the parieto-cerebellar network--with activations in the right inferior parietal lobe and the right posterior cerebellum. These findings provide the first evidence of both cerebellar and parietal involvement during the spatial realignment phase of prism adaptation. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Variance in composition of inquiline communities in leaves of Sarracenia purpurea L. on multiple spatial scales.

PubMed

Harvey, E; Miller, T E

1996-11-01

A survey of the abundances of species that inhabit the water-bearing leaves of the pitcher plant Sarracenia purpurea was conducted at several different spatial scales in northern Florida. Individual leaves are hosts to communities of inquiline species, including mosquitoes, midges, mites, copepods, cladocerans, and a diverse bacterial assemblage. Inquiline communities were quantified from four pitchers per plant, three plants per subpopulation, two subpopulations per population, and three populations. Species varied in abundance at different spatial scales. Variation in the abundances of mosquitoes and copepods was not significantly associated with any spatial scale. Midges varied in abundance at the level of populations; one population contained significantly more midges than the other two. Cladocerans varied at the level of the subpopulation, whereas mites varied at the level of the individual plants. Bacterial communities were described by means of Biolog plates, which quantify the types of carbon media used by the bacteria in each pitcher. Bacterial communities were found to vary significantly in composition among individual plants but not among populations or subpopulations. These results suggest that independent factors determining the abundances of individual species are important in determining community patterns in pitcher-plant inquilines.

Integrating spatially explicit representations of landscape perceptions into land change research

USGS Publications Warehouse

Dorning, Monica; Van Berkel, Derek B.; Semmens, Darius J.

2017-01-01

Purpose of ReviewHuman perceptions of the landscape can influence land-use and land-management decisions. Recognizing the diversity of landscape perceptions across space and time is essential to understanding land change processes and emergent landscape patterns. We summarize the role of landscape perceptions in the land change process, demonstrate advances in quantifying and mapping landscape perceptions, and describe how these spatially explicit techniques have and may benefit land change research.Recent FindingsMapping landscape perceptions is becoming increasingly common, particularly in research focused on quantifying ecosystem services provision. Spatial representations of landscape perceptions, often measured in terms of landscape values and functions, provide an avenue for matching social and environmental data in land change studies. Integrating these data can provide new insights into land change processes, contribute to landscape planning strategies, and guide the design and implementation of land change models.SummaryChallenges remain in creating spatial representations of human perceptions. Maps must be accompanied by descriptions of whose perceptions are being represented and the validity and uncertainty of those representations across space. With these considerations, rapid advancements in mapping landscape perceptions hold great promise for improving representation of human dimensions in landscape ecology and land change research.

Evaluation of Simulated Clinical Breast Exam Motion Patterns Using Marker-Less Video Tracking

PubMed Central

Azari, David P.; Pugh, Carla M.; Laufer, Shlomi; Kwan, Calvin; Chen, Chia-Hsiung; Yen, Thomas Y.; Hu, Yu Hen; Radwin, Robert G.

2016-01-01

Objective This study investigates using marker-less video tracking to evaluate hands-on clinical skills during simulated clinical breast examinations (CBEs). Background There are currently no standardized and widely accepted CBE screening techniques. Methods Experienced physicians attending a national conference conducted simulated CBEs presenting different pathologies with distinct tumorous lesions. Single hand exam motion was recorded and analyzed using marker-less video tracking. Four kinematic measures were developed to describe temporal (time pressing and time searching) and spatial (area covered and distance explored) patterns. Results Mean differences between time pressing, area covered, and distance explored varied across the simulated lesions. Exams were objectively categorized as either sporadic, localized, thorough, or efficient for both temporal and spatial categories based on spatiotemporal characteristics. The majority of trials were temporally or spatially thorough (78% and 91%), exhibiting proportionally greater time pressing and time searching (temporally thorough) and greater area probed with greater distance explored (spatially thorough). More efficient exams exhibited proportionally more time pressing with less time searching (temporally efficient) and greater area probed with less distance explored (spatially efficient). Just two (5.9 %) of the trials exhibited both high temporal and spatial efficiency. Conclusions Marker-less video tracking was used to discriminate different examination techniques and measure when an exam changes from general searching to specific probing. The majority of participants exhibited more thorough than efficient patterns. Application Marker-less video kinematic tracking may be useful for quantifying clinical skills for training and assessment. PMID:26546381

Urban Natural Environments, Obesity, and Health-Related Quality of Life among Hispanic Children Living in Inner-City Neighborhoods

PubMed Central

Kim, Jun-Hyun; Lee, Chanam; Sohn, Wonmin

2016-01-01

Although a substantial body of literature has provided evidence supporting the positive effects of natural environments on well-being, little has been known about the specific spatial patterns of urban nature in promoting health-related quality of life (HRQOL) among children. This study assessed the association that the urban natural environment measured by landscape spatial patterns may have with obesity and HRQOL among Hispanic children. Ninety-two 4th and 5th grade students were recruited from Houston, Texas, and the Pediatric Quality of Life Inventory (PedsQL) was used to capture the children’s HRQOL. The quality of urban natural environments was assessed by quantifying the landscape spatial patterns, using landscape indices generated by Geographic Information Systems and remote sensing. From the bivariate analyses, children’s body mass index showed a significantly negative association with their HRQOL. After controlling for socio-demographic factors, the results revealed that larger and more tree areas were positively correlated with children’s HRQOL. In addition, those children living in areas with tree patches further apart from each other showed higher HRQOL. This research adds to the current multi-disciplinary area of research on environment-health relationships by investigating the roles of urban greeneries and linking their spatial structures with children’s HRQOL. PMID:26771623

Urban Natural Environments, Obesity, and Health-Related Quality of Life among Hispanic Children Living in Inner-City Neighborhoods.

PubMed

Kim, Jun-Hyun; Lee, Chanam; Sohn, Wonmin

2016-01-12

Although a substantial body of literature has provided evidence supporting the positive effects of natural environments on well-being, little has been known about the specific spatial patterns of urban nature in promoting health-related quality of life (HRQOL) among children. This study assessed the association that the urban natural environment measured by landscape spatial patterns may have with obesity and HRQOL among Hispanic children. Ninety-two 4th and 5th grade students were recruited from Houston, Texas, and the Pediatric Quality of Life Inventory (PedsQL) was used to capture the children's HRQOL. The quality of urban natural environments was assessed by quantifying the landscape spatial patterns, using landscape indices generated by Geographic Information Systems and remote sensing. From the bivariate analyses, children's body mass index showed a significantly negative association with their HRQOL. After controlling for socio-demographic factors, the results revealed that larger and more tree areas were positively correlated with children's HRQOL. In addition, those children living in areas with tree patches further apart from each other showed higher HRQOL. This research adds to the current multi-disciplinary area of research on environment-health relationships by investigating the roles of urban greeneries and linking their spatial structures with children's HRQOL.

Quantifying opening-mode fracture spatial organization in horizontal wellbore image logs, core and outcrop: Application to Upper Cretaceous Frontier Formation tight gas sandstones, USA

NASA Astrophysics Data System (ADS)

Li, J. Z.; Laubach, S. E.; Gale, J. F. W.; Marrett, R. A.

2018-03-01

The Upper Cretaceous Frontier Formation is a naturally fractured gas-producing sandstone in Wyoming. Regionally, random and statistically more clustered than random patterns exist in the same upper to lower shoreface depositional facies. East-west- and north-south-striking regional fractures sampled using image logs and cores from three horizontal wells exhibit clustered patterns, whereas data collected from east-west-striking fractures in outcrop have patterns that are indistinguishable from random. Image log data analyzed with the correlation count method shows clusters ∼35 m wide and spaced ∼50 to 90 m apart as well as clusters up to 12 m wide with periodic inter-cluster spacings. A hierarchy of cluster sizes exists; organization within clusters is likely fractal. These rocks have markedly different structural and burial histories, so regional differences in degree of clustering are unsurprising. Clustered patterns correspond to fractures having core quartz deposition contemporaneous with fracture opening, circumstances that some models suggest might affect spacing patterns by interfering with fracture growth. Our results show that quantifying and identifying patterns as statistically more or less clustered than random delineates differences in fracture patterns that are not otherwise apparent but that may influence gas and water production, and therefore may be economically important.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Effects of ignition location models on the burn patterns of simulated wildfires

USGS Publications Warehouse

Bar-Massada, A.; Syphard, A.D.; Hawbaker, T.J.; Stewart, S.I.; Radeloff, V.C.

2011-01-01

Fire simulation studies that use models such as FARSITE often assume that ignition locations are distributed randomly, because spatially explicit information about actual ignition locations are difficult to obtain. However, many studies show that the spatial distribution of ignition locations, whether human-caused or natural, is non-random. Thus, predictions from fire simulations based on random ignitions may be unrealistic. However, the extent to which the assumption of ignition location affects the predictions of fire simulation models has never been systematically explored. Our goal was to assess the difference in fire simulations that are based on random versus non-random ignition location patterns. We conducted four sets of 6000 FARSITE simulations for the Santa Monica Mountains in California to quantify the influence of random and non-random ignition locations and normal and extreme weather conditions on fire size distributions and spatial patterns of burn probability. Under extreme weather conditions, fires were significantly larger for non-random ignitions compared to random ignitions (mean area of 344.5 ha and 230.1 ha, respectively), but burn probability maps were highly correlated (r = 0.83). Under normal weather, random ignitions produced significantly larger fires than non-random ignitions (17.5 ha and 13.3 ha, respectively), and the spatial correlations between burn probability maps were not high (r = 0.54), though the difference in the average burn probability was small. The results of the study suggest that the location of ignitions used in fire simulation models may substantially influence the spatial predictions of fire spread patterns. However, the spatial bias introduced by using a random ignition location model may be minimized if the fire simulations are conducted under extreme weather conditions when fire spread is greatest. ?? 2010 Elsevier Ltd.

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

USGS Publications Warehouse

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

2009-01-01

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

Global terrestrial water storage connectivity revealed using complex climate network analyses

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

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

PubMed

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

2017-07-01

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

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

USGS Publications Warehouse

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

2017-01-01

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

Submillimeter-scale heterogeneity of labile phosphorus in sediments characterized by diffusive gradients in thin films and spatial analysis.

PubMed

Meng, Yuting; Ding, Shiming; Gong, Mengdan; Chen, Musong; Wang, Yan; Fan, Xianfang; Shi, Lei; Zhang, Chaosheng

2018-03-01

Sediments have a heterogeneous distribution of labile redox-sensitive elements due to a drastic downward transition from oxic to anoxic condition as a result of organic matter degradation. Characterization of the heterogeneous nature of sediments is vital for understanding of small-scale biogeochemical processes. However, there are limited reports on the related specialized methodology. In this study, the monthly distributions of labile phosphorus (P), a redox-sensitive limiting nutrient, were measured in the eutrophic Lake Taihu by Zr-oxide diffusive gradients in thin films (Zr-oxide DGT) on a two-dimensional (2D) submillimeter level. Geographical information system (GIS) techniques were used to visualize the labile P distribution at such a micro-scale, showing that the DGT-labile P was low in winter and high in summer. Spatial analysis methods, including semivariogram and Moran's I, were used to quantify the spatial variation of DGT-labile P. The distribution of DGT-labile P had clear submillimeter-scale spatial patterns with significant spatial autocorrelation during the whole year and displayed seasonal changes. High values of labile P with strong spatial variation were observed in summer, while low values of labile P with relatively uniform spatial patterns were detected in winter, demonstrating the strong influences of temperature on the mobility and spatial distribution of P in sediment profiles. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantifying the morphodynamics of river restoration schemes using Unmanned Aerial Vehicles (UAVs)

NASA Astrophysics Data System (ADS)

Williams, Richard; Byrne, Patrick; Gilles, Eric; Hart, John; Hoey, Trevor; Maniatis, George; Moir, Hamish; Reid, Helen; Ves, Nikolas

2017-04-01

River restoration schemes are particularly sensitive to morphological adjustment during the first set of high-flow events that they are subjected to. Quantifying elevation change associated with morphological adjustment can contribute to improved adaptive decision making to ensure river restoration scheme objectives are achieved. To date the relatively high cost, technical demands and challenging logistics associated with acquiring repeat, high-resolution topographic surveys has resulted in a significant barrier to monitoring the three-dimensional morphodynamics of river restoration schemes. The availability of low-cost, consumer grade Unmanned Aerial Vehicles that are capable of acquiring imagery for processing using Structure-from-Motion Multi-View Stereo (SfM MVS) photogrammetry has the potential to transform the survey the morphodynamics of river restoration schemes. Application guidance does, however, need to be developed to fully exploit the advances of UAV technology and SfM MVS processing techniques. In particular, there is a need to quantify the effect of the number and spatial distribution of ground targets on vertical error. This is particularly significant because vertical errors propagate when mapping morphological change, and thus determine the evidence that is available for decision making. This presentation presents results from a study that investigated how the number and spatial distribution of targets influenced vertical error, and then used the findings to determine survey protocols for a monitoring campaign that has quantified morphological change across a number of restoration schemes. At the Swindale river restoration scheme, Cumbria, England, 31 targets were distributed across a 700 m long reach and the centre of each target was surveyed using RTK-GPS. Using the targets as General Control Points (GCPs) or checkpoints, they were divided into three different spatial patterns (centre, edge and random) and used for processing images acquired from a SenseFly Swinglet CAM UAV with a Canon IXUS 240 HS camera. Results indicate that if targets were distributed centrally then vertical distortions would be most notable in outer region of the processing domain; if an edge pattern was used then vertical errors were greatest in the central region of the processing domain; if targets were distributed randomly then errors were more evenly distributed. For this optimal random layout, vertical errors were lowest when 15 to 23 targets were used as GCPs. The best solution achieved planimetric (XY) errors of 0.006 m and vertical (Z) errors of 0.05 m. This result was used to determine target density and distribution for repeat surveys on two other restoration schemes, Whit Beck (Cumbria, England) and Allt Lorgy (Highlands, Scotland). These repeat surveys have been processed to produce DEMs of Difference (DoDs). The DoDs have been used to quantify the spatial distribution of erosion and deposition of these schemes due to high-flow events. Broader interpretation enables insight into patterns of morphological sensitivity that are related to scheme design.

Quantifying stream thermal regimes at management-pertinent scales: combining thermal infrared and stationary stream temperature data in a novel modeling framework.

USGS Publications Warehouse

Vatland, Shane J.; Gresswell, Robert E.; Poole, Geoffrey C.

2015-01-01

Accurately quantifying stream thermal regimes can be challenging because stream temperatures are often spatially and temporally heterogeneous. In this study, we present a novel modeling framework that combines stream temperature data sets that are continuous in either space or time. Specifically, we merged the fine spatial resolution of thermal infrared (TIR) imagery with hourly data from 10 stationary temperature loggers in a 100 km portion of the Big Hole River, MT, USA. This combination allowed us to estimate summer thermal conditions at a relatively fine spatial resolution (every 100 m of stream length) over a large extent of stream (100 km of stream) during during the warmest part of the summer. Rigorous evaluation, including internal validation, external validation with spatially continuous instream temperature measurements collected from a Langrangian frame of reference, and sensitivity analyses, suggests the model was capable of accurately estimating longitudinal patterns in summer stream temperatures for this system Results revealed considerable spatial and temporal heterogeneity in summer stream temperatures and highlighted the value of assessing thermal regimes at relatively fine spatial and temporal scales. Preserving spatial and temporal variability and structure in abiotic stream data provides a critical foundation for understanding the dynamic, multiscale habitat needs of mobile stream organisms. Similarly, enhanced understanding of spatial and temporal variation in dynamic water quality attributes, including temporal sequence and spatial arrangement, can guide strategic placement of monitoring equipment that will subsequently capture variation in environmental conditions directly pertinent to research and management objectives.

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.

Spatial and temporal distribution of trunk-injected imidacloprid in apple tree canopies.

PubMed

Aćimović, Srđan G; VanWoerkom, Anthony H; Reeb, Pablo D; Vandervoort, Christine; Garavaglia, Thomas; Cregg, Bert M; Wise, John C

2014-11-01

Pesticide use in orchards creates drift-driven pesticide losses which contaminate the environment. Trunk injection of pesticides as a target-precise delivery system could greatly reduce pesticide losses. However, pesticide efficiency after trunk injection is associated with the underinvestigated spatial and temporal distribution of the pesticide within the tree crown. This study quantified the spatial and temporal distribution of trunk-injected imidacloprid within apple crowns after trunk injection using one, two, four or eight injection ports per tree. The spatial uniformity of imidacloprid distribution in apple crowns significantly increased with more injection ports. Four ports allowed uniform spatial distribution of imidacloprid in the crown. Uniform and non-uniform spatial distributions were established early and lasted throughout the experiment. The temporal distribution of imidacloprid was significantly non-uniform. Upper and lower crown positions did not significantly differ in compound concentration. Crown concentration patterns indicated that imidacloprid transport in the trunk occurred through radial diffusion and vertical uptake with a spiral pattern. By showing where and when a trunk-injected compound is distributed in the apple tree canopy, this study addresses a key knowledge gap in terms of explaining the efficiency of the compound in the crown. These findings allow the improvement of target-precise pesticide delivery for more sustainable tree-based agriculture. © 2014 Society of Chemical Industry.

Introducing Co-Activation Pattern Metrics to Quantify Spontaneous Brain Network Dynamics

PubMed Central

Chen, Jingyuan E.; Chang, Catie; Greicius, Michael D.; Glover, Gary H.

2015-01-01

Recently, fMRI researchers have begun to realize that the brain's intrinsic network patterns may undergo substantial changes during a single resting state (RS) scan. However, despite the growing interest in brain dynamics, metrics that can quantify the variability of network patterns are still quite limited. Here, we first introduce various quantification metrics based on the extension of co-activation pattern (CAP) analysis, a recently proposed point-process analysis that tracks state alternations at each individual time frame and relies on very few assumptions; then apply these proposed metrics to quantify changes of brain dynamics during a sustained 2-back working memory (WM) task compared to rest. We focus on the functional connectivity of two prominent RS networks, the default-mode network (DMN) and executive control network (ECN). We first demonstrate less variability of global Pearson correlations with respect to the two chosen networks using a sliding-window approach during WM task compared to rest; then we show that the macroscopic decrease in variations in correlations during a WM task is also well characterized by the combined effect of a reduced number of dominant CAPs, increased spatial consistency across CAPs, and increased fractional contributions of a few dominant CAPs. These CAP metrics may provide alternative and more straightforward quantitative means of characterizing brain network dynamics than time-windowed correlation analyses. PMID:25662866

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2014-05-01

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

Space invaders? A search for patterns underlying the coexistence of alien black rats and Galápagos rice rats.

PubMed

Harris, Donna B; Gregory, Stephen D; Macdonald, David W

2006-08-01

The introduction and spread of the black rat Rattus rattus is believed to have caused the worst decline of any vertebrate taxon in Galápagos. However, the "extinct" Santiago rice rat Nesoryzomys swarthi has recently been rediscovered in sympatry with R. rattus providing the first exception to this general pattern of displacement. We carried out an exploratory investigation of this novel system with the aim of identifying patterns that may facilitate the apparent coexistence of the two species. We carried out an extensive survey of Santiago Island to map the current distribution of the endemic rice rat and to explore broad scale distribution-habitat associations. We then used live-trapping, radio-tracking, and spool-and-line tracking to quantify abundance-habitat correlations and to test for evidence of interspecific spatial segregation, alteration of N. swarthi activity patterns (spatial and temporal), and microhabitat partitioning. We found that N. swarthi has disappeared from part of its historical range and appears to be restricted to a 14 km stretch of the north-central coast, characterised by high density of the cactus Opuntia galapageia. In contrast, the generalist R. rattus was found at all survey sites. We found no evidence of spatial segregation, and home range size, temporal activity and density of N. swarthi did not vary with local density of R. rattus. However, pre-dawn and post-dusk N. swarthi activity levels increased with R. rattus density perhaps reflecting an increase in foraging effort necessary to compensate for the costs of interspecific exploitation or interference competition. The distribution, microhabitat selection, and abundance-habitat relations of N. swarthi suggest that the endemic cactus O. galapageia may facilitate interspecific coexistence. Further research should include a comparison of inter-seasonal resource preference and foraging activity of the two species coupled with replicated field experiments to confirm and quantify competition and to elucidate the mechanism of competitive coexistence.

Self-organization and forcing templates in coastal barrier response to storms

NASA Astrophysics Data System (ADS)

Lazarus, E.

2015-12-01

When a storm event pushes water up and over a coastal barrier, cross-shore flow transports sediment from the barrier face to the back-barrier environment. This natural physical process is called "overwash", and "washover" is the sedimentary deposit it forms. Overwash and washover support critical coastal habitats, and enable barriers to maintain their height and width relative to rising sea level. On developed barrier coasts, overwash constitutes a natural hazard, which sea-level rise will exacerbate. Overwash is also a prerequisite for barrier breaching and coastal flooding. Predicting occurrence and characteristics of overwash and washover has significant societal value. Hazard models typically assume that pre-storm barrier morphology determines how the barrier changes during a storm. However, classic work has documented the absence of a relationship between pre/post-storm topography in some cases, and has also identified rhythmic patterns in washover alongshore. Previous explanations for these spatial patterns have looked to forcing templates, forms that get imprinted in the barrier shape. An alternative explanation is that washover patterns self-organize, emerging from feedbacks between water flow and sediment transport. Self-organization and forcing templates are often framed as mutually exclusive, but patterns likely form across a continuum of conditions. Here, I use data from a new physical experiment to suggest that spatial patterns in washover can self-organize within the limit of a forcing template of some critical "strength", beyond which pre/post-storm morphologies are highly correlated. Quantifying spatial patterns in washover deposits opens exciting questions regarding coastal morphodynamic response to storms. Measurement of relative template strength over extended spatial (and temporal) scales has the potential to improve hazard assessment and prediction, particularly where template strength is low and self-organization dominates barrier change.

Habitat use of the Louisiana Waterthrush during the non-breeding season in Puerto Rico

Treesearch

M.T. Hallworth; L.R. Reitsma; K. Parent

2011-01-01

We used radiotelemetry to quantify habitat and spatial use patterns of neighboring Louisiana Waterthrush (Parkesia motacilla) along two streams in the Caribbean National Forest in Puerto Rico during 2005–2007. Home range sizes varied with younger birds having larger home ranges and core areas than older birds. All birds occupied some length of stream but a wide range...

Multivariate landscape trajectory analysis: An example using simulation modeling of American marten habitat change under four timber harvest scenarios

Treesearch

Samuel A. Cushman; Kevin McGarigal

2007-01-01

Integrating temporal variabilily into spatial analyses is one of the abiding challenges in landscape ecology. In this chapter we use landscape trajectory analysis to assess changes in landscape patterns over time. Landscape trajectory analysis is an approach to quantify changes in landscape structure over time. There are three key concepts which underlie the...

Rural and suburban sprawl in the U.S. midwest from 1940 to 2000 in its relation to forest fragmentation

Treesearch

Volker C. Radeloff; Roger B. Hammer; Susan I. Stewart

2005-01-01

Housing growth and its environmental effects pose major conservation challenges. We sought to (]) quantify spatial and temporal patterns of housing growth across the US. Midwest from 1940-2000, (2) identify ecoregions strongly affected by housing growth, (3) assess the extent to which forests occur near housing, and (4) relate housing to forest fragmentation. We used...

Identification of Resting State Networks Involved in Executive Function.

PubMed

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

2016-06-01

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

Delayed response and biosonar perception explain movement coordination in trawling bats.

PubMed

Giuggioli, Luca; McKetterick, Thomas J; Holderied, Marc

2015-03-01

Animal coordinated movement interactions are commonly explained by assuming unspecified social forces of attraction, repulsion and alignment with parameters drawn from observed movement data. Here we propose and test a biologically realistic and quantifiable biosonar movement interaction mechanism for echolocating bats based on spatial perceptual bias, i.e. actual sound field, a reaction delay, and observed motor constraints in speed and acceleration. We found that foraging pairs of bats flying over a water surface swapped leader-follower roles and performed chases or coordinated manoeuvres by copying the heading a nearby individual has had up to 500 ms earlier. Our proposed mechanism based on the interplay between sensory-motor constraints and delayed alignment was able to recreate the observed spatial actor-reactor patterns. Remarkably, when we varied model parameters (response delay, hearing threshold and echolocation directionality) beyond those observed in nature, the spatio-temporal interaction patterns created by the model only recreated the observed interactions, i.e. chases, and best matched the observed spatial patterns for just those response delays, hearing thresholds and echolocation directionalities found to be used by bats. This supports the validity of our sensory ecology approach of movement coordination, where interacting bats localise each other by active echolocation rather than eavesdropping.

New approaches to spatially analyse primary health care usage patterns in rural South Africa.

PubMed

Tanser, F; Hosegood, V; Benzler, J; Solarsh, G

2001-10-01

To develop indices to quantitatively assess and understand the spatial usage patterns of health facilities in the Hlabisa district of South Africa. We mapped and interviewed more than 23 000 homesteads (approximately 200 000 people) in Hlabisa district, South Africa and spatially analysed their modal primary health usage patterns using a geographical information system. We generated contour maps of health service use and quantified the relationship between clinic catchments and distance-defined catchments using inclusion and exclusion error. We propose the distance usage index (DUI) as an overall spatial measure of clinic usage. This index is the sum of the distances from clinic to all client homesteads divided by the sum of the distances from clinic to all homesteads within its distance-defined catchment. The index encompasses inclusion, exclusion, and strength of patient attraction for each clinic. Eighty-seven per cent of homesteads use the nearest clinic. Residents of homesteads travel an average Euclidean distance of 4.72 km to attend clinics. There is a significant logarithmic relationship between distance from clinic and their use by homesteads (r(2)=0.774, P < 0.0001). The DUI values range between 31 and 198% (mean=110%, SD=43.7) for 12 clinics and highlight clinic usage patterns across the district. The DUI is a powerful and informative composite measure of clinic usage. The results of the study have important implications for health care provision in developing countries.

Pattern Formation and Strong Nonlinear Interactions in Exciton-Polariton Condensates

NASA Astrophysics Data System (ADS)

Ge, Li; Nersisyan, Ani; Oztop, Baris; Tureci, Hakan

2014-03-01

Exciton-polaritons generated by light-induced potentials can spontaneously condense into macroscopic quantum states that display nontrivial spatial and temporal density modulation. While these patterns and their dynamics can be reproduced through the solution of the generalized Gross-Pitaevskii equation, a predictive theory of their thresholds, oscillation frequencies, and multi-pattern interactions has so far been lacking. Here we represent such an approach based on current-carrying quasi-modes of the non-Hermitian potential induced by the pump. The presented theory allows us to capture the patterns formed in the steady-state directly and account for nonlinearities exactly. We find a simple but powerful expression for thresholds of condensation and the associated frequencies of oscillations, quantifying the contribution of particle formation, leakage, and interactions. We also show that the evolution of the condensate with increasing pump strength is strongly geometry dependent and can display contrasting features such as enhancement or reduction of the spatial localization of the condensate. We acknowledge support by DARPA under Grant No. N66001-11-1-4162 and NSF under CAREER Grant No. DMR-1151810.

Strong Spatial Influence on Colonization Rates in a Pioneer Zooplankton Metacommunity

PubMed Central

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

2012-01-01

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

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

PubMed

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

2012-01-01

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

Quantifying drivers of wild pig movement across multiple spatial and temporal scales

USGS Publications Warehouse

Kay, Shannon L.; Fischer, Justin W.; Monaghan, Andrew J.; Beasley, James C; Boughton, Raoul; Campbell, Tyler A; Cooper, Susan M; Ditchkoff, Stephen S.; Hartley, Stephen B.; Kilgo, John C; Wisely, Samantha M; Wyckoff, A Christy; Vercauteren, Kurt C.; Pipen, Kim M

2017-01-01

The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

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

PubMed

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

2017-04-01

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

Use of Mobile Device Data To Better Estimate Dynamic Population Size for Wastewater-Based Epidemiology.

PubMed

Thomas, Kevin V; Amador, Arturo; Baz-Lomba, Jose Antonio; Reid, Malcolm

2017-10-03

Wastewater-based epidemiology is an established approach for quantifying community drug use and has recently been applied to estimate population exposure to contaminants such as pesticides and phthalate plasticizers. A major source of uncertainty in the population weighted biomarker loads generated is related to estimating the number of people present in a sewer catchment at the time of sample collection. Here, the population quantified from mobile device-based population activity patterns was used to provide dynamic population normalized loads of illicit drugs and pharmaceuticals during a known period of high net fluctuation in the catchment population. Mobile device-based population activity patterns have for the first time quantified the high degree of intraday, week, and month variability within a specific sewer catchment. Dynamic population normalization showed that per capita pharmaceutical use remained unchanged during the period when static normalization would have indicated an average reduction of up to 31%. Per capita illicit drug use increased significantly during the monitoring period, an observation that was only possible to measure using dynamic population normalization. The study quantitatively confirms previous assessments that population estimates can account for uncertainties of up to 55% in static normalized data. Mobile device-based population activity patterns allow for dynamic normalization that yields much improved temporal and spatial trend analysis.

Fishermen Follow Fine-scaled Physical Ocean Features For Finance

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

The Upper Mississippi River floodscape: spatial patterns of flood inundation and associated plant community distributions

USGS Publications Warehouse

DeJager, Nathan R.; Rohweder, Jason J.; Yin, Yao; Hoy, Erin E.

2016-01-01

Questions How is the distribution of different plant communities associated with patterns of flood inundation across a large floodplain landscape? Location Thirty-eight thousand nine hundred and seventy hectare of floodplain, spanning 320 km of the Upper Mississippi River (UMR). Methods High-resolution elevation data (Lidar) and 30 yr of daily river stage data were integrated to produce a ‘floodscape’ map of growing season flood inundation duration. The distributions of 16 different remotely sensed plant communities were quantified along the gradient of flood duration. Results Models fitted to the cumulative frequency of occurrence of different vegetation types as a function of flood duration showed that most types exist along a continuum of flood-related occurrence. The diversity of community types was greatest at high elevations (0–10 d of flooding), where both upland and lowland community types were found, as well as at very low elevations (70–180 d of flooding), where a variety of lowland herbaceous communities were found. Intermediate elevations (20–60 d of flooding) tended to be dominated by floodplain forest and had the lowest diversity of community types. Conclusions Although variation in flood inundation is often considered to be the main driver of spatial patterns in floodplain plant communities, few studies have quantified flood–vegetation relationships at broad scales. Our results can be used to identify targets for restoration of historical hydrological regimes or better anticipate hydro-ecological effects of climate change at broad scales.

Estimates of reservoir methane emissions based on a spatially ...

EPA Pesticide Factsheets

Global estimates of methane (CH4) emissions from reservoirs are poorly constrained, partly due to the challenges of accounting for intra-reservoir spatial variability. Reservoir-scale emission rates are often estimated by extrapolating from measurement made at a few locations; however, error and bias associated with this approach can be large and difficult to quantify. Here we use a generalized random tessellation survey (GRTS) design to generate estimates of central tendency and variance at multiple spatial scales in a reservoir. GRTS survey designs are probabilistic and spatially balanced which eliminates bias associated with expert judgment in site selection. GRTS surveys also allow for variance estimates that account for spatial pattern in emission rates. Total CH4 emission rates (i.e. sum of ebullition and diffusive emissions) were 4.8 (±2.1), 33.0 (±10.7), and 8.3 (±2.2) mg CH4 m-2 h-1 in open-waters, tributary associated areas, and the entire reservoir for the period in August 2014 during which 115 sites were sampled across an 7.98 km2 reservoir in Southwestern, Ohio, USA. Tributary areas occupy 12% of the reservoir surface, but were the source of 41% of total CH4 emissions, highlighting the importance of riverine-lacustrine transition zones. Ebullition accounted for >90% of CH4 emission at all spatial scales. Confidence interval estimates that incorporated spatial pattern in CH4 emissions were up to 29% narrower than when spatial independence

Land use change modeling through scenario-based cellular automata Markov: improving spatial forecasting.

PubMed

Jahanishakib, Fatemeh; Mirkarimi, Seyed Hamed; Salmanmahiny, Abdolrassoul; Poodat, Fatemeh

2018-05-08

Efficient land use management requires awareness of past changes, present actions, and plans for future developments. Part of these requirements is achieved using scenarios that describe a future situation and the course of changes. This research aims to link scenario results with spatially explicit and quantitative forecasting of land use development. To develop land use scenarios, SMIC PROB-EXPERT and MORPHOL methods were used. It revealed eight scenarios as the most probable. To apply the scenarios, we considered population growth rate and used a cellular automata-Markov chain (CA-MC) model to implement the quantified changes described by each scenario. For each scenario, a set of landscape metrics was used to assess the ecological integrity of land use classes in terms of fragmentation and structural connectivity. The approach enabled us to develop spatial scenarios of land use change and detect their differences for choosing the most integrated landscape pattern in terms of landscape metrics. Finally, the comparison between paired forecasted scenarios based on landscape metrics indicates that scenarios 1-1, 2-2, 3-2, and 4-1 have a more suitable integrity. The proposed methodology for developing spatial scenarios helps executive managers to create scenarios with many repetitions and customize spatial patterns in real world applications and policies.

Reconstructing a spatially heterogeneous epidemic: Characterising the geographic spread of 2009 A/H1N1pdm infection in England

NASA Astrophysics Data System (ADS)

Birrell, Paul J.; Zhang, Xu-Sheng; Pebody, Richard G.; Gay, Nigel J.; de Angelis, Daniela

2016-07-01

Understanding how the geographic distribution of and movements within a population influence the spatial spread of infections is crucial for the design of interventions to curb transmission. Existing knowledge is typically based on results from simulation studies whereas analyses of real data remain sparse. The main difficulty in quantifying the spatial pattern of disease spread is the paucity of available data together with the challenge of incorporating optimally the limited information into models of disease transmission. To address this challenge the role of routine migration on the spatial pattern of infection during the epidemic of 2009 pandemic influenza in England is investigated here through two modelling approaches: parallel-region models, where epidemics in different regions are assumed to occur in isolation with shared characteristics; and meta-region models where inter-region transmission is expressed as a function of the commuter flux between regions. Results highlight that the significantly less computationally demanding parallel-region approach is sufficiently flexible to capture the underlying dynamics. This suggests that inter-region movement is either inaccurately characterized by the available commuting data or insignificant once its initial impact on transmission has subsided.

A soil-landscape framework for understanding spatial and temporal variability in biogeochemical processes in catchments

NASA Astrophysics Data System (ADS)

McGuire, K. J.; Bailey, S. W.; Ross, D. S.

2017-12-01

Heterogeneity in biophysical properties within catchments challenges how we quantify and characterize biogeochemical processes and interpret catchment outputs. Interactions between the spatiotemporal variability of hydrological states and fluxes and soil development can spatially structure catchments, leading to a framework for understanding patterns in biogeochemical processes. In an upland, glaciated landscape at the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, we are embracing the structure and organization of soils to understand the spatial relations between runoff production zones, distinct soil-biogeochemical environments, and solute retention and release. This presentation will use observations from the HBEF to demonstrate that a soil-landscape framework is essential in understanding the spatial and temporal variability of biogeochemical processes in this catchment. Specific examples will include how laterally developed soils reveal the location of active runoff production zones and lead to gradients in primary mineral dissolution and the distribution of weathering products along hillslopes. Soil development patterns also highlight potential carbon and nitrogen cycling hotspots, differentiate acidic conditions, and affect the regulation of surface water quality. Overall, this work demonstrates the importance of understanding the landscape-level structural organization of soils in characterizing the variation and extent of biogeochemical processes that occur in catchments.

Apparent plasticity in functional traits determining competitive ability and spatial distribution: a case from desert.

PubMed

Xie, Jiang-Bo; Xu, Gui-Qing; Jenerette, G Darrel; Bai, Yong-fei; Wang, Zhong-Yuan; Li, Yan

2015-07-20

Species competitive abilities and their distributions are closely related to functional traits such as biomass allocation patterns. When we consider how nutrient supply affects competitive abilities, quantifying the apparent and true plasticity in functional traits is important because the allometric relationships among traits are universal in plants. We propose to integrate the notion of allometry and the classical reaction norm into a composite theoretical framework that quantifies the apparent and true plasticity. Combining the framework with a meta-analysis, a series of field surveys and a competition experiment, we aimed to determine the causes of the dune/interdune distribution patterns of two Haloxylon species in the Gurbantonggut Desert. We found that (1) the biomass allocation patterns of both Haloxylon species in responses to environmental conditions were apparent rather than true plasticity and (2) the allometric allocation patterns affected the plants' competition for soil nutrient supply. A key implication of our results is that the apparent plasticity in functional traits of plants determines their response to environmental change. Without identifying the apparent and true plasticity, we would substantially overestimate the magnitude, duration and even the direction of plant responses in functional traits to climate change.

Apparent plasticity in functional traits determining competitive ability and spatial distribution: a case from desert

PubMed Central

Xie, Jiang-Bo; Xu, Gui-Qing; Jenerette, G. Darrel; Bai, Yong-fei; Wang, Zhong-Yuan; Li, Yan

2015-01-01

Species competitive abilities and their distributions are closely related to functional traits such as biomass allocation patterns. When we consider how nutrient supply affects competitive abilities, quantifying the apparent and true plasticity in functional traits is important because the allometric relationships among traits are universal in plants. We propose to integrate the notion of allometry and the classical reaction norm into a composite theoretical framework that quantifies the apparent and true plasticity. Combining the framework with a meta-analysis, a series of field surveys and a competition experiment, we aimed to determine the causes of the dune/interdune distribution patterns of two Haloxylon species in the Gurbantonggut Desert. We found that (1) the biomass allocation patterns of both Haloxylon species in responses to environmental conditions were apparent rather than true plasticity and (2) the allometric allocation patterns affected the plants’ competition for soil nutrient supply. A key implication of our results is that the apparent plasticity in functional traits of plants determines their response to environmental change. Without identifying the apparent and true plasticity, we would substantially overestimate the magnitude, duration and even the direction of plant responses in functional traits to climate change. PMID:26190745

Exploring the effect of the spatial scale of fishery management.

PubMed

Takashina, Nao; Baskett, Marissa L

2016-02-07

For any spatially explicit management, determining the appropriate spatial scale of management decisions is critical to success at achieving a given management goal. Specifically, managers must decide how much to subdivide a given managed region: from implementing a uniform approach across the region to considering a unique approach in each of one hundred patches and everything in between. Spatially explicit approaches, such as the implementation of marine spatial planning and marine reserves, are increasingly used in fishery management. Using a spatially explicit bioeconomic model, we quantify how the management scale affects optimal fishery profit, biomass, fishery effort, and the fraction of habitat in marine reserves. We find that, if habitats are randomly distributed, the fishery profit increases almost linearly with the number of segments. However, if habitats are positively autocorrelated, then the fishery profit increases with diminishing returns. Therefore, the true optimum in management scale given cost to subdivision depends on the habitat distribution pattern. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effects of rainfall spatial variability and intermittency on shallow landslide triggering patterns at a catchment scale

NASA Astrophysics Data System (ADS)

von Ruette, J.; Lehmann, P.; Or, D.

2014-10-01

The occurrence of shallow landslides is often associated with intense and prolonged rainfall events, where infiltrating water reduces soil strength and may lead to abrupt mass release. Despite general understanding of the role of rainfall water in slope stability, the prediction of rainfall-induced landslides remains a challenge due to natural heterogeneity that affect hydrologic loading patterns and the largely unobservable internal progressive failures. An often overlooked and potentially important factor is the role of rainfall variability in space and time on landslide triggering that is often obscured by coarse information (e.g., hourly radar data at spatial resolution of a few kilometers). To quantify potential effects of rainfall variability on failure dynamics, spatial patterns, landslide numbers and volumes, we employed a physically based "Catchment-scale Hydromechanical Landslide Triggering" (CHLT) model for a study area where a summer storm in 2002 triggered 51 shallow landslides. In numerical experiments based on the CHLT model, we applied the measured rainfall amount of 53 mm in different artificial spatiotemporal rainfall patterns, resulting in between 30 and 100 landslides and total released soil volumes between 3000 and 60,000 m3 for the various scenarios. Results indicate that low intensity rainfall below soil's infiltration capacity resulted in the largest mechanical perturbation. This study illustrates how small-scale rainfall variability that is often overlooked by present operational rainfall data may play a key role in shaping landslide patterns.

Quantifying high resolution transitional breaks in plant and mammal distributions at regional extent and their association with climate, topography and geology.

PubMed

Di Virgilio, Giovanni; Laffan, Shawn W; Ebach, Malte C

2013-01-01

We quantify spatial turnover in communities of 1939 plant and 59 mammal species at 2.5 km resolution across a topographically heterogeneous region in south-eastern Australia to identify distributional breaks and low turnover zones where multiple species distributions overlap. Environmental turnover is measured to determine how climate, topography and geology influence biotic turnover differently across a variety of biogeographic breaks and overlaps. We identify the genera driving turnover and confirm the versatility of this approach across spatial scales and locations. Directional moving window analyses, rotated through 360°, were used to measure spatial turnover variation in different directions between gridded cells containing georeferenced plant and mammal occurrences and environmental variables. Generalised linear models were used to compare taxic turnover results with equivalent analyses for geology, regolith weathering, elevation, slope, solar radiation, annual precipitation and annual mean temperature, both uniformly across the entire study area and by stratifying it into zones of high and low turnover. Identified breaks and transitions were compared to a conservation bioregionalisation framework widely used in Australia. Detailed delineations of plant and mammal turnover zones with gradational boundaries denoted subtle variation in species assemblages. Turnover patterns often diverged from bioregion boundaries, though plant turnover adhered most closely. A prominent break zone contained either comparable or greater numbers of unique genera than adjacent overlaps, but these were concentrated in a small subsection relatively under-protected by conservation reserves. The environmental correlates of biotic turnover varied for different turnover zones in different subsections of the study area. Topography and temperature showed much stronger relationships with plant turnover in a topographically complex overlap, relative to a lowland overlap where weathering was most predictive. This method can quantify transitional turnover patterns from small to broad extents, at different resolutions for any location, and complements broad-scale bioregionalisation schemes in conservation planning.

Post-fire reconstructions of fire intensity from fire severity data: quantifying the role of spatial variability of fire intensity on forest dynamics

NASA Astrophysics Data System (ADS)

Baker, Patrick; Oborne, Lisa

2015-04-01

Large, high-intensity fires have direct and long-lasting effects on forest ecosystems and present a serious threat to human life and property. However, even within the most catastrophic fires there is important variability in local-scale intensity that has important ramifications for forest mortality and regeneration. Quantifying this variability is difficult due to the rarity of catastrophic fire events, the extreme conditions at the time of the fires, and their large spatial extent. Instead fire severity is typically measured or estimated from observed patterns of vegetation mortality; however, differences in species- and size-specific responses to fires often makes fire severity a poor proxy for fire intensity. We developed a statistical method using simple, plot-based measurements of individual tree mortality to simultaneously estimate plot-level fire intensity and species-specific mortality patterns as a function of tree size. We applied our approach to an area of forest burned in the catastrophic Black Saturday fires that occurred near Melbourne, Australia, in February 2009. Despite being the most devastating fire in the past 70 years and our plots being located in the area that experienced some of the most intense fires in the 350,000 ha fire complex, we found that the estimated fire intensity was highly variable at multiple spatial scales. All eight tree species in our study differed in their susceptibility to fire-induced mortality, particularly among the largest size classes. We also found that seedling height and species richness of the post-fire seedling communities were both positively correlated with fire intensity. Spatial variability in disturbance intensity has important, but poorly understood, consequences for the short- and long-term dynamics of forests in the wake of catastrophic wildfires. Our study provides a tool to estimate fire intensity after a fire has passed, allowing new opportunities for linking spatial variability in fire intensity to forest ecosystem dynamics.

Identifying, characterizing and predicting spatial patterns of lacustrine groundwater discharge

NASA Astrophysics Data System (ADS)

Tecklenburg, Christina; Blume, Theresa

2017-10-01

Lacustrine groundwater discharge (LGD) can significantly affect lake water balances and lake water quality. However, quantifying LGD and its spatial patterns is challenging because of the large spatial extent of the aquifer-lake interface and pronounced spatial variability. This is the first experimental study to specifically study these larger-scale patterns with sufficient spatial resolution to systematically investigate how landscape and local characteristics affect the spatial variability in LGD. We measured vertical temperature profiles around a 0.49 km2 lake in northeastern Germany with a needle thermistor, which has the advantage of allowing for rapid (manual) measurements and thus, when used in a survey, high spatial coverage and resolution. Groundwater inflow rates were then estimated using the heat transport equation. These near-shore temperature profiles were complemented with sediment temperature measurements with a fibre-optic cable along six transects from shoreline to shoreline and radon measurements of lake water samples to qualitatively identify LGD patterns in the offshore part of the lake. As the hydrogeology of the catchment is sufficiently homogeneous (sandy sediments of a glacial outwash plain; no bedrock control) to avoid patterns being dominated by geological discontinuities, we were able to test the common assumptions that spatial patterns of LGD are mainly controlled by sediment characteristics and the groundwater flow field. We also tested the assumption that topographic gradients can be used as a proxy for gradients of the groundwater flow field. Thanks to the extensive data set, these tests could be carried out in a nested design, considering both small- and large-scale variability in LGD. We found that LGD was concentrated in the near-shore area, but alongshore variability was high, with specific regions of higher rates and higher spatial variability. Median inflow rates were 44 L m-2 d-1 with maximum rates in certain locations going up to 169 L m-2 d-1. Offshore LGD was negligible except for two local hotspots on steep steps in the lake bed topography. Large-scale groundwater inflow patterns were correlated with topography and the groundwater flow field, whereas small-scale patterns correlated with grain size distributions of the lake sediment. These findings confirm results and assumptions of theoretical and modelling studies more systematically than was previously possible with coarser sampling designs. However, we also found that a significant fraction of the variance in LGD could not be explained by these controls alone and that additional processes need to be considered. While regression models using these controls as explanatory variables had limited power to predict LGD rates, the results nevertheless encourage the use of topographic indices and sediment heterogeneity as an aid for targeted campaigns in future studies of groundwater discharge to lakes.

Programming curvature using origami tessellations

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

Flow patterns and bathymetric signatures on the delta front of a prograding river delta

NASA Astrophysics Data System (ADS)

Shaw, J.; Mohrig, D. C.; Wagner, R. W.

2016-02-01

The transition of water between laterally confined channels and the unchannelized delta front controls the growth pattern of river deltas, but is difficult to measure on field-scale deltas. We quantify flow patterns, bathymetry and bathymetric evolution for the subaqueous delta front on the Wax Lake Delta (WLD), a rapidly prograding delta in coastal Louisiana. The flow direction field, mapped using streaklines composed of biogenic slicks on the water surface, shows that a significant portion of flow ( 59%) departs subaqueous channels laterally over the subaqueous margins of the channel seaward of the shoreline. Synoptic datasets of bathymetry and flow direction allow spatial changes in flow velocity to be quantified. Most lateral flow divergence and deceleration occurs within 3-8 channel widths outboard of subaqueous channel margins, rather than downstream of channel tips. In interdistributary bays, deposit elevation decreases with a basinward slope of 2.4 x 10-4 with distance from a channel margin along any flow path. Flow patterns and this slope produce constructional features called interdistributary troughs - topographic lows in the center of interdistributary bays. These data show that flow patterns and bathymetry on the delta front are coupled both at the transition from channelized to unchannelized flow and in the depositional regions outside the distributary network.

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

PubMed Central

Arima, E. Y.

2016-01-01

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

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

PubMed

Arima, E Y

2016-01-01

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

Comparative Spatial Dynamics of Japanese Encephalitis and Acute Encephalitis Syndrome in Nepal

PubMed Central

Robertson, Colin; Pant, Dhan Kumar; Joshi, Durga Datt; Sharma, Minu; Dahal, Meena; Stephen, Craig

2013-01-01

Japanese Encephalitis (JE) is a vector-borne disease of major importance in Asia. Recent increases in cases have spawned the development of more stringent JE surveillance. Due to the difficulty of making a clinical diagnosis, increased tracking of common symptoms associated with JE—generally classified as the umbrella term, acute encephalitis syndrome (AES) has been developed in many countries. In Nepal, there is some debate as to what AES cases are, and how JE risk factors relate to AES risk. Three parts of this analysis included investigating the temporal pattern of cases, examining the age and vaccination status patterns among AES surveillance data, and then focusing on spatial patterns of risk factors. AES and JE cases from 2007–2011 reported at a district level (n = 75) were examined in relation to landscape risk factors. Landscape pattern indices were used to quantify landscape patterns associated with JE risk. The relative spatial distribution of landscape risk factors were compared using geographically weighted regression. Pattern indices describing the amount of irrigated land edge density and the degree of landscape mixing for irrigated areas were positively associated with JE and AES, while fragmented forest measured by the number of forest patches were negatively associated with AES and JE. For both JE and AES, the local GWR models outperformed global models, indicating spatial heterogeneity in risks. Temporally, the patterns of JE and AES risk were almost identical; suggesting the relative higher caseload of AES compared to JE could provide a valuable early-warning signal for JE surveillance and reduce diagnostic testing costs. Overall, the landscape variables associated with a high degree of landscape mixing and small scale irrigated agriculture were positively linked to JE and AES risk, highlighting the importance of integrating land management policies, disease prevention strategies and promoting healthy sustainable livelihoods in both rural and urban-fringe developing areas. PMID:23894277

Discontinuities concentrate mobile predators: Quantifying organism-environment interactions at a seascape scale

USGS Publications Warehouse

Kennedy, Christina G.; Mather, Martha E.; Smith, Joseph M.; Finn, John T.; Deegan, Linda A.

2016-01-01

Understanding environmental drivers of spatial patterns is an enduring ecological problem that is critical for effective biological conservation. Discontinuities (ecologically meaningful habitat breaks), both naturally occurring (e.g., river confluence, forest edge, drop-off) and anthropogenic (e.g., dams, roads), can influence the distribution of highly mobile organisms that have land- or seascape scale ranges. A geomorphic discontinuity framework, expanded to include ecological patterns, provides a way to incorporate important but irregularly distributed physical features into organism–environment relationships. Here, we test if migratory striped bass (Morone saxatilis) are consistently concentrated by spatial discontinuities and why. We quantified the distribution of 50 acoustically tagged striped bass at 40 sites within Plum Island Estuary, Massachusetts during four-monthly surveys relative to four physical discontinuities (sandbar, confluence, channel network, drop-off), one continuous physical feature (depth variation), and a geographic location variable (region). Despite moving throughout the estuary, striped bass were consistently clustered in the middle geographic region at sites with high sandbar area, close to channel networks, adjacent to complex confluences, with intermediate levels of bottom unevenness, and medium sized drop-offs. In addition, the highest striped bass concentrations occurred at sites with the greatest additive physical heterogeneity (i.e., where multiple discontinuities co-occurred). The need to incorporate irregularly distributed features in organism–environment relationships will increase as high-quality telemetry and GIS data accumulate for mobile organisms. The spatially explicit approach we used to address this challenge can aid both researchers who seek to understand the impact of predators on ecosystems and resource managers who require new approaches for biological conservation.

How do frugivores track resources? Insights from spatial analyses of bird foraging in a tropical forest

USGS Publications Warehouse

Saracco, J.F.; Collazo, J.A.; Groom, Martha J.

2004-01-01

Frugivores often track ripe fruit abundance closely across local areas despite the ephemeral and typically patchy distributions of this resource. We use spatial auto- and cross-correlation analyses to quantify spatial patterns of fruit abundance and avian frugivory across a 4-month period within a forested 4.05-ha study grid in Puerto Rico. Analyses focused on two tanager species, Spindalis portoricensis and Nesospingus speculiferus, and their principal food plants. Three broad questions are addressed: (1) at what spatial scales is fruit abundance and frugivory patchy; (2) at what spatial scales do frugivores respond to fruit abundance; and (3) to what extent do spatial patterns of frugivory overlap between bird species? Fruit patch size, species composition, and heterogeneity was variable among months, despite fruit patch locations remaining relatively consistent between months. Positive correlations between frugivory and fruit abundance suggested tanagers successfully tracked fruit abundance. Frugivory was, however, more localized than fruit abundance. Scales of spatial overlap in frugivory and monthly variation in the foraging locations of the two tanager species suggested that interspecific facilitation may have been important in determining bird foraging locations. In particular, S. portoricensis, a specialist frugivore, may have relied on the loud calls of the gregarious generalist, N. speculiferus, to find new foraging areas. Such a mechanism could help explain the formation of mixed species feeding flocks and highlights the potential importance of facilitation between species that share resources. ?? Springer-Verlag 2004.

Landscape patterns of understory composition and richness across a moisture and nitrogen mineralization gradient in Ohio (U.S.A.) Quercus forests

Treesearch

Todd F. Hutchinson; Ralph E.J. Boerner; Louis R. Iverson; Steve Sutherland; Elaine Kennedy Sutherland

1999-01-01

This study quantified relationships of understory vascular plant species composition and richness along environmental gradients over a broad spatial scale in second-growth oak forests in eastern North America. Species frequencies were recorded in 108 25 x 25 m plots in four study sites extending over 70 km in southern Ohio, U.S.A. The plots were stratified into three...

Modeling fire severity in black spruce stands in the Alaskan boreal forest using spectral and non-spectral geospatial data

Treesearch

K. Barrett; E.S. Kasischke; A.D. McGuire; M.R. Turetsky; E.S. Kane

2010-01-01

Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to...

Rooting strategies in a subtropical savanna: a landscape-scale three-dimensional assessment.

PubMed

Zhou, Yong; Boutton, Thomas W; Wu, X Ben; Wright, Cynthia L; Dion, Anais L

2018-04-01

In resource-limited savannas, the distribution and abundance of fine roots play an important role in acquiring essential resources and structuring vegetation patterns and dynamics. However, little is known regarding the three-dimensional distribution of fine roots in savanna ecosystems at the landscape scale. We quantified spatial patterns of fine root density to a depth of 1.2 m in a subtropical savanna landscape using spatially specific sampling. Kriged maps revealed that fine root density was highest at the centers of woody patches, decreased towards the canopy edges, and reached lowest values within the grassland matrix throughout the entire soil profile. Lacunarity analyses indicated that spatial heterogeneities of fine root density decreased continuously to a depth of 50 cm and then increased in deeper portions of the soil profile across this landscape. This vertical pattern might be related to inherent differences in root distribution between trees/shrubs and herbaceous species, and the presence/absence of an argillic horizon across this landscape. The greater density of fine roots beneath woody patches in both upper and lower portions of the soil profile suggests an ability to acquire disproportionately more resources than herbaceous species, which may facilitate the development and persistence of woody patches across this landscape.

Delayed Response and Biosonar Perception Explain Movement Coordination in Trawling Bats

PubMed Central

Giuggioli, Luca; McKetterick, Thomas J.; Holderied, Marc

2015-01-01

Animal coordinated movement interactions are commonly explained by assuming unspecified social forces of attraction, repulsion and alignment with parameters drawn from observed movement data. Here we propose and test a biologically realistic and quantifiable biosonar movement interaction mechanism for echolocating bats based on spatial perceptual bias, i.e. actual sound field, a reaction delay, and observed motor constraints in speed and acceleration. We found that foraging pairs of bats flying over a water surface swapped leader-follower roles and performed chases or coordinated manoeuvres by copying the heading a nearby individual has had up to 500 ms earlier. Our proposed mechanism based on the interplay between sensory-motor constraints and delayed alignment was able to recreate the observed spatial actor-reactor patterns. Remarkably, when we varied model parameters (response delay, hearing threshold and echolocation directionality) beyond those observed in nature, the spatio-temporal interaction patterns created by the model only recreated the observed interactions, i.e. chases, and best matched the observed spatial patterns for just those response delays, hearing thresholds and echolocation directionalities found to be used by bats. This supports the validity of our sensory ecology approach of movement coordination, where interacting bats localise each other by active echolocation rather than eavesdropping. PMID:25811627

Functional imaging of the nonhuman primate Placenta with endogenous blood oxygen level-dependent contrast.

PubMed

Schabel, M C; Roberts, V H J; Lo, J O; Platt, S; Grant, K A; Frias, A E; Kroenke, C D

2016-11-01

To characterize spatial patterns of T2* in the placenta of the rhesus macaque (Macaca mulatta), to correlate these patterns with placental perfusion determined using dynamic contrast-enhanced MRI (DCE-MRI), and to evaluate the potential for using the blood oxygen level-dependent effect to quantify placental perfusion without the use of exogenous contrast reagent. MRI was performed on three pregnant rhesus macaques at gestational day 110. Multiecho spoiled gradient echo measurements were used to compute maps of T2*. Spatial maxima in these maps were compared with foci of early enhancement determined by DCE-MRI. Local maxima in T2* maps were strongly correlated with spiral arteries identified by DCE-MRI, with mean spatial separations ranging from 2.34 to 6.11 mm in the three animals studied. Spatial patterns of R2* ( = 1/ T2*) within individual placental lobules can be quantitatively analyzed using a simple model to estimate fetal arterial oxyhemoglobin concentration [Hbo,f] and a parameter viPS/Φ, reflecting oxygen transport to the fetus. Estimated mean values of [Hbo,f] ranged from 4.25 mM to 4.46 mM, whereas viPS/Φ ranged from 2.80 × 10 5 cm -3 to 1.61 × 10 6 cm -3 . Maternal spiral arteries show strong spatial correlation with foci of extended T2* observed in the primate placenta. A simple model of oxygen transport accurately describes the spatial dependence of R2* within placental lobules and enables assessment of placental function and oxygenation without requiring administration of an exogenous contrast reagent. Magn Reson Med 76:1551-1562, 2016. © 2015 International Society for Magnetic Resonance in Medicine. © 2015 International Society for Magnetic Resonance in Medicine.

Quantifying spatial patterns in the Yakama Nation Tribal Forest and Okanogan-Wenatchee National Forest to assess forest health

NASA Astrophysics Data System (ADS)

Wilder, T. F.

2013-05-01

Over the past century western United States have experienced drastic anthropogenic land use change from practices such as agriculture, fire exclusion, and timber harvesting. These changes have complex social, cultural, economic, and ecological interactions and consequences. This research studied landscapes patterns of watersheds with similar LANDFIRE potential vegetation in the Southern Washington Cascades physiographic province, within the Yakama Nation Tribal Forest (YTF) and Okanogan-Wenatchee National Forest, Naches Ranger District (NRD). In the selected watersheds, vegetation-mapping units were delineated and populated based on physiognomy of homogeneous areas of vegetative composition and structure using high-resolution aerial photos. Cover types and structural classes were derived from the raw, photo-interpreted vegetation attributes for individual vegetation mapping units and served as individual and composite response variables to quantify and assess spatial patterns and forest health conditions between the two ownerships. Structural classes in both the NRD and YTF were spatially clustered (Z-score 3.1, p-value 0.01; Z-score 2.3, p-value 0.02, respectively), however, ownership and logging type both explained a significant amount of variance in structural class composition. Based on FRAGSTATS landscape metrics, structural classes in the NRD displayed greater clustering and fragmentation with lower interspersion relative to the YTF. The NRD landscape was comprised of 47.4% understory reinitiation structural class type and associated high FRAGASTAT class metrics demonstrated high aggregation with moderate interspersion. Stem exclusion open canopy displayed the greatest dispersal of structural class types throughout the NRD, but adjacencies were correlated to other class types. In the YTF, stem exclusion open canopy comprised 37.7% of the landscape and displayed a high degree of aggregation and interspersion about clusters throughout the YTF. Composite cover type-structural class spatial autocorrelation was clustered in the NRD (Z-score 5.1, p-value 0.01), while the YTF exhibited a random spatial pattern. After accounting for location effects, logging type was the most significant factor explaining variation in composite cover-structure composition. FRAGSTATS landscape metrics identified composite cover-structure classes in the NRD displayed greater aggregation and fragmentation with lower interspersion relative to the YTF. The NRD landscape was comprised of 30.5% Pinus ponderosa-understory reinitiation and associated class metrics demonstrated a high degree of aggregation and fragmentation with low interspersion. Pinus ponderosa-stem exclusion open canopy comprised 24.6% of the YTF landscape and associated class metrics displayed moderate aggregation and fragmentation with high interspersion. A discussion integrating the results and existing relevant literature was indited to assess management regime influences on landscape patterns and, in turn, forest health attributes. This dialog is in provision of enhancing collaboration to optimize forest-health restoration activities across ownerships throughout the study area.

A field comparison of multiple techniques to quantify groundwater - surface-water interactions

USGS Publications Warehouse

González-Pinzón, Ricardo; Ward, Adam S; Hatch, Christine E; Wlostowski, Adam N; Singha, Kamini; Gooseff, Michael N.; Haggerty, Roy; Harvey, Judson; Cirpka, Olaf A; Brock, James T

2015-01-01

Groundwater–surface-water (GW-SW) interactions in streams are difficult to quantify because of heterogeneity in hydraulic and reactive processes across a range of spatial and temporal scales. The challenge of quantifying these interactions has led to the development of several techniques, from centimeter-scale probes to whole-system tracers, including chemical, thermal, and electrical methods. We co-applied conservative and smart reactive solute-tracer tests, measurement of hydraulic heads, distributed temperature sensing, vertical profiles of solute tracer and temperature in the stream bed, and electrical resistivity imaging in a 450-m reach of a 3rd-order stream. GW-SW interactions were not spatially expansive, but were high in flux through a shallow hyporheic zone surrounding the reach. NaCl and resazurin tracers suggested different surface–subsurface exchange patterns in the upper ⅔ and lower ⅓ of the reach. Subsurface sampling of tracers and vertical thermal profiles quantified relatively high fluxes through a 10- to 20-cm deep hyporheic zone with chemical reactivity of the resazurin tracer indicated at 3-, 6-, and 9-cm sampling depths. Monitoring of hydraulic gradients along transects with MINIPOINT streambed samplers starting ∼40 m from the stream indicated that groundwater discharge prevented development of a larger hyporheic zone, which progressively decreased from the stream thalweg toward the banks. Distributed temperature sensing did not detect extensive inflow of ground water to the stream, and electrical resistivity imaging showed limited large-scale hyporheic exchange. We recommend choosing technique(s) based on: 1) clear definition of the questions to be addressed (physical, biological, or chemical processes), 2) explicit identification of the spatial and temporal scales to be covered and those required to provide an appropriate context for interpretation, and 3) maximizing generation of mechanistic understanding and reducing costs of implementing multiple techniques through collaborative research.

Vegetation cover in relation to socioeconomic factors in a tropical city assessed from sub-meter resolution imagery.

PubMed

Martinuzzi, Sebastián; Ramos-González, Olga M; Muñoz-Erickson, Tischa A; Locke, Dexter H; Lugo, Ariel E; Radeloff, Volker C

2018-04-01

Fine-scale information about urban vegetation and social-ecological relationships is crucial to inform both urban planning and ecological research, and high spatial resolution imagery is a valuable tool for assessing urban areas. However, urban ecology and remote sensing have largely focused on cities in temperate zones. Our goal was to characterize urban vegetation cover with sub-meter (<1 m) resolution aerial imagery, and identify social-ecological relationships of urban vegetation patterns in a tropical city, the San Juan Metropolitan Area, Puerto Rico. Our specific objectives were to (1) map vegetation cover using sub-meter spatial resolution (0.3-m) imagery, (2) quantify the amount of residential and non-residential vegetation, and (3) investigate the relationship between patterns of urban vegetation vs. socioeconomic and environmental factors. We found that 61% of the San Juan Metropolitan Area was green and that our combination of high spatial resolution imagery and object-based classification was highly successful for extracting vegetation cover in a moist tropical city (97% accuracy). In addition, simple spatial pattern analysis allowed us to separate residential from non-residential vegetation with 76% accuracy, and patterns of residential and non-residential vegetation varied greatly across the city. Both socioeconomic (e.g., population density, building age, detached homes) and environmental variables (e.g., topography) were important in explaining variations in vegetation cover in our spatial regression models. However, important socioeconomic drivers found in cities in temperate zones, such as income and home value, were not important in San Juan. Climatic and cultural differences between tropical and temperate cities may result in different social-ecological relationships. Our study provides novel information for local land use planners, highlights the value of high spatial resolution remote sensing data to advance ecological research and urban planning in tropical cities, and emphasizes the need for more studies in tropical cities. © 2017 by the Ecological Society of America.

Spatial and temporal dynamics of commercial reef-fish fisheries on the West Florida Shelf: Understanding drivers of fleet behavior and the implications for future management

NASA Astrophysics Data System (ADS)

Cockrell, M.; Murawski, S. A.; Sanchirico, J. N.; O'Farrell, S.; Strelcheck, A.

2016-02-01

Spatial and temporal patterns of fishing activity have historically been described over relatively coarse scales or with limited datasets. However, new and innovative approaches for fisheries management will require an understanding of both species population dynamics and fleet behavior at finer spatial and temporal resolution. In this study we describe the spatial and temporal patterns of commercial reef-fish fisheries on the West Florida Shelf (WFS) from 2006-14, using a combination of on-board observer, catch logbook, and vessel satellite tracking data. The satellite tracking data is both high resolution (ie, records from each vessel at least once every hour for the duration of a trip), and required of all federally-permitted reef fish vessels in the Gulf of Mexico, making this a uniquely rich and powerful dataset. Along with spatial and temporal fishery dynamics, we quantified concomitant patterns in fishery economics and catch metrics, such as total landings and catch composition. Fishery patterns were correlated to a number of variables across the vessel, trip, and whole fleet scales, including vessel size, distance from home port, number of days at sea, and days available to fish. Notably, changes in management structure during the years examined (eg, establishment of a seasonal closed area in 2009 and implementation of an individual fishing quota system for Grouper-Tilefish in 2010), as well as emergency spatial closures during the Deepwater Horizon oil spill in 2010, enabled us to examine the impacts of specific management frameworks on the WFS reef-fish fishery. This research highlights the need to better understand the biological, economic, and social impacts within fisheries when managing for conservation and fisheries sustainability. We discuss our results in the context of a changing policy and management landscape for marine and coastal resources in the Gulf of Mexico.

Multiscale thermal refugia and stream habitat associations of chinook salmon in northwestern Oregon

USGS Publications Warehouse

Torgersen, Christian E.; Price, David M.; Li, Hiram W.; McIntosh, B.A.

1999-01-01

We quantified distribution and behavior of adult spring chinook salmon (Oncorhynchus tshawytscha) related to patterns of stream temperature and physical habitat at channel-unit, reach-, and section-level spatial scales in a wilderness stream and a disturbed stream in the John Day River basin in northeastern Oregon. We investigated the effectiveness of thermal remote sensing for analyzing spatial patterns of stream temperature and assessed habitat selection by spring chinook salmon, evaluating whether thermal refugia might be responsible for the persistence of these stocks in rivers where water temperatures frequently exceed their upper tolerance levels (25A?C) during spawning migration. By presenting stream temperature and the ecology of chinook salmon in a historical context, we could evaluate how changes in riverine habitat and thermal spatial structure, which can be caused by land-use practices, may influence distributional patterns of chinook salmon. Thermal remote sensing provided spatially continuous maps of stream temperature for reaches used by chinook salmon in the upper subbasins of the Middle Fork and North Fork John Day River. Electivity analysis and logistic regression were used to test for associations between the longitudinal distribution of salmon and cool-water areas and stream habitat characteristics. Chinook salmon were distributed nonuniformly in reaches throughout each stream. Salmon distribution and cool water temperature patterns were most strongly related at reach-level spatial scales in the warm stream, the Middle Fork (maximum likelihood ratio: P 0.30). Pools were preferred by adult chinook salmon in both subbasins (Bonferroni confidence interval: P a?? 0.05); however, riffles were used proportionately more frequently in the North Fork than in the Middle Fork. Our observations of thermal refugia and their use by chinook salmon at multiple spatial scales reveal that, although heterogeneity in the longitudinal stream temperature profile may be viewed as an ecological warning sign, thermal patchiness in streams also should be recognized for its biological potential to provide habitat for species existing at the margin of their environmental tolerances.

Advanced analysis of forest fire clustering

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail; Pereira, Mario; Golay, Jean

2017-04-01

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

Effects of Topography-driven Micro-climatology on Evaporation

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed

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

2016-10-01

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

Spatial and Temporal Characteristics of the 2009 A/H1N1 Influenza Pandemic in Peru

PubMed Central

Chowell, Gerardo; Viboud, Cécile; Munayco, Cesar V.; Gómez, Jorge; Simonsen, Lone; Miller, Mark A.; Tamerius, James; Fiestas, Victor; Halsey, Eric S.; Laguna-Torres, Victor A.

2011-01-01

Background Highly refined surveillance data on the 2009 A/H1N1 influenza pandemic are crucial to quantify the spatial and temporal characteristics of the pandemic. There is little information about the spatial-temporal dynamics of pandemic influenza in South America. Here we provide a quantitative description of the age-specific morbidity pandemic patterns across administrative areas of Peru. Methods We used daily cases of influenza-like-illness, tests for A/H1N1 influenza virus infections, and laboratory-confirmed A/H1N1 influenza cases reported to the epidemiological surveillance system of Peru's Ministry of Health from May 1 to December 31, 2009. We analyzed the geographic spread of the pandemic waves and their association with the winter school vacation period, demographic factors, and absolute humidity. We also estimated the reproduction number and quantified the association between the winter school vacation period and the age distribution of cases. Results The national pandemic curve revealed a bimodal winter pandemic wave, with the first peak limited to school age children in the Lima metropolitan area, and the second peak more geographically widespread. The reproduction number was estimated at 1.6–2.2 for the Lima metropolitan area and 1.3–1.5 in the rest of Peru. We found a significant association between the timing of the school vacation period and changes in the age distribution of cases, while earlier pandemic onset was correlated with large population size. By contrast there was no association between pandemic dynamics and absolute humidity. Conclusions Our results indicate substantial spatial variation in pandemic patterns across Peru, with two pandemic waves of varying timing and impact by age and region. Moreover, the Peru data suggest a hierarchical transmission pattern of pandemic influenza A/H1N1 driven by large population centers. The higher reproduction number of the first pandemic wave could be explained by high contact rates among school-age children, the age group most affected during this early wave. PMID:21712984

Artistic forms and complexity.

PubMed

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

2011-04-01

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

Physical-chemical mechanisms of pattern formation during gastrulation

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Optimizing Fukushima Emissions Through Pattern Matching and Genetic Algorithms

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Simpson, M. D.; Philip, C. S.; Baskett, R.

2017-12-01

Hazardous conditions during the Fukushima Daiichi nuclear power plant (NPP) accident hindered direct observations of the emissions of radioactive materials into the atmosphere. A wide range of emissions are estimated from bottom-up studies using reactor inventories and top-down approaches based on inverse modeling. We present a new inverse modeling estimate of cesium-137 emitted from the Fukushima NPP. Our estimate considers weather uncertainty through a large ensemble of Weather Research and Forecasting model simulations and uses the FLEXPART atmospheric dispersion model to transport and deposit cesium. The simulations are constrained by observations of the spatial distribution of cumulative cesium deposited on the surface of Japan through April 2, 2012. Multiple spatial metrics are used to quantify differences between observed and simulated deposition patterns. In order to match the observed pattern, we use a multi-objective genetic algorithm to optimize the time-varying emissions. We find that large differences with published bottom-up estimates are required to explain the observations. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Characterization and consequences of intermittent sediment oxygenation by macrofauna: interpretation of high-resolution data sets

NASA Astrophysics Data System (ADS)

Meile, C. D.; Dwyer, I.; Zhu, Q.; Polerecky, L.; Volkenborn, N.

2017-12-01

Mineralization of organic matter in marine sediments leads to the depletion of oxygen, while activities of infauna introduce oxygenated seawater to the subsurface. In permeable sediments solutes can be transported from animals and their burrows into the surrounding sediment through advection over several centimeters. The intermittency of pumping leads to a spatially heterogeneous distribution of oxidants, with the temporal dynamics depending on sediment reactivity and activity patterns of the macrofauna. Here, we present results from a series of experiments in which these dynamics are studied at high spatial and temporal resolution using planar optodes. From O2, pH and pCO2 optode data, we quantify rates of O2 consumption and dissolved inorganic carbon production, as well alkalinity dynamics, with millimeter-scale resolution. Simulating intermittent irrigation by imposed pumping patterns in thin aquaria, we derive porewater flow patterns, which together with the production and consumption rates cause the chemical distributions and the establishment of reaction fronts. Our analysis thus establishes a quantitative connection between the locally dynamic redox conditions relevant for biogeochemical transformations and macroscopic observations commonly made with sediment cores.

Using soil residence time to delineate spatial and temporal patterns of transient landscape response

NASA Astrophysics Data System (ADS)

Almond, Peter; Roering, Josh; Hales, T. C.

2007-09-01

On hillslopes the balance between soil transport and production determines local soil thickness and the age distribution of particles that comprise the soil (where age refers to the time elapsed since detachment from bedrock). The mean of this age distribution is defined as the residence time, and in a landscape with time-invariant topography (i.e., morphologic steady state), the spatial uniformity of soil production ensures that the residence time of soils is spatially invariant. Thus, given constant soil-forming factors, spatial variation of soil properties reflects differences in residence time driven by nonuniform soil production. Spatially extensive soil databases, which are often freely available in electronic form, provide a cheap and accessible means of analyzing patterns of soil residence time and quantifying landscape dynamics. Here we use a soil chronosequence to calibrate a chronofunction describing the reddening of soils in the Oregon Coast Range, which is then used to quantify the spatial distribution of soil residence time. In contrast to the popular conception that the Oregon Coast Range experiences uniform erosion, we observe systematic variations in soil residence time driven by stream capture, deep-seated landsliding, and lateral channel migration. Large, contiguous areas with short residence time soils (hue 10YR) occur west of the Siuslaw River-Long Tom Creek drainage divide, whereas soil patches with redder hues of 7.5YR or 5YR indicate longer residence times and transient landscape conditions. These zones of red soils (5YR) occur east of the Siuslaw-Long Tom divide, coinciding with low-gradient ridge and valley topography and deeply alluviated valleys resulting from drainage reversal in the Quaternary. Patches of red soils are also associated with deep-seated landslides at various locations in our study area. Our calculated soil residence times appear subject to overestimation resulting from limitations of the simple weathering index used here and chronofunction calibration uncertainties. Nonetheless, our soil residence time estimates appear accurate to within an order of magnitude and provide a useful constraint on landscape dynamics over geomorphic timescales.

Portable (handheld) clinical device for quantitative spectroscopy of skin, utilizing spatial frequency domain reflectance techniques

NASA Astrophysics Data System (ADS)

Saager, Rolf B.; Dang, An N.; Huang, Samantha S.; Kelly, Kristen M.; Durkin, Anthony J.

2017-09-01

Spatial Frequency Domain Spectroscopy (SFDS) is a technique for quantifying in-vivo tissue optical properties. SFDS employs structured light patterns that are projected onto tissues using a spatial light modulator, such as a digital micromirror device. In combination with appropriate models of light propagation, this technique can be used to quantify tissue optical properties (absorption, μa, and scattering, μs', coefficients) and chromophore concentrations. Here we present a handheld implementation of an SFDS device that employs line (one dimensional) imaging. This instrument can measure 1088 spatial locations that span a 3 cm line as opposed to our original benchtop SFDS system that only collects a single 1 mm diameter spot. This imager, however, retains the spectral resolution (˜1 nm) and range (450-1000 nm) of our original benchtop SFDS device. In the context of homogeneous turbid media, we demonstrate that this new system matches the spectral response of our original system to within 1% across a typical range of spatial frequencies (0-0.35 mm-1). With the new form factor, the device has tremendously improved mobility and portability, allowing for greater ease of use in a clinical setting. A smaller size also enables access to different tissue locations, which increases the flexibility of the device. The design of this portable system not only enables SFDS to be used in clinical settings but also enables visualization of properties of layered tissues such as skin.

SPECIAL - The Savanna Patterns of Energy and Carbon Integrated Across the Landscape campaign

NASA Astrophysics Data System (ADS)

Beringer, J.; Hacker, J.; Hutley, L. B.; Leuning, R.; Arndt, S. K.; Amiri, R.; Bannehr, L.; Cernusak, L. A.; Grover, S.; Hensley, C.; Hocking, D. J.; Isaac, P. R.; Jamali, H.; Kanniah, K.; Livesley, S.; Neininger, B.; Paw U, K.; Sea, W. B.; Straten, D.; Tapper, N. J.; Weinmann, R. A.; Wood, S.; Zegelin, S. J.

2010-12-01

We undertook a significant field campaign (SPECIAL) to examine spatial patterns and processes of land surface-atmosphere exchanges (radiation, heat, moisture, CO2 and other trace gasses) across scales from leaf to landscape scales within Australian savannas. Such savanna ecosystems occur in over 20 countries and cover approximately 15% of the world’s land surface. They consist of a mix of trees and grasses that coexist, but are spatially highly varied in their physical structure, species composition and physiological function. This spatial variation is driven by climate factors (rainfall gradients and seasonality) and disturbances (fire, grazing, herbivory, cyclones). Variations in savanna structure, composition and function (i.e. leaf area and function, stem density, albedo, roughness) interact with the overlying atmosphere directly through exchanges of heat and moisture, which alter the overlying boundary layer. Variability in ecosystem types across the landscape can alter regional to global circulation patterns. Equally, savannas are an important part of the global carbon cycle and can influence the climate through net uptake or release of CO2. We utilized a combination of multiscale measurements including fixed flux towers, aircraft-based flux and regional budget measurements, and satellite remotely sensed quantities to quantify the spatial variability utilizing a continental scale rainfall gradient that resulted in a variety of savanna types. The ultimate goal of our research is to be able to produce robust estimates of regional carbon and water cycles to inform land management policy about how they may respond to future environmental changes.

Stochastic Analysis and Probabilistic Downscaling of Soil Moisture

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Sensitivity of landscape metrics to changing scale of remote sensing data in spatial pattern analysis: effect, criticality and scaling.

NASA Astrophysics Data System (ADS)

Xu, C.; Zhao, S.; Zhao, B.

2017-12-01

Spatial heterogeneity is scale-dependent, that is, the quantification and representation of spatial pattern vary with the resolution and extent. Overwhelming practices focused on scale effect of landscape metrics, and predicable scaling relationships found among some of them are thought to be the most effective and precise way to quantify multi-scale characteristics. However, previous studies tended to consider a narrow range of scales, and few focused on the critical threshold of scaling function. Here we examine the scalograms of 38 widely-used landscape-level metrics in a more integral spectrum of grain size among 96 landscapes with various extent (i.e. from 25km2 up towards to 221 km2), which sampled randomly from NLCD product. Our goal is to explore the existence of scaling domain and whether the response of metrics to changing resolution would be influenced by spatial extent. Results clearly show the existence of scaling domain for 13 of them (Type II), while the behaviors of other 13 (Type I) exhibit simple scaling functions and the rest (Type III) demonstrate various forms like no obvious change or fluctuation across the integral spectrum of grain size. In addition, an invariant power law scaling relationship was found between critical resolution and spatial extent for metrics falling into Type II, as the critical resolution is proportional to Eρ (ρ is a constant, and E is the extent). All the scaling exponents (ρ) are positive, suggesting that the critical resolutions for these characteristics of landscape structure can be relaxed as the spatial extent expands. This agrees well with empirical perception that coarser grain size might be allowed for spatial data with larger extent. Furthermore, the parameters of scaling functions for metrics falling into Type I and Type II vary with spatial extent, and power law or logarithmic relationships could be identified between them for some metrics. Our finding support the existence of self-organized criticality for a hierarchically-structured landscape. Although the underlying mechanism driving the scaling relationship remains unclear, it could provide guidance toward general principles in spatial pattern analysis and on selecting the proper resolution to avoid the misrepresentation of spatial pattern and profound biases in further ecological progress research.

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

PubMed

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

2007-01-01

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

Understanding The Individual Impacts Of Human Interventions And Climate Change On Hydrologic Variables In India

NASA Astrophysics Data System (ADS)

Sharma, T.; Chhabra, S., Jr.; Karmakar, S.; Ghosh, S.

2015-12-01

We have quantified the historical climate change and Land Use Land Cover (LULC) change impacts on the hydrologic variables of Indian subcontinent by using Variable Infiltration Capacity (VIC) mesoscale model at 0.5° spatial resolution and daily temporal resolution. The results indicate that the climate change in India has predominating effects on the basic water balance components such as water yield, evapotranspiration and soil moisture. This analysis is with the assumption of naturalised hydrologic cycle, i.e., the impacts of human interventions like construction of controlled (primarily dams, diversions and reservoirs) and water withdrawals structures are not taken into account. The assumption is unrealistic since there are numerous anthropogenic disturbances which result in large changes on vegetation composition and distribution patterns. These activities can directly or indirectly influence the dynamics of water cycle; subsequently affecting the hydrologic processes like plant transpiration, infiltration, evaporation, runoff and sublimation. Here, we have quantified the human interventions by using the reservoir and irrigation module of VIC model which incorporates the irrigation schemes, reservoir characteristics and water withdrawals. The impact of human interventions on hydrologic variables in many grids are found more predominant than climate change and might be detrimental to water resources at regional level. This spatial pattern of impacts will facilitate water manager and planners to design and station hydrologic structures for a sustainable water resources management.

Time Lapse Electrical Resistivity to Connect Evapotranspiration and Groundwater Fluxes in the Critical Zone

NASA Astrophysics Data System (ADS)

Jarvis, S. K.; Harmon, R. E.; Barnard, H. R.; Randall, J.; Singha, K.

2017-12-01

The critical zone (CZ)—an open system extending from canopy top to the base of groundwater—is a highly dynamic and heterogeneous environment. In forested terrain, trees make up a large component of the CZ. This work aims to quantify the connection between vegetation and subsurface water storage at a hillslope scale within a forested watershed in the H.J. Andrews Experimental Forest, Oregon. To identify the mechanism(s) controlling the connection at the hillslope scale, we observe patterns in electrical conductivity using 2D-time lapse-DC resistivity. To compare inversions through time a representative error model was determined using L-curve criterion. Inverted data show high spatial variability in ground electrical conductivity and variation at both diel and seasonal timescales. These changes are most pronounced in areas corresponding to dense vegetation. The diel pattern in electrical conductivity is also observed in monitored sap flow sensors, water-level gauges, tensiometers, and sediment thermal probes. To quantify the temporal connection between these data over the course of the growing season a cross correlation analysis was conducted. Preliminary data show that over the course of the growing season transpiration becomes decoupled from both groundwater and soil moisture. Further decomposition of the inverted time lapse data will highlight spatial variability in electrical conductivity providing insight into the where, when, and how(s) of tree-modified subsurface storage.

Comparing methods of measuring geographic patterns in temporal trends: an application to county-level heart disease mortality in the United States, 1973 to 2010.

PubMed

Vaughan, Adam S; Kramer, Michael R; Waller, Lance A; Schieb, Linda J; Greer, Sophia; Casper, Michele

2015-05-01

To demonstrate the implications of choosing analytical methods for quantifying spatiotemporal trends, we compare the assumptions, implementation, and outcomes of popular methods using county-level heart disease mortality in the United States between 1973 and 2010. We applied four regression-based approaches (joinpoint regression, both aspatial and spatial generalized linear mixed models, and Bayesian space-time model) and compared resulting inferences for geographic patterns of local estimates of annual percent change and associated uncertainty. The average local percent change in heart disease mortality from each method was -4.5%, with the Bayesian model having the smallest range of values. The associated uncertainty in percent change differed markedly across the methods, with the Bayesian space-time model producing the narrowest range of variance (0.0-0.8). The geographic pattern of percent change was consistent across methods with smaller declines in the South Central United States and larger declines in the Northeast and Midwest. However, the geographic patterns of uncertainty differed markedly between methods. The similarity of results, including geographic patterns, for magnitude of percent change across these methods validates the underlying spatial pattern of declines in heart disease mortality. However, marked differences in degree of uncertainty indicate that Bayesian modeling offers substantially more precise estimates. Copyright © 2015 Elsevier Inc. All rights reserved.

Do we really use rainfall observations consistent with reality in hydrological modelling?

NASA Astrophysics Data System (ADS)

Ciampalini, Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Moussa, Roger; Le Bissonnais, Yves

2017-04-01

Spatial and temporal patterns in rainfall control how water reaches soil surface and interacts with soil properties (i.e., soil wetting, infiltration, saturation). Once a hydrological event is defined by a rainfall with its spatiotemporal variability and by some environmental parameters such as soil properties (including land use, topographic and anthropic features), the evidence shows that each parameter variation produces different, specific outputs (e.g., runoff, flooding etc.). In this study, we focus on the effect of rainfall patterns because, due to the difficulty to dispose of detailed data, their influence in modelling is frequently underestimated or neglected. A rainfall event affects a catchment non uniformly, it is spatially localized and its pattern moves in space and time. The way and the time how the water reaches the soil and saturates it respect to the geometry of the catchment deeply influences soil saturation, runoff, and then sediment delivery. This research, approaching a hypothetical, simple case, aims to stimulate the debate on the reliability of the rainfall quality used in hydrological / soil erosion modelling. We test on a small catchment of the south of France (Roujan, Languedoc Roussillon) the influence of rainfall variability with the use of a HD hybrid hydrological - soil erosion model, combining a cinematic wave with the St. Venant equation and a simplified "bucket" conceptual model for ground water, able to quantify the effect of different spatiotemporal patterns of a very-high-definition synthetic rainfall. Results indicate that rainfall spatiotemporal patterns are crucial simulating an erosive event: differences between spatially uniform rainfalls, as frequently adopted in simulations, and some hypothetical rainfall patterns here applied, reveal that the outcome of a simulated event can be highly underestimated.

The Nature of Antarctic Temperature Change

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Can trait patterns along gradients predict plant community responses to climate change?

PubMed

Guittar, John; Goldberg, Deborah; Klanderud, Kari; Telford, Richard J; Vandvik, Vigdis

2016-10-01

Plant functional traits vary consistently along climate gradients and are therefore potential predictors of plant community response to climate change. We test this space-for-time assumption by combining a spatial gradient study with whole-community turf transplantation along temperature and precipitation gradients in a network of 12 grassland sites in Southern Norway. Using data on eight traits for 169 species and annual vegetation censuses of 235 turfs over 5 yr, we quantify trait-based responses to climate change by comparing observed community dynamics in transplanted turfs to field-parameterized null model simulations. Three traits related to species architecture (maximum height, number of dormant meristems, and ramet-ramet connection persistence) varied consistently along spatial temperature gradients and also correlated to changes in species abundances in turfs transplanted to warmer climates. Two traits associated with resource acquisition strategy (SLA, leaf area) increased along spatial temperature gradients but did not correlate to changes in species abundances following warming. No traits correlated consistently with precipitation. Our study supports the hypothesis that spatial associations between plant traits and broad-scale climate variables can be predictive of community response to climate change, but it also suggests that not all traits with clear patterns along climate gradients will necessarily influence community response to an equal degree. © 2016 by the Ecological Society of America.

Spatial elements of mortality risk in old-growth forests

USGS Publications Warehouse

Das, Adrian; Battles, John; van Mantgem, Phillip J.; Stephenson, Nathan L.

2008-01-01

For many species of long-lived organisms, such as trees, survival appears to be the most critical vital rate affecting population persistence. However, methods commonly used to quantify tree death, such as relating tree mortality risk solely to diameter growth, almost certainly do not account for important spatial processes. Our goal in this study was to detect and, if present, to quantify the relevance of such processes. For this purpose, we examined purely spatial aspects of mortality for four species, Abies concolor, Abies magnifica, Calocedrus decurrens, and Pinus lambertiana, in an old-growth conifer forest in the Sierra Nevada of California, USA. The analysis was performed using data from nine fully mapped long-term monitoring plots.In three cases, the results unequivocally supported the inclusion of spatial information in models used to predict mortality. For Abies concolor, our results suggested that growth rate may not always adequately capture increased mortality risk due to competition. We also found evidence of a facilitative effect for this species, with mortality risk decreasing with proximity to conspecific neighbors. For Pinus lambertiana, mortality risk increased with density of conspecific neighbors, in keeping with a mechanism of increased pathogen or insect pressure (i.e., a Janzen-Connell type effect). Finally, we found that models estimating risk of being crushed were strongly improved by the inclusion of a simple index of spatial proximity.Not only did spatial indices improve models, those improvements were relevant for mortality prediction. For P. lambertiana, spatial factors were important for estimation of mortality risk regardless of growth rate. For A. concolor, although most of the population fell within spatial conditions in which mortality risk was well described by growth, trees that died occurred outside those conditions in a disproportionate fashion. Furthermore, as stands of A. concolor become increasingly dense, such spatial factors are likely to become increasingly important. In general, models that fail to account for spatial pattern are at risk of failure as conditions change.

The spatial epidemiology of trauma: the potential of geographic information science to organize data and reveal patterns of injury and services

PubMed Central

Schuurman, Nadine; Hameed, S. Morad; Fiedler, Robert; Bell, Nathaniel; Simons, Richard K.

2008-01-01

Despite important advances in the prevention and treatment of trauma, preventable injuries continue to impact the lives of millions of people. Motor vehicle collisions and violence claim close to 3 million lives each year worldwide. Public health agencies have promoted the need for systematic and ongoing surveillance as a foundation for successful injury control. Surveillance has been used to quantify the incidence of injury for the prioritization of further research, monitor trends over time, identify new injury patterns, and plan and evaluate prevention and intervention efforts. Advances in capability to handle spatial data and substantial increases in computing power have positioned geographic information science (GIS) as a potentially important tool for health surveillance and the spatial organization of health care, and for informing prevention and acute care interventions. Two themes emerge in the trauma literature with respect to GIS theory and techniques: identifying determinants associated with the risk of trauma to guide injury prevention efforts and evaluating the spatial organization and accessibility of acute trauma care systems. We review the current literature on trauma and GIS research and provide examples of the importance of accounting for spatial scale when using spatial analysis for surveillance. The examples illustrate the effect of scale on incident analysis, the geographic variation of major injury across British Columbia's health service delivery areas (HSDAs) and the rates of variation of injury within individual HSDAs. PMID:18841227

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

NASA Astrophysics Data System (ADS)

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

2015-03-01

Spatial variability of throughfall isotopic composition in forests is indicative of complex processes occurring in the canopy and remains insufficiently understood to properly characterize precipitation inputs to the catchment water balance. Here we investigate variability of throughfall isotopic composition with the objectives: (1) to quantify the spatial variability in event-scale samples, (2) to determine if there are persistent controls over the variability and how these affect variability of seasonally accumulated throughfall, and (3) to analyze the distribution of measured throughfall isotopic composition associated with varying sampling regimes. We measured throughfall over two, three-month periods in western Oregon, USA under a Douglas-fir canopy. The mean spatial range of δ18O for each event was 1.6‰ and 1.2‰ through Fall 2009 (11 events) and Spring 2010 (7 events), respectively. However, the spatial pattern of isotopic composition was not temporally stable causing season-total throughfall to be less variable than event throughfall (1.0‰; range of cumulative δ18O for Fall 2009). Isotopic composition was not spatially autocorrelated and not explained by location relative to tree stems. Sampling error analysis for both field measurements and Monte-Carlo simulated datasets representing different sampling schemes revealed the standard deviation of differences from the true mean as high as 0.45‰ (δ18O) and 1.29‰ (d-excess). The magnitude of this isotopic variation suggests that small sample sizes are a source of substantial experimental error.

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.

Quantifying Climatological Ranges and Anomalies for Pacific Coral Reef Ecosystems

PubMed Central

Gove, Jamison M.; Williams, Gareth J.; McManus, Margaret A.; Heron, Scott F.; Sandin, Stuart A.; Vetter, Oliver J.; Foley, David G.

2013-01-01

Coral reef ecosystems are exposed to a range of environmental forcings that vary on daily to decadal time scales and across spatial scales spanning from reefs to archipelagos. Environmental variability is a major determinant of reef ecosystem structure and function, including coral reef extent and growth rates, and the abundance, diversity, and morphology of reef organisms. Proper characterization of environmental forcings on coral reef ecosystems is critical if we are to understand the dynamics and implications of abiotic–biotic interactions on reef ecosystems. This study combines high-resolution bathymetric information with remotely sensed sea surface temperature, chlorophyll-a and irradiance data, and modeled wave data to quantify environmental forcings on coral reefs. We present a methodological approach to develop spatially constrained, island- and atoll-scale metrics that quantify climatological range limits and anomalous environmental forcings across U.S. Pacific coral reef ecosystems. Our results indicate considerable spatial heterogeneity in climatological ranges and anomalies across 41 islands and atolls, with emergent spatial patterns specific to each environmental forcing. For example, wave energy was greatest at northern latitudes and generally decreased with latitude. In contrast, chlorophyll-a was greatest at reef ecosystems proximate to the equator and northern-most locations, showing little synchrony with latitude. In addition, we find that the reef ecosystems with the highest chlorophyll-a concentrations; Jarvis, Howland, Baker, Palmyra and Kingman are each uninhabited and are characterized by high hard coral cover and large numbers of predatory fishes. Finally, we find that scaling environmental data to the spatial footprint of individual islands and atolls is more likely to capture local environmental forcings, as chlorophyll-a concentrations decreased at relatively short distances (>7 km) from 85% of our study locations. These metrics will help identify reef ecosystems most exposed to environmental stress as well as systems that may be more resistant or resilient to future climate change. PMID:23637939

Quantifying climatological ranges and anomalies for Pacific coral reef ecosystems.

PubMed

Gove, Jamison M; Williams, Gareth J; McManus, Margaret A; Heron, Scott F; Sandin, Stuart A; Vetter, Oliver J; Foley, David G

2013-01-01

Coral reef ecosystems are exposed to a range of environmental forcings that vary on daily to decadal time scales and across spatial scales spanning from reefs to archipelagos. Environmental variability is a major determinant of reef ecosystem structure and function, including coral reef extent and growth rates, and the abundance, diversity, and morphology of reef organisms. Proper characterization of environmental forcings on coral reef ecosystems is critical if we are to understand the dynamics and implications of abiotic-biotic interactions on reef ecosystems. This study combines high-resolution bathymetric information with remotely sensed sea surface temperature, chlorophyll-a and irradiance data, and modeled wave data to quantify environmental forcings on coral reefs. We present a methodological approach to develop spatially constrained, island- and atoll-scale metrics that quantify climatological range limits and anomalous environmental forcings across U.S. Pacific coral reef ecosystems. Our results indicate considerable spatial heterogeneity in climatological ranges and anomalies across 41 islands and atolls, with emergent spatial patterns specific to each environmental forcing. For example, wave energy was greatest at northern latitudes and generally decreased with latitude. In contrast, chlorophyll-a was greatest at reef ecosystems proximate to the equator and northern-most locations, showing little synchrony with latitude. In addition, we find that the reef ecosystems with the highest chlorophyll-a concentrations; Jarvis, Howland, Baker, Palmyra and Kingman are each uninhabited and are characterized by high hard coral cover and large numbers of predatory fishes. Finally, we find that scaling environmental data to the spatial footprint of individual islands and atolls is more likely to capture local environmental forcings, as chlorophyll-a concentrations decreased at relatively short distances (>7 km) from 85% of our study locations. These metrics will help identify reef ecosystems most exposed to environmental stress as well as systems that may be more resistant or resilient to future climate change.

Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA.

PubMed

Cao, Xiaodong; MacNaughton, Piers; Deng, Zhengyi; Yin, Jie; Zhang, Xi; Allen, Joseph G

2018-02-02

Twitter provides a rich database of spatiotemporal information about users who broadcast their real-time opinions, sentiment, and activities. In this paper, we sought to investigate the holistic influence of land use and time period on public sentiment. A total of 880,937 tweets posted by 26,060 active users were collected across Massachusetts (MA), USA, through 31 November 2012 to 3 June 2013. The IBM Watson Alchemy API (application program interface) was employed to quantify the sentiment scores conveyed by tweets on a large scale. Then we statistically analyzed the sentiment scores across different spaces and times. A multivariate linear mixed-effects model was used to quantify the fixed effects of land use and the time period on the variations in sentiment scores, considering the clustering effect of users. The results exposed clear spatiotemporal patterns of users' sentiment. Higher sentiment scores were mainly observed in the commercial and public areas, during the noon/evening and on weekends. Our findings suggest that social media outputs can be used to better understand the spatial and temporal patterns of public happiness and well-being in cities and regions.

Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA

PubMed Central

MacNaughton, Piers; Deng, Zhengyi; Yin, Jie; Zhang, Xi; Allen, Joseph G.

2018-01-01

Twitter provides a rich database of spatiotemporal information about users who broadcast their real-time opinions, sentiment, and activities. In this paper, we sought to investigate the holistic influence of land use and time period on public sentiment. A total of 880,937 tweets posted by 26,060 active users were collected across Massachusetts (MA), USA, through 31 November 2012 to 3 June 2013. The IBM Watson Alchemy API (application program interface) was employed to quantify the sentiment scores conveyed by tweets on a large scale. Then we statistically analyzed the sentiment scores across different spaces and times. A multivariate linear mixed-effects model was used to quantify the fixed effects of land use and the time period on the variations in sentiment scores, considering the clustering effect of users. The results exposed clear spatiotemporal patterns of users’ sentiment. Higher sentiment scores were mainly observed in the commercial and public areas, during the noon/evening and on weekends. Our findings suggest that social media outputs can be used to better understand the spatial and temporal patterns of public happiness and well-being in cities and regions. PMID:29393869

Population structure and cultural geography of a folktale in Europe

PubMed Central

Ross, Robert M.; Greenhill, Simon J.; Atkinson, Quentin D.

2013-01-01

Despite a burgeoning science of cultural evolution, relatively little work has focused on the population structure of human cultural variation. By contrast, studies in human population genetics use a suite of tools to quantify and analyse spatial and temporal patterns of genetic variation within and between populations. Human genetic diversity can be explained largely as a result of migration and drift giving rise to gradual genetic clines, together with some discontinuities arising from geographical and cultural barriers to gene flow. Here, we adapt theory and methods from population genetics to quantify the influence of geography and ethnolinguistic boundaries on the distribution of 700 variants of a folktale in 31 European ethnolinguistic populations. We find that geographical distance and ethnolinguistic affiliation exert significant independent effects on folktale diversity and that variation between populations supports a clustering concordant with European geography. This pattern of geographical clines and clusters parallels the pattern of human genetic diversity in Europe, although the effects of geographical distance and ethnolinguistic boundaries are stronger for folktales than genes. Our findings highlight the importance of geography and population boundaries in models of human cultural variation and point to key similarities and differences between evolutionary processes operating on human genes and culture. PMID:23390109

Spatial variation and seasonal dynamics of leaf-area index in the arctic tundra-implications for linking ground observations and satellite images

NASA Astrophysics Data System (ADS)

Juutinen, Sari; Virtanen, Tarmo; Kondratyev, Vladimir; Laurila, Tuomas; Linkosalmi, Maiju; Mikola, Juha; Nyman, Johanna; Räsänen, Aleksi; Tuovinen, Juha-Pekka; Aurela, Mika

2017-09-01

Vegetation in the arctic tundra typically consists of a small-scale mosaic of plant communities, with species differing in growth forms, seasonality, and biogeochemical properties. Characterization of this variation is essential for understanding and modeling the functioning of the arctic tundra in global carbon cycling, as well as for evaluating the resolution requirements for remote sensing. Our objective was to quantify the seasonal development of the leaf-area index (LAI) and its variation among plant communities in the arctic tundra near Tiksi, coastal Siberia, consisting of graminoid, dwarf shrub, moss, and lichen vegetation. We measured the LAI in the field and used two very-high-spatial resolution multispectral satellite images (QuickBird and WorldView-2), acquired at different phenological stages, to predict landscape-scale patterns. We used the empirical relationships between the plant community-specific LAI and degree-day accumulation (0 °C threshold) and quantified the relationship between the LAI and satellite NDVI (normalized difference vegetation index). Due to the temporal difference between the field data and satellite images, the LAI was approximated for the imagery dates, using the empirical model. LAI explained variation in the NDVI values well (R 2 adj. 0.42-0.92). Of the plant functional types, the graminoid LAI showed the largest seasonal amplitudes and was the main cause of the varying spatial patterns of the NDVI and the related LAI between the two images. Our results illustrate how the short growing season, rapid development of the LAI, yearly climatic variation, and timing of the satellite data should be accounted for in matching imagery and field verification data in the Arctic region.

Spherical Deconvolution of Multichannel Diffusion MRI Data with Non-Gaussian Noise Models and Spatial Regularization

PubMed Central

Canales-Rodríguez, Erick J.; Caruyer, Emmanuel; Aja-Fernández, Santiago; Radua, Joaquim; Yurramendi Mendizabal, Jesús M.; Iturria-Medina, Yasser; Melie-García, Lester; Alemán-Gómez, Yasser; Thiran, Jean-Philippe; Sarró, Salvador; Pomarol-Clotet, Edith; Salvador, Raymond

2015-01-01

Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel MRI signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in human brain data. PMID:26470024

Quantifying Seasonal Dynamic Water Storage in a Fractured Bedrock Vadose Zone With Borehole Nuclear Magnetic Resonance

NASA Astrophysics Data System (ADS)

Schmidt, L.; Minton, B.; Soto-Kerans, N.; Rempe, D.; Heidari, Z.

2017-12-01

In many uplands landscapes, water is transiently stored in the weathered and fractured bedrock that underlies soils. The timing and spatial pattern of this "rock moisture" has strong implications for ecological and biogeochemical processes that influence global cycling of water and solutes. However, available technologies for direct monitoring of rock moisture are limited. Here, we quantify temporal and spatial changes in rock moisture at the field scale across thick (up to 20 m) fractured vadose zone profiles using a novel narrow diameter borehole nuclear magnetic resonance system (BNMR). Successive BNMR surveys were performed using the Vista Clara Inc. Dart system in a network of boreholes within two steep, intensively hydrologically monitored hillslopes associated with the Eel River Critical Zone Observatory (ERCZO) in Northern California. BNMR data showed agreement with estimates of the temporal and spatial pattern of rock moisture depletion over the dry season via downhole neutron and gamma density surveys, as well as permanently installed continuous time domain reflectometry. Observable shifts in the BNMR-derived T2 distribution over time provide a direct measure of changes in the amount of water held within different pore sizes (large vs. small) in fractured rock. Analysis of both BNMR and laboratory-scale NMR (using a 2MHz benchtop NMR spectrometer) measurements of ERCZO core samples at variable saturation suggest that rock moisture changes associated with summer depletion occur within both large (fracture) and small (matrix) pore sizes. Collectively, our multi-method field- and laboratory- scale measurements highlight the potential for BNMR to improve quantification of rock moisture storage for better understanding of the biogeochemical and ecohydrological implications of rock moisture circulation in the Critical Zone.

Population substructure and space use of Foxe Basin polar bears.

PubMed

Sahanatien, Vicki; Peacock, Elizabeth; Derocher, Andrew E

2015-07-01

Climate change has been identified as a major driver of habitat change, particularly for sea ice-dependent species such as the polar bear (Ursus maritimus). Population structure and space use of polar bears have been challenging to quantify because of their circumpolar distribution and tendency to range over large areas. Knowledge of movement patterns, home range, and habitat is needed for conservation and management. This is the first study to examine the spatial ecology of polar bears in the Foxe Basin management unit of Nunavut, Canada. Foxe Basin is in the mid-Arctic, part of the seasonal sea ice ecoregion and it is being negatively affected by climate change. Our objectives were to examine intrapopulation spatial structure, to determine movement patterns, and to consider how polar bear movements may respond to changing sea ice habitat conditions. Hierarchical and fuzzy cluster analyses were used to assess intrapopulation spatial structure of geographic position system satellite-collared female polar bears. Seasonal and annual movement metrics (home range, movement rates, time on ice) and home-range fidelity (static and dynamic overlap) were compared to examine the influence of regional sea ice on movements. The polar bears were distributed in three spatial clusters, and there were differences in the movement metrics between clusters that may reflect sea ice habitat conditions. Within the clusters, bears moved independently of each other. Annual and seasonal home-range fidelity was observed, and the bears used two movement patterns: on-ice range residency and annual migration. We predict that home-range fidelity may decline as the spatial and temporal predictability of sea ice changes. These new findings also provide baseline information for managing and monitoring this polar bear population.

Least-cost transportation networks predict spatial interaction of invasion vectors.

PubMed

Drake, D Andrew R; Mandrak, Nicholas E

2010-12-01

Human-mediated dispersal among aquatic ecosystems often results in biotic transfer between drainage basins. Such activities may circumvent biogeographic factors, with considerable ecological, evolutionary, and economic implications. However, the efficacy of predictions concerning community changes following inter-basin movements are limited, often because the dispersal mechanism is poorly understood (e.g., quantified only partially). To date, spatial-interaction models that predict the movement of humans as vectors of biotic transfer have not incorporated patterns of human movement through transportation networks. As a necessary first step to determine the role of anglers as invasion vectors across a land-lake ecosystem, we investigate their movement potential within Ontario, Canada. To determine possible model improvements resulting from inclusion of network travel, spatial-interaction models were constructed using standard Euclidean (e.g., straight-line) distance measures and also with distances derived from least-cost routing of human transportation networks. Model comparisons determined that least-cost routing both provided the most parsimonious model and also excelled at forecasting spatial interactions, with a proportion of 0.477 total movement deviance explained. The distribution of movements was characterized by many relatively short to medium travel distances (median = 292.6 km) with fewer lengthier distances (75th percentile = 484.6 km, 95th percentile = 775.2 km); however, even the shortest movements were sufficient to overcome drainage-basin boundaries. Ranking of variables in order of their contribution within the most parsimonious model determined that distance traveled, origin outflow, lake attractiveness, and sportfish richness significantly influence movement patterns. Model improvements associated with least-cost routing of human transportation networks imply that patterns of human-mediated invasion are fundamentally linked to the spatial configuration and relative impedance of human transportation networks, placing increased importance on understanding their contribution to the invasion process.

Microbes on mountainsides: Contrasting elevational patterns of bacterial and plant diversity

PubMed Central

Bryant, Jessica A.; Lamanna, Christine; Morlon, Hélène; Kerkhoff, Andrew J.; Enquist, Brian J.; Green, Jessica L.

2008-01-01

The study of elevational diversity gradients dates back to the foundation of biogeography. Although elevational patterns of plant and animal diversity have been studied for centuries, such patterns have not been reported for microorganisms and remain poorly understood. Here, in an effort to assess the generality of elevational diversity patterns, we examined soil bacterial and plant diversity along an elevation gradient. To gain insight into the forces that structure these patterns, we adopted a multifaceted approach to incorporate information about the structure, diversity, and spatial turnover of montane communities in a phylogenetic context. We found that observed patterns of plant and bacterial diversity were fundamentally different. While bacterial taxon richness and phylogenetic diversity decreased monotonically from the lowest to highest elevations, plants followed a unimodal pattern, with a peak in richness and phylogenetic diversity at mid-elevations. At all elevations bacterial communities had a tendency to be phylogenetically clustered, containing closely related taxa. In contrast, plant communities did not exhibit a uniform phylogenetic structure across the gradient: they became more overdispersed with increasing elevation, containing distantly related taxa. Finally, a metric of phylogenetic beta-diversity showed that bacterial lineages were not randomly distributed, but rather exhibited significant spatial structure across the gradient, whereas plant lineages did not exhibit a significant phylogenetic signal. Quantifying the influence of sample scale in intertaxonomic comparisons remains a challenge. Nevertheless, our findings suggest that the forces structuring microorganism and macroorganism communities along elevational gradients differ. PMID:18695215

Identifying and Prioritizing Greater Sage-Grouse Nesting and Brood-Rearing Habitat for Conservation in Human-Modified Landscapes

PubMed Central

Dzialak, Matthew R.; Olson, Chad V.; Harju, Seth M.; Webb, Stephen L.; Mudd, James P.; Winstead, Jeffrey B.; Hayden-Wing, L.D.

2011-01-01

Background Balancing animal conservation and human use of the landscape is an ongoing scientific and practical challenge throughout the world. We investigated reproductive success in female greater sage-grouse (Centrocercus urophasianus) relative to seasonal patterns of resource selection, with the larger goal of developing a spatially-explicit framework for managing human activity and sage-grouse conservation at the landscape level. Methodology/Principal Findings We integrated field-observation, Global Positioning Systems telemetry, and statistical modeling to quantify the spatial pattern of occurrence and risk during nesting and brood-rearing. We linked occurrence and risk models to provide spatially-explicit indices of habitat-performance relationships. As part of the analysis, we offer novel biological information on resource selection during egg-laying, incubation, and night. The spatial pattern of occurrence during all reproductive phases was driven largely by selection or avoidance of terrain features and vegetation, with little variation explained by anthropogenic features. Specifically, sage-grouse consistently avoided rough terrain, selected for moderate shrub cover at the patch level (within 90 m2), and selected for mesic habitat in mid and late brood-rearing phases. In contrast, risk of nest and brood failure was structured by proximity to anthropogenic features including natural gas wells and human-created mesic areas, as well as vegetation features such as shrub cover. Conclusions/Significance Risk in this and perhaps other human-modified landscapes is a top-down (i.e., human-mediated) process that would most effectively be minimized by developing a better understanding of specific mechanisms (e.g., predator subsidization) driving observed patterns, and using habitat-performance indices such as those developed herein for spatially-explicit guidance of conservation intervention. Working under the hypothesis that industrial activity structures risk by enhancing predator abundance or effectiveness, we offer specific recommendations for maintaining high-performance habitat and reducing low-performance habitat, particularly relative to the nesting phase, by managing key high-risk anthropogenic features such as industrial infrastructure and water developments. PMID:22022587

Spatial Patterns of Variability in Antarctic Surface Temperature: Connections to the Southern Hemisphere Annular Mode and the Southern Oscillation

NASA Technical Reports Server (NTRS)

Kwok, Ron; Comiso, Josefino C.; Koblinsky, Chester J. (Technical Monitor)

2002-01-01

The 17-year (1982-1998) trend in surface temperature shows a general cooling over the Antarctic continent, warming of the sea ice zone, with moderate changes over the oceans. Warming of the peripheral seas is associated with negative trends in the regional sea ice extent. Effects of the Southern Hemisphere Annular Mode (SAM) and the extrapolar Southern Oscillation (SO) on surface temperature are quantified through regression analysis. Positive polarities of the SAM are associated with cold anomalies over most of Antarctica, with the most notable exception of the Antarctic Peninsula. Positive temperature anomalies and ice edge retreat in the Pacific sector are associated with El Nino episodes. Over the past two decades, the drift towards high polarity in the SAM and negative polarity in the SO indices couple to produce a spatial pattern with warmer temperatures in the Antarctic Peninsula and peripheral seas, and cooler temperatures over much of East Antarctica.

[Delineation of ecological security pattern based on ecological network].

PubMed

Fu, Qiang; Gu, Chao Lin

2017-03-18

Ecological network can be used to describe and assess the relationship between spatial organization of landscapes and species survival under the condition of the habitat fragmentation. Taking Qingdao City as the research area, woodland and wetland ecological networks in 2005 were simulated based on least cost path method, and the ecological networks were classified by their corridors' cumulative cost value. We made importance distinction of ecological network structure elements such as patches and corridors using betweenness centrality index and correlation length-percentage of importance of omitted patches index, and then created the structure system of ecological network. Considering the effects brought by the newly-added construction land from 2005 to 2013, we proposed the ecological security pattern for construction land change of Qingdao City. The results showed that based on ecological network framework, graph theory based methods could be used to quantify both attributes of specific ecological land (e.g., the area of an ecological network patch) and functional connection between ecological lands. Between 2005 and 2013, large area of wetlands had been destroyed by newly-added construction land, while the role of specific woodland and wetland played in the connection of the whole network had not been considered. The delineation of ecological security pattern based on ecological network could optimize regional ecological basis, provide accurate spatial explicit decision for ecological conservation and restoration, and meanwhile provide scientific and reasonable space guidance for urban spatial expansion.

Effects of developmental variability on the dynamics and self-organization of cell populations

NASA Astrophysics Data System (ADS)

Prabhakara, Kaumudi H.; Gholami, Azam; Zykov, Vladimir S.; Bodenschatz, Eberhard

2017-11-01

We report experimental and theoretical results for spatiotemporal pattern formation in cell populations, where the parameters vary in space and time due to mechanisms intrinsic to the system, namely Dictyostelium discoideum (D.d.) in the starvation phase. We find that different patterns are formed when the populations are initialized at different developmental stages, or when populations at different initial developmental stages are mixed. The experimentally observed patterns can be understood with a modified Kessler-Levine model that takes into account the initial spatial heterogeneity of the cell populations and a developmental path introduced by us, i.e. the time dependence of the various biochemical parameters. The dynamics of the parameters agree with known biochemical studies. Most importantly, the modified model reproduces not only our results, but also the observations of an independent experiment published earlier. This shows that pattern formation can be used to understand and quantify the temporal evolution of the system parameters.

Pattern Selection and Super-Patterns in Opinion Dynamics

NASA Astrophysics Data System (ADS)

Ben-Naim, Eli; Scheel, Arnd

We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes of the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. The spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.

Paleobotany and palynology of the Bristol Hill Coal Member (Bond Formation) and Friendsville Coal Member (Mattoon Formation) of the Illinois Basin (Upper Pennsylvanian)

USGS Publications Warehouse

Willard, D.A.; Phillips, T.L.

1993-01-01

Late Pennsylvanian coal swamps of the Illinois Basin were dominated by Psarnius tree ferns with a spatially heterogeneous distribution of medullosan pteridosperms (subdominant), calamites, sigillarian lycopsids, and cordaites. Miospore and coal-ball plant assemblages from the Missourian-age Bristol Hill Coal Member (Mattoon Formation) of southeastern Illinois were quantified to analyze vegetational patterns in Late Pennsylvanian peat swamps and to compare vegetational composition of the coals. -from Authors

Graffiti for science: Qualitative detection of erosional patterns through bedrock erosion painting

NASA Astrophysics Data System (ADS)

Beer, Alexander R.; Kirchner, James W.; Turowski, Jens M.

2016-04-01

Bedrock erosion is a crucial constraint on stream channel incision, and hence whole landscape evolution, in steep mountainous terrain and tectonically active regions. Several interacting processes lead to bedrock erosion in stream channels, with hydraulic shear detachment, plucking, and abrasion due to sediment impacts generally being the most efficient. Bedrock topography, together with the sediment tools and cover effects, regulate the rate and spatial pattern of in situ surface change. Measurements of natural bedrock erosion rates are valuable for understanding the underlying process physics, as well as for modelling landscape evolution and designing engineered structures. However, quantifying spatially distributed bedrock erosion rates in natural settings is challenging and few such measurements exist. We studied spatial bedrock erosion in a 30m-long bedrock gorge in the Gornera, a glacial meltwater stream above Zermatt. This stream is flushed episodically with sediment-laden streamflow due to hydropower operations upstream, with negligible discharge in the gorge in between these flushing events. We coated several bedrock surface patches with environmentally safe, and water-insoluble outdoor paint to document the spatial pattern of surface abrasion, or to be more precise, to document its driving forces. During four consecutive years, the change of the painted areas was recorded repeatedly with photographs before the painting was renewed. These photographs visually documented the spatial patterns of vertical erosion (channel incision), of lateral erosion (channel widening) and of downstream-directed erosion (channel clearance). The observed qualitative patterns were verified through comparison to quantitative change detection analyses based on annual high-resolution terrestrial laser scanning surveys of the bedrock surfaces. Comparison of repeated photographs indicated a temporal cover effect and a general height limit of the tools effect above the streambed during flushing events. Further, the photographs clearly show the erosional development of a UFCS (upstream-facing convex surface) feature with an upstream-facing surface full of impact marks, a sharp crest-line, and an adjacent downstream-facing surface preserved from sediment impacts. This pilot study documents that bedrock erosion painting provides an easy, cost-efficient and clear qualitative method for detecting the spatial distribution of bedrock erosion and inferring its controlling factors. Our results show that the susceptibility of a painted surface to abrasion is controlled by its position in the channel and its spatial orientation relative to the sediment-laden flow. Erosion painting is a scientifically useful form of graffiti that could be widely applied in both natural and laboratory settings, providing insight into patterns and processes of erosion.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Understanding the effects of predictability, duration, and spatial pattern of drying on benthic invertebrate assemblages in two contrasting intermittent streams

PubMed Central

von Schiller, Daniel; Barberá, Gonzalo G.; Díaz, Angela M.; Arce, Maria Isabel; del Campo, Rubén; Tockner, Klement

2018-01-01

In the present study, we examined the effects of different drying conditions on the composition, structure and function of benthic invertebrate assemblages. We approached this objective by comparing invertebrate assemblages in perennial and intermittent sites along two intermittent Mediterranean streams with contrasting predictability, duration, and spatial patterns of drying: Fuirosos (high predictability, short duration, downstream drying pattern) and Rogativa (low predictability, long duration, patchy drying pattern). Specifically, we quantified the contribution of individual taxa to those differences, the degree of nestedness, and shifts in the composition, structure and function of benthic invertebrate assemblages along flow intermittence gradients. We observed greater effects of drying on the benthic invertebrate composition in Fuirosos than in Rogativa, resulting in a higher dissimilarity of assemblages between perennial and intermittent sites, as well as a lower degree of nestedness. Furthermore, a higher number of biotic metrics related to richness, abundance and biological traits were significantly different between perennial and intermittent sites in Fuirosos, despite a shorter dry period compared to Rogativa. At the same time, slightly different responses were detected during post-drying (autumn) than pre-drying (spring) conditions in this stream. In Rogativa, shifts in benthic invertebrate assemblages along increasing gradients of flow intermittence were found for three metrics (Ephemeroptera, Plecoptera and Trichoptera (EPT) and Odonata, Coleoptera and Heteroptera (OCH) abundances and aerial active dispersal. Furthermore, we demonstrated that combined gradients of dry period duration and distance to nearest perennial reach can generate complex, and different, responses of benthic invertebrate assemblages, depending on the flow intermittence metric. Our study advances the notion that special attention should be paid to the predictability, duration and spatial patterns of drying in intermittent streams in order to disentangle the effects of drying on benthic invertebrate assemblages, in particular in areas subject to high spatial heterogeneity and temporal variability in drying conditions. PMID:29590140

Ametropia, retinal anatomy, and OCT abnormality patterns in glaucoma. 2. Impacts of optic nerve head parameters

NASA Astrophysics Data System (ADS)

Baniasadi, Neda; Wang, Mengyu; Wang, Hui; Jin, Qingying; Elze, Tobias

2017-12-01

Clinicians use retinal nerve fiber layer thickness (RNFLT) measured by optical coherence tomography (OCT) as an adjunct to glaucoma diagnosis. Ametropia is accompanied by changes to the optic nerve head (ONH), which may affect how OCT machines mark RNFLT measurements as abnormal. These changes in abnormality patterns may bias glaucoma diagnosis. Here, we investigate the relationship between OCT abnormality patterns and the following ONH-related and ametropia-associated parameters on 421 eyes of glaucoma patients: optic disc tilt and torsion, central retinal vessel trunk location (CRVTL), and nasal and temporal retinal curvature adjacent to ONH, quantified as nasal/temporal slopes of the inner limiting membrane. We applied multivariate logistic regression with abnormality marks as regressands to 40,401 locations of the peripapillary region and generated spatial maps of locations of false positive/negative abnormality marks independent of glaucoma severity. Effects of torsion and temporal slope were negligible. The effect of tilt could be explained by covariation with ametropia. For CRVTL/nasal slope, abnormality pattern shifts at 7.2%/23.5% of the peripapillary region were detected, respectively, independent of glaucoma severity and ametropia. Therefore, CRVTL and nasal curvature should be included in OCT RNFLT norms. Our spatial location maps may aid clinicians to improve diagnostic accuracy.

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.

Spatial Patterns of Soil Respiration Links Above and Belowground Processes along a Boreal Aspen Fire Chronosequence

PubMed Central

Das Gupta, Sanatan; Mackenzie, M. Derek

2016-01-01

Fire in boreal ecosystems is known to affect CO2 efflux from forest soils, which is commonly termed soil respiration (Rs). However, there is limited information on how fire and recovery from this disturbance affects spatial variation in Rs. The main objective of this study was to quantify the spatial variability of Rs over the growing season in a boreal aspen (Populus tremuloides Michx.) fire chronosequence. The chronosequence included three stands in northern Alberta; a post fire stand (1 year old, PF), a stand at canopy closure (9 years old, CC), and a mature stand (72 years old, MA). Soil respiration, temperature and moisture were measured monthly from May to August using an intensive spatial sampling protocol (n = 42, minimum lag = 2 m). Key aboveground and belowground properties were measured one time at each sampling point. No spatial structure was detected in Rs of the PF stand during the peak growing season (June and July), whereas Rs was auto-correlated at a scale of < 6 m in the CC and MA stands. The PF stand had the lowest mean Rs (4.60 μmol C m-2 s-1) followed by the CC (5.41 μmol C m-2 s-1), and the MA (7.32 μmol C m-2 s-1) stand. Forest floor depth was the only aboveground factor that influenced the spatial pattern of Rs in all three stands and was strongest in the PF stand. Enzyme activity and fine root biomass, on the other hand, were the significant belowground factors driving the spatial pattern of Rs in the CC and MA stands. Persistent joint aboveground and belowground control on Rs in the CC and MA stands indicates a tight spatial coupling, which was not observed in the PF stand. Overall, the current study suggests that fire in the boreal aspen ecosystem alters the spatial structure of Rs and that fine scale heterogeneity develops quickly as stands reach the canopy closure phase (<10 years). PMID:27832089

Spatial Patterns of Soil Respiration Links Above and Belowground Processes along a Boreal Aspen Fire Chronosequence.

PubMed

Das Gupta, Sanatan; Mackenzie, M Derek

2016-01-01

Fire in boreal ecosystems is known to affect CO2 efflux from forest soils, which is commonly termed soil respiration (Rs). However, there is limited information on how fire and recovery from this disturbance affects spatial variation in Rs. The main objective of this study was to quantify the spatial variability of Rs over the growing season in a boreal aspen (Populus tremuloides Michx.) fire chronosequence. The chronosequence included three stands in northern Alberta; a post fire stand (1 year old, PF), a stand at canopy closure (9 years old, CC), and a mature stand (72 years old, MA). Soil respiration, temperature and moisture were measured monthly from May to August using an intensive spatial sampling protocol (n = 42, minimum lag = 2 m). Key aboveground and belowground properties were measured one time at each sampling point. No spatial structure was detected in Rs of the PF stand during the peak growing season (June and July), whereas Rs was auto-correlated at a scale of < 6 m in the CC and MA stands. The PF stand had the lowest mean Rs (4.60 μmol C m-2 s-1) followed by the CC (5.41 μmol C m-2 s-1), and the MA (7.32 μmol C m-2 s-1) stand. Forest floor depth was the only aboveground factor that influenced the spatial pattern of Rs in all three stands and was strongest in the PF stand. Enzyme activity and fine root biomass, on the other hand, were the significant belowground factors driving the spatial pattern of Rs in the CC and MA stands. Persistent joint aboveground and belowground control on Rs in the CC and MA stands indicates a tight spatial coupling, which was not observed in the PF stand. Overall, the current study suggests that fire in the boreal aspen ecosystem alters the spatial structure of Rs and that fine scale heterogeneity develops quickly as stands reach the canopy closure phase (<10 years).

Spatial distribution and risk assessment of radionuclides in soils around a coal-fired power plant: A case study from the city of Baoji, China

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

Dai Lijun; Wei Haiyan; Wang Lingqing

2007-06-15

Coal burning may enhance human exposure to the natural radionuclides that occur around coal-fired power plants (CFPP). In this study, the spatial distribution and hazard assessment of radionuclides found in soils around a CFPP were investigated using statistics, geostatistics, and geographic information system (GIS) techniques. The concentrations of {sup 226}Ra, {sup 232}Th, and {sup 40}K in soils range from 12.54 to 40.18, 38.02 to 72.55, and 498.02 to 1126.98 Bq kg{sup -1}, respectively. Ordinary kriging was carried out to map the spatial patterns of radionuclides, and disjunctive kriging was used to quantify the probability of radium equivalent activity (Ra{sub eq})more » higher than the threshold. The maps show that the spatial variability of the natural radionuclide concentrations in soils was apparent. The results of this study could provide valuable information for risk assessment of environmental pollution and decision support.« less

Spatial distribution and risk assessment of radionuclides in soils around a coal-fired power plant: A case study from the city of Baoji, China

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

Dai, L.J.; Wei, H.Y.; Wang, L.Q.

2007-06-15

Coal burning may enhance human exposure to the natural radionuclides that occur around coal-fired power plants (CFPP). In this study, the spatial distribution and hazard assessment of radionuclides found in soils around a CFPP were investigated using statistics, geostatistics, and geographic information system (GIS) techniques. The concentrations of Ra-226, Th-232, and K-40 in soils range from 12.54 to 40.18, 38.02 to 72.55, and 498.02 to 1126.98 Bq kg{sup -1}, respectively. Ordinary kriging was carried out to map the spatial patterns of radionuclides, and disjunctive kriging was used to quantify the probability of radium equivalent activity (Ra{sub eq}) higher than themore » threshold. The maps show that the spatial variability of the natural radionuclide concentrations in soils was apparent. The results of this study could provide valuable information for risk assessment of environmental pollution and decision support.« less

Temporal Instabilities in Amblyopic Perception: A Quantitative Approach.

PubMed

Thiel, Aylin; Iftime, Adrian

2016-04-01

The purpose of this study is to quantify the temporal characteristics of spatial misperceptions in human amblyopia. Twenty-two adult participants with strabismus, strabismic, anisometropic, or mixed amblyopia were asked to describe their subjective percept of static geometrical patterns with different spatial frequencies and shapes, as seen with their non-dominant eye. We generated digital reconstructions of their perception (static images or movies) that were subsequently validated by the subjects using consecutive matching sessions. We calculated the Shannon entropy variation in time for each recorded movie, as a measure of temporal instability. Nineteen of the 22 subjects perceived temporal instabilities that can be broadly classified in two categories. We found that the average frequency of the perceived temporal instabilities is ∼1 Hz. The stimuli with higher spatial frequencies yielded more often temporally unstable perceptions with higher frequencies. We suggest that type and amount of temporal instabilities in amblyopic vision are correlated with the etiology and spatial frequency of the stimulus.

Multi-scale characterization of topographic anisotropy

NASA Astrophysics Data System (ADS)

Roy, S. G.; Koons, P. O.; Osti, B.; Upton, P.; Tucker, G. E.

2016-05-01

We present the every-direction variogram analysis (EVA) method for quantifying orientation and scale dependence of topographic anisotropy to aid in differentiation of the fluvial and tectonic contributions to surface evolution. Using multi-directional variogram statistics to track the spatial persistence of elevation values across a landscape, we calculate anisotropy as a multiscale, direction-sensitive variance in elevation between two points on a surface. Tectonically derived topographic anisotropy is associated with the three-dimensional kinematic field, which contributes (1) differential surface displacement and (2) crustal weakening along fault structures, both of which amplify processes of surface erosion. Based on our analysis, tectonic displacements dominate the topographic field at the orogenic scale, while a combination of the local displacement and strength fields are well represented at the ridge and valley scale. Drainage network patterns tend to reflect the geometry of underlying active or inactive tectonic structures due to the rapid erosion of faults and differential uplift associated with fault motion. Regions that have uniform environmental conditions and have been largely devoid of tectonic strain, such as passive coastal margins, have predominantly isotropic topography with typically dendritic drainage network patterns. Isolated features, such as stratovolcanoes, are nearly isotropic at their peaks but exhibit a concentric pattern of anisotropy along their flanks. The methods we provide can be used to successfully infer the settings of past or present tectonic regimes, and can be particularly useful in predicting the location and orientation of structural features that would otherwise be impossible to elude interpretation in the field. Though we limit the scope of this paper to elevation, EVA can be used to quantify the anisotropy of any spatially variable property.

Tracking the global footprint of fisheries

NASA Astrophysics Data System (ADS)

Kroodsma, David A.; Mayorga, Juan; Hochberg, Timothy; Miller, Nathan A.; Boerder, Kristina; Ferretti, Francesco; Wilson, Alex; Bergman, Bjorn; White, Timothy D.; Block, Barbara A.; Woods, Paul; Sullivan, Brian; Costello, Christopher; Worm, Boris

2018-02-01

Although fishing is one of the most widespread activities by which humans harvest natural resources, its global footprint is poorly understood and has never been directly quantified. We processed 22 billion automatic identification system messages and tracked >70,000 industrial fishing vessels from 2012 to 2016, creating a global dynamic footprint of fishing effort with spatial and temporal resolution two to three orders of magnitude higher than for previous data sets. Our data show that industrial fishing occurs in >55% of ocean area and has a spatial extent more than four times that of agriculture. We find that global patterns of fishing have surprisingly low sensitivity to short-term economic and environmental variation and a strong response to cultural and political events such as holidays and closures.

Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains.

PubMed

Crombach, Anton; Cicin-Sain, Damjan; Wotton, Karl R; Jaeger, Johannes

2012-01-01

Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, "medium-throughput" pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.

Exhaled Aerosol Pattern Discloses Lung Structural Abnormality: A Sensitivity Study Using Computational Modeling and Fractal Analysis

PubMed Central

Xi, Jinxiang; Si, Xiuhua A.; Kim, JongWon; Mckee, Edward; Lin, En-Bing

2014-01-01

Background Exhaled aerosol patterns, also called aerosol fingerprints, provide clues to the health of the lung and can be used to detect disease-modified airway structures. The key is how to decode the exhaled aerosol fingerprints and retrieve the lung structural information for a non-invasive identification of respiratory diseases. Objective and Methods In this study, a CFD-fractal analysis method was developed to quantify exhaled aerosol fingerprints and applied it to one benign and three malign conditions: a tracheal carina tumor, a bronchial tumor, and asthma. Respirations of tracer aerosols of 1 µm at a flow rate of 30 L/min were simulated, with exhaled distributions recorded at the mouth. Large eddy simulations and a Lagrangian tracking approach were used to simulate respiratory airflows and aerosol dynamics. Aerosol morphometric measures such as concentration disparity, spatial distributions, and fractal analysis were applied to distinguish various exhaled aerosol patterns. Findings Utilizing physiology-based modeling, we demonstrated substantial differences in exhaled aerosol distributions among normal and pathological airways, which were suggestive of the disease location and extent. With fractal analysis, we also demonstrated that exhaled aerosol patterns exhibited fractal behavior in both the entire image and selected regions of interest. Each exhaled aerosol fingerprint exhibited distinct pattern parameters such as spatial probability, fractal dimension, lacunarity, and multifractal spectrum. Furthermore, a correlation of the diseased location and exhaled aerosol spatial distribution was established for asthma. Conclusion Aerosol-fingerprint-based breath tests disclose clues about the site and severity of lung diseases and appear to be sensitive enough to be a practical tool for diagnosis and prognosis of respiratory diseases with structural abnormalities. PMID:25105680

Longitudinal thermal heterogeneity in rivers and refugia for coldwater species: Effects of scale and climate change

USGS Publications Warehouse

Fullerton, A.H.; Torgersen, Christian E.; Lawer, J.J.; Steel, E. A.; Ebersole, J.L.; Lee, S.Y.

2018-01-01

Climate-change driven increases in water temperature pose challenges for aquatic organisms. Predictions of impacts typically do not account for fine-grained spatiotemporal thermal patterns in rivers. Patches of cooler water could serve as refuges for anadromous species like salmon that migrate during summer. We used high-resolution remotely sensed water temperature data to characterize summer thermal heterogeneity patterns for 11,308 km of second–seventh-order rivers throughout the Pacific Northwest and northern California (USA). We evaluated (1) water temperature patterns at different spatial resolutions, (2) the frequency, size, and spacing of cool thermal patches suitable for Pacific salmon (i.e., contiguous stretches ≥ 0.25 km, ≤ 15 °C and ≥ 2 °C, aooler than adjacent water), and (3) potential influences of climate change on availability of cool patches. Thermal heterogeneity was nonlinearly related to the spatial resolution of water temperature data, and heterogeneity at fine resolution (< 1 km) would have been difficult to quantify without spatially continuous data. Cool patches were generally > 2.7 and < 13.0 km long, and spacing among patches was generally > 5.7 and < 49.4 km. Thermal heterogeneity varied among rivers, some of which had long uninterrupted stretches of warm water ≥ 20 °C, and others had many smaller cool patches. Our models predicted little change in future thermal heterogeneity among rivers, but within-river patterns sometimes changed markedly compared to contemporary patterns. These results can inform long-term monitoring programs as well as near-term climate-adaptation strategies.

Quantifying the Temporal Inequality of Nutrient Loads with a Novel Metric

NASA Astrophysics Data System (ADS)

Gall, H. E.; Schultz, D.; Rao, P. S.; Jawitz, J. W.; Royer, M.

2015-12-01

Inequality is an emergent property of many complex systems. For a given series of stochastic events, some events generate a disproportionately large contribution to system responses compared to other events. In catchments, such responses cause streamflow and solute loads to exhibit strong temporal inequality, with the vast majority of discharge and solute loads exported during short periods of time during which high-flow events occur. These periods of time are commonly referred to as "hot moments". Although this temporal inequality is widely recognized, there is currently no uniform metric for assessing it. We used a novel application of Lorenz Inequality, a method commonly used in economics to quantify income inequality, to quantify the spatial and temporal inequality of streamflow and nutrient (nitrogen and phosphorus) loads exported to the Chesapeake Bay. Lorenz Inequality and the corresponding Gini Coefficient provide an analytical tool for quantifying inequality that can be applied at any temporal or spatial scale. The Gini coefficient (G) is a formal measure of inequality that varies from 0 to 1, with a value of 0 indicating perfect equality (i.e., fluxes and loads are constant in time) and 1 indicating perfect inequality (i.e., all of the discharge and solute loads are exported during one instant in time). Therefore, G is a simple yet powerful tool for providing insight into the temporal inequality of nutrient transport. We will present the results of our detailed analysis of streamflow and nutrient time series data collected since the early 1980's at 30 USGS gauging stations in the Chesapeake Bay watershed. The analysis is conducted at an annual time scale, enabling trends and patterns to be assessed both temporally (over time at each station) and spatially (for the same period of time across stations). The results of this analysis have the potential to create a transformative new framework for identifying "hot moments", improving our ability to temporally and spatially target implementation of best management practices to ultimately improve water quality in the Chesapeake Bay. This method also provides insight into the temporal scales at which hydrologic and biogeochemical variability dominate nutrient export dynamics.

A unifying framework for quantifying the nature of animal interactions.

PubMed

Potts, Jonathan R; Mokross, Karl; Lewis, Mark A

2014-07-06

Collective phenomena, whereby agent-agent interactions determine spatial patterns, are ubiquitous in the animal kingdom. On the other hand, movement and space use are also greatly influenced by the interactions between animals and their environment. Despite both types of interaction fundamentally influencing animal behaviour, there has hitherto been no unifying framework for the models proposed in both areas. Here, we construct a general method for inferring population-level spatial patterns from underlying individual movement and interaction processes, a key ingredient in building a statistical mechanics for ecological systems. We show that resource selection functions, as well as several examples of collective motion models, arise as special cases of our framework, thus bringing together resource selection analysis and collective animal behaviour into a single theory. In particular, we focus on combining the various mechanistic models of territorial interactions in the literature with step selection functions, by incorporating interactions into the step selection framework and demonstrating how to derive territorial patterns from the resulting models. We demonstrate the efficacy of our model by application to a population of insectivore birds in the Amazon rainforest. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Mapping turbidity patterns in the Po river prodelta using multi-temporal Landsat 8 imagery

NASA Astrophysics Data System (ADS)

Braga, Federica; Zaggia, Luca; Bellafiore, Debora; Bresciani, Mariano; Giardino, Claudia; Lorenzetti, Giuliano; Maicu, Francesco; Manzo, Ciro; Riminucci, Francesco; Ravaioli, Mariangela; Brando, Vittorio Ernesto

2017-11-01

Thirty-meters resolution turbidity maps derived from Landsat 8 (L8) images were used to investigate spatial and temporal variations of suspended matter patterns and distribution in the area of Po River prodelta (Italy) in the period from April 2013 to October 2015. The main focus of the work was the study of small and sub-mesoscale structures, linking them to the main forcings that control the fate of suspended sediments in the northern Adriatic Sea. A number of hydrologic and meteorological events of different extent and duration was captured by L8 data, quantifying how river discharge and meteo-marine conditions modulate the distribution of turbidity on- and off-shore. At sub-mesoscale, peculiar patterns and smaller structures, as multiple plumes and sand bars, were identified thanks to the unprecedented spatial and radiometric resolution of L8 sensor. The use of these satellite-derived products provides interesting information, particularly on turbidity distribution among the different delta distributaries in specific fluvial regimes that fills the knowledge gap of traditional studies based only on in situ data. A novel approach using satellite data within model implementation is then suggested.

Spatial and temporal structure of typhoid outbreaks in Washington, D.C., 1906–1909: evaluating local clustering with the Gi* statistic

PubMed Central

Hinman, Sarah E; Blackburn, Jason K; Curtis, Andrew

2006-01-01

Background To better understand the distribution of typhoid outbreaks in Washington, D.C., the U.S. Public Health Service (PHS) conducted four investigations of typhoid fever. These studies included maps of cases reported between 1 May – 31 October 1906 – 1909. These data were entered into a GIS database and analyzed using Ripley's K-function followed by the Gi* statistic in yearly intervals to evaluate spatial clustering, the scale of clustering, and the temporal stability of these clusters. Results The Ripley's K-function indicated no global spatial autocorrelation. The Gi* statistic indicated clustering of typhoid at multiple scales across the four year time period, refuting the conclusions drawn in all four PHS reports concerning the distribution of cases. While the PHS reports suggested an even distribution of the disease, this study quantified both areas of localized disease clustering, as well as mobile larger regions of clustering. Thus, indicating both highly localized and periodic generalized sources of infection within the city. Conclusion The methodology applied in this study was useful for evaluating the spatial distribution and annual-level temporal patterns of typhoid outbreaks in Washington, D.C. from 1906 to 1909. While advanced spatial analyses of historical data sets must be interpreted with caution, this study does suggest that there is utility in these types of analyses and that they provide new insights into the urban patterns of typhoid outbreaks during the early part of the twentieth century. PMID:16566830

Spatial and temporal structure of typhoid outbreaks in Washington, D.C., 1906-1909: evaluating local clustering with the Gi* statistic.

PubMed

Hinman, Sarah E; Blackburn, Jason K; Curtis, Andrew

2006-03-27

To better understand the distribution of typhoid outbreaks in Washington, D.C., the U.S. Public Health Service (PHS) conducted four investigations of typhoid fever. These studies included maps of cases reported between 1 May - 31 October 1906 - 1909. These data were entered into a GIS database and analyzed using Ripley's K-function followed by the Gi* statistic in yearly intervals to evaluate spatial clustering, the scale of clustering, and the temporal stability of these clusters. The Ripley's K-function indicated no global spatial autocorrelation. The Gi* statistic indicated clustering of typhoid at multiple scales across the four year time period, refuting the conclusions drawn in all four PHS reports concerning the distribution of cases. While the PHS reports suggested an even distribution of the disease, this study quantified both areas of localized disease clustering, as well as mobile larger regions of clustering. Thus, indicating both highly localized and periodic generalized sources of infection within the city. The methodology applied in this study was useful for evaluating the spatial distribution and annual-level temporal patterns of typhoid outbreaks in Washington, D.C. from 1906 to 1909. While advanced spatial analyses of historical data sets must be interpreted with caution, this study does suggest that there is utility in these types of analyses and that they provide new insights into the urban patterns of typhoid outbreaks during the early part of the twentieth century.

Spatial analysis of lymphatic filariasis distribution in the Nile Delta in relation to some environmental variables using geographic information system technology.

PubMed

Hassan, A N; Dister, S; Beck, L

1998-04-01

Geographic information system (GIS) was used to analyze the spatial distribution of filariasis in the Nile Delta. The study involved 201 villages belonging to Giza, Qalubiya, Monoufiya, Gharbiya, and Dakahliya governorates. Villages with similar microfilarial (mf) prevalence rates were observed to cluster within 1-2 km distance, then, clustering started to decrease significantly with distance up to 5 km (Pearson correlation coefficient = -0.98). the likelihood of negative and high prevalence villages being contiguous was very low (approximately 1.8%, n = 612 village-pairs) indicating homogeneity in disease processes within the defined spatial scales. Of the villages located within 2 km from the main Nile branches (n = 46), 95% exhibited low prevalence. In addition, the spatial pattern of mf prevalence was shown to be negatively associated with annual rainfall and relative humidity, while it was positively associated with annual daily temperature. Average mf prevalence in warmer, relatively drier areas receiving 25 mm of rain was significantly higher (3.9%) than that in less warmer but more humid areas receiving 50 mm of rain (1.6%) (P < 0.0001). Based on the results of the present study, GIS was used to generate a "filariasis risk map" that could be used by health authorities to efficiently direct surveillance and control efforts. This investigation identified some of the factors underlying filariasis spatial pattern, quantified clustering and demonstrated the potential of GIS application in vector-borne disease epidemiology.

The role of spatial aggregation in forensic entomology.

PubMed

Fiene, Justin G; Sword, Gregory A; Van Laerhoven, Sherah L; Tarone, Aaron M

2014-01-01

A central concept in forensic entomology is that arthropod succession on carrion is predictable and can be used to estimate the postmortem interval (PMI) of human remains. However, most studies have reported significant variation in successional patterns, particularly among replicate carcasses, which has complicated estimates of PMIs. Several forensic entomology researchers have proposed that further integration of ecological and evolutionary theory in forensic entomology could help advance the application of succession data for producing PMI estimates. The purpose of this essay is to draw attention to the role of spatial aggregation of arthropods among carrion resources as a potentially important aspect to consider for understanding and predicting the assembly of arthropods on carrion over time. We review ecological literature related to spatial aggregation of arthropods among patchy and ephemeral resources, such as carrion, and when possible integrate these results with published forensic literature. We show that spatial aggregation of arthropods across resources is commonly reported and has been used to provide fundamental insight for understanding regional and local patterns of arthropod diversity and coexistence. Moreover, two suggestions are made for conducting future research. First, because intraspecific aggregation affects species frequency distributions across carcasses, data from replicate carcasses should not be combined, but rather statistically quantified to generate occurrence probabilities. Second, we identify a need for studies that tease apart the degree to which community assembly on carrion is spatially versus temporally structured, which will aid in developing mechanistic hypotheses on the ecological factors shaping community assembly on carcasses.

Global patterns and predictors of fish species richness in estuaries.

PubMed

Vasconcelos, Rita P; Henriques, Sofia; França, Susana; Pasquaud, Stéphanie; Cardoso, Inês; Laborde, Marina; Cabral, Henrique N

2015-09-01

1. Knowledge of global patterns of biodiversity and regulating variables is indispensable to develop predictive models. 2. The present study used predictive modelling approaches to investigate hypotheses that explain the variation in fish species richness between estuaries over a worldwide spatial extent. Ultimately, such models will allow assessment of future changes in ecosystem structure and function as a result of environmental changes. 3. A comprehensive worldwide data base was compiled of the fish assemblage composition and environmental characteristics of estuaries. Generalized Linear Models were used to quantify how variation in species richness among estuaries is related to historical events, energy dynamics and ecosystem characteristics, while controlling for sampling effects. 4. At the global extent, species richness differed among marine biogeographic realms and continents and increased with mean sea surface temperature, terrestrial net primary productivity and the stability of connectivity with a marine ecosystem (open vs. temporarily open estuaries). At a smaller extent (within a marine biogeographic realm or continent), other characteristics were also important in predicting variation in species richness, with species richness increasing with estuary area and continental shelf width. 5. The results suggest that species richness in an estuary is defined by predictors that are spatially hierarchical. Over the largest spatial extents, species richness is influenced by the broader distributions and habitat use patterns of marine and freshwater species that can colonize estuaries, which are in turn governed by history contingency, energy dynamics and productivity variables. Species richness is also influenced by more regional and local parameters that can further affect the process of community colonization in an estuary including the connectivity of the estuary with the adjacent marine habitat, and, over smaller spatial extents, the size of these habitats. In summary, patterns of species richness in estuaries across large spatial extents seem to reflect from global to local processes acting on community colonization. The importance of considering spatial extent, sampling effects and of combining history and contemporary environmental characteristics when exploring biodiversity is highlighted. © 2015 The Authors. Journal of Animal Ecology published by John Wiley & Sons on behalf of the British Ecological Society.

Spatio-temporal analysis of irregular vocal fold oscillations: Biphonation due to desynchronization of spatial modes

NASA Astrophysics Data System (ADS)

Neubauer, Jürgen; Mergell, Patrick; Eysholdt, Ulrich; Herzel, Hanspeter

2001-12-01

This report is on direct observation and modal analysis of irregular spatio-temporal vibration patterns of vocal fold pathologies in vivo. The observed oscillation patterns are described quantitatively with multiline kymograms, spectral analysis, and spatio-temporal plots. The complex spatio-temporal vibration patterns are decomposed by empirical orthogonal functions into independent vibratory modes. It is shown quantitatively that biphonation can be induced either by left-right asymmetry or by desynchronized anterior-posterior vibratory modes, and the term ``AP (anterior-posterior) biphonation'' is introduced. The presented phonation examples show that for normal phonation the first two modes sufficiently explain the glottal dynamics. The spatio-temporal oscillation pattern associated with biphonation due to left-right asymmetry can be explained by the first three modes. Higher-order modes are required to describe the pattern for biphonation induced by anterior-posterior vibrations. Spatial irregularity is quantified by an entropy measure, which is significantly higher for irregular phonation than for normal phonation. Two asymmetry measures are introduced: the left-right asymmetry and the anterior-posterior asymmetry, as the ratios of the fundamental frequencies of left and right vocal fold and of anterior-posterior modes, respectively. These quantities clearly differentiate between left-right biphonation and anterior-posterior biphonation. This paper proposes methods to analyze quantitatively irregular vocal fold contour patterns in vivo and complements previous findings of desynchronization of vibration modes in computer modes and in in vitro experiments.

A random forest approach for predicting the presence of Echinococcus multilocularis intermediate host Ochotona spp. presence in relation to landscape characteristics in western China

PubMed Central

Marston, Christopher G.; Danson, F. Mark; Armitage, Richard P.; Giraudoux, Patrick; Pleydell, David R.J.; Wang, Qian; Qui, Jiamin; Craig, Philip S.

2014-01-01

Understanding distribution patterns of hosts implicated in the transmission of zoonotic disease remains a key goal of parasitology. Here, random forests are employed to model spatial patterns of the presence of the plateau pika (Ochotona spp.) small mammal intermediate host for the parasitic tapeworm Echinococcus multilocularis which is responsible for a significant burden of human zoonoses in western China. Landsat ETM+ satellite imagery and digital elevation model data were utilized to generate quantified measures of environmental characteristics across a study area in Sichuan Province, China. Land cover maps were generated identifying the distribution of specific land cover types, with landscape metrics employed to describe the spatial organisation of land cover patches. Random forests were used to model spatial patterns of Ochotona spp. presence, enabling the relative importance of the environmental characteristics in relation to Ochotona spp. presence to be ranked. An index of habitat aggregation was identified as the most important variable in influencing Ochotona spp. presence, with area of degraded grassland the most important land cover class variable. 71% of the variance in Ochotona spp. presence was explained, with a 90.98% accuracy rate as determined by ‘out-of-bag’ error assessment. Identification of the environmental characteristics influencing Ochotona spp. presence enables us to better understand distribution patterns of hosts implicated in the transmission of Em. The predictive mapping of this Em host enables the identification of human populations at increased risk of infection, enabling preventative strategies to be adopted. PMID:25386042

Spatial and temporal dynamics of lake whitefish (Coregonus clupeaformis) health indicators: linking individual-based indicators to a management-relevant endpoint

USGS Publications Warehouse

Wagner, Tyler; Jones, Michael L.; Ebener, Mark P.; Arts, Michael T.; Brenden, Travis O.; Honeyfield, Dale C.; Wright, Gregory M.; Faisal, Mohamed

2010-01-01

We examined the spatial and temporal dynamics of health indicators in four lake whitefish (Coregonus clupeaformis) stocks located in northern lakes Michigan and Huron from 2003 to 2006. The specific objectives were to (1) quantify spatial and temporal variability in health indicators; (2) examine relationships among nutritional indicators and stock-specific spatial and temporal dynamics of pathogen prevalence and intensity of infection; and (3) examine relationships between indicators measured on individual fish and stock-specific estimates of natural mortality. The percent of the total variation attributed to spatial and temporal sources varied greatly depending on the health indicator examined. The most notable pattern was a downward trend in the concentration of highly unsaturated fatty acids (HUFAs), observed in all stocks, in the polar lipid fraction of lake whitefish dorsal muscle tissue over the three study years. Variation among stocks and years for some indicators were correlated with the prevalence and intensity of the swimbladder nematode Cystidicola farionis, suggesting that our measures of fish health were related, at some level, with disease dynamics. We did not find relationships between spatial patterns in fish health indicators and estimates of natural mortality rates for the stocks. Our research highlights the complexity of the interactions between fish nutritional status, disease dynamics, and natural mortality in wild fish populations. Additional research that identifies thresholds of health indicators, below (or above) which survival may be reduced, will greatly help in understanding the relationship between indicators measured on individual fish and potential population-level effects.

Landscape Characterization and Representativeness Analysis for Understanding Sampling Network Coverage

DOE Data Explorer

Maddalena, Damian; Hoffman, Forrest; Kumar, Jitendra; Hargrove, William

2014-08-01

Sampling networks rarely conform to spatial and temporal ideals, often comprised of network sampling points which are unevenly distributed and located in less than ideal locations due to access constraints, budget limitations, or political conflict. Quantifying the global, regional, and temporal representativeness of these networks by quantifying the coverage of network infrastructure highlights the capabilities and limitations of the data collected, facilitates upscaling and downscaling for modeling purposes, and improves the planning efforts for future infrastructure investment under current conditions and future modeled scenarios. The work presented here utilizes multivariate spatiotemporal clustering analysis and representativeness analysis for quantitative landscape characterization and assessment of the Fluxnet, RAINFOR, and ForestGEO networks. Results include ecoregions that highlight patterns of bioclimatic, topographic, and edaphic variables and quantitative representativeness maps of individual and combined networks.

Holocene history of deep-seated landsliding in the North Fork Stillaguamish River valley from surface roughness analysis, radiocarbon dating, and numerical landscape evolution modeling

NASA Astrophysics Data System (ADS)

Booth, Adam M.; LaHusen, Sean R.; Duvall, Alison R.; Montgomery, David R.

2017-02-01

Documenting spatial and temporal patterns of past landsliding is a challenging step in quantifying the effect of landslides on landscape evolution. While landslide inventories can map spatial distributions, lack of dateable material, landslide reactivations, or time, access, and cost constraints generally limit dating large numbers of landslides to analyze temporal patterns. Here we quantify the record of the Holocene history of deep-seated landsliding along a 25 km stretch of the North Fork Stillaguamish River valley, Washington State, USA, including the 2014 Oso landslide, which killed 43 people. We estimate the ages of more than 200 deep-seated landslides in glacial sediment by defining an empirical relationship between landslide deposit age from radiocarbon dating and landslide deposit surface roughness. We show that roughness systematically decreases with age as a function of topographic wavelength, consistent with models of disturbance-driven soil transport. The age-roughness model predicts a peak in landslide frequency at 1000 calibrated (cal) years B.P., with very few landslide deposits older than 7000 cal years B.P. or younger than 100 cal years B.P., likely reflecting a combination of preservation bias and a complex history of changing climate, base level, and seismic shaking in the study area. Most recent landslides have occurred where channels actively interact with the toes of hillslopes composed of glacial sediments, suggesting that lateral channel migration is a primary control on the location of large deep-seated landslides in the valley.

Modeling habitat and environmental factors affecting mosquito abundance in Chesapeake, Virginia

NASA Astrophysics Data System (ADS)

Bellows, Alan Scott

The models I present in this dissertation were designed to enable mosquito control agencies in the mid-Atlantic region that oversee large jurisdictions to rapidly track the spatial and temporal distributions of mosquito species, especially those species known to be vectors of eastern equine encephalitis and West Nile virus. I was able to keep these models streamlined, user-friendly, and not cost-prohibitive using empirically based digital data to analyze mosquito-abundance patterns in real landscapes. This research is presented in three major chapters: (II) a series of semi-static habitat suitability indices (HSI) grounded on well-documented associations between mosquito abundance and environmental variables, (III) a dynamic model for predicting both spatial and temporal mosquito abundance based on a topographic soil moisture index and recent weather patterns, and (IV) a set of protocols laid out to aid mosquito control agencies for the use of these models. The HSIs (Chapter II) were based on relationships of mosquitoes to digital surrogates of soil moisture and vegetation characteristics. These models grouped mosquitoes species derived from similarities in habitat requirements, life-cycle type, and vector competence. Quantification of relationships was determined using multiple linear regression models. As in Chapter II, relationships between mosquito abundance and environmental factors in Chapter III were quantified using regression models. However, because this model was, in part, a function of changes in weather patterns, it enables the prediction of both 'where' and 'when' mosquito outbreaks are likely to occur. This model is distinctive among similar studies in the literature because of my use of NOAA's NEXRAD Doppler radar (3-hr precipitation accumulation data) to quantify the spatial and temporal distributions in precipitation accumulation. \\ Chapter IV is unique among the chapters in this dissertation because in lieu of presenting new research, it summarizes the preprocessing steps and analyses used in the HSIs and the dynamic, weather-based, model generated in Chapters II and III. The purpose of this chapter is to provide the reader and potential users with the necessary protocols for modeling the spatial and temporal abundances and distributions of mosquitoes, with emphasis on Culiseta melanura, in a real-world landscape of the mid-Atlantic region. This chapter also provides enhancements that could easily be incorporated into an environmentally sensitive integrated pest management program.

[Spatial-temporal pattern of sustainable intensification of agricultural land-use in Shandong Province, China.

PubMed

Niu, Shan Dong; Lyu, Xiao; Shi, Yang Yang

2018-02-01

Under the theoretical framework of sustainable intensification of agricultural land-use (SIALU), We used material flow analysis (MFA) method to establish evaluation index system for SIALU by utilizing data in 2000, 2005, 2010 and 2015 to quantify the level of SIALU of 17 cities in Shandong Province, and analyzed the variation in input-output of resources factors of agricultural land, spatial distribution of resource productivity and environmental economic efficiency, in order to reveal spatial-temporal differentiation of SIALU. Results showed that the direct material input to agricultural lands decreased, whereas hidden flow, stock and pollutant emissions increased gradually from 2000 to 2015. The material productivity of all cities in the province showed that the coastal areas in the peninsula were relatively lower than the southern region, and the level of material productivity in the northwest region was relatively higher. Environmental economic efficiency was gradually enhanced, and the western region was relatively higher than coastal area of the peninsula. During the period examined here, the spatial pattern of SIALU of various cities showed clustered distribution change, with the western region tending to gradually increase and the eastern region tending to gradually reduce. The dynamics of SIALU among different regions were divided into six grades: Northwestern Shandong > Northern Shandong > Southwestern Shandong > Southern Shandong > Central Shandong > Coastal areas of Shandong Peninsula.

Species-driven phases and increasing structure in early-successional plant communities.

PubMed

Zaplata, Markus K; Winter, Susanne; Fischer, Anton; Kollmann, Johannes; Ulrich, Werner

2013-01-01

Successional phases describe changes in ecological communities that proceed in steps rather than continuously. Despite their importance for the understanding of ecosystem development, there still exists no reliable definition of phases and no quantitative measure of phase transitions. In order to obtain these data, we investigated primary succession in an artificial catchment (6 ha) in eastern Germany over a period of 6 years. The data set consists of records of plant species and their cover values, and initial substrate properties, both from plots in a regular grid (20 m × 20 m) suitable for spatial data analysis. Community assembly was studied by analyses of species co-occurrence and nestedness. Additionally, we correlated lognormal and log series distributions of species abundance to each community. We here introduce a new general method for detection of successional phases based on the degree of transient spatial homogeneity in the study system. Spatially coherent vegetation patterns revealed nonoverlapping partitions within this sequence of primary succession and were characterized as two distinct ecological phases. Patterns of species co-occurrence were increasingly less random, and hence the importance of demographic stochasticity and neutral community assembly decreased during the study period. Our findings highlight the spatial dimension of successional phases and quantify the degree of change between these steps. They are an element for advancing a more reliable terminology of ecological successions.

Hybrid Modeling Approach to Estimate Exposures of Hazardous Air Pollutants (HAPs) for the National Air Toxics Assessment (NATA).

PubMed

Scheffe, Richard D; Strum, Madeleine; Phillips, Sharon B; Thurman, James; Eyth, Alison; Fudge, Steve; Morris, Mark; Palma, Ted; Cook, Richard

2016-11-15

A hybrid air quality model has been developed and applied to estimate annual concentrations of 40 hazardous air pollutants (HAPs) across the continental United States (CONUS) to support the 2011 calendar year National Air Toxics Assessment (NATA). By combining a chemical transport model (CTM) with a Gaussian dispersion model, both reactive and nonreactive HAPs are accommodated across local to regional spatial scales, through a multiplicative technique designed to improve mass conservation relative to previous additive methods. The broad scope of multiple pollutants capturing regional to local spatial scale patterns across a vast spatial domain is precedent setting within the air toxics community. The hybrid design exhibits improved performance relative to the stand alone CTM and dispersion model. However, model performance varies widely across pollutant categories and quantifiably definitive performance assessments are hampered by a limited observation base and challenged by the multiple physical and chemical attributes of HAPs. Formaldehyde and acetaldehyde are the dominant HAP concentration and cancer risk drivers, characterized by strong regional signals associated with naturally emitted carbonyl precursors enhanced in urban transport corridors with strong mobile source sector emissions. The multiple pollutant emission characteristics of combustion dominated source sectors creates largely similar concentration patterns across the majority of HAPs. However, reactive carbonyls exhibit significantly less spatial variability relative to nonreactive HAPs across the CONUS.

Separating the effects of environment and space on tree species distribution: from population to community.

PubMed

Lin, Guojun; Stralberg, Diana; Gong, Guiquan; Huang, Zhongliang; Ye, Wanhui; Wu, Linfang

2013-01-01

Quantifying the relative contributions of environmental conditions and spatial factors to species distribution can help improve our understanding of the processes that drive diversity patterns. In this study, based on tree inventory, topography and soil data from a 20-ha stem-mapped permanent forest plot in Guangdong Province, China, we evaluated the influence of different ecological processes at different spatial scales using canonical redundancy analysis (RDA) at the community level and multiple linear regression at the species level. At the community level, the proportion of explained variation in species distribution increased with grid-cell sizes, primarily due to a monotonic increase in the explanatory power of environmental variables. At the species level, neither environmental nor spatial factors were important determinants of overstory species' distributions at small cell sizes. However, purely spatial variables explained most of the variation in the distributions of understory species at fine and intermediate cell sizes. Midstory species showed patterns that were intermediate between those of overstory and understory species. At the 20-m cell size, the influence of spatial factors was stronger for more dispersal-limited species, suggesting that much of the spatial structuring in this community can be explained by dispersal limitation. Comparing environmental factors, soil variables had higher explanatory power than did topography for species distribution. However, both topographic and edaphic variables were highly spatial structured. Our results suggested that dispersal limitation has an important influence on fine-intermediate scale (from several to tens of meters) species distribution, while environmental variability facilitates species distribution at intermediate (from ten to tens of meters) and broad (from tens to hundreds of meters) scales.

Vegetation change alters soil profile δ15N values at the landscape scale in a subtropical savanna

NASA Astrophysics Data System (ADS)

Zhou, Y.; Mushinski, R. M.; Hyodo, A.; Wu, X. B.; Boutton, T. W.

2017-12-01

The assessment of spatial variation in soil δ15N could provide integrative insights on soil N cycling processes across multiple spatial scales. However, little is known about spatial patterns of δ15N within soil profiles in arid and semiarid ecosystems, especially those undergoing vegetation change with a distinct shift in dominance and/or functional type. We quantified how changes from grass to woody plant dominance altered spatial patterns of δ15N throughout a 1.2 m soil profile by collecting 320 spatially-specific soil cores in a 160 m × 100 m subtropical savanna landscape that has undergone encroachment by Prosopis glandulosa (an N2-fixer) during the past century. Leaf δ15N was comparable among different plant life-forms, while fine roots from woody species had significantly lower δ15N than herbaceous species across this landscape. Woody encroachment significantly decreased soil δ15N throughout the entire soil profile, and created horizontal spatial patterns of soil δ15N that strongly resembled the spatial distribution of woody patches and were evident within each depth increment. The lower soil δ15N values that characterized areas beneath woody canopies were mostly due to the encroaching woody species, especially the N2-fixer P. glandulosa, which delivered 15N-depleted organic matter via root turnover to soils along the profile. Soil δ15N increased with depth, reached maximum values at an intermediate depth, and decreased at greater depths. Higher δ15N values at intermediate soil depths were correlated with the presence of a subsurface clay-rich argillic horizon across this landscape which may favor more rapid rates of N-cycling processes that can cause N losses and 15N enrichment of the residual soil N. These results indicate that succession from grassland to woodland has altered spatial variation in soil δ15N across the landscape and to considerable depth, suggesting significant changes in the relative rates of N-inputs vs. N-losses in this subtropical system after vegetation change.

Quantifying spatial and temporal patterns of flow intermittency using spatially contiguous runoff data

NASA Astrophysics Data System (ADS)

Yu (于松延), Songyan; Bond, Nick R.; Bunn, Stuart E.; Xu, Zongxue; Kennard, Mark J.

2018-04-01

River channel drying caused by intermittent stream flow is a widely-recognized factor shaping stream ecosystems. There is a strong need to quantify the distribution of intermittent streams across catchments to inform management. However, observational gauge networks provide only point estimates of streamflow variation. Increasingly, this limitation is being overcome through the use of spatially contiguous estimates of the terrestrial water-balance, which can also assist in estimating runoff and streamflow at large-spatial scales. Here we proposed an approach to quantifying spatial and temporal variation in monthly flow intermittency throughout river networks in eastern Australia. We aggregated gridded (5 × 5 km) monthly water-balance data with a hierarchically nested catchment dataset to simulate catchment runoff accumulation throughout river networks from 1900 to 2016. We also predicted zero flow duration for the entire river network by developing a robust predictive model relating measured zero flow duration (% months) to environmental predictor variables (based on 43 stream gauges). We then combined these datasets by using the predicted zero flow duration from the regression model to determine appropriate 'zero' flow thresholds for the modelled discharge data, which varied spatially across the catchments examined. Finally, based on modelled discharge data and identified actual zero flow thresholds, we derived summary metrics describing flow intermittency across the catchment (mean flow duration and coefficient-of-variation in flow permanence from 1900 to 2016). We also classified the relative degree of flow intermittency annually to characterise temporal variation in flow intermittency. Results showed that the degree of flow intermittency varied substantially across streams in eastern Australia, ranging from perennial streams flowing permanently (11-12 months) to strongly intermittent streams flowing 4 months or less of year. Results also showed that the temporal extent of flow intermittency varied dramatically inter-annually from 1900 to 2016, with the proportion of intermittent (weakly and strongly intermittent) streams ranging in length from 3% to nearly 100% of the river network, but there was no evidence of an increasing trend towards flow intermittency over this period. Our approach to generating spatially explicit and catchment-wide estimates of streamflow intermittency can facilitate improved ecological understanding and management of intermittent streams in Australia and around the world.

Spatial scale and distribution of neurovascular signals underlying decoding of orientation and eye of origin from fMRI data

PubMed Central

Harrison, Charlotte; Jackson, Jade; Oh, Seung-Mock; Zeringyte, Vaida

2016-01-01

Multivariate pattern analysis of functional magnetic resonance imaging (fMRI) data is widely used, yet the spatial scales and origin of neurovascular signals underlying such analyses remain unclear. We compared decoding performance for stimulus orientation and eye of origin from fMRI measurements in human visual cortex with predictions based on the columnar organization of each feature and estimated the spatial scales of patterns driving decoding. Both orientation and eye of origin could be decoded significantly above chance in early visual areas (V1–V3). Contrary to predictions based on a columnar origin of response biases, decoding performance for eye of origin in V2 and V3 was not significantly lower than that in V1, nor did decoding performance for orientation and eye of origin differ significantly. Instead, response biases for both features showed large-scale organization, evident as a radial bias for orientation, and a nasotemporal bias for eye preference. To determine whether these patterns could drive classification, we quantified the effect on classification performance of binning voxels according to visual field position. Consistent with large-scale biases driving classification, binning by polar angle yielded significantly better decoding performance for orientation than random binning in V1–V3. Similarly, binning by hemifield significantly improved decoding performance for eye of origin. Patterns of orientation and eye preference bias in V2 and V3 showed a substantial degree of spatial correlation with the corresponding patterns in V1, suggesting that response biases in these areas originate in V1. Together, these findings indicate that multivariate classification results need not reflect the underlying columnar organization of neuronal response selectivities in early visual areas. NEW & NOTEWORTHY Large-scale response biases can account for decoding of orientation and eye of origin in human early visual areas V1–V3. For eye of origin this pattern is a nasotemporal bias; for orientation it is a radial bias. Differences in decoding performance across areas and stimulus features are not well predicted by differences in columnar-scale organization of each feature. Large-scale biases in extrastriate areas are spatially correlated with those in V1, suggesting biases originate in primary visual cortex. PMID:27903637

A Simple Force-Motion Relation for Migrating Cells Revealed by Multipole Analysis of Traction Stress

PubMed Central

Tanimoto, Hirokazu; Sano, Masaki

2014-01-01

For biophysical understanding of cell motility, the relationship between mechanical force and cell migration must be uncovered, but it remains elusive. Since cells migrate at small scale in dissipative circumstances, the inertia force is negligible and all forces should cancel out. This implies that one must quantify the spatial pattern of the force instead of just the summation to elucidate the force-motion relation. Here, we introduced multipole analysis to quantify the traction stress dynamics of migrating cells. We measured the traction stress of Dictyostelium discoideum cells and investigated the lowest two moments, the force dipole and quadrupole moments, which reflect rotational and front-rear asymmetries of the stress field. We derived a simple force-motion relation in which cells migrate along the force dipole axis with a direction determined by the force quadrupole. Furthermore, as a complementary approach, we also investigated fine structures in the stress field that show front-rear asymmetric kinetics consistent with the multipole analysis. The tight force-motion relation enables us to predict cell migration only from the traction stress patterns. PMID:24411233

Plant Ontogeny, Spatial Distance, and Soil Type Influence Patterns of Relatedness in a Common Amazonian Tree

PubMed Central

Barbosa, Carlos Eduardo A.; Misiewicz, Tracy M.; Fine, Paul V. A.; Costa, Flávia R. C.

2013-01-01

The formation of spatial genetic structure (SGS) may originate from different patterns of seed deposition in the landscape, and is mostly determined by seed dispersal limitation. After dispersal, mechanisms such as filtering by environmental factors or attack by herbivores/pathogens throughout plant development stages, and potentially either disrupt or intensify SGS patterns. We investigated how the genotype of Protium subserratum (Burseraceae), a common tree species in the Ducke Reserve, Brazil, is distributed across the landscape. We used seven microsatellite markers to assess the SGS among plants at different life stages and in different environments. By quantifying the patterns of relatedness among plants of different sizes, we inferred the ontogenetic stage in which SGS changes occurred, and compared these effects across soil types. Relatedness among seedlings decreased when distance between seedlings increased, especially for the youngest seedlings. However, this trend was not continued by older plants, as relatedness values were higher among neighboring individuals of the juvenile and adult size class. Contrasting relatedness patterns between seedlings and larger individuals suggests a trade-off between the negative effects of being near closely-related adults (e.g. due to herbivore and pathogen attack) and the advantage of being in a site favorable to establishment. We also found that soil texture strongly influenced density-dependence patterns, as young seedlings in clay soils were more related to each other than were seedlings in bottomland sandy soils, suggesting that the mechanisms that create and maintain patterns of SGS within a population may interact with environmental heterogeneity. PMID:23667502

The Urban Heat Island Impact in Consideration of Spatial Pattern of Urban Landscape and Structure

NASA Astrophysics Data System (ADS)

Kim, J.; Lee, D. K.; Jeong, W.; Sung, S.; Park, J.

2015-12-01

Preceding study has established a clear relationship between land surface temperature and area of land covers. However, only few studies have specifically examined the effects of spatial patterns of land covers and urban structure. To examine how much the local climate is affected by the spatial pattern in highly urbanized city, we investigated the correlation between land surface temperature and spatial patterns of land covers. In the analysis of correlation, we categorized urban structure to four different land uses: Apartment residential area, low rise residential area, industrial area and central business district. Through this study, we aims to examine the types of residential structure and land cover pattern for reducing urban heat island and sustainable development. Based on land surface temperature, we investigated the phenomenon of urban heat island through using the data of remote sensing. This study focused on Daegu in Korea. This city, one of the hottest city in Korea has basin form. We used high-resolution land cover data and land surface temperature by using Landsat8 satellite image to examine 100 randomly selected sample sites of 884.15km2 (1)In each land use, we quantified several landscape-levels and class-level landscape metrics for the sample study sites. (2)In addition, we measured the land surface temperature in 3 year hot summer seasons (July to September). Then, we investigated the pattern of land surface temperature for each land use through Ecognition package. (3)We deducted the Pearson correlation coefficients between land surface temperature and each landscape metrics. (4)We analyzed the variance among the four land uses. (5)Using linear regression, we determined land surface temperature model for each land use. (6)Through this analysis, we aims to examine the best pattern of land cover and artificial structure for reducing urban heat island effect in highly urbanized city. The results of linear regression showed that proportional land cover of grass, tree, water and impervious surfaces well explained the temperature in apartment residential areas. In contrast, the changes in the pattern of water, grass, tree and impervious surfaces were the best to determine the temperature in low rise residential area, central business district and industrial area.

Quantifying Information Flow During Emergencies

NASA Astrophysics Data System (ADS)

Gao, Liang; Song, Chaoming; Gao, Ziyou; Barabási, Albert-László; Bagrow, James P.; Wang, Dashun

2014-02-01

Recent advances on human dynamics have focused on the normal patterns of human activities, with the quantitative understanding of human behavior under extreme events remaining a crucial missing chapter. This has a wide array of potential applications, ranging from emergency response and detection to traffic control and management. Previous studies have shown that human communications are both temporally and spatially localized following the onset of emergencies, indicating that social propagation is a primary means to propagate situational awareness. We study real anomalous events using country-wide mobile phone data, finding that information flow during emergencies is dominated by repeated communications. We further demonstrate that the observed communication patterns cannot be explained by inherent reciprocity in social networks, and are universal across different demographics.

Using ATM laser altimetry to constrain surface mass balance estimates and supraglacial hydrology of the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Studinger, M.; Medley, B.; Manizade, S.; Linkswiler, M. A.

2016-12-01

Repeat airborne laser altimetry measurements can provide large-scale field observations to better quantify spatial and temporal variability of surface processes contributing to seasonal elevation change and therefore surface mass balance. As part of NASA's Operation IceBridge the Airborne Topographic Mapper (ATM) laser altimeter measured the surface elevation of the Greenland Ice Sheet during spring (March - May) and fall (September - October) of 2015. Comparison of the two surveys reveals a general trend of thinning for outlet glaciers and for the ice sheet in a manner related to elevation and latitude. In contrast, some thickening is observed on the west (but not on the east) side of the ice divide above 2200 m elevation in the southern half, below latitude 69°N.The observed magnitude and spatial patterns of the summer melt signal can be utilized as input into ice sheet models and for validating reanalysis of regional climate models such as RACMO and MAR. We use seasonal anomalies in MERRA-2 climate fields (temperature, precipitation) to understand the observed spatial signal in seasonal change. Aside from surface elevation change, runoff from meltwater pooling in supraglacial lakes and meltwater channels accounts for at least half of the total mass loss. The ability of the ATM laser altimeters to image glacial hydrological features in 3-D and determine the depth of supraglacial lakes could be used for process studies and for quantifying melt processes over large scales. The 1-meter footprint diameter of ATM laser on the surface, together with a high shot density, allows for the production of large-scale, high-resolution, geodetic quality DEMs (50 x 50 cm) suitable for fine-scale glacial hydrology research and as input to hydrological models quantifying runoff.

Population Structure and Dispersal Patterns within and between Atlantic and Mediterranean Populations of a Large-Range Pelagic Seabird

PubMed Central

Genovart, Meritxell; Thibault, Jean-Claude; Igual, José Manuel; Bauzà-Ribot, Maria del Mar; Rabouam, Corinne; Bretagnolle, Vincent

2013-01-01

Dispersal is critically linked to the demographic and evolutionary trajectories of populations, but in most seabird species it may be difficult to estimate. Using molecular tools, we explored population structure and the spatial dispersal pattern of a highly pelagic but philopatric seabird, the Cory's shearwater Calonectris diomedea. Microsatellite fragments were analysed from samples collected across almost the entire breeding range of the species. To help disentangle the taxonomic status of the two subspecies described, the Atlantic form C. d. borealis and the Mediterranean form C. d. diomedea, we analysed genetic divergence between subspecies and quantified both historical and recent migration rates between the Mediterranean and Atlantic basins. We also searched for evidence of isolation by distance (IBD) and addressed spatial patterns of gene flow. We found a low genetic structure in the Mediterranean basin. Conversely, strong genetic differentiation appeared in the Atlantic basin. Even if the species was mostly philopatric (97%), results suggest recent dispersal between basins, especially from the Atlantic to the Mediterranean (aprox. 10% of migrants/generation across the last two generations). Long-term gene flow analyses also suggested an historical exchange between basins (about 70 breeders/generation). Spatial analysis of genetic variation indicates that distance is not the main factor in shaping genetic structure in this species. Given our results we recommend gathering more data before concluded whether these taxa should be treated as two species or subspecies. PMID:23950986

Functional Connectivity of Precipitation Networks in the Brazilian Rainforest-Savanna Transition Zone

NASA Astrophysics Data System (ADS)

Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

2016-12-01

In the Brazilian rainforest-savanna transition zone, vegetation change has the potential to significantly affect precipitation patterns. Deforestation, in particular, can affect precipitation patterns by increasing land surface albedo, increasing aerosol loading to the atmosphere, changing land surface roughness, and reducing transpiration. Understanding land surface-precipitation couplings in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching and agriculture, hydropower generation, and drinking water management. Simulations suggest complex, scale-dependent interactions between precipitation and land cover. For example, the size and distribution of deforested patches has been found to affect precipitation patterns. We take an empirical approach to ask: (1) what are the dominant spatial and temporal length scales of precipitation coupling in the Brazilian rainforest-savanna transition zone? (2) How do these length scales change over time? (3) How does the connectivity of precipitation change over time? The answers to these questions will help address fundamental questions about the impacts of deforestation on precipitation. We use rain gauge data from 1100 rain gauges intermittently covering the period 1980 - 2013, a period of intensive land cover change in the region. The dominant spatial and temporal length scales of precipitation coupling are resolved using transfer entropy, a metric from information theory. Connectivity of the emergent network of couplings is quantified using network statistics. Analyses using transfer entropy and network statistics reveal the spatial and temporal interdependencies of rainfall events occurring in different parts of the study domain.

Quantifying Sources and Fluxes of Aquatic Carbon in U.S. Streams and Reservoirs Using Spatially Referenced Regression Models

NASA Astrophysics Data System (ADS)

Boyer, E. W.; Smith, R. A.; Alexander, R. B.; Schwarz, G. E.

2004-12-01

Organic carbon (OC) is a critical water quality characteristic in riverine systems that is an important component of the aquatic carbon cycle and energy balance. Examples of processes controlled by OC interactions are complexation of trace metals; enhancement of the solubility of hydrophobic organic contaminants; formation of trihalomethanes in drinking water; and absorption of visible and UV radiation. Organic carbon also can have indirect effects on water quality by influencing internal processes of aquatic ecosystems (e.g. photosynthesis and autotrophic and heterotrophic activity). The importance of organic matter dynamics on water quality has been recognized, but challenges remain in quantitatively addressing OC processes over broad spatial scales in a hydrological context. In this study, we apply spatially referenced watershed models (SPARROW) to statistically estimate long-term mean-annual rates of dissolved- and total- organic carbon export in streams and reservoirs across the conterminous United States. We make use of a GIS framework for the analysis, describing sources, transport, and transformations of organic matter from spatial databases providing characterizations of climate, land use, primary productivity, topography, soils, and geology. This approach is useful because it illustrates spatial patterns of organic carbon fluxes in streamflow, highlighting hot spots (e.g., organic-rich environments in the southeastern coastal plain). Further, our simulations provide estimates of the relative contributions to streams from allochthonous and autochthonous sources. We quantify surface water fluxes of OC with estimates of uncertainty in relation to the overall US carbon budget; our simulations highlight that aquatic sources and sinks of OC may be a more significant component of regional carbon cycling than was previously thought. Further, we are using our simulations to explore the potential role of climate and other changes in the terrestrial environment on OC fluxes in aquatic systems.

The Pattern Across the Continental United States of Evapotranspiration Variability Associated with Water Availability

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Salvucci, Guido D.; Rigden, Angela J.; Jung, Martin; Collatz, G. James; Schubert, Siegfried D.

2015-01-01

The spatial pattern across the continental United States of the interannual variance of warm season water-dependent evapotranspiration, a pattern of relevance to land-atmosphere feedback, cannot be measured directly. Alternative and indirect approaches to estimating the pattern, however, do exist, and given the uncertainty of each, we use several such approaches here. We first quantify the water dependent evapotranspiration variance pattern inherent in two derived evapotranspiration datasets available from the literature. We then search for the pattern in proxy geophysical variables (air temperature, stream flow, and NDVI) known to have strong ties to evapotranspiration. The variances inherent in all of the different (and mostly independent) data sources show some differences but are generally strongly consistent they all show a large variance signal down the center of the U.S., with lower variances toward the east and (for the most part) toward the west. The robustness of the pattern across the datasets suggests that it indeed represents the pattern operating in nature. Using Budykos hydroclimatic framework, we show that the pattern can largely be explained by the relative strength of water and energy controls on evapotranspiration across the continent.

Land use and carbon dynamics in the southeastern United States from 1992 to 2050

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang; Sohl, Terry L.; Young, Claudia; Werner, Jeremy M.

2013-01-01

Land use and land cover change (LUCC) plays an important role in determining the spatial distribution, magnitude, and temporal change of terrestrial carbon sources and sinks. However, the impacts of LUCC are not well understood and quantified over large areas. The goal of this study was to quantify the spatial and temporal patterns of carbon dynamics in various terrestrial ecosystems in the southeastern United States from 1992 to 2050 using a process-based modeling system and then to investigate the impacts of LUCC. Spatial LUCC information was reconstructed and projected using the FOREcasting SCEnarios of future land cover (FORE-SCE) model according to information derived from Landsat observations and other sources. Results indicated that urban expansion (from 3.7% in 1992 to 9.2% in 2050) was expected to be the primary driver for other land cover changes in the region, leading to various declines in forest, cropland, and hay/pasture. The region was projected to be a carbon sink of 60.4 gC m−2 yr−1 on average during the study period, primarily due to the legacy impacts of large-scale conversion of cropland to forest that happened since the 1950s. Nevertheless, the regional carbon sequestration rate was expected to decline because of the slowing down of carbon accumulation in aging forests and the decline of forest area.

In vivo quantification of plant starch reserves at micrometer resolution using X-ray microCT imaging and machine learning.

PubMed

Earles, J Mason; Knipfer, Thorsten; Tixier, Aude; Orozco, Jessica; Reyes, Clarissa; Zwieniecki, Maciej A; Brodersen, Craig R; McElrone, Andrew J

2018-03-08

Starch is the primary energy storage molecule used by most terrestrial plants to fuel respiration and growth during periods of limited to no photosynthesis, and its depletion can drive plant mortality. Destructive techniques at coarse spatial scales exist to quantify starch, but these techniques face methodological challenges that can lead to uncertainty about the lability of tissue-specific starch pools and their role in plant survival. Here, we demonstrate how X-ray microcomputed tomography (microCT) and a machine learning algorithm can be coupled to quantify plant starch content in vivo, repeatedly and nondestructively over time in grapevine stems (Vitis spp.). Starch content estimated for xylem axial and ray parenchyma cells from microCT images was correlated strongly with enzymatically measured bulk-tissue starch concentration on the same stems. After validating our machine learning algorithm, we then characterized the spatial distribution of starch concentration in living stems at micrometer resolution, and identified starch depletion in live plants under experimental conditions designed to halt photosynthesis and starch production, initiating the drawdown of stored starch pools. Using X-ray microCT technology for in vivo starch monitoring should enable novel research directed at resolving the spatial and temporal patterns of starch accumulation and depletion in woody plant species. No claim to original US Government works New Phytologist © 2018 New Phytologist Trust.

Implementation of a Time Series Analysis for the Assessment of the Role of Climate Variability in a Post-Disturbance Savanna System

NASA Astrophysics Data System (ADS)

Gibbes, C.; Southworth, J.; Waylen, P. R.

2013-05-01

How do climate variability and climate change influence vegetation cover and vegetation change in savannas? A landscape scale investigation of the effect of changes in precipitation on vegetation is undertaken through the employment of a time series analysis. The multi-national study region is located within the Kavango-Zambezi region, and is delineated by the Okavango, Kwando, and Zambezi watersheds. A mean-variance time-series analysis quantifies vegetation dynamics and characterizes vegetation response to climate. The spatially explicit approach used to quantify the persistence of vegetation productivity permits the extraction of information regarding long term climate-landscape dynamics. Results show a pattern of reduced mean annual precipitation and increased precipitation variability across key social and ecological areas within the study region. Despite decreased mean annual precipitation since the mid to late 1970's vegetation trends predominantly indicate increasing biomass. The limited areas which have diminished vegetative cover relate to specific vegetation types, and are associated with declines in precipitation variability. Results indicate that in addition to short term changes in vegetation cover, long term trends in productive biomass are apparent, relate to spatial differences in precipitation variability, and potentially represent shifts vegetation composition. This work highlights the importance of time-series analyses for examining climate-vegetation linkages in a spatially explicit manner within a highly vulnerable region of the world.

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

USGS Publications Warehouse

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

2009-01-01

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

Where does boreal stream DOC come from? - Quantifying the contribution from different landscape compartments using stable C isotope ratios.

NASA Astrophysics Data System (ADS)

Brink Bylund, J.; Bastviken, D.; Morth, C.; Laudon, H.; Giesler, R.; Buffam, I.

2007-12-01

Stable carbon isotope (δ13C) ratios are frequently used as a source tracer of e.g. organic matter (OM) produced in terrestrial versus aquatic environments. To our knowledge there has been no previous attempt to quantify the relative contribution of dissolved organic carbon (DOC) from various landscape compartments in catchments of different sizes. Here, we test to what extent δ13C values can be used also to quantify the relative contribution of DOC from wetlands/riparian zones along streams, and off stream forest habitats, respectively. We present data on spatial and temporal variability of DOC concentrations and δ13C-DOC values, during the year of 2005 in Krycklan catchment, a boreal stream network in northern Sweden. Ten stream sites, ranging from order 1 to 4, were monitored in sub catchments with different wetland coverage. Spatial variation of DOC concentration showed a weak but statistically significant relationship with wetland area, with higher concentration with increasing percent of wetland in the drainage area. During base flow the difference in δ13C-DOC values was significantly different between forest (-27.5‰) and wetland (-28.1‰). This spatial pattern disappears during spring peak flow when higher discharge flushing upper soil layer and the riparian zone on DOC in the catchments. A simple mixing model using DOC and δ13C-DOC showed that stream water DOC could be describe as a mixture of DOC coming from forest (deep) groundwater and wetland/riparian zone water. The result indicates that during spring peak flow almost all stream DOC (84-100%) is derived from wetlands and riparian zones. The wetland/riparian water dominates the stream DOC flux at all hydrological events, except for two sites, one forest dominated and one mixed catchment, where the forest groundwater dominated the DOC transport during base flow. Although the total wetland area in Krycklan catchment only represent 8.3%, it contributed, together with riparian zones, to as much as 83% of the yearly DOC transport. This study shows that there is a great potential in using stable carbon isotopes to quantify the relative contribution of DOC from various landscape compartments in catchments. Quantitative patterns are crucial for several reasons. It is for example necessary in predicting the response to global warming which will result in a changed hydrology and shifts in the relative area of the landscape compartments in boreal environments. KEY WORDS carbon isotopes; dissolved organic carbon; streams; boreal; landscape compartments; wetland; groundwater

Using dynamic Brownian bridge movement modelling to measure temporal patterns of habitat selection.

PubMed

Byrne, Michael E; Clint McCoy, J; Hinton, Joseph W; Chamberlain, Michael J; Collier, Bret A

2014-09-01

Accurately describing animal space use is vital to understanding how wildlife use habitat. Improvements in GPS technology continue to facilitate collection of telemetry data at high spatial and temporal resolutions. Application of the recently introduced dynamic Brownian bridge movement model (dBBMM) to such data is promising as the method explicitly incorporates the behavioural heterogeneity of a movement path into the estimated utilization distribution (UD). Utilization distributions defining space use are normally estimated for time-scales ranging from weeks to months, obscuring much of the fine-scale information available from high-volume GPS data sets. By accounting for movement heterogeneity, the dBBMM provides a rigorous, behaviourally based estimate of space use between each set of relocations. Focusing on UDs generated between individual sets of locations allows us to quantify fine-scale circadian variation in habitat use. We used the dBBMM to estimate UDs bounding individual time steps for three terrestrial species with different life histories to illustrate how the method can be used to identify fine-scale variations in habitat use. We also demonstrate how dBBMMs can be used to characterize circadian patterns of habitat selection and link fine-scale patterns of habitat use to behaviour. We observed circadian patterns of habitat use that varied seasonally for a white-tailed deer (Odocoileus virginianus) and coyote (Canis latrans). We found seasonal patterns in selection by the white-tailed deer and were able to link use of conifer forests and agricultural fields to behavioural state of the coyote. Additionally, we were able to quantify the date in which a Rio Grande wild turkey (Meleagris gallopavo intermedia) initiated laying as well as when during the day, she was most likely to visit the nest site to deposit eggs. The ability to quantify circadian patterns of habitat use may have important implications for research and management of wildlife. Additionally, the ability to link such patterns to behaviour may aid in the development of mechanistic models of habitat selection. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Distinguishing cognitive state with multifractal complexity of hippocampal interspike interval sequences

PubMed Central

Fetterhoff, Dustin; Kraft, Robert A.; Sandler, Roman A.; Opris, Ioan; Sexton, Cheryl A.; Marmarelis, Vasilis Z.; Hampson, Robert E.; Deadwyler, Sam A.

2015-01-01

Fractality, represented as self-similar repeating patterns, is ubiquitous in nature and the brain. Dynamic patterns of hippocampal spike trains are known to exhibit multifractal properties during working memory processing; however, it is unclear whether the multifractal properties inherent to hippocampal spike trains reflect active cognitive processing. To examine this possibility, hippocampal neuronal ensembles were recorded from rats before, during and after a spatial working memory task following administration of tetrahydrocannabinol (THC), a memory-impairing component of cannabis. Multifractal detrended fluctuation analysis was performed on hippocampal interspike interval sequences to determine characteristics of monofractal long-range temporal correlations (LRTCs), quantified by the Hurst exponent, and the degree/magnitude of multifractal complexity, quantified by the width of the singularity spectrum. Our results demonstrate that multifractal firing patterns of hippocampal spike trains are a marker of functional memory processing, as they are more complex during the working memory task and significantly reduced following administration of memory impairing THC doses. Conversely, LRTCs are largest during resting state recordings, therefore reflecting different information compared to multifractality. In order to deepen conceptual understanding of multifractal complexity and LRTCs, these measures were compared to classical methods using hippocampal frequency content and firing variability measures. These results showed that LRTCs, multifractality, and theta rhythm represent independent processes, while delta rhythm correlated with multifractality. Taken together, these results provide a novel perspective on memory function by demonstrating that the multifractal nature of spike trains reflects hippocampal microcircuit activity that can be used to detect and quantify cognitive, physiological, and pathological states. PMID:26441562

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

PubMed

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

2013-12-01

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

Automated delineation and characterization of drumlins using a localized contour tree approach

NASA Astrophysics Data System (ADS)

Wang, Shujie; Wu, Qiusheng; Ward, Dylan

2017-10-01

Drumlins are ubiquitous landforms in previously glaciated regions, formed through a series of complex subglacial processes operating underneath the paleo-ice sheets. Accurate delineation and characterization of drumlins are essential for understanding the formation mechanism of drumlins as well as the flow behaviors and basal conditions of paleo-ice sheets. Automated mapping of drumlins is particularly important for examining the distribution patterns of drumlins across large spatial scales. This paper presents an automated vector-based approach to mapping drumlins from high-resolution light detection and ranging (LiDAR) data. The rationale is to extract a set of concentric contours by building localized contour trees and establishing topological relationships. This automated method can overcome the shortcomings of previously manual and automated methods for mapping drumlins, for instance, the azimuthal biases during the generation of shaded relief images. A case study was carried out over a portion of the New York Drumlin Field. Overall 1181 drumlins were identified from the LiDAR-derived DEM across the study region, which had been underestimated in previous literature. The delineation results were visually and statistically compared to the manual digitization results. The morphology of drumlins was characterized by quantifying the length, width, elongation ratio, height, area, and volume. Statistical and spatial analyses were conducted to examine the distribution pattern and spatial variability of drumlin size and form. The drumlins and the morphologic characteristics exhibit significant spatial clustering rather than randomly distributed patterns. The form of drumlins varies from ovoid to spindle shapes towards the downstream direction of paleo ice flows, along with the decrease in width, area, and volume. This observation is in line with previous studies, which may be explained by the variations in sediment thickness and/or the velocity increases of ice flows towards ice front.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau.

PubMed

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-08-24

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau

NASA Astrophysics Data System (ADS)

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-08-01

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau

PubMed Central

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-01-01

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302–480 km, while the annual precipitation showed smaller scales of 111–182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions. PMID:27553388

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

PubMed

Leibold, Mathew A; Loeuille, Nicolas

2015-12-01

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

Spatial variations in the consumption of illicit stimulant drugs across Australia: A nationwide application of wastewater-based epidemiology.

PubMed

Lai, Foon Yin; O'Brien, Jake; Bruno, Raimondo; Hall, Wayne; Prichard, Jeremy; Kirkbride, Paul; Gartner, Coral; Thai, Phong; Carter, Steve; Lloyd, Belinda; Burns, Lucy; Mueller, Jochen

2016-10-15

Obtaining representative information on illicit drug use and patterns across a country remains difficult using surveys because of low response rates and response biases. A range of studies have used wastewater-based epidemiology (WBE) as a complementary approach to monitor community-wide illicit drug use. In Australia, no large-scale WBE studies have been conducted to date to reveal illicit drug use profiles in a national context. In this study, we performed the first Australia-wide WBE monitoring to examine spatial patterns in the use of three illicit stimulants (cocaine, as its human metabolite benzoylecgonine; methamphetamine; and 3,4-methylendioxymethamphetamine (MDMA)). A total of 112 daily composite wastewater samples were collected from 14 wastewater treatment plants across four states and two territories. These covered approximately 40% of the Australian population. We identified and quantified illicit drug residues using liquid chromatography coupled with tandem mass spectrometry. There were distinctive spatial patterns of illicit stimulant use in Australia. Multivariate analyses showed that consumption of cocaine and MDMA was higher in the large cities than in rural areas. Also, cocaine consumption differed significantly between different jurisdictions. Methamphetamine consumption was more similar between urban and rural locations. Only a few cities had elevated levels of use. Extrapolation of the WBE estimates suggested that the annual consumption was 3tonnes for cocaine and 9tonnes combined for methamphetamine and MDMA, which outweighed the annual seizure amount by 25 times and 45 times, respectively. These ratios imply the difficulty of detecting the trafficking of these stimulants in Australia, possibly more so for methamphetamine than cocaine. The obtained spatial pattern of use was compared with that in the most recent national household survey. Together both WBE and survey methods provide a more comprehensive evaluation of drug use that can assist governments in developing policies to reduce drug use and harm in the communities. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatiotemporal changes of land use patterns in high mountain areas of Northeast Turkey: a case study in Maçka.

PubMed

Sen, Gokhan; Bayramoglu, Mahmut M; Toksoy, Devlet

2015-08-01

High mountain forests (HMFs) have an important significance in forest ecosystems, but the benefits from such ecosystems have been compromised in recent years. In Turkey, HMFs constitute significant portions of Turkish forests because they cover 4% of Turkey; 15% of all Turkish forest areas are HMFs. The Eastern Black Sea region has a particular importance for HMFs due to its biological diversity and the rich presence of endemic species. This study analyzes the changes in spatial and temporal patterns of forest cover in HMF from 1973 to 2008 in the town of Maçka, which is located at the center of the Eastern Black Sea region of Turkey. The spatial and temporal change patterns of land use are quantified by interpreting spatial data. Remote sensing (RS), geographical information system (GIS), and a spatial pattern analysis program for categorical maps (FRAGSTATS) have been used for data collection, analysis, and presentation. The results showed that the HMF areas had biphasic growth from 1973 to 2008. Despite a net increase of 200.6 ha in forested areas between 1984 and 2008, there was an overall decrease from 1973 to 2008. The annual percentage of forestation for the forest areas within the study period was 0.04% in Maçka. The amount of aggregated forest area fragments rose from 388 in 1973 to 711 in 2008. The increase in the HMF of Maçka can be explained to some extent by the change in the demographic structure of Maçka and its plateaus, which contributed to changes in the daily life of the population of Maçka and its villages, such as changes in annual incomes, their lifestyles, decrease in transhumance and stockbreeding, decrease in the time of dwelling on the plateaus, and changes in the traditional architectural style.

Understanding Multifunctional Agricultural Land by Using Low Cost and Open Source Solutions to Quantify Ecosystem Function and Services

NASA Astrophysics Data System (ADS)

Forsmoo, Joel; Anderson, Karen; Brazier, Richard; Macleod, Kit; Wilkinson, Mark

2016-04-01

There is a need to advance our understanding of how the spatial structure of farmed landscapes contributes to the provision of functions and services. Agricultural land is of critical importance in NW Europe, covering large parts of NW Europe's temperate land. Moreover, these agricultural areas are primarily intensively managed, with a focus on maximizing food and fibre production. Such landscapes therefore can provide a wealth of ecosystem goods and services (ESs) including regulation of climate, erosion regulation, hydrology, water quality, nutrient cycling and biodiversity conservation. However, it has been shown they are key sources of sediment, phosphorous, nitrogen and storm runoff contributing to flooding, and therefore it is likely that most agricultural landscapes do not maximize the services or benefits that they might provide. The focus of this study is the spatio-temporal assessment of carbon sequestration (particularly through proxies such as above-ground biomass) and hydrological processes on agricultural land. Understanding and quantifying both of these is important to (a) inform payments for ecosystem services frameworks, (b) evaluate and improve carbon sequestration models, (c) manage the flood risk, (d) downstream water security and (e) water quality. Quantifying both of these ESs is dependent on data describing the fine spatial and temporal structure and function of the landscape. Common practice has been to use remote sensing techniques, e.g. satellites, providing coarse spatial resolution (around 30cm at 20° off nadir) and/or temporal resolution (around 5 days revisit time at <20° off nadir). In this paper we will explain how imaging data from lightweight and easily deployed unmanned aerial vehicles (UAVs) can be used to generate structure from motion (SFM) products describing the very fine detailed (<3 cm pixel resolution) structure of the agricultural environment. We will demonstrate how these products can be delivered using advanced free and open source post-processing alternatives and low cost sensors (digital cameras) and platforms (UAVs). We furthermore draw attention to the influence post-processing solutions have on the accuracy of the final product, the digital surface model (DSM), by using recently acquired data. Specifically, when applied in a structurally complex field site with irregular surface roughness patterns, over a land use gradient, from livestock grazing to agricultural crops. We will demonstrate the added value of using very fine detail data, highlighting important structural properties and patterns overlooked with coarser spatial resolution data.

Temporal, Spatial, and Diurnal Patterns in Avian Activity at the Shuttle Landing Facility, John F. Kennedy Space Center, Florida, USA

NASA Technical Reports Server (NTRS)

Larson, Vickie L.; Rowe, Sean P.; Breininger, David R.

1997-01-01

Spatial and temporal patterns in bird abundance within the five-mile airspace at the Shuttle Landing Facility (SLF) on John F. Kennedy Space Center (KSC), Florida, USA were investigated for purposes of quantifying Bird Aircraft Strike Hazards (BASH). The airspace is surrounded by the Merritt Island National Wildlife Refuge (MINWR) which provides habitat for approximately 331 resident and migratory bird species. Potential bird strike hazards were greatest around sunrise and sunset for most avian taxonomic groups, including wading birds, most raptors, pelicans, gulls/terns, shorebirds, and passerines. Turkey Vultures and Black Vultures were identified as a primary threat to aircraft operations and were represented in 33% of the samples. Diurnal vulture activity varied seasonally with the development of air thermals in the airspace surrounding the SLF. Variation in the presence and abundance of migratory species was shown for American Robins, swallows, and several species of shorebirds. Analyses of bird activities provides for planning of avionics operations during periods of low-dsk and allows for risk minimization measures during periods of high-risk.

Temporal-spatial variation and source apportionment of soil heavy metals in the representative river-alluviation depositional system.

PubMed

Wang, Cheng; Yang, Zhongfang; Zhong, Cong; Ji, Junfeng

2016-09-01

The contributions of major driving forces on temporal changes of heavy metals in the soil in a representative river-alluviation area at the lower of Yangtze River were successfully quantified by combining geostatistics analysis with the modified principal component scores & multiple linear regressions approach (PCS-MLR). The results showed that the temporal (2003-2014) changes of Cu, Zn, Ni and Cr presented a similar spatial distribution pattern, whereas the Cd and Hg showed the distinctive patterns. The temporal changes of soil Cu, Zn, Ni and Cr may be predominated by the emission of the shipbuilding industry, whereas the significant changes of Cd and Hg were possibly predominated by the geochemical and geographical processes, such as the erosion of the Yangtze River water and leaching because of soil acidification. The emission of metal-bearing shipbuilding industry contributed an estimated 74%-83% of the changes in concentrations of Cu, Zn, Ni and Cr, whereas the geochemical and geographical processes may contribute 58% of change of Cd in the soil and 59% of decrease of Hg. Copyright © 2016 Elsevier Ltd. All rights reserved.

The roosting spatial network of a bird-predator bat.

PubMed

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

2009-04-01

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

Hydrological model uncertainty due to spatial evapotranspiration estimation methods

NASA Astrophysics Data System (ADS)

Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub

2016-05-01

Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

NASA Technical Reports Server (NTRS)

Chudnovsky, Alexandra A.; Koutrakis, Petros; Kloog, Itai; Melly, Steven; Nordio, Francesco; Lyapustin, Alexei; Wang, Jujie; Schwartz, Joel

2014-01-01

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

Quantifying Structural and Compositional Changes in Forest Cover in NW Yunnan, China

NASA Astrophysics Data System (ADS)

Hakkenberg, C.

2012-12-01

NW Yunnan, China is a region renowned for high levels of biodiversity, endemism and genetically distinct refugial plant populations. It is also a focal area for China's national reforestation efforts like the Natural Forest Protection Program (NFPP), intended to control erosion in the Upper Yangtze watershed. As part of a larger project to investigate the role of reforestation programs in facilitating the emergence of increasingly species-rich forest communities on a previously degraded and depauperate land mosaic in montane SW China, this study uses a series of Landsat TM images to quantify the spatial pattern and rate of structural and compositional change in forests recovering from medium to large-scale disturbances in the area over the past 25 years. Beyond the fundamental need to assess the outcomes of one of the world's largest reforestation programs, this research offers approaches to confronting two critical methodological issues: (1) techniques for characterizing subtle changes in the nature of vegetation cover, and (2) reducing change detection uncertainty due to persistent cloud cover and shadow. To address difficulties in accurately assessing the structure and composition of vegetative regrowth, a biophysical model was parameterized with over 300 ground-truthed canopy cover assessment points to determine pattern and rate of long-term vegetation changes. To combat pervasive shadow and cloud cover, an interactive generalized additive model (GAM) model based on topographic and spatial predictors was used to overcome some of the constraints of satellite image analysis in Himalayan regions characterized by extreme topography and extensive cloud cover during the summer monsoon. The change detection is assessed for accuracy using ground-truthed observations in a variety of forest cover types and topographic positions. Results indicate effectiveness in reducing the areal extent of unclassified regions and increasing total change detection accuracy. In addition to quantifying forest cover change in this section of NW Yunnan, the analysis attempts to qualify that change - distinguishing among distinct disturbance histories and post-recovery successional pathways.

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

USGS Publications Warehouse

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

2018-01-01

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

Development of Sound Localization Strategies in Children with Bilateral Cochlear Implants

PubMed Central

Zheng, Yi; Godar, Shelly P.; Litovsky, Ruth Y.

2015-01-01

Localizing sounds in our environment is one of the fundamental perceptual abilities that enable humans to communicate, and to remain safe. Because the acoustic cues necessary for computing source locations consist of differences between the two ears in signal intensity and arrival time, sound localization is fairly poor when a single ear is available. In adults who become deaf and are fitted with cochlear implants (CIs) sound localization is known to improve when bilateral CIs (BiCIs) are used compared to when a single CI is used. The aim of the present study was to investigate the emergence of spatial hearing sensitivity in children who use BiCIs, with a particular focus on the development of behavioral localization patterns when stimuli are presented in free-field horizontal acoustic space. A new analysis was implemented to quantify patterns observed in children for mapping acoustic space to a spatially relevant perceptual representation. Children with normal hearing were found to distribute their responses in a manner that demonstrated high spatial sensitivity. In contrast, children with BiCIs tended to classify sound source locations to the left and right; with increased bilateral hearing experience, they developed a perceptual map of space that was better aligned with the acoustic space. The results indicate experience-dependent refinement of spatial hearing skills in children with CIs. Localization strategies appear to undergo transitions from sound source categorization strategies to more fine-grained location identification strategies. This may provide evidence for neural plasticity, with implications for training of spatial hearing ability in CI users. PMID:26288142

Predicting Fish Growth Potential and Identifying Water Quality Constraints: A Spatially-Explicit Bioenergetics Approach

NASA Astrophysics Data System (ADS)

Budy, Phaedra; Baker, Matthew; Dahle, Samuel K.

2011-10-01

Anthropogenic impairment of water bodies represents a global environmental concern, yet few attempts have successfully linked fish performance to thermal habitat suitability and fewer have distinguished co-varying water quality constraints. We interfaced fish bioenergetics, field measurements, and Thermal Remote Imaging to generate a spatially-explicit, high-resolution surface of fish growth potential, and next employed a structured hypothesis to detect relationships among measures of fish performance and co-varying water quality constraints. Our thermal surface of fish performance captured the amount and spatial-temporal arrangement of thermally-suitable habitat for three focal species in an extremely heterogeneous reservoir, but interpretation of this pattern was initially confounded by seasonal covariation of water residence time and water quality. Subsequent path analysis revealed that in terms of seasonal patterns in growth potential, catfish and walleye responded to temperature, positively and negatively, respectively; crappie and walleye responded to eutrophy (negatively). At the high eutrophy levels observed in this system, some desired fishes appear to suffer from excessive cultural eutrophication within the context of elevated temperatures whereas others appear to be largely unaffected or even enhanced. Our overall findings do not lead to the conclusion that this system is degraded by pollution; however, they do highlight the need to use a sensitive focal species in the process of determining allowable nutrient loading and as integrators of habitat suitability across multiple spatial and temporal scales. We provide an integrated approach useful for quantifying fish growth potential and identifying water quality constraints on fish performance at spatial scales appropriate for whole-system management.

Development of Sound Localization Strategies in Children with Bilateral Cochlear Implants.

PubMed

Zheng, Yi; Godar, Shelly P; Litovsky, Ruth Y

2015-01-01

Localizing sounds in our environment is one of the fundamental perceptual abilities that enable humans to communicate, and to remain safe. Because the acoustic cues necessary for computing source locations consist of differences between the two ears in signal intensity and arrival time, sound localization is fairly poor when a single ear is available. In adults who become deaf and are fitted with cochlear implants (CIs) sound localization is known to improve when bilateral CIs (BiCIs) are used compared to when a single CI is used. The aim of the present study was to investigate the emergence of spatial hearing sensitivity in children who use BiCIs, with a particular focus on the development of behavioral localization patterns when stimuli are presented in free-field horizontal acoustic space. A new analysis was implemented to quantify patterns observed in children for mapping acoustic space to a spatially relevant perceptual representation. Children with normal hearing were found to distribute their responses in a manner that demonstrated high spatial sensitivity. In contrast, children with BiCIs tended to classify sound source locations to the left and right; with increased bilateral hearing experience, they developed a perceptual map of space that was better aligned with the acoustic space. The results indicate experience-dependent refinement of spatial hearing skills in children with CIs. Localization strategies appear to undergo transitions from sound source categorization strategies to more fine-grained location identification strategies. This may provide evidence for neural plasticity, with implications for training of spatial hearing ability in CI users.

Dispersal, environmental niches and oceanic-scale turnover in deep-sea bivalves

PubMed Central

McClain, Craig R.; Stegen, James C.; Hurlbert, Allen H.

2012-01-01

Patterns of beta-diversity or distance decay at oceanic scales are completely unknown for deep-sea communities. Even when appropriate data exist, methodological problems have made it difficult to discern the relative roles of environmental filtering and dispersal limitation for generating faunal turnover patterns. Here, we combine a spatially extensive dataset on deep-sea bivalves with a model incorporating ecological dynamics and shared evolutionary history to quantify the effects of environmental filtering and dispersal limitation. Both the model and empirical data are used to relate functional, taxonomic and phylogenetic similarity between communities to environmental and spatial distances separating them for 270 sites across the Atlantic Ocean. This study represents the first ocean-wide analysis examining distance decay as a function of a broad suite of explanatory variables. We find that both strong environmental filtering and dispersal limitation drive turnover in taxonomic, functional and phylogenetic composition in deep-sea bivalves, explaining 26 per cent, 34 per cent and 9 per cent of the variation, respectively. This contrasts with previous suggestions that dispersal is not limiting in broad-scale biogeographic and biodiversity patterning in marine systems. However, rates of decay in similarity with environmental distance were eightfold to 44-fold steeper than with spatial distance. Energy availability is the most influential environmental variable evaluated, accounting for 3.9 per cent, 9.4 per cent and 22.3 per cent of the variation in functional, phylogenetic and taxonomic similarity, respectively. Comparing empirical patterns with process-based theoretical predictions provided quantitative estimates of dispersal limitation and niche breadth, indicating that 95 per cent of deep-sea bivalve propagules will be able to persist in environments that deviate from their optimum by up to 2.1 g m−2 yr−1 and typically disperse 749 km from their natal site. PMID:22189399

Understanding the Patterns and Drivers of Air Pollution on Multiple Time Scales: The Case of Northern China.

PubMed

Liu, Yupeng; Wu, Jianguo; Yu, Deyong; Hao, Ruifang

2018-06-01

China's rapid economic growth during the past three decades has resulted in a number of environmental problems, including the deterioration of air quality. It is necessary to better understand how the spatial pattern of air pollutants varies with time scales and what drive these changes. To address these questions, this study focused on one of the most heavily air-polluted areas in North China. We first quantified the spatial pattern of air pollution, and then systematically examined the relationships of air pollution to several socioeconomic and climatic factors using the constraint line method, correlation analysis, and stepwise regression on decadal, annual, and seasonal scales. Our results indicate that PM 2.5 was the dominant air pollutant in the Beijing-Tianjin-Hebei region, while PM 2.5 and PM 10 were both important pollutants in the Agro-pastoral Transitional Zone (APTZ) region. Our statistical analyses suggest that energy consumption and gross domestic product (GDP) in the industry were the most important factors for air pollution on the decadal scale, but the impacts of climatic factors could also be significant. On the annual and seasonal scales, high wind speed, low relative humidity, and long sunshine duration constrained PM 2.5 accumulation; low wind speed and high relative humidity constrained PM 10 accumulation; and short sunshine duration and high wind speed constrained O 3 accumulation. Our study showed that analyses on multiple temporal scales are not only necessary to determine key drivers of air pollution, but also insightful for understanding the spatial patterns of air pollution, which was important for urban planning and air pollution control.

Long-term analysis of spatio-temporal patterns in population dynamics and demography of juvenile Pinfish (Lagodon rhomboides)

NASA Astrophysics Data System (ADS)

Chacin, D. H.; Switzer, T. S.; Ainsworth, C. H.; Stallings, C. D.

2016-12-01

In estuarine systems, proximity to the ocean has the potential to directly and indirectly drive patterns of fish distribution and population dynamics. To test this hypothesis, we conducted a comprehensive analysis of fisheries-independent data and quantified patterns of density, biomass, and growth rates of juvenile Pinfish (Lagodon rhomboides) across spatial and temporal scales in Tampa Bay, Florida, USA. Spatially, the highest density and biomass were found in the outermost regions (closest to the Gulf of Mexico) of the Bay, and these patterns were generally consistent temporally. Inter-annually, Pinfish density and biomass were the highest during periods coinciding with favorable oceanographic conditions (e.g., anomalously intense and prolonged upwelling) for across-shelf transport of larvae from spawning grounds in the Gulf to Tampa Bay. Intra-annually, density and biomass were the highest during spring and summer likely due to the combined effects of spawning timing (and delivery of new settlers), and high somatic growth fueled by increased secondary and primary productivity. Declines in density and biomass during the late summer through early winter were possibly due to high post-settlement mortality and egress to offshore habitats. Pinfish increased predictably in size across the months of the calendar year, and tended to be larger and grew faster in the innermost regions of the Bay, which were located farthest from the Gulf. Pinfish density was related to the proximity to the Gulf of Mexico, with the outermost regions of the Bay having greater seagrass cover, higher salinity, and being closer to the offshore larval pool where spawning occurs. Thus, this study provided evidence that distance to the ocean was an important driver of biotic and abiotic factors that influenced Pinfish demographic rates across spatial and temporal scales in the largest estuary in Florida.

Impacts of Landscape Context on Patterns of Wind Downfall Damage in a Fragmented Amazonian Landscape

NASA Astrophysics Data System (ADS)

Schwartz, N.; Uriarte, M.; DeFries, R. S.; Gutierrez-Velez, V. H.; Fernandes, K.; Pinedo-Vasquez, M.

2015-12-01

Wind is a major disturbance in the Amazon and has both short-term impacts and lasting legacies in tropical forests. Observed patterns of damage across landscapes result from differences in wind exposure and stand characteristics, such as tree stature, species traits, successional age, and fragmentation. Wind disturbance has important consequences for biomass dynamics in Amazonian forests, and understanding the spatial distribution and size of impacts is necessary to quantify the effects on carbon dynamics. In November 2013, a mesoscale convective system was observed over the study area in Ucayali, Peru, a highly human modified and fragmented forest landscape. We mapped downfall damage associated with the storm in order to ask: how does the severity of damage vary within forest patches, and across forest patches of different sizes and successional ages? We applied spectral mixture analysis to Landsat images from 2013 and 2014 to calculate the change in non-photosynthetic vegetation fraction after the storm, and combined it with C-band SAR data from the Sentinel-1 satellite to predict downfall damage measured in 30 field plots using random forest regression. We then applied this model to map damage in forests across the study area. Using a land cover classification developed in a previous study, we mapped secondary and mature forest, and compared the severity of damage in the two. We found that damage was on average higher in secondary forests, but patterns varied spatially. This study demonstrates the utility of using multiple sources of satellite data for mapping wind disturbance, and adds to our understanding of the sources of variation in wind-related damage. Ultimately, an improved ability to map wind impacts and a better understanding of their spatial patterns can contribute to better quantification of carbon dynamics in Amazonian landscapes.

Understanding the Patterns and Drivers of Air Pollution on Multiple Time Scales: The Case of Northern China

NASA Astrophysics Data System (ADS)

Liu, Yupeng; Wu, Jianguo; Yu, Deyong; Hao, Ruifang

2018-06-01

China's rapid economic growth during the past three decades has resulted in a number of environmental problems, including the deterioration of air quality. It is necessary to better understand how the spatial pattern of air pollutants varies with time scales and what drive these changes. To address these questions, this study focused on one of the most heavily air-polluted areas in North China. We first quantified the spatial pattern of air pollution, and then systematically examined the relationships of air pollution to several socioeconomic and climatic factors using the constraint line method, correlation analysis, and stepwise regression on decadal, annual, and seasonal scales. Our results indicate that PM2.5 was the dominant air pollutant in the Beijing-Tianjin-Hebei region, while PM2.5 and PM10 were both important pollutants in the Agro-pastoral Transitional Zone (APTZ) region. Our statistical analyses suggest that energy consumption and gross domestic product (GDP) in the industry were the most important factors for air pollution on the decadal scale, but the impacts of climatic factors could also be significant. On the annual and seasonal scales, high wind speed, low relative humidity, and long sunshine duration constrained PM2.5 accumulation; low wind speed and high relative humidity constrained PM10 accumulation; and short sunshine duration and high wind speed constrained O3 accumulation. Our study showed that analyses on multiple temporal scales are not only necessary to determine key drivers of air pollution, but also insightful for understanding the spatial patterns of air pollution, which was important for urban planning and air pollution control.

Pattern selection and super-patterns in the bounded confidence model

DOE PAGES

Ben-Naim, E.; Scheel, A.

2015-10-26

We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes ofmore » the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. Furthermore, the spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.« less

Geo-located Twitter as proxy for global mobility patterns.

PubMed

Hawelka, Bartosz; Sitko, Izabela; Beinat, Euro; Sobolevsky, Stanislav; Kazakopoulos, Pavlos; Ratti, Carlo

2014-05-27

Pervasive presence of location-sharing services made it possible for researchers to gain an unprecedented access to the direct records of human activity in space and time. This article analyses geo-located Twitter messages in order to uncover global patterns of human mobility. Based on a dataset of almost a billion tweets recorded in 2012, we estimate the volume of international travelers by country of residence. Mobility profiles of different nations were examined based on such characteristics as mobility rate, radius of gyration, diversity of destinations, and inflow-outflow balance. Temporal patterns disclose the universally valid seasons of increased international mobility and the particular character of international travels of different nations. Our analysis of the community structure of the Twitter mobility network reveals spatially cohesive regions that follow the regional division of the world. We validate our result using global tourism statistics and mobility models provided by other authors and argue that Twitter is exceptionally useful for understanding and quantifying global mobility patterns.

Quantitative analysis and temperature-induced variations of moiré pattern in fiber-coupled imaging sensors.

PubMed

Karbasi, Salman; Arianpour, Ashkan; Motamedi, Nojan; Mellette, William M; Ford, Joseph E

2015-06-10

Imaging fiber bundles can map the curved image surface formed by some high-performance lenses onto flat focal plane detectors. The relative alignment between the focal plane array pixels and the quasi-periodic fiber-bundle cores can impose an undesirable space variant moiré pattern, but this effect may be greatly reduced by flat-field calibration, provided that the local responsivity is known. Here we demonstrate a stable metric for spatial analysis of the moiré pattern strength, and use it to quantify the effect of relative sensor and fiber-bundle pitch, and that of the Bayer color filter. We measure the thermal dependence of the moiré pattern, and the achievable improvement by flat-field calibration at different operating temperatures. We show that a flat-field calibration image at a desired operating temperature can be generated using linear interpolation between white images at several fixed temperatures, comparing the final image quality with an experimentally acquired image at the same temperature.

Pattern selection and super-patterns in the bounded confidence model

NASA Astrophysics Data System (ADS)

Ben-Naim, E.; Scheel, A.

2015-10-01

We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes of the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. The spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.

Current and Future Patterns of Global Marine Mammal Biodiversity

PubMed Central

Kaschner, Kristin; Tittensor, Derek P.; Ready, Jonathan; Gerrodette, Tim; Worm, Boris

2011-01-01

Quantifying the spatial distribution of taxa is an important prerequisite for the preservation of biodiversity, and can provide a baseline against which to measure the impacts of climate change. Here we analyse patterns of marine mammal species richness based on predictions of global distributional ranges for 115 species, including all extant pinnipeds and cetaceans. We used an environmental suitability model specifically designed to address the paucity of distributional data for many marine mammal species. We generated richness patterns by overlaying predicted distributions for all species; these were then validated against sightings data from dedicated long-term surveys in the Eastern Tropical Pacific, the Northeast Atlantic and the Southern Ocean. Model outputs correlated well with empirically observed patterns of biodiversity in all three survey regions. Marine mammal richness was predicted to be highest in temperate waters of both hemispheres with distinct hotspots around New Zealand, Japan, Baja California, the Galapagos Islands, the Southeast Pacific, and the Southern Ocean. We then applied our model to explore potential changes in biodiversity under future perturbations of environmental conditions. Forward projections of biodiversity using an intermediate Intergovernmental Panel for Climate Change (IPCC) temperature scenario predicted that projected ocean warming and changes in sea ice cover until 2050 may have moderate effects on the spatial patterns of marine mammal richness. Increases in cetacean richness were predicted above 40° latitude in both hemispheres, while decreases in both pinniped and cetacean richness were expected at lower latitudes. Our results show how species distribution models can be applied to explore broad patterns of marine biodiversity worldwide for taxa for which limited distributional data are available. PMID:21625431

Estimating irrigated areas from satellite and model soil moisture data over the contiguous US

NASA Astrophysics Data System (ADS)

Zaussinger, Felix; Dorigo, Wouter; Gruber, Alexander

2017-04-01

Information about irrigation is crucial for a number of applications such as drought- and yield management and contributes to a better understanding of the water-cycle, land-atmosphere interactions as well as climate projections. Currently, irrigation is mainly quantified by national agricultural statistics, which do not include spatial information. The digital Global Map of Irrigated Areas (GMIA) has been the first effort to quantify irrigation at the global scale by merging these statistics with remote sensing data. Also, the MODIS-Irrigated Agriculture Dataset (MirAD-US) was created by merging annual peak MODIS-NDVI with US county level irrigation statistics. In this study we aim to map irrigated areas by confronting time series of various satellite soil moisture products with soil moisture from the ERA-Interim/Land reanalysis product. We follow the assumption that irrigation signals are not modelled in the reanalysis product, nor contributing to its forcing data, but affecting the spatially continuous remote sensing observations. Based on this assumption, spatial patterns of irrigation are derived from differences between the temporal slopes of the modelled and remotely sensed time series during the irrigation season. Results show that a combination of ASCAT and ERA-Interim/Land show spatial patterns which are in good agreement with the MIrAD-US, particularly within the Mississippi Delta, Texas and eastern Nebraska. In contrast, AMSRE shows weak agreements, plausibly due to a higher vegetation dependency of the soil moisture signal. There is no significant agreement to the MIrAD-US in California, which is possibly related to higher crop-diversity and lower field sizes. Also, a strong signal in the region of the Great Corn Belt is observed, which is generally not outlined as an irrigated area. It is not yet clear to what extent the signal obtained in the Mississippi Delta is related to re-reflection effects caused by standing water due to flood or furrow irrigation practices. Consequently, future research should focus on the specific effects of different irrigation practices and crop types. This study is supported by the European Union's FP7 EartH2Observe "Global Earth Observation for Integrated Water Resource Assessment" project (grant agreement number 331 603608).

Forest dynamics in the U.S. indicate disproportionate attrition in western forests, rural areas and public lands

PubMed Central

2017-01-01

Forests are experiencing significant changes; studying geographic patterns in forests is critical in understanding the impact of forest dynamics to biodiversity, soil erosion, water chemistry and climate. Few studies have examined forest geographic pattern changes other than fragmentation; however, other spatial processes of forest dynamics are of equal importance. Here, we study forest attrition, the complete removal of forest patches, that can result in complete habitat loss, severe decline of population sizes and species richness, and shifts of local and regional environmental conditions. We aim to develop a simple yet insightful proximity-based spatial indicator capturing forest attrition that is independent of spatial scale and boundaries with worldwide application potential. Using this proximity indicator, we evaluate forest attrition across ecoregions, land ownership and urbanization stratifications across continental United States of America. Nationally, the total forest cover loss was approximately 90,400 km2, roughly the size of the state of Maine, constituting a decline of 2.96%. Examining the spatial arrangement of this change the average FAD was 3674m in 1992 and increased by 514m or 14.0% in 2001. Simulations of forest cover loss indicate only a 10m FAD increase suggesting that the observed FAD increase was more than an order of magnitude higher than expected. Furthermore, forest attrition is considerably higher in the western United States, in rural areas and in public lands. Our mathematical model (R2 = 0.93) supports estimation of attrition for a given forest cover. The FAD metric quantifies forest attrition across spatial scales and geographic boundaries and assesses unambiguously changes over time. The metric is applicable to any landscape and offers a new complementary insight on forest landscape patterns from local to global scales, improving future exploration of drivers and repercussions of forest cover changes and supporting more informative management of forest carbon, changing climate and species biodiversity. PMID:28225787

Forest dynamics in the U.S. indicate disproportionate attrition in western forests, rural areas and public lands.

PubMed

Yang, Sheng; Mountrakis, Giorgos

2017-01-01

Forests are experiencing significant changes; studying geographic patterns in forests is critical in understanding the impact of forest dynamics to biodiversity, soil erosion, water chemistry and climate. Few studies have examined forest geographic pattern changes other than fragmentation; however, other spatial processes of forest dynamics are of equal importance. Here, we study forest attrition, the complete removal of forest patches, that can result in complete habitat loss, severe decline of population sizes and species richness, and shifts of local and regional environmental conditions. We aim to develop a simple yet insightful proximity-based spatial indicator capturing forest attrition that is independent of spatial scale and boundaries with worldwide application potential. Using this proximity indicator, we evaluate forest attrition across ecoregions, land ownership and urbanization stratifications across continental United States of America. Nationally, the total forest cover loss was approximately 90,400 km2, roughly the size of the state of Maine, constituting a decline of 2.96%. Examining the spatial arrangement of this change the average FAD was 3674m in 1992 and increased by 514m or 14.0% in 2001. Simulations of forest cover loss indicate only a 10m FAD increase suggesting that the observed FAD increase was more than an order of magnitude higher than expected. Furthermore, forest attrition is considerably higher in the western United States, in rural areas and in public lands. Our mathematical model (R2 = 0.93) supports estimation of attrition for a given forest cover. The FAD metric quantifies forest attrition across spatial scales and geographic boundaries and assesses unambiguously changes over time. The metric is applicable to any landscape and offers a new complementary insight on forest landscape patterns from local to global scales, improving future exploration of drivers and repercussions of forest cover changes and supporting more informative management of forest carbon, changing climate and species biodiversity.

Spatiotemporal dynamics of a digital phase-locked loop based coupled map lattice system

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

Banerjee, Tanmoy, E-mail: tbanerjee@phys.buruniv.ac.in; Paul, Bishwajit; Sarkar, B. C.

2014-03-15

We explore the spatiotemporal dynamics of a coupled map lattice (CML) system, which is realized with a one dimensional array of locally coupled digital phase-locked loops (DPLLs). DPLL is a nonlinear feedback-controlled system widely used as an important building block of electronic communication systems. We derive the phase-error equation of the spatially extended system of coupled DPLLs, which resembles a form of the equation of a CML system. We carry out stability analysis for the synchronized homogeneous solutions using the circulant matrix formalism. It is shown through extensive numerical simulations that with the variation of nonlinearity parameter and coupling strengthmore » the system shows transitions among several generic features of spatiotemporal dynamics, viz., synchronized fixed point solution, frozen random pattern, pattern selection, spatiotemporal intermittency, and fully developed spatiotemporal chaos. We quantify the spatiotemporal dynamics using quantitative measures like average quadratic deviation and spatial correlation function. We emphasize that instead of using an idealized model of CML, which is usually employed to observe the spatiotemporal behaviors, we consider a real world physical system and establish the existence of spatiotemporal chaos and other patterns in this system. We also discuss the importance of the present study in engineering application like removal of clock-skew in parallel processors.« less

Spatiotemporal dynamics of a digital phase-locked loop based coupled map lattice system.

PubMed

Banerjee, Tanmoy; Paul, Bishwajit; Sarkar, B C

2014-03-01

We explore the spatiotemporal dynamics of a coupled map lattice (CML) system, which is realized with a one dimensional array of locally coupled digital phase-locked loops (DPLLs). DPLL is a nonlinear feedback-controlled system widely used as an important building block of electronic communication systems. We derive the phase-error equation of the spatially extended system of coupled DPLLs, which resembles a form of the equation of a CML system. We carry out stability analysis for the synchronized homogeneous solutions using the circulant matrix formalism. It is shown through extensive numerical simulations that with the variation of nonlinearity parameter and coupling strength the system shows transitions among several generic features of spatiotemporal dynamics, viz., synchronized fixed point solution, frozen random pattern, pattern selection, spatiotemporal intermittency, and fully developed spatiotemporal chaos. We quantify the spatiotemporal dynamics using quantitative measures like average quadratic deviation and spatial correlation function. We emphasize that instead of using an idealized model of CML, which is usually employed to observe the spatiotemporal behaviors, we consider a real world physical system and establish the existence of spatiotemporal chaos and other patterns in this system. We also discuss the importance of the present study in engineering application like removal of clock-skew in parallel processors.

Spatiotemporal dynamics of a digital phase-locked loop based coupled map lattice system

NASA Astrophysics Data System (ADS)

Banerjee, Tanmoy; Paul, Bishwajit; Sarkar, B. C.

2014-03-01

We explore the spatiotemporal dynamics of a coupled map lattice (CML) system, which is realized with a one dimensional array of locally coupled digital phase-locked loops (DPLLs). DPLL is a nonlinear feedback-controlled system widely used as an important building block of electronic communication systems. We derive the phase-error equation of the spatially extended system of coupled DPLLs, which resembles a form of the equation of a CML system. We carry out stability analysis for the synchronized homogeneous solutions using the circulant matrix formalism. It is shown through extensive numerical simulations that with the variation of nonlinearity parameter and coupling strength the system shows transitions among several generic features of spatiotemporal dynamics, viz., synchronized fixed point solution, frozen random pattern, pattern selection, spatiotemporal intermittency, and fully developed spatiotemporal chaos. We quantify the spatiotemporal dynamics using quantitative measures like average quadratic deviation and spatial correlation function. We emphasize that instead of using an idealized model of CML, which is usually employed to observe the spatiotemporal behaviors, we consider a real world physical system and establish the existence of spatiotemporal chaos and other patterns in this system. We also discuss the importance of the present study in engineering application like removal of clock-skew in parallel processors.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Resolution of VTI anisotropy with elastic full-waveform inversion: theory and basic numerical examples

NASA Astrophysics Data System (ADS)

Podgornova, O.; Leaney, S.; Liang, L.

2018-07-01

Extracting medium properties from seismic data faces some limitations due to the finite frequency content of the data and restricted spatial positions of the sources and receivers. Some distributions of the medium properties make low impact on the data (including none). If these properties are used as the inversion parameters, then the inverse problem becomes overparametrized, leading to ambiguous results. We present an analysis of multiparameter resolution for the linearized inverse problem in the framework of elastic full-waveform inversion. We show that the spatial and multiparameter sensitivities are intertwined and non-sensitive properties are spatial distributions of some non-trivial combinations of the conventional elastic parameters. The analysis accounts for the Hessian information and frequency content of the data; it is semi-analytical (in some scenarios analytical), easy to interpret and enhances results of the widely used radiation pattern analysis. Single-type scattering is shown to have limited sensitivity, even for full-aperture data. Finite-frequency data lose multiparameter sensitivity at smooth and fine spatial scales. Also, we establish ways to quantify a spatial-multiparameter coupling and demonstrate that the theoretical predictions agree well with the numerical results.

Strong biotic influences on regional patterns of climate regulation services

NASA Astrophysics Data System (ADS)

Serna-Chavez, H. M.; Swenson, N. G.; Weiser, M. D.; van Loon, E. E.; Bouten, W.; Davidson, M. D.; van Bodegom, P. M.

2017-05-01

Climate regulation services from forests are an important leverage in global-change mitigation treaties. Like most ecosystem services, climate regulation is the product of various ecological phenomena with unique spatial features. Elucidating which abiotic and biotic factors relate to spatial patterns of climate regulation services advances our understanding of what underlies climate-mitigation potential and its variation within and across ecosystems. Here we quantify and contrast the statistical relations between climate regulation services (albedo and evapotranspiration, primary productivity, and soil carbon) and abiotic and biotic factors. We focus on 16,955 forest plots in a regional extent across the eastern United States. We find the statistical effects of forest litter and understory carbon on climate regulation services to be as strong as those of temperature-precipitation interactions. These biotic factors likely influence climate regulation through changes in vegetation and canopy density, radiance scattering, and decomposition rates. We also find a moderate relation between leaf nitrogen traits and primary productivity at this regional scale. The statistical relation between climate regulation and temperature-precipitation ranges, seasonality, and climatic thresholds highlights a strong feedback with global climate change. Our assessment suggests the expression of strong biotic influences on climate regulation services at a regional, temperate extent. Biotic homogenization and management practices manipulating forest structure and succession will likely strongly impact climate-mitigation potential. The identity, strength, and direction of primary influences differed for each process involved in climate regulation. Hence, different abiotic and biotic factors are needed to monitor and quantify the full climate-mitigation potential of temperate forest ecosystems.

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

PubMed

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

2015-01-01

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

Hydroclimatology of Dual Peak Cholera Incidence in Bengal Region: Inferences from a Spatial Explicit Model

NASA Astrophysics Data System (ADS)

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

2010-12-01

The seasonality of cholera and its relation with environmental drivers are receiving increasing interest and research efforts, yet they remain unsatisfactorily understood. A striking example is the observed annual cycle of cholera incidence in the Bengal region which exhibits two peaks despite the main environmental drivers that have been linked to the disease (air and sea surface temperature, zooplankton density, river discharge) follow a synchronous single-peak annual pattern. A first outbreak, mainly affecting the coastal regions, occurs in spring and it is followed, after a period of low incidence during summer, by a second, usually larger, peak in autumn also involving regions situated farther inland. A hydroclimatological explanation for this unique seasonal cycle has been recently proposed: the low river spring flows favor the intrusion of brackish water (the natural environment of the causative agent of the disease) which, in turn, triggers the first outbreak. The summer rising river discharges have a temporary dilution effect and prompt the repulsion of contaminated water which lowers the disease incidence. However, the monsoon flooding, together with the induced crowding of the population and the failure of the sanitation systems, can possibly facilitate the spatial transmission of the disease and promote the autumn outbreak. We test this hypothesis using a mechanistic, spatially explicit model of cholera epidemic. The framework directly accounts for the role of the river network in transporting and redistributing cholera bacteria among human communities as well as for the annual fluctuation of the river flow. The model is forced with the actual environmental drivers of the region, namely river flow and temperature. Our results show that these two drivers, both having a single peak in the summer, can generate a double peak cholera incidence pattern. Besides temporal patterns, the model is also able to qualitatively reproduce spatial patterns characterized by a spring peak confined to the coastal area and a autumn peak involving the whole region. The modeling exercise allows to identify the relevant processes and to understand how they concert to the generation of this peculiar pattern. Finally, the range of epidemiological and hydrological conditions under which dual or a single peaks are expected is quantified.

Angle-Beam Shear Wave Scattering from Buried Crack-like Defects in Bonded Specimens (Postprint)

DTIC Science & Technology

2017-02-01

wavenumber filtering and spatial windowing is proposed and implemented as an alternative approach to quantify scattering from damage. 15. SUBJECT...TERMS Backscattering . Ultrasonography . Spatial filtering . Ultrasonic scattering . Scattering measurement 16. SECURITY CLASSIFICATION OF: 17...of frequency- wavenumber filtering and spatial windowing is proposed and implemented as an alternative approach to quantify scattering from damage

Integrated circuit-based electrochemical sensor for spatially resolved detection of redox-active metabolites in biofilms.

PubMed

Bellin, Daniel L; Sakhtah, Hassan; Rosenstein, Jacob K; Levine, Peter M; Thimot, Jordan; Emmett, Kevin; Dietrich, Lars E P; Shepard, Kenneth L

2014-01-01

Despite advances in monitoring spatiotemporal expression patterns of genes and proteins with fluorescent probes, direct detection of metabolites and small molecules remains challenging. A technique for spatially resolved detection of small molecules would benefit the study of redox-active metabolites that are produced by microbial biofilms and can affect their development. Here we present an integrated circuit-based electrochemical sensing platform featuring an array of working electrodes and parallel potentiostat channels. 'Images' over a 3.25 × 0.9 mm(2) area can be captured with a diffusion-limited spatial resolution of 750 μm. We demonstrate that square wave voltammetry can be used to detect, identify and quantify (for concentrations as low as 2.6 μM) four distinct redox-active metabolites called phenazines. We characterize phenazine production in both wild-type and mutant Pseudomonas aeruginosa PA14 colony biofilms, and find correlations with fluorescent reporter imaging of phenazine biosynthetic gene expression.

Development of a distributed air pollutant dry deposition modeling framework.

PubMed

Hirabayashi, Satoshi; Kroll, Charles N; Nowak, David J

2012-12-01

A distributed air pollutant dry deposition modeling system was developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry deposition of carbon monoxide (CO), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and particulate matter less than 10 microns (PM10) to trees can be spatially quantified. Employing nationally available road network, traffic volume, air pollutant emission/measurement and meteorological data, the developed system provides a framework for the U.S. city managers to identify spatial patterns of urban forest and locate potential areas for future urban forest planting and protection to improve air quality. To exhibit the usability of the framework, a case study was performed for July and August of 2005 in Baltimore, MD. Copyright © 2012 Elsevier Ltd. All rights reserved.

Immigrant community integration in world cities

PubMed Central

Lamanna, Fabio; Lenormand, Maxime; Salas-Olmedo, María Henar; Romanillos, Gustavo; Gonçalves, Bruno

2018-01-01

As a consequence of the accelerated globalization process, today major cities all over the world are characterized by an increasing multiculturalism. The integration of immigrant communities may be affected by social polarization and spatial segregation. How are these dynamics evolving over time? To what extent the different policies launched to tackle these problems are working? These are critical questions traditionally addressed by studies based on surveys and census data. Such sources are safe to avoid spurious biases, but the data collection becomes an intensive and rather expensive work. Here, we conduct a comprehensive study on immigrant integration in 53 world cities by introducing an innovative approach: an analysis of the spatio-temporal communication patterns of immigrant and local communities based on language detection in Twitter and on novel metrics of spatial integration. We quantify the Power of Integration of cities –their capacity to spatially integrate diverse cultures– and characterize the relations between different cultures when acting as hosts or immigrants. PMID:29538383

Shallow rocky nursery habitat for fish: Spatial variability of juvenile fishes among this poorly protected essential habitat.

PubMed

Cheminée, Adrien; Rider, Mary; Lenfant, Philippe; Zawadzki, Audrey; Mercière, Alexandre; Crec'hriou, Romain; Mercader, Manon; Saragoni, Gilles; Neveu, Reda; Ternon, Quentin; Pastor, Jérémy

2017-06-15

Coastal nursery habitats are essential for the renewal of adult fish populations. We quantified the availability of a coastal nursery habitat (shallow heterogeneous rocky bottoms) and the spatial variability of its juvenile fish populations along 250km of the Catalan coastline (France and Spain). Nurseries were present in 27% of the coastline, but only 2% of them benefited from strict protection status. For nine taxa characteristic of this habitat, total juvenile densities varied significantly between nursery sites along the coastline, with the highest densities being found on the northern sites. Recruitment level (i.e. a proxy of nursery value) was not explained by protection level, but it was moderately and positively correlated with an anthropization index. Patterns of spatial variations were taxa-specific. Exceptional observations of four juveniles of the protected grouper Epinephelus marginatus were recorded. Our data on habitat availability and recruitment levels provides important informations which help to focus MPA management efforts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrated circuit-based electrochemical sensor for spatially resolved detection of redox-active metabolites in biofilms

PubMed Central

Bellin, Daniel L.; Sakhtah, Hassan; Rosenstein, Jacob K.; Levine, Peter M.; Thimot, Jordan; Emmett, Kevin; Dietrich, Lars E. P.; Shepard, Kenneth L.

2014-01-01

Despite advances in monitoring spatiotemporal expression patterns of genes and proteins with fluorescent probes, direct detection of metabolites and small molecules remains challenging. A technique for spatially resolved detection of small molecules would benefit the study of redox-active metabolites produced by microbial biofilms, which can drastically affect colony development. Here we present an integrated circuit-based electrochemical sensing platform featuring an array of working electrodes and parallel potentiostat channels. “Images” over a 3.25 × 0.9 mm area can be captured with a diffusion-limited spatial resolution of 750 μm. We demonstrate that square wave voltammetry can be used to detect, identify, and quantify (for concentrations as low as 2.6 μM) four distinct redox-active metabolites called phenazines. We characterize phenazine production in both wild-type and mutant Pseudomonas aeruginosa PA14 colony biofilms, and find correlations with fluorescent reporter imaging of phenazine biosynthetic gene expression. PMID:24510163

Information spreading by a combination of MEG source estimation and multivariate pattern classification.

PubMed

Sato, Masashi; Yamashita, Okito; Sato, Masa-Aki; Miyawaki, Yoichi

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of "information spreading" may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined.

Information spreading by a combination of MEG source estimation and multivariate pattern classification

PubMed Central

Sato, Masashi; Yamashita, Okito; Sato, Masa-aki

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of “information spreading” may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined. PMID:29912968

Assessing spatial and temporal snowpack evolution and melt with time-lapse photography

NASA Astrophysics Data System (ADS)

Bush, C. E.; Ewers, B. E.; Beverly, D.; Speckman, H. N.; Hyde, K.; Ohara, N.

2015-12-01

Snowpack supplies and stores water for many ecosystems of the greater Rocky Mountain region. In Wyoming the snowpack supplies water to 18 states east and west of the Continental Divide. The spatial variability in physical and biological processes creates a heterogeneous pattern of snow evolution. Understanding these processes within individual plots and throughout the entire watershed increases the predictive power of snow distribution, melt rates and contribution to streamflow. However, on site sampling of snow can be an expensive and arduous process. The objective of this experiment was to quantify spatial and temporal patterns of snowpack evolution and melt rates while minimizing perturbations to snowpack through the use of time-lapse photography via trail cameras. Field cameras were assessed as a method to quantify snow depths throughout the 120 ha No Name watershed at approximately 3000 m elevation in central Wyoming. RGB trail cameras were installed at three systematically chosen sites within the watershed to correlate physical and biological drivers of snow distribution. Five stakes were placed in each site in heterogeneous spots that remained in the frame of the camera. Stakes were divided into five centimeter increments, alternating black and white bars, with red bars denoting each half meter. Images were then taken at two-hour intervals over a period of three-months and analyzed with the ImageJ program. Snowpack distributions, as well as melt rates, were variable at both the plot and watershed scales. Meteorological and physical drivers, primarily topography and radiation, accounted for the greatest variability when comparing among plot across the watershed; however, LAI and soil and air temperature were the most significant drivers within plots. Snow-melt rate increased as soils and course woody debris became exposed increasing ground and soil temperature. These data will improve process model predictions of streamflow from the watershed.

Spatial variation in abundance, size and orientation of juvenile corals related to the biomass of parrotfishes on the Great Barrier Reef, Australia.

PubMed

Trapon, Melanie L; Pratchett, Morgan S; Hoey, Andrew S

2013-01-01

For species with complex life histories such as scleractinian corals, processes occurring early in life can greatly influence the number of individuals entering the adult population. A plethora of studies have examined settlement patterns of coral larvae, mostly on artificial substrata, and the composition of adult corals across multiple spatial and temporal scales. However, relatively few studies have examined the spatial distribution of small (≤50 mm diameter) sexually immature corals on natural reef substrata. We, therefore, quantified the variation in the abundance, composition and size of juvenile corals (≤50 mm diameter) among 27 sites, nine reefs, and three latitudes spanning over 1000 km on Australia's Great Barrier Reef. Overall, 2801 juveniles were recorded with a mean density of 6.9 (±0.3 SE) ind.m(-2), with Acropora, Pocillopora, and Porites accounting for 84.1% of all juvenile corals surveyed. Size-class structure, orientation on the substrate and taxonomic composition of juvenile corals varied significantly among latitudinal sectors. The abundance of juvenile corals varied both within (6-13 ind.m(-2)) and among reefs (2.8-11.1 ind.m(-2)) but was fairly similar among latitudes (6.1-8.2 ind.m(-2)), despite marked latitudinal variation in larval supply and settlement rates previously found at this scale. Furthermore, the density of juvenile corals was negatively correlated with the biomass of scraping and excavating parrotfishes across all sites, revealing a potentially important role of parrotfishes in determining distribution patterns of juvenile corals on the Great Barrier Reef. While numerous studies have advocated the importance of parrotfishes for clearing space on the substrate to facilitate coral settlement, our results suggest that at high biomass they may have a detrimental effect on juvenile coral assemblages. There is, however, a clear need to directly quantify rates of mortality and growth of juvenile corals to understand the relative importance of these mechanisms in shaping juvenile, and consequently adult, coral assemblages.

Ecohydrological Interfaces as Dynamic Hotspots of Biogeochemical Cycling

NASA Astrophysics Data System (ADS)

Krause, Stefan; Lewandowski, Joerg; Hannah, David; McDonald, Karlie; Folegot, Silvia; Baranov, Victor

2016-04-01

Ecohydrological interfaces, represent the boundaries between water-dependent ecosystems that can alter substantially the fluxes of energy and matter. There is still a critical gap of understanding the organisational principles of the drivers and controls of spatially and temporally variable ecohydrological interface functions. This knowledge gap limits our capacity to efficiently quantify, predict and manage the services provided by complex ecosystems. Many ecohydrological interfaces are characterized by step changes in microbial metabolic activity, steep redox gradients and often even thermodynamic phase shifts, for instance at the interfaces between atmosphere and water or soil matrix and macro-pores interfaces. This paper integrates investigations from point scale laboratory microcosm experiments with reach and subcatchment scale tracer experiments and numerical modeling studies to elaborate similarities in the drivers and controls that constitute the enhanced biogeochemical activity of different types of ecohydrologica interfaces across a range of spatial and temporal scales. We therefore combine smart metabolic activity tracers to quantify the impact of bioturbating benthic fauna onto ecosystem respiration and oxygen consumption and investigate at larger scale, how microbial metabolic activity and carbon turnover at the water-sediment interface are controlled by sediment physical and chemical properties as well as water temperatures. Numerical modeling confirmed that experimentally identified hotspots of streambed biogeochemical cycling were controlled by patterns of physical properties such as hydraulic conductivities or bioavailability of organic matter, impacting on residence time distributions and hence reaction times. In contrast to previous research, our investigations thus confirmed that small-scale variability of physical and chemical interface properties had a major impact on biogeochemical processing at the investigated ecohydrological interfaces. Our results furthermore indicate that to fully understand spatial patterns and temporal dynamics of ecohydrological interface functioning, including hotspots and hot moments, detailed knowledge of the impacts of biological behavior on the physic-chemical ecosystem conditions, and vice-versa, is required.

Ecohydrological Interfaces as Dynamic Hotspots of Biogeochemical Cycling

NASA Astrophysics Data System (ADS)

Krause, S.

2015-12-01

Ecohydrological interfaces, represent the boundaries between water-dependent ecosystems that can alter substantially the fluxes of energy and matter. There is still a critical gap of understanding the organisational principles of the drivers and controls of spatially and temporally variable ecohydrological interface functions. This knowledge gap limits our capacity to efficiently quantify, predict and manage the services provided by complex ecosystems. Many ecohydrological interfaces are characterized by step changes in microbial metabolic activity, steep redox gradients and often even thermodynamic phase shifts, for instance at the interfaces between atmosphere and water or soil matrix and macro-pores interfaces. This paper integrates investigations from point scale microcosm experiments with reach and subcatchment scale tracer experiments and numerical modeling studies to elaborate similarities in the drivers and controls that constitute the enhanced biogeochemical activity of different types of ecohydrologica interfaces across a range of spatial and temporal scales. We therefore combine smart metabolic activity tracers to quantify the impact of bioturbating benthic fauna onto ecosystem respiration and oxygen consumption and investigate at larger scale, how microbial metabolic activity and carbon turnover at the water-sediment interface are controlled by sediment physical and chemical properties as well as water temperatures. Numerical modeling confirmed that experimentally identified hotspots of streambed biogeochemical cycling were controlled by patterns of physical properties such as hydraulic conductivities or bioavailability of organic matter, impacting on residence time distributions and hence reaction times. In contrast to previous research, our investigations thus confirmed that small-scale variability of physical and chemical interface properties had a major impact on biogeochemical processing at the investigated ecohydrological interfaces. Our results furthermore indicate that to fully understand spatial patterns and temporal dynamics of ecohydrological interface functioning, including hotspots and hot moments, detailed knowledge of the impacts of biological behavior on the physic-chemical ecosystem conditions, and vice-versa, is required.

Context-aware pattern discovery for moving object trajectories

NASA Astrophysics Data System (ADS)

Sharif, Mohammad; Asghar Alesheikh, Ali; Kaffash Charandabi, Neda

2018-05-01

Movement of point objects are highly sensitive to the underlying situations and conditions during the movement, which are known as contexts. Analyzing movement patterns, while accounting the contextual information, helps to better understand how point objects behave in various contexts and how contexts affect their trajectories. One potential solution for discovering moving objects patterns is analyzing the similarities of their trajectories. This article, therefore, contextualizes the similarity measure of trajectories by not only their spatial footprints but also a notion of internal and external contexts. The dynamic time warping (DTW) method is employed to assess the multi-dimensional similarities of trajectories. Then, the results of similarity searches are utilized in discovering the relative movement patterns of the moving point objects. Several experiments are conducted on real datasets that were obtained from commercial airplanes and the weather information during the flights. The results yielded the robustness of DTW method in quantifying the commonalities of trajectories and discovering movement patterns with 80 % accuracy. Moreover, the results revealed the importance of exploiting contextual information because it can enhance and restrict movements.

Multi-Dimensional Pattern Discovery of Trajectories Using Contextual Information

NASA Astrophysics Data System (ADS)

Sharif, M.; Alesheikh, A. A.

2017-10-01

Movement of point objects are highly sensitive to the underlying situations and conditions during the movement, which are known as contexts. Analyzing movement patterns, while accounting the contextual information, helps to better understand how point objects behave in various contexts and how contexts affect their trajectories. One potential solution for discovering moving objects patterns is analyzing the similarities of their trajectories. This article, therefore, contextualizes the similarity measure of trajectories by not only their spatial footprints but also a notion of internal and external contexts. The dynamic time warping (DTW) method is employed to assess the multi-dimensional similarities of trajectories. Then, the results of similarity searches are utilized in discovering the relative movement patterns of the moving point objects. Several experiments are conducted on real datasets that were obtained from commercial airplanes and the weather information during the flights. The results yielded the robustness of DTW method in quantifying the commonalities of trajectories and discovering movement patterns with 80 % accuracy. Moreover, the results revealed the importance of exploiting contextual information because it can enhance and restrict movements.

Quantifying urban river-aquifer fluid exchange processes: a multi-scale problem.

PubMed

Ellis, Paul A; Mackay, Rae; Rivett, Michael O

2007-04-01

Groundwater-river exchanges in an urban setting have been investigated through long term field monitoring and detailed modelling of a 7 km reach of the Tame river as it traverses the unconfined Triassic Sandstone aquifer that lies beneath the City of Birmingham, UK. Field investigations and numerical modelling have been completed at a range of spatial and temporal scales from the metre to the kilometre scale and from event (hourly) to multi-annual time scales. The objective has been to quantify the spatial and temporal flow distributions governing mixing processes at the aquifer-river interface that can affect the chemical activity in the hyporheic zone of this urbanised river. The hyporheic zone is defined to be the zone of physical mixing of river and aquifer water. The results highlight the multi-scale controls that govern the fluid exchange distributions that influence the thickness of the mixing zone between urban rivers and groundwater and the patterns of groundwater flow through the bed of the river. The morphologies of the urban river bed and the adjacent river bank sediments are found to be particularly influential in developing the mixing zone at the interface between river and groundwater. Pressure transients in the river are also found to exert an influence on velocity distribution in the bed material. Areas of significant mixing do not appear to be related to the areas of greatest groundwater discharge and therefore this relationship requires further investigation to quantify the actual remedial capacity of the physical hyporheic zone.

Geographical Gradients in Argentinean Terrestrial Mammal Species Richness and Their Environmental Correlates

PubMed Central

Márquez, Ana L.; Real, Raimundo; Kin, Marta S.; Guerrero, José Carlos; Galván, Betina; Barbosa, A. Márcia; Olivero, Jesús; Palomo, L. Javier; Vargas, J. Mario; Justo, Enrique

2012-01-01

We analysed the main geographical trends of terrestrial mammal species richness (SR) in Argentina, assessing how broad-scale environmental variation (defined by climatic and topographic variables) and the spatial form of the country (defined by spatial filters based on spatial eigenvector mapping (SEVM)) influence the kinds and the numbers of mammal species along these geographical trends. We also evaluated if there are pure geographical trends not accounted for by the environmental or spatial factors. The environmental variables and spatial filters that simultaneously correlated with the geographical variables and SR were considered potential causes of the geographic trends. We performed partial correlations between SR and the geographical variables, maintaining the selected explanatory variables statistically constant, to determine if SR was fully explained by them or if a significant residual geographic pattern remained. All groups and subgroups presented a latitudinal gradient not attributable to the spatial form of the country. Most of these trends were not explained by climate. We used a variation partitioning procedure to quantify the pure geographic trend (PGT) that remained unaccounted for. The PGT was larger for latitudinal than for longitudinal gradients. This suggests that historical or purely geographical causes may also be relevant drivers of these geographical gradients in mammal diversity. PMID:23028254

Monthly AOD maps combining strengths of remote sensing products

NASA Astrophysics Data System (ADS)

Kinne, Stefan

2010-05-01

The mid-visible aerosol optical depth (AOD) is the most prominent property to quantify aerosol amount the atmospheric column. Almost all aerosol retrievals of satellite sensors provide estimates for this property, however, often with limited success. As sensors differ in capabilities individual retrievals have local and regional strengths and weaknesses. Focusing on individual retrieval strengths a satellite based AOD composite has been constructed. Hereby, every retrieval performance has been assessed in statistical comparisons to ground-based sun-photometry, which provide highly accurate references though only at few globally distributed monitoring sites. Based on these comparisons, which consider bias as well as spatial patterns and seasonality, the regionally best performing satellite AOD products are combined. The resulting remote sensing AOD composite provide a general reference for the spatial and temporal AOD distribution on an (almost) global basis - solely tied to sensor data.

Solar Eclipse Effect on Shelter Air Temperature

NASA Technical Reports Server (NTRS)

Segal, M.; Turner, R. W.; Prusa, J.; Bitzer, R. J.; Finley, S. V.

1996-01-01

Decreases in shelter temperature during eclipse events were quantified on the basis of observations, numerical model simulations, and complementary conceptual evaluations. Observations for the annular eclipse on 10 May 1994 over the United States are presented, and these provide insights into the temporal and spatial changes in the shelter temperature. The observations indicated near-surface temperature drops of as much as 6 C. Numerical model simulations for this eclipse event, which provide a complementary evaluation of the spatial and temporal patterns of the temperature drops, predict similar decreases. Interrelationships between the temperature drop, degree of solar irradiance reduction, and timing of the peak eclipse are also evaluated for late spring, summer, and winter sun conditions. These simulations suggest that for total eclipses the drops in shelter temperature in midlatitudes can be as high as 7 C for a spring morning eclipse.

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

PubMed

Liao, Xiaohan; Xue, Cunjin; Su, Fenzhen

2017-01-01

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

Measuring landscape-scale spread and persistence of an invaded submerged plant community from airborne remote sensing.

PubMed

Santos, Maria J; Khanna, Shruti; Hestir, Erin L; Greenberg, Jonathan A; Ustin, Susan L

2016-09-01

Processes of spread and patterns of persistence of invasive species affect species and communities in the new environment. Predicting future rates of spread is of great interest for timely management decisions, but this depends on models that rely on understanding the processes of invasion and historic observations of spread and persistence. Unfortunately, the rates of spread and patterns of persistence are difficult to model or directly observe, especially when multiple rates of spread and diverse persistence patterns may be co-occurring over the geographic distribution of the invaded ecosystem. Remote sensing systematically acquires data over large areas at fine spatial and spectral resolutions over multiple time periods that can be used to quantify spread processes and persistence patterns. We used airborne imaging spectroscopy data acquired once a year for 5 years from 2004 to 2008 to map an invaded submerged aquatic vegetation (SAV) community across 2220 km 2 of waterways in the Sacramento-San Joaquin River Delta, California, USA, and measured its spread rate and its persistence. Submerged aquatic vegetation covered 13-23 km 2 of the waterways (6-11%) every year. Yearly new growth accounted for 40-60% of the SAV area, ~50% of which survived to following year. Spread rates were overall negative and persistence decreased with time. From this dataset, we were able to identify both radial and saltatorial spread of the invaded SAV in the entire extent of the Delta over time. With both decreasing spread rate and persistence, it is possible that over time the invasion of this SAV community could decrease its ecological impact. A landscape-scale approach allows measurements of all invasion fronts and the spatial anisotropies associated with spread processes and persistence patterns, without spatial interpolation, at locations both proximate and distant to the focus of invasion at multiple points in time. © 2016 by the Ecological Society of America.

Using multi-spectral imagery to detect and map stress induced by Russian wheat aphid

NASA Astrophysics Data System (ADS)

Backoulou, Georges Ferdinand

Scope and Method of Study. The rationale of this study was to assess the stress in wheat field induced by the Russian wheat aphid using multispectral imagery. The study was conducted to (a) determine the relationship between RWA and edaphic and topographic factors; (b) identify and quantify the spatial pattern of RWA infestation within wheat fields; (c) differentiate the stress induced by RWA from other stress causing factors. Data used for the analysis included RWA population density from the wheat field in, Texas, Colorado, Wyoming, and Nebraska, Digital Elevation Model from the Unites States Geological Survey (USGS), soil data from the Soil Survey Geographic database (SSURGO), and multispectral imagery acquired in the panhandle of Oklahoma. Findings and Conclusions. The study revealed that the population density of the Russian wheat aphid was related to topographic and edaphic factors. Slope and sand were predictor variables that were positively related to the density of RWA at the field level. The study has also demonstrated that stress induced by the RWA has a specific spatial pattern that can be distinguished from other stress causing factors using a combination of landscape metrics and topographic and edaphic characteristics of wheat fields. Further field-based studies using multispectral imagery and spatial pattern analysis are suggested. The suggestions require acquiring biweekly multispectral imagery and collecting RWA, topographic and edaphic data at the sampling points during the phonological growth development of wheat plants. This is an approach that may pretend to have great potential for site specific technique for the integrated pest management.

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

NASA Astrophysics Data System (ADS)

Babonis, Gregory Scott

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

Change In Course Pattern Of The Teesta River: After Effect Of An Engineering Project

NASA Astrophysics Data System (ADS)

Ashrafi, Z. M.; Shuvo, S. D.; Mahmud, M. S.

2016-12-01

Bangladesh is blessed by rivers that contribute to country's agriculture, landscape development and water supply. Due to nature of the river's flow and morphology, several engineering project have been initiated to enhance its utility, Teesta barrage was one of them. After two decades of its construction in Northern Bangladesh, several study identified major impacts on local ecosystem due to hindrance in water flow. However, how Teesta River evolved in last 25 years after the barrage construction, has not been quantified yet. This study quantifies the downstream evolution of Teesta River in after-construction period (1990-2015). Time series earth observation satellite (Landsat) data and geo-spatial techniques have been utilized to understand the changes in course pattern. Besides, sinuosity index has been used to quantify it. Analysis shows that the river is becoming more braided with the rise of numerous `Char' areas (islands); as well as bifurcation of the main channel, creating newer channels increasingly. Statistically significant changes in Sinuosity Index (SI) of the Teesta river has found in post construction period. In some locations SI increased which indicate that the river is becoming more and more winding than straight it used to be around 1990. It is also found that the river is shifting towards the east where the number of human settlement is higher. The rate of shifting has accelerated during the 2000s. There are places where the course has moved about 3 kilometers from its earlier course. Therefore, higher number of human settlements are in threat of river bank erosion in recent years. River bank management should be developed considering the pattern of course change so that rural settlement can save from destructive river bank erosion.

A simple force-motion relation for migrating cells revealed by multipole analysis of traction stress.

PubMed

Tanimoto, Hirokazu; Sano, Masaki

2014-01-07

For biophysical understanding of cell motility, the relationship between mechanical force and cell migration must be uncovered, but it remains elusive. Since cells migrate at small scale in dissipative circumstances, the inertia force is negligible and all forces should cancel out. This implies that one must quantify the spatial pattern of the force instead of just the summation to elucidate the force-motion relation. Here, we introduced multipole analysis to quantify the traction stress dynamics of migrating cells. We measured the traction stress of Dictyostelium discoideum cells and investigated the lowest two moments, the force dipole and quadrupole moments, which reflect rotational and front-rear asymmetries of the stress field. We derived a simple force-motion relation in which cells migrate along the force dipole axis with a direction determined by the force quadrupole. Furthermore, as a complementary approach, we also investigated fine structures in the stress field that show front-rear asymmetric kinetics consistent with the multipole analysis. The tight force-motion relation enables us to predict cell migration only from the traction stress patterns. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Stochastic Downscaling of Digital Elevation Models

NASA Astrophysics Data System (ADS)

Rasera, Luiz Gustavo; Mariethoz, Gregoire; Lane, Stuart N.

2016-04-01

High-resolution digital elevation models (HR-DEMs) are extremely important for the understanding of small-scale geomorphic processes in Alpine environments. In the last decade, remote sensing techniques have experienced a major technological evolution, enabling fast and precise acquisition of HR-DEMs. However, sensors designed to measure elevation data still feature different spatial resolution and coverage capabilities. Terrestrial altimetry allows the acquisition of HR-DEMs with centimeter to millimeter-level precision, but only within small spatial extents and often with dead ground problems. Conversely, satellite radiometric sensors are able to gather elevation measurements over large areas but with limited spatial resolution. In the present study, we propose an algorithm to downscale low-resolution satellite-based DEMs using topographic patterns extracted from HR-DEMs derived for example from ground-based and airborne altimetry. The method consists of a multiple-point geostatistical simulation technique able to generate high-resolution elevation data from low-resolution digital elevation models (LR-DEMs). Initially, two collocated DEMs with different spatial resolutions serve as an input to construct a database of topographic patterns, which is also used to infer the statistical relationships between the two scales. High-resolution elevation patterns are then retrieved from the database to downscale a LR-DEM through a stochastic simulation process. The output of the simulations are multiple equally probable DEMs with higher spatial resolution that also depict the large-scale geomorphic structures present in the original LR-DEM. As these multiple models reflect the uncertainty related to the downscaling, they can be employed to quantify the uncertainty of phenomena that are dependent on fine topography, such as catchment hydrological processes. The proposed methodology is illustrated for a case study in the Swiss Alps. A swissALTI3D HR-DEM (with 5 m resolution) and a SRTM-derived LR-DEM from the Western Alps are used to downscale a SRTM-based LR-DEM from the eastern part of the Alps. The results show that the method is capable of generating multiple high-resolution synthetic DEMs that reproduce the spatial structure and statistics of the original DEM.

Quantifying relief on alluvial fans using airborne lidar to reveal patterns of sediment accumulation

NASA Astrophysics Data System (ADS)

Morelan, A. E., III; Oskin, M. E.

2017-12-01

We present a method of quantifying detailed surface relief on alluvial fans from high-resolution topography. Average slope and curvature of the fan are used together to empirically derive an idealized, radially symmetric fan surface, from which we compute residual topography. Maps produced using this technique highlight spatial patterns of fan deposition and avulsion. Regions of high residual topography reveal active and abandoned sediment lobes accumulated from recent depositional events, often with well-defined channels at their apex. Preliminary observations suggest that surface relief is uniform across a collection of fans in a given region and source lithology. Alluvial fans with granitic catchment lithologies in eastern California (n=12), each with varying source catchment size and mean fan slope, all show relief of around 4 meters. A collection of fans from the Carrizo Plain in central California (n=12), with source catchments set within Miocene marine and nonmarine sedimentary rocks, show significantly lower relief values around 2 meters. We hypothesize that particle grain size determines this contrasting relief through its control on the thickness of fan-building debris flows. In both settings we find that sediment lobes tend to extend toward the fan toe. This pattern supports a process, observed in analog experiments, of fan deposition dominated by back-filling and overtopping of distributary channels by debris-flows.

Spatial organization and correlation properties quantify structural changes on mesoscale of parenchymatous plant tissue

NASA Astrophysics Data System (ADS)

Valous, N. A.; Delgado, A.; Drakakis, K.; Sun, D.-W.

2014-02-01

The study of plant tissue parenchyma's intercellular air spaces contributes to the understanding of anatomy and physiology. This is challenging due to difficulty in making direct measurements of the pore space and the complex mosaic of parenchymatous tissue. The architectural complexity of pore space has shown that single geometrical measurements are not sufficient for characterization. The inhomogeneity of distribution depends not only on the percentage content of phase, but also on how the phase fills the space. The lacunarity morphometric, as multiscale measure, provides information about the distribution of gaps that correspond to degree of spatial organization in parenchyma. Additionally, modern theories have suggested strategies, where the focus has shifted from the study of averages and histograms to the study of patterns in data fluctuations. Detrended fluctuation analysis provides information on the correlation properties of the parenchyma at different spatial scales. The aim is to quantify (with the aid of the aforementioned metrics), the mesostructural changes—that occur from one cycle of freezing and thawing—in the void phase of pome fruit parenchymatous tissue, acquired with X-ray microcomputed tomography. Complex systems methods provide numerical indices and detailed insights regarding the freezing-induced modifications upon the arrangement of cells and voids. These structural changes have the potential to lead to physiological disorders. The work can further stimulate interest for the analysis of internal plant tissue structures coupled with other physico-chemical processes or phenomena.

Elevational species shifts in a warmer climate are overestimated when based on weather station data.

PubMed

Scherrer, Daniel; Schmid, Samuel; Körner, Christian

2011-07-01

Strong topographic variation interacting with low stature alpine vegetation creates a multitude of micro-habitats poorly represented by common 2 m above the ground meteorological measurements (weather station data). However, the extent to which the actual habitat temperatures in alpine landscapes deviate from meteorological data at different spatial scales has rarely been quantified. In this study, we assessed thermal surface and soil conditions across topographically rich alpine landscapes by thermal imagery and miniature data loggers from regional (2-km(2)) to plot (1-m(2)) scale. The data were used to quantify the effects of spatial sampling resolution on current micro-habitat distributions and habitat loss due to climate warming scenarios. Soil temperatures showed substantial variation among slopes (2-3 K) dependent on slope exposure, within slopes (3-4 K) due to micro-topography and within 1-m(2) plots (1 K) as a result of plant cover effects. A reduction of spatial sampling resolution from 1 × 1 m to 100 × 100 m leads to an underestimation of current habitat diversity by 25% and predicts a six-times higher habitat loss in a 2-K warming scenario. Our results demonstrate that weather station data are unable to reflect the complex thermal patterns of aerodynamically decoupled alpine vegetation at the investigated scales. Thus, the use of interpolated weather station data to describe alpine life conditions without considering the micro-topographically induced thermal mosaic might lead to misinterpretation and inaccurate prediction.

Fourier analysis of mitochondrial distribution in oocytes

NASA Astrophysics Data System (ADS)

Hollmann, Joseph L.; Brooks, Dana H.; Newmark, Judith A.; Warner, Carol M.; DiMarzio, Charles A.

2011-03-01

This paper describes a novel approach to quantifying mitochondrial patterns which are typically described using the qualitative terms "diffuse" "aggregated" and are potentially key indicators for an oocyte's health and survival potential post-implantation. An oocyte was isolated in a confocal image and a coarse grid was superimposed upon it. The spatial spectrum was calculated and an aggregation factor was generated. A classifier for healthy cells was developed and verified. The aggregation factor showed a clear distinction between the healthy and unhealthy oocytes. The ultimate goal is to screen oocytes for viability preimplantation, thus improving the outcome of in vitro fertilization (IVF) treatments.

Dynamics of primary and secondary microbubbles created by laser-induced breakdown of an optically trapped nanoparticle

PubMed Central

Arita, Y.; Antkowiak, M.; Venugopalan, V.; Gunn-Moore, F. J.; Dholakia, K.

2012-01-01

Laser-induced breakdown of an optically trapped nanoparticle is a unique system for studying cavitation dynamics. It offers additional degrees of freedom, namely the nanoparticle material, its size, and the relative position between the laser focus and the center of the optically trapped nanoparticle. We quantify the spatial and temporal dynamics of the cavitation and secondary bubbles created in this system and use hydrodynamic modeling to quantify the observed dynamic shear stress of the expanding bubble. In the final stage of bubble collapse, we visualize the formation of multiple submicrometer secondary bubbles around the toroidal bubble on the substrate. We show that the pattern of the secondary bubbles typically has its circular symmetry broken along an axis whose unique angle rotates over time. This is a result of vorticity along the jet towards the boundary upon bubble collapse near solid boundaries. PMID:22400669

Quantifying the sensitivity of post-glacial sea level change to laterally varying viscosity

NASA Astrophysics Data System (ADS)

Crawford, Ophelia; Al-Attar, David; Tromp, Jeroen; Mitrovica, Jerry X.; Austermann, Jacqueline; Lau, Harriet C. P.

2018-05-01

We present a method for calculating the derivatives of measurements of glacial isostatic adjustment (GIA) with respect to the viscosity structure of the Earth and the ice sheet history. These derivatives, or kernels, quantify the linearised sensitivity of measurements to the underlying model parameters. The adjoint method is used to enable efficient calculation of theoretically exact sensitivity kernels within laterally heterogeneous earth models that can have a range of linear or non-linear viscoelastic rheologies. We first present a new approach to calculate GIA in the time domain, which, in contrast to the more usual formulation in the Laplace domain, is well suited to continuously varying earth models and to the use of the adjoint method. Benchmarking results show excellent agreement between our formulation and previous methods. We illustrate the potential applications of the kernels calculated in this way through a range of numerical calculations relative to a spherically symmetric background model. The complex spatial patterns of the sensitivities are not intuitive, and this is the first time that such effects are quantified in an efficient and accurate manner.

Spatial pattern characteristics of water footprint for maize production in Northeast China.

PubMed

Duan, Peili; Qin, Lijie; Wang, Yeqiao; He, Hongshi

2016-01-30

Water footprint (WF) methodology is essential for quantifying total water consumption of crop production and making efficient water management policies. This study calculated the green, blue, grey and total WFs of maize production in Northeast China from 1998 to 2012 and compared the values of the provinces. This study also analyzed the spatial variation and structure characteristics of the WFs at the prefecture level. The annual average WF of maize production was 1029 m(3) per ton, which was 51% green, 21% blue and 28% grey. The WF of maize production was highest in Liaoning Province, moderate in Heilongjiang Province and lowest in Jilin Province. The spatial differences of the WFs calculated for the 36 major maize production prefectures were significant in Northeast China. There was a moderate positive spatial autocorrelation among prefectures that had similar WFs. Local indicator of spatial autocorrelation index (LISA) analysis identified prefectures with higher WFs in the southeast region of Liaoning Province and the southwest region of Heilongjiang Province and prefectures with lower WFs in the middle of Jilin Province. Spatial differences in the WF of maize production were caused mainly by variations in climate conditions, soil quality, irrigation facilities and maize yield. The spatial distribution of WFs can help provide a scientific basis for optimizing maize production distribution and then formulate strategies to reduce the WF of maize production. © 2015 Society of Chemical Industry.

Asynchronous vegetation phenology enhances winter body condition of a large mobile herbivore.

PubMed

Searle, Kate R; Rice, Mindy B; Anderson, Charles R; Bishop, Chad; Hobbs, N T

2015-10-01

Understanding how spatial and temporal heterogeneity influence ecological processes forms a central challenge in ecology. Individual responses to heterogeneity shape population dynamics, therefore understanding these responses is central to sustainable population management. Emerging evidence has shown that herbivores track heterogeneity in nutritional quality of vegetation by responding to phenological differences in plants. We quantified the benefits mule deer (Odocoileus hemionus) accrue from accessing habitats with asynchronous plant phenology in northwest Colorado over 3 years. Our analysis examined both the direct physiological and indirect environmental effects of weather and vegetation phenology on mule deer winter body condition. We identified several important effects of annual weather patterns and topographical variables on vegetation phenology in the home ranges of mule deer. Crucially, temporal patterns of vegetation phenology were linked with differences in body condition, with deer tending to show poorer body condition in areas with less asynchronous vegetation green-up and later vegetation onset. The direct physiological effect of previous winter precipitation on mule deer body condition was much less important than the indirect effect mediated by vegetation phenology. Additionally, the influence of vegetation phenology on body fat was much stronger than that of overall vegetation productivity. In summary, changing annual weather patterns, particularly in relation to seasonal precipitation, have the potential to alter body condition of this important ungulate species during the critical winter period. This finding highlights the importance of maintaining large contiguous areas of spatially and temporally variable resources to allow animals to compensate behaviourally for changing climate-driven resource patterns.

Mentoring Temporal and Spatial Variations in Rainfall across Wadi Ar-Rumah, Saudi Arabia

NASA Astrophysics Data System (ADS)

Alharbi, T.; Ahmed, M.

2015-12-01

Across the Kingdom of Saudi Arabia (KSA), the fresh water resources are limited only to those found in aquifer systems. Those aquifers were believed to be recharged during the previous wet climatic period but still receiving modest local recharge in interleaving dry periods such as those prevailing at present. Quantifying temporal and spatial variabilities in rainfall patterns, magnitudes, durations, and frequencies is of prime importance when it comes to sustainable management of such aquifer systems. In this study, an integrated approach, using remote sensing and field data, was used to assess the past, the current, and the projected spatial and temporal variations in rainfall over one of the major watersheds in KSA, Wadi Ar-Rumah. This watershed was selected given its larger areal extent and population intensity. Rainfall data were extracted from (1) the Climate Prediction Centers (CPC) Merged Analysis of Precipitation (CMAP; spatial coverage: global; spatial resolution: 2.5° × 2.5°; temporal coverage: January 1979 to April 2015; temporal resolution: monthly), and (2) the Tropical Rainfall Measuring Mission (TRMM; spatial coverage: 50°N to 50°S; spatial resolution: 0.25° × 0.25°; temporal coverage: January 1998 to March 2015; temporal resolution: 3 hours) and calibrated against rainfall measurements extracted from rain gauges. Trends in rainfall patterns were examined over four main investigation periods: period I (01/1979 to 12/1985), period II (01/1986 to 12/1992), period III (01/1993 to 12/2002), and period IV (01/2003 to 12/2014). Our findings indicate: (1) a significant increase (+14.19 mm/yr) in rainfall rates were observed during period I, (2) a significant decrease in rainfall rates were observed during periods II (-5.80 mm/yr), III (-9.38 mm/yr), and IV (-2.46 mm/yr), and (3) the observed variations in rainfall rates are largely related to the temporal variations in the northerlies (also called northwesterlies) and the monsoonal wind regimes.

Spatial prediction of near surface soil water retention functions using hydrogeophysics and empirical orthogonal functions

NASA Astrophysics Data System (ADS)

Gibson, Justin; Franz, Trenton E.

2018-06-01

The hydrological community often turns to widely available spatial datasets such as the NRCS Soil Survey Geographic database (SSURGO) to characterize the spatial variability of soil properties. When used to spatially characterize and parameterize watershed models, this has served as a reasonable first approximation when lacking localized or incomplete soil data. Within agriculture, soil data has been left relatively coarse when compared to numerous other data sources measured. This is because localized soil sampling is both expensive and time intense, thus a need exists in better connecting spatial datasets with ground observations. Given that hydrogeophysics is data-dense, rapid, non-invasive, and relatively easy to adopt, it is a promising technique to help dovetail localized soil sampling with spatially exhaustive datasets. In this work, we utilize two common near surface geophysical methods, cosmic-ray neutron probe and electromagnetic induction, to identify temporally stable spatial patterns of measured geophysical properties in three 65 ha agricultural fields in western Nebraska. This is achieved by repeat geophysical observations of the same study area across a range of wet to dry field conditions in order to evaluate with an empirical orthogonal function. Shallow cores were then extracted within each identified zone and water retention functions were generated in the laboratory. Using EOF patterns as a covariate, we quantify the predictive skill of estimating soil hydraulic properties in areas without measurement using a bootstrap validation analysis. Results indicate that sampling locations informed via repeat hydrogeophysical surveys, required only five cores to reduce the cross-validation root mean squared error by an average of 64% as compared to soil parameters predicted by a commonly used benchmark, SSURGO and ROSETTA. The reduction to five strategically located samples within the 65 ha fields reduces sampling efforts by up to ∼90% as compared to the common practice of soil grid sampling every 1 ha.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Innovating Big Data Computing Geoprocessing for Analysis of Engineered-Natural Systems

NASA Astrophysics Data System (ADS)

Rose, K.; Baker, V.; Bauer, J. R.; Vasylkivska, V.

2016-12-01

Big data computing and analytical techniques offer opportunities to improve predictions about subsurface systems while quantifying and characterizing associated uncertainties from these analyses. Spatial analysis, big data and otherwise, of subsurface natural and engineered systems are based on variable resolution, discontinuous, and often point-driven data to represent continuous phenomena. We will present examples from two spatio-temporal methods that have been adapted for use with big datasets and big data geo-processing capabilities. The first approach uses regional earthquake data to evaluate spatio-temporal trends associated with natural and induced seismicity. The second algorithm, the Variable Grid Method (VGM), is a flexible approach that presents spatial trends and patterns, such as those resulting from interpolation methods, while simultaneously visualizing and quantifying uncertainty in the underlying spatial datasets. In this presentation we will show how we are utilizing Hadoop to store and perform spatial analyses to efficiently consume and utilize large geospatial data in these custom analytical algorithms through the development of custom Spark and MapReduce applications that incorporate ESRI Hadoop libraries. The team will present custom `Big Data' geospatial applications that run on the Hadoop cluster and integrate with ESRI ArcMap with the team's probabilistic VGM approach. The VGM-Hadoop tool has been specially built as a multi-step MapReduce application running on the Hadoop cluster for the purpose of data reduction. This reduction is accomplished by generating multi-resolution, non-overlapping, attributed topology that is then further processed using ESRI's geostatistical analyst to convey a probabilistic model of a chosen study region. Finally, we will share our approach for implementation of data reduction and topology generation via custom multi-step Hadoop applications, performance benchmarking comparisons, and Hadoop-centric opportunities for greater parallelization of geospatial operations.

Fire Impacts on Mixed Pine-oak Forests Assessed with High Spatial Resolution Imagery, Imaging Spectroscopy, and LiDAR

NASA Astrophysics Data System (ADS)

Meng, R.; Wu, J.; Zhao, F. R.; Kathy, S. L.; Dennison, P. E.; Cook, B.; Hanavan, R. P.; Serbin, S.

2016-12-01

As a primary disturbance agent, fire significantly influences forest ecosystems, including the modification or resetting of vegetation composition and structure, which can then significantly impact landscape-scale plant function and carbon stocks. Most ecological processes associated with fire effects (e.g. tree damage, mortality, and vegetation recovery) display fine-scale, species specific responses but can also vary spatially within the boundary of the perturbation. For example, both oak and pine species are fire-adapted, but fire can still induce changes in composition, structure, and dominance in a mixed pine-oak forest, mainly because of their varying degrees of fire adaption. Evidence of post-fire shifts in dominance between oak and pine species has been documented in mixed pine-oak forests, but these processes have been poorly investigated in a spatially explicit manner. In addition, traditional field-based means of quantifying the response of partially damaged trees across space and time is logistically challenging. Here we show how combining high resolution satellite imagery (i.e. Worldview-2,WV-2) and airborne imaging spectroscopy and LiDAR (i.e. NASA Goddard's Lidar, Hyperspectral and Thermal airborne imager, G-LiHT) can be effectively used to remotely quantify spatial and temporal patterns of vegetation recovery following a top-killing fire that occurred in 2012 within mixed pine-oak forests in the Long Island Central Pine Barrens Region, New York. We explore the following questions: 1) what are the impacts of fire on species composition, dominance, plant health, and vertical structure; 2) what are the recovery trajectories of forest biomass, structure, and spectral properties for three years following the fire; and 3) to what extent can fire impacts be captured and characterized by multi-sensor remote sensing techniques from active and passive optical remote sensing.

Quantifying rates of cell migration and cell proliferation in co-culture barrier assays reveals how skin and melanoma cells interact during melanoma spreading and invasion.

PubMed

Haridas, Parvathi; Penington, Catherine J; McGovern, Jacqui A; McElwain, D L Sean; Simpson, Matthew J

2017-06-21

Malignant spreading involves the migration of cancer cells amongst other native cell types. For example, in vivo melanoma invasion involves individual melanoma cells migrating through native skin, which is composed of several distinct subpopulations of cells. Here, we aim to quantify how interactions between melanoma and fibroblast cells affect the collective spreading of a heterogeneous population of these cells in vitro. We perform a suite of circular barrier assays that includes: (i) monoculture assays with fibroblast cells; (ii) monoculture assays with SK-MEL-28 melanoma cells; and (iii) a series of co-culture assays initiated with three different ratios of SK-MEL-28 melanoma cells and fibroblast cells. Using immunostaining, detailed cell density histograms are constructed to illustrate how the two subpopulations of cells are spatially arranged within the spreading heterogeneous population. Calibrating the solution of a continuum partial differential equation to the experimental results from the monoculture assays allows us to estimate the cell diffusivity and the cell proliferation rate for the melanoma and the fibroblast cells, separately. Using the parameter estimates from the monoculture assays, we then make a prediction of the spatial spreading in the co-culture assays. Results show that the parameter estimates obtained from the monoculture assays lead to a reasonably accurate prediction of the spatial arrangement of the two subpopulations in the co-culture assays. Overall, the spatial pattern of spreading of the melanoma cells and the fibroblast cells is very similar in monoculture and co-culture conditions. Therefore, we find no clear evidence of any interactions other than cell-to-cell contact and crowding effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

Epidemiological Characteristics and Space-Time Analysis of the 2015 Dengue Outbreak in the Metropolitan Region of Tainan City, Taiwan

PubMed Central

Ng, Ka-Chon; Nguyen, Thi Luong

2018-01-01

The metropolitan region of Tainan City in southern Taiwan experienced a dengue outbreak in 2015. This manuscript describes basic epidemiological features of this outbreak and uses spatial and temporal analysis tools to understand the spread of dengue during the outbreak. The analysis found that, independently of gender, dengue incidence rate increased with age, and proportionally affected more males below the age of 40 years but females above the age of 40 years. A spatial scan statistic was applied to detect clusters of disease transmission. The scan statistic found that dengue spread in a north-south diffusion direction, which is across the North, West-Central and South districts of Tainan City. Spatial regression models were used to quantify factors associated with transmission. This analysis indicated that neighborhoods with high proportions of residential area (or low wetland cover) were associated with dengue transmission. However, these association patterns were non-linear. The findings presented here can help Taiwanese public health agencies to understand the fundamental epidemiological characteristics and diffusion patterns of the 2015 dengue outbreak in Tainan City. This type of information is fundamental for policy making to prevent future uncontrolled dengue outbreaks, given that results from this study suggest that control interventions should be emphasized in the North and West-Central districts of Tainan city, in areas with a moderate percentage of residential land cover. PMID:29495351

Dispersal kernels and their drivers captured with a hydrodynamic model and spatial indices: A case study on anchovy ( Engraulis encrasicolus) early life stages in the Bay of Biscay

NASA Astrophysics Data System (ADS)

Huret, M.; Petitgas, P.; Woillez, M.

2010-10-01

Dispersal of fish early life stages explains part of the recruitment success, through interannual variability in spawning, transport and survival. Dispersal results from a complex interaction between physical and biological processes acting at different temporal and spatial scales, and at the individual or population level. In this paper we quantify the response of anchovy egg and larval dispersal in the Bay of Biscay to the following sources of variability: vertical larval behaviour, drift duration, adult spawning location and timing, and spatio-temporal variability in the hydrodynamics. We use simulations of Lagrangian trajectories in a 3-dimensional hydrodynamic model, as well as spatial indices describing different properties of the dispersal kernel: the mean transport (distance, direction), its variance, occupation of space by particles and their aggregation. We show that larval drift duration has a major impact on the dispersion at scales of ˜100 km, but that vertical behaviour becomes dominant reducing dispersion at scales of ˜1-10 km. Spawning location plays a major role in explaining connectivity patterns, in conjunction with spawning temporal variability. Interannual variability in the circulation dominates over seasonal variability. However, seasonal patterns become predominant for coastal spawning locations, revealing a recurrent shift in the direction of dispersal during the anchovy spawning season.

Epidemiological Characteristics and Space-Time Analysis of the 2015 Dengue Outbreak in the Metropolitan Region of Tainan City, Taiwan.

PubMed

Chuang, Ting-Wu; Ng, Ka-Chon; Nguyen, Thi Luong; Chaves, Luis Fernando

2018-02-26

The metropolitan region of Tainan City in southern Taiwan experienced a dengue outbreak in 2015. This manuscript describes basic epidemiological features of this outbreak and uses spatial and temporal analysis tools to understand the spread of dengue during the outbreak. The analysis found that, independently of gender, dengue incidence rate increased with age, and proportionally affected more males below the age of 40 years but females above the age of 40 years. A spatial scan statistic was applied to detect clusters of disease transmission. The scan statistic found that dengue spread in a north-south diffusion direction, which is across the North, West-Central and South districts of Tainan City. Spatial regression models were used to quantify factors associated with transmission. This analysis indicated that neighborhoods with high proportions of residential area (or low wetland cover) were associated with dengue transmission. However, these association patterns were non-linear. The findings presented here can help Taiwanese public health agencies to understand the fundamental epidemiological characteristics and diffusion patterns of the 2015 dengue outbreak in Tainan City. This type of information is fundamental for policy making to prevent future uncontrolled dengue outbreaks, given that results from this study suggest that control interventions should be emphasized in the North and West-Central districts of Tainan city, in areas with a moderate percentage of residential land cover.

Quantifying the effect of crop spatial arrangement on weed suppression using functional-structural plant modelling.

PubMed

Evers, Jochem B; Bastiaans, Lammert

2016-05-01

Suppression of weed growth in a crop canopy can be enhanced by improving crop competitiveness. One way to achieve this is by modifying the crop planting pattern. In this study, we addressed the question to what extent a uniform planting pattern increases the ability of a crop to compete with weed plants for light compared to a random and a row planting pattern, and how this ability relates to crop and weed plant density as well as the relative time of emergence of the weed. To this end, we adopted the functional-structural plant modelling approach which allowed us to explicitly include the 3D spatial configuration of the crop-weed canopy and to simulate intra- and interspecific competition between individual plants for light. Based on results of simulated leaf area development, canopy photosynthesis and biomass growth of the crop, we conclude that differences between planting pattern were small, particularly if compared to the effects of relative time of emergence of the weed, weed density and crop density. Nevertheless, analysis of simulated weed biomass demonstrated that a uniform planting of the crop improved the weed-suppression ability of the crop canopy. Differences in weed suppressiveness between planting patterns were largest with weed emergence before crop emergence, when the suppressive effect of the crop was only marginal. With simultaneous emergence a uniform planting pattern was 8 and 15 % more competitive than a row and a random planting pattern, respectively. When weed emergence occurred after crop emergence, differences between crop planting patterns further decreased as crop canopy closure was reached early on regardless of planting pattern. We furthermore conclude that our modelling approach provides promising avenues to further explore crop-weed interactions and aid in the design of crop management strategies that aim at improving crop competitiveness with weeds.

Committed climate change due to historical land use and management: the concept

NASA Astrophysics Data System (ADS)

Freibauer, Annette; Dolman, Han; Don, Axel; Poeplau, Christopher

2013-04-01

A significant fraction of the European land surface has changed its land use over the last 50 years. Management practices have changed in the same period in most land use systems. These changes have affected the carbon and greenhouse gas (GHG) balance of the European land surface. Land use intensity, defined here loosely as the degree to which humans interfere with the land, strongly affects GHG emissions. Land use and land management changes suggest that the variability of the carbon balance and of GHG emissions of cultivated land areas in Europe is much more driven by land use history and management than driven by climate. Importantly changes in land use and its management have implications for future GHG emissions, and therefore present a committed climate change, defined as inevitable future additional climate change induced by past human activity. It is one of the key goals of the large-scale integrating research project "GHG-Europe - Greenhouse gas management in European land use systems" to quantify the committed climate change due to legacy effects by land use and management. The project is funded by the European Commission in the 7th framework programme (Grant agreement no.: 244122). This poster will present the conceptual approach taken to reach this goal. (1) First of all we need to proof that at site, or regional level the management effects are larger than climate effects on carbon balance and GHG emissions. Observations from managed sites and regions will serve as empirical basis. Attribution experiments with models based on process understanding are run on managed sites and regions will serve to demonstrate that the observed patterns of the carbon balance and GHG emissions can only be reproduced when land use and management are included as drivers. (2) The legacy of land use changes will be quantified by combining spatially explicit time series of land use changes with response functions of carbon pools. This will allow to separate short-term and long-term effects of land-use changes, to quantify how much current changes in biomass and soil carbon are driven by past land use change and how much future changes in biomass and soil carbon have already been committed by past and present land use changes. (3) The legacy of land management changes will be quantified by combining spatially explicit time series of land management activities with response functions and relatively simple models of carbon pools and greenhouse gases. This will allow to detect major trends and spatial patterns in carbon and GHG fluxes driven by intensification or extensification over the last decades. The poster will concentrate on background, concept of the legacy analysis, data sources and the scientific strategy for deriving the climate change committed by past and present land use and management in Europe.

Fractal analysis of urban catchments and their representation in semi-distributed models: imperviousness and sewer system

NASA Astrophysics Data System (ADS)

Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Ochoa-Rodriguez, Susana; Willems, Patrick; Ichiba, Abdellah; Wang, Lipen; Pina, Rui; Van Assel, Johan; Bruni, Guendalina; Murla Tuyls, Damian; ten Veldhuis, Marie-Claire

2017-04-01

Land use distribution and sewer system geometry exhibit complex scale dependent patterns in urban environment. This scale dependency is even more visible in a rasterized representation where only a unique class is affected to each pixel. Such features are well grasped with fractal tools, which are based scale invariance and intrinsically designed to characterise and quantify the space filled by a geometrical set exhibiting complex and tortuous patterns. Fractal tools have been widely used in hydrology but seldom in the specific context of urban hydrology. In this paper, they are used to analyse surface and sewer data from 10 urban or peri-urban catchments located in 5 European countries in the framework of the NWE Interreg RainGain project (www.raingain.eu). The aim was to characterise urban catchment properties accounting for the complexity and inhomogeneity typical of urban water systems. Sewer system density and imperviousness (roads or buildings), represented in rasterized maps of 2 m x 2 m pixels, were analysed to quantify their fractal dimension, characteristic of scaling invariance. It appears that both sewer density and imperviousness exhibit scale invariant features that can be characterized with the help of fractal dimensions ranging from 1.6 to 2, depending on the catchment. In a given area, consistent results were found for the two geometrical features, yielding a robust and innovative way of quantifying the level of urbanization. The representation of imperviousness in operational semi-distributed hydrological models for these catchments was also investigated by computing fractal dimensions of the geometrical sets made up of the sub-catchments with coefficients of imperviousness greater than a range of thresholds. It enables to quantify how well spatial structures of imperviousness are represented in the urban hydrological models.

Quantifying drivers of wild pig movement across multiple spatial and temporal scales.

PubMed

Kay, Shannon L; Fischer, Justin W; Monaghan, Andrew J; Beasley, James C; Boughton, Raoul; Campbell, Tyler A; Cooper, Susan M; Ditchkoff, Stephen S; Hartley, Steve B; Kilgo, John C; Wisely, Samantha M; Wyckoff, A Christy; VerCauteren, Kurt C; Pepin, Kim M

2017-01-01

The movement behavior of an animal is determined by extrinsic and intrinsic factors that operate at multiple spatio-temporal scales, yet much of our knowledge of animal movement comes from studies that examine only one or two scales concurrently. Understanding the drivers of animal movement across multiple scales is crucial for understanding the fundamentals of movement ecology, predicting changes in distribution, describing disease dynamics, and identifying efficient methods of wildlife conservation and management. We obtained over 400,000 GPS locations of wild pigs from 13 different studies spanning six states in southern U.S.A., and quantified movement rates and home range size within a single analytical framework. We used a generalized additive mixed model framework to quantify the effects of five broad predictor categories on movement: individual-level attributes, geographic factors, landscape attributes, meteorological conditions, and temporal variables. We examined effects of predictors across three temporal scales: daily, monthly, and using all data during the study period. We considered both local environmental factors such as daily weather data and distance to various resources on the landscape, as well as factors acting at a broader spatial scale such as ecoregion and season. We found meteorological variables (temperature and pressure), landscape features (distance to water sources), a broad-scale geographic factor (ecoregion), and individual-level characteristics (sex-age class), drove wild pig movement across all scales, but both the magnitude and shape of covariate relationships to movement differed across temporal scales. The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc ) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Migration phenology and seasonal fidelity of an Arctic marine predator in relation to sea ice dynamics.

PubMed

Cherry, Seth G; Derocher, Andrew E; Thiemann, Gregory W; Lunn, Nicholas J

2013-07-01

Understanding how seasonal environmental conditions affect the timing and distribution of synchronized animal movement patterns is a central issue in animal ecology. Migration, a behavioural adaptation to seasonal environmental fluctuations, is a fundamental part of the life history of numerous species. However, global climate change can alter the spatiotemporal distribution of resources and thus affect the seasonal movement patterns of migratory animals. We examined sea ice dynamics relative to migration patterns and seasonal geographical fidelity of an Arctic marine predator, the polar bear (Ursus maritimus). Polar bear movement patterns were quantified using satellite-linked telemetry data collected from collars deployed between 1991-1997 and 2004-2009. We showed that specific sea ice characteristics can predict the timing of seasonal polar bear migration on and off terrestrial refugia. In addition, fidelity to specific onshore regions during the ice-free period was predicted by the spatial pattern of sea ice break-up but not by the timing of break-up. The timing of migration showed a trend towards earlier arrival of polar bears on shore and later departure from land, which has been driven by climate-induced declines in the availability of sea ice. Changes to the timing of migration have resulted in polar bears spending progressively longer periods of time on land without access to sea ice and their marine mammal prey. The links between increased atmospheric temperatures, sea ice dynamics, and the migratory behaviour of an ice-dependent species emphasizes the importance of quantifying and monitoring relationships between migratory wildlife and environmental cues that may be altered by climate change. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

Using Airborne LIDAR Data to Determine Old vs. Young Cottonwood Trees in the Riparian Corridor of the San Pedro River

NASA Astrophysics Data System (ADS)

Farid, A.; Goodrich, D.; Sartori, M.; Sorooshian, S.

2003-12-01

Quantification of vegetation patterns and properties is needed to determine their role in the landscape and to develop management plans to conserve natural resources. Vegetation patterns can be mapped from the ground, or by using aerial photography or satellite imagery. However, quantifying the physical properties of vegetation patterns with ground-based or remote sensing technology is difficult, time consuming, and often costly. Digital data from an airborne lidar (light detecting and ranging) instrument offers an alternative method for quantifying vegetation properties and patterns. Using lidar, a study was conducted in the San Pedro National Riparian Conservation Area in an attempt to differentiate young and old Cottonwood trees in southeastern Arizona as young and old cottonwoods have significantly different water use per unit area of canopy. The lidar data was acquired in June 2003, using Optech's ALTM (Airborne Laser Terrain Mapper), during flyovers conducted at an altitude of 750 m. It has been demonstrated that the height of old and young cottonwood canopies can be measured by using lidar. Canopy heights measured with the lidar show a good degree of correlation with ground-based measurements. Methodologically, the first step required is to differentiate old from young cottonwood canopies by the differences in canopy height obtained from lidar data. In addition to vegetation heights, spatial patterns of crown area, canopy cover, and intensity of return laser pulse are measured for both old and young cottonwood trees with the lidar data. The second stage of this study demonstrates that these other parameters of old and young cottonwood trees, when extrapolated from lidar, are significantly different. This study indicates the potential of airborne lidar data to distinguish between different ages of cottonwood forest canopy for large areas quickly and quantitatively.

Recognize PM2.5 sources and emission patterns via high-density sensor network: An application case in Beijing

NASA Astrophysics Data System (ADS)

Ba, Yu tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Zhang, Da wei; Yin, Wen jun

2017-04-01

Beijing suffered severe air pollution during wintertime, 2016, with the unprecedented high level pollutants monitored. As the most dominant pollutant, fine particulate matter (PM2.5) was measured via high-density sensor network (>1000 fixed monitors across 16000 km2 area). This campaign provided precise observations (spatial resolution ≈ 3 km, temporal resolution = 10 min, error of measure < 5 ug/m3) to track potential emission sources. In addition, these observations coupled with WRF-Chem model (Weather Research and Forecasting model coupled with Chemistry) were analyzed to elucidate the effects of atmospheric transportations across regions, both horizontal and vertical, on emission patterns during this haze period. The results quantified the main cause of regional transport and local emission, and highlighted the importance of cross-region cooperation in anti-pollution campaigns.

Mapping of Mechanical Strains and Stresses around Quiescent Engineered Three-Dimensional Epithelial Tissues

PubMed Central

Gjorevski, Nikolce; Nelson, Celeste M.

2012-01-01

Understanding how physical signals guide biological processes requires qualitative and quantitative knowledge of the mechanical forces generated and sensed by cells in a physiologically realistic three-dimensional (3D) context. Here, we used computational modeling and engineered epithelial tissues of precise geometry to define the experimental parameters that are required to measure directly the mechanical stress profile of 3D tissues embedded within native type I collagen. We found that to calculate the stresses accurately in these settings, we had to account for mechanical heterogeneities within the matrix, which we visualized and quantified using confocal reflectance and atomic force microscopy. Using this technique, we were able to obtain traction forces at the epithelium-matrix interface, and to resolve and quantify patterns of mechanical stress throughout the surrounding matrix. We discovered that whereas single cells generate tension by contracting and pulling on the matrix, the contraction of multicellular tissues can also push against the matrix, causing emergent compression. Furthermore, tissue geometry defines the spatial distribution of mechanical stress across the epithelium, which communicates mechanically over distances spanning hundreds of micrometers. Spatially resolved mechanical maps can provide insight into the types and magnitudes of physical parameters that are sensed and interpreted by multicellular tissues during normal and pathological processes. PMID:22828342

Nucleon localization and fragment formation in nuclear fission

DOE PAGES

Zhang, C. L.; Schuetrumpf, B.; Nazarewicz, W.

2016-12-27

An electron localization measure was originally introduced to characterize chemical bond structures in molecules. Recently, a nucleon localization based on Hartree-Fock densities has been introduced to investigate α-cluster structures in light nuclei. Compared to the local nucleonic densities, the nucleon localization function has been shown to be an excellent indicator of shell effects and cluster correlations. In this work, using the spatial nucleon localization measure, we investigated the emergence of fragments in fissioning heavy nuclei using the self-consistent energy density functional method with a quantified energy density functional optimized for fission studies. We studied the particle densities and spatial nucleonmore » localization distributions along the fission pathways of 264Fm, 232Th, and 240Pu. We demonstrated that the fission fragments were formed fairly early in the evolution, well before scission. To illustrate the usefulness of the localization measure, we showed how the hyperdeformed state of 232Th could be understood in terms of a quasimolecular state made of 132Sn and 100Zr fragments. Compared to nucleonic distributions, the nucleon localization function more effectively quantifies nucleonic clustering: its characteristic oscillating pattern, traced back to shell effects, is a clear fingerprint of cluster/fragment configurations. This is of particular interest for studies of fragment formation and fragment identification in fissioning nuclei.« less

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

Zhang, C. L.; Schuetrumpf, B.; Nazarewicz, W.

An electron localization measure was originally introduced to characterize chemical bond structures in molecules. Recently, a nucleon localization based on Hartree-Fock densities has been introduced to investigate α-cluster structures in light nuclei. Compared to the local nucleonic densities, the nucleon localization function has been shown to be an excellent indicator of shell effects and cluster correlations. In this work, using the spatial nucleon localization measure, we investigated the emergence of fragments in fissioning heavy nuclei using the self-consistent energy density functional method with a quantified energy density functional optimized for fission studies. We studied the particle densities and spatial nucleonmore » localization distributions along the fission pathways of 264Fm, 232Th, and 240Pu. We demonstrated that the fission fragments were formed fairly early in the evolution, well before scission. To illustrate the usefulness of the localization measure, we showed how the hyperdeformed state of 232Th could be understood in terms of a quasimolecular state made of 132Sn and 100Zr fragments. Compared to nucleonic distributions, the nucleon localization function more effectively quantifies nucleonic clustering: its characteristic oscillating pattern, traced back to shell effects, is a clear fingerprint of cluster/fragment configurations. This is of particular interest for studies of fragment formation and fragment identification in fissioning nuclei.« less

Temporal and spatial variation in allocating annual traffic activity across an urban region and implications for air quality assessments

PubMed Central

Batterman, Stuart

2015-01-01

Patterns of traffic activity, including changes in the volume and speed of vehicles, vary over time and across urban areas and can substantially affect vehicle emissions of air pollutants. Time-resolved activity at the street scale typically is derived using temporal allocation factors (TAFs) that allow the development of emissions inventories needed to predict concentrations of traffic-related air pollutants. This study examines the spatial and temporal variation of TAFs, and characterizes prediction errors resulting from their use. Methods are presented to estimate TAFs and their spatial and temporal variability and used to analyze total, commercial and non-commercial traffic in the Detroit, Michigan, U.S. metropolitan area. The variability of total volume estimates, quantified by the coefficient of variation (COV) representing the percentage departure from expected hourly volume, was 21, 33, 24 and 33% for weekdays, Saturdays, Sundays and holidays, respectively. Prediction errors mostly resulted from hour-to-hour variability on weekdays and Saturdays, and from day-to-day variability on Sundays and holidays. Spatial variability was limited across the study roads, most of which were large freeways. Commercial traffic had different temporal patterns and greater variability than noncommercial vehicle traffic, e.g., the weekday variability of hourly commercial volume was 28%. The results indicate that TAFs for a metropolitan region can provide reasonably accurate estimates of hourly vehicle volume on major roads. While vehicle volume is only one of many factors that govern on-road emission rates, air quality analyses would be strengthened by incorporating information regarding the uncertainty and variability of traffic activity. PMID:26688671

Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis

PubMed Central

Gopal, Shruti; Miller, Robyn L.; Michael, Andrew; Adali, Tulay; Cetin, Mustafa; Rachakonda, Srinivas; Bustillo, Juan R.; Cahill, Nathan; Baum, Stefi A.; Calhoun, Vince D.

2016-01-01

Spatial variability in resting functional MRI (fMRI) brain networks has not been well studied in schizophrenia, a disease known for both neurodevelopmental and widespread anatomic changes. Motivated by abundant evidence of neuroanatomical variability from previous studies of schizophrenia, we draw upon a relatively new approach called independent vector analysis (IVA) to assess this variability in resting fMRI networks. IVA is a blind-source separation algorithm, which segregates fMRI data into temporally coherent but spatially independent networks and has been shown to be especially good at capturing spatial variability among subjects in the extracted networks. We introduce several new ways to quantify differences in variability of IVA-derived networks between schizophrenia patients (SZs = 82) and healthy controls (HCs = 89). Voxelwise amplitude analyses showed significant group differences in the spatial maps of auditory cortex, the basal ganglia, the sensorimotor network, and visual cortex. Tests for differences (HC-SZ) in the spatial variability maps suggest, that at rest, SZs exhibit more activity within externally focused sensory and integrative network and less activity in the default mode network thought to be related to internal reflection. Additionally, tests for difference of variance between groups further emphasize that SZs exhibit greater network variability. These results, consistent with our prediction of increased spatial variability within SZs, enhance our understanding of the disease and suggest that it is not just the amplitude of connectivity that is different in schizophrenia, but also the consistency in spatial connectivity patterns across subjects. PMID:26106217

Modeling and measuring the relationships between sediment transport processes, alluvial bedforms and channel-scale morphodynamics in sandy braided rivers.

NASA Astrophysics Data System (ADS)

Nicholas, A. P.; Ashworth, P. J.; Best, J.; Lane, S. N.; Parsons, D. R.; Sambrook Smith, G.; Simpson, C.; Strick, R. J. P.; Unsworth, C. A.

2017-12-01

Recent years have seen significant advances in the development and application of morphodynamic models to simulate river evolution. Despite this progress, significant challenges remain to be overcome before such models can provide realistic simulations of river response to environmental change, or be used to determine the controls on alluvial channel patterns and deposits with confidence. This impasse reflects a wide range of factors, not least the fact that many of the processes that control river behaviour operate at spatial scales that cannot be resolved by such models. For example, sand-bed rivers are characterised by multiple scales of topography (e.g., dunes, bars, channels), the finest of which must often by parameterized, rather than represented explicitly in morphodynamic models. We examine these issues using a combination of numerical modeling and field observations. High-resolution aerial imagery and Digital Elevation Models obtained for the sandy braided South Saskatchewan River in Canada are used to quantify dune, bar and channel morphology and their response to changing flow discharge. Numerical simulations are carried out using an existing morphodynamic model based on the 2D shallow water equations, coupled with new parameterisations of the evolution and influence of alluvial bedforms. We quantify the spatial patterns of sediment flux using repeat images of dune migration and bar evolution. These data are used to evaluate model predictions of sediment transport and morphological change, and to assess the degree to which model performance is controlled by the parametrization of roughness and sediment transport phenomena linked to subgrid-scale bedforms (dunes). The capacity of such models to replicate the characteristic multi-scale morphology of bars in sand-bed rivers, and the contrasting morphodynamic signatures of braiding during low and high flow conditions, is also assessed.

Opposing assembly mechanisms in a neotropical dry forest: implications for phylogenetic and functional community ecology.

PubMed

Swenson, Nathan G; Enquist, Brian J

2009-08-01

Species diversity is promoted and maintained by ecological and evolutionary processes operating on species attributes through space and time. The degree to which variability in species function regulates distribution and promotes coexistence of species has been debated. Previous work has attempted to quantify the relative importance of species function by using phylogenetic relatedness as a proxy for functional similarity. The key assumption of this approach is that function is phylogenetically conserved. If this assumption is supported, then the phylogenetic dispersion in a community should mirror the functional dispersion. Here we quantify functional trait dispersion along several key axes of tree life-history variation and on multiple spatial scales in a Neotropical dry-forest community. We next compare these results to previously reported patterns of phylogenetic dispersion in this same forest. We find that, at small spatial scales, coexisting species are typically more functionally clustered than expected, but traits related to adult and regeneration niches are overdispersed. This outcome was repeated when the analyses were stratified by size class. Some of the trait dispersion results stand in contrast to the previously reported phylogenetic dispersion results. In order to address this inconsistency we examined the strength of phylogenetic signal in traits at different depths in the phylogeny. We argue that: (1) while phylogenetic relatedness may be a good general multivariate proxy for ecological similarity, it may have a reduced capacity to depict the functional mechanisms behind species coexistence when coexisting species simultaneously converge and diverge in function; and (2) the previously used metric of phylogenetic signal provided erroneous inferences about trait dispersion when married with patterns of phylogenetic dispersion.

Regional water quality patterns in an alluvial aquifer: direct and indirect influences of rivers.

PubMed

Baillieux, A; Campisi, D; Jammet, N; Bucher, S; Hunkeler, D

2014-11-15

The influence of rivers on the groundwater quality in alluvial aquifers can be twofold: direct and indirect. Rivers can have a direct influence via recharge and an indirect one by controlling the distribution of fine-grained, organic-carbon rich flood deposits that induce reducing conditions. These direct and indirect influences were quantified for a large alluvial aquifer on the Swiss Plateau (50km(2)) in interaction with an Alpine river using nitrate as an example. The hydrochemistry and stable isotope composition of water were characterized using a network of 115 piezometers and pumping stations covering the entire aquifer. Aquifer properties, land use and recharge zones were evaluated as well. This information provided detailed insight into the factors that control the spatial variability of groundwater quality. Three main factors were identified: (1) diffuse agricultural pollution sources; (2) dilution processes resulting from river water infiltrations, revealed by the δ(18)OH2O and δ(2)HH2O contents of groundwater; and (3) denitrification processes, controlled by the spatial variability of flood deposits governed by fluvial depositional processes. It was possible to quantify the dependence of the nitrate concentration on these three factors at any sampling point of the aquifer using an end-member mixing model, where the average nitrate concentration in recharge from the agricultural area was evaluated at 52mg/L, and the nitrate concentration of infiltrating river at approximately 6mg/L. The study shows the importance of considering the indirect and direct impacts of rivers on alluvial aquifers and provides a methodological framework to evaluate aquifer scale water quality patterns. Copyright © 2014 Elsevier B.V. All rights reserved.

Modeling vertebrate diversity in Oregon using satellite imagery

NASA Astrophysics Data System (ADS)

Cablk, Mary Elizabeth

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

Quantifying the synergistic effect of the precipitation and land use on sandy desertification at county level: a case study in Naiman Banner, Northern China.

PubMed

Xiaodong, Ge; Jinren, Ni; Zhenshan, Li; Ronggui, Hu; Xin, Ming; Qing, Ye

2013-07-15

Assessing the driving forces of sandy desertification is fundamental and important for its control. It has been widely accepted that both climatic conditions and land use have great impact on sandy desertification in northern China. However, the relative role and synergistic effect of each driving force of sandy desertification are still not clear. In this paper, an indicator named as SI was defined to represent the integrated probability of sandy desertification caused by land use. A quantitative method was developed for characterizing the relative roles of annual precipitation and land use to sandy desertification in both spatial and temporal dimensions at county level. Results showed that, at county level, land use was the main cause of sandy desertification for Naiman Banner since 1987-2009. In the case of spatial dimension, the different combination of land use types decided the distribution of sandy desertification probability and finally decided the spatial pattern of bared sand land. In the case of temporal dimension, the synergistic effect of land use and precipitation highly influenced the spatial distribution of sandy desertification. Copyright © 2013 Elsevier Ltd. All rights reserved.

Spatial variability of detrended soil plow layer penetrometer resistance transect in a sugarcane field

NASA Astrophysics Data System (ADS)

Pérez, Luis D.; Cumbrera, Ramiro; Mato, Juan; Millán, Humberto; Tarquis, Ana M.

2015-04-01

Spatial variability of soil properties is relevant for identifying those zones with physical degradation. In this sense, one has to face the problem of identifying the origin and distribution of spatial variability patterns (Brouder et al., 2001; Millán et al., 2012). The objective of the present work was to quantify the spatial structure of soil penetrometer resistance (PR) collected from a transect data consisted of 221 points equidistant. In each sampling, readings were obtained from 0 cm till 70 cm of depth, with an interval of 5 cm (Pérez, 2012). The study was conducted on a Vertisol (Typic Hapludert) dedicated to sugarcane (Saccharum officinarum L.) production during the last sixty years (Pérez et al., 2010). Recently, scaling approach has been applied on the determination of the scaling data properties (Tarquis et al., 2008; Millán et al., 2012; Pérez, 2012). We focus in the Hurst analysis to characterize the data variability for each depth. Previously a detrended analysis was conducted in order to better study de intrinsic variability of the series. The Hurst exponent (H) for each depth was estimated showing a characteristic pattern and differentiating PR evolution in depth. References Brouder, S., Hofmann, B., Reetz, H.F., 2001. Evaluating spatial variability of soil parameters for input management. Better Crops 85, 8-11. Millán, H; AM Tarquís, Luís D. Pérez, Juan Mato, Mario González-Posada, 2012. Spatial variability patterns of some Vertisol properties at a field scale using standardized data. Soil and Tillage Research, 120, 76-84. Pérez, Luís D. 2012. Influencia de la maquinaria agrícola sobre la variabilidad espacial de la compactación del suelo. Aplicación de la metodología geoestadística-fractal. PhD thesis, UPM (In Spanish). Pérez, Luís D., Humberto Millán, Mario González-Posada 2010. Spatial complexity of soil plow layer penetrometer resistance as influenced by sugarcane harvesting: A prefractal approach. Soil and Tillage Research, 110(1), 77-86. Tarquis, A.M., N. Bird, M.C. Cartagena, A. Whitmore and Y. Pachepsky, 2008. Multiscale entropy-based analyses of soil transect data. Vadose Zone Journal, 7(2), 563-569.

Modelling Geomechanical Heterogeneity of Rock Masses Using Direct and Indirect Geostatistical Conditional Simulation Methods

NASA Astrophysics Data System (ADS)

Eivazy, Hesameddin; Esmaieli, Kamran; Jean, Raynald

2017-12-01

An accurate characterization and modelling of rock mass geomechanical heterogeneity can lead to more efficient mine planning and design. Using deterministic approaches and random field methods for modelling rock mass heterogeneity is known to be limited in simulating the spatial variation and spatial pattern of the geomechanical properties. Although the applications of geostatistical techniques have demonstrated improvements in modelling the heterogeneity of geomechanical properties, geostatistical estimation methods such as Kriging result in estimates of geomechanical variables that are not fully representative of field observations. This paper reports on the development of 3D models for spatial variability of rock mass geomechanical properties using geostatistical conditional simulation method based on sequential Gaussian simulation. A methodology to simulate the heterogeneity of rock mass quality based on the rock mass rating is proposed and applied to a large open-pit mine in Canada. Using geomechanical core logging data collected from the mine site, a direct and an indirect approach were used to model the spatial variability of rock mass quality. The results of the two modelling approaches were validated against collected field data. The study aims to quantify the risks of pit slope failure and provides a measure of uncertainties in spatial variability of rock mass properties in different areas of the pit.

Surrogate taxa and fossils as reliable proxies of spatial biodiversity patterns in marine benthic communities.

PubMed

Tyler, Carrie L; Kowalewski, Michał

2017-03-15

Rigorous documentation of spatial heterogeneity (β-diversity) in present-day and preindustrial ecosystems is required to assess how marine communities respond to environmental and anthropogenic drivers. However, the overwhelming majority of contemporary and palaeontological assessments have centred on single higher taxa. To evaluate the validity of single taxa as community surrogates and palaeontological proxies, we compared macrobenthic communities and sympatric death assemblages at 52 localities in Onslow Bay (NC, USA). Compositional heterogeneity did not differ significantly across datasets based on live molluscs, live non-molluscs, and all live organisms. Death assemblages were less heterogeneous spatially, likely reflecting homogenization by time-averaging. Nevertheless, live and dead datasets were greater than 80% congruent in pairwise comparisons to the literature estimates of β-diversity in other marine ecosystems, yielded concordant bathymetric gradients, and produced nearly identical ordinations consistently delineating habitats. Congruent estimates from molluscs and non-molluscs suggest that single groups can serve as reliable community proxies. High spatial fidelity of death assemblages supports the emerging paradigm of Conservation Palaeobiology. Integrated analyses of ecological and palaeontological data based on surrogate taxa can quantify anthropogenic changes in marine ecosystems and advance our understanding of spatial and temporal aspects of biodiversity. © 2017 The Author(s).

Spatial decorrelation stretch of annual (2003-2014) Daymet precipitation summaries on a 1-km grid for California, Nevada, Arizona, and Utah.

PubMed

Ch Miliaresis, George

2016-06-01

A method is presented for elevation (H) and spatial position (X, Y) decorrelation stretch of annual precipitation summaries on a 1-km grid for SW USA for the period 2003 to 2014. Multiple linear regression analysis of the first and second principal component (PC) quantifies the variance in the multi-temporal precipitation imagery that is explained by X, Y, and elevation (h). The multi-temporal dataset is reconstructed from the PC1 and PC2 residual images and the later PCs by taking into account the variance that is not related to X, Y, and h. Clustering of the reconstructed precipitation dataset allowed the definition of positive (for example, in Sierra Nevada, Salt Lake City) and negative (for example, in San Joaquin Valley, Nevada, Colorado Plateau) precipitation anomalies. The temporal and spatial patterns defined from the spatially standardized multi-temporal precipitation imagery provide a tool of comparison for regions in different geographic environments according to the deviation from the precipitation amount that they are expected to receive as function of X, Y, and h. Such a standardization allows the definition of less or more sensitive to climatic change regions and gives an insight in the spatial impact of atmospheric circulation that causes the annual precipitation.

A Scalable Field Study Protocol and Rationale for Passive Ambient Air Sampling: A Spatial Phytosampling for Leaf Data Collection

PubMed Central

Oyana, Tonny J.; Lomnicki, Slawomir M.; Guo, Chuqi; Cormier, Stephania A.

2018-01-01

Stable, bioreactive, radicals known as environmentally persistent free radicals (EPFRs) have been found to exist on the surface of airborne PM2.5. These EPFRs have been found to form during many combustion processes, are present in vehicular exhaust, and persist in the environment for weeks and biological systems for up to 12 h. To measure EPFRs in PM samples, high volume samplers are required and measurements are less representative of community exposure; therefore, we developed a novel spatial phytosampling methodology to study the spatial patterns of EPFR concentrations using plants. Leaf samples for laboratory PM analysis were collected from 188 randomly drawn sampling sites within a 500-m buffer zone of pollution sources across a sampling grid measuring 32.9 × 28.4 km in Memphis, Tennessee. PM was isolated from the intact leaves and size fractionated, and EPFRs on PM quantified by electron paramagnetic resonance spectroscopy. The radical concentration was found to positively correlate with the EPFR g-value, thus indicating cumulative content of oxygen centered radicals in PM with higher EPFR load. Our spatial phytosampling approach reveals spatial variations and potential “hotspots” risk due to EPFR exposure across Memphis and provides valuable insights for identifying exposure and demographic differences for health studies. PMID:28805054

Capturing the Two Dimensions of Residential Segregation at the Neighborhood Level for Health Research

PubMed Central

Oka, Masayoshi; Wong, David W. S.

2014-01-01

Two conceptual and methodological foundations of segregation studies are that (i) segregation involves more than one group, and (ii) segregation measures need to quantify how different population groups are distributed across space. Therefore, percentage of population belonging to a group is not an appropriate measure of segregation because it does not describe how populations are spread across different areal units or neighborhoods. In principle, evenness and isolation are the two distinct dimensions of segregation that capture the spatial patterns of population groups. To portray people’s daily environment more accurately, segregation measures need to account for the spatial relationships between areal units and to reflect the situations at the neighborhood scale. For these reasons, the use of local spatial entropy-based diversity index (SHi) and local spatial isolation index (Si) to capture the evenness and isolation dimensions of segregation, respectively, are preferable. However, these two local spatial segregation indexes have rarely been incorporated into health research. Rather ineffective and insufficient segregation measures have been used in previous studies. Hence, this paper empirically demonstrates how the two measures can reflect the two distinct dimensions of segregation at the neighborhood level, and argues conceptually and set the stage for their future use to effectively and meaningfully examine the relationships between residential segregation and health. PMID:25202687

Imaging spectroscopy links aspen genotype with below-ground processes at landscape scales

PubMed Central

Madritch, Michael D.; Kingdon, Clayton C.; Singh, Aditya; Mock, Karen E.; Lindroth, Richard L.; Townsend, Philip A.

2014-01-01

Fine-scale biodiversity is increasingly recognized as important to ecosystem-level processes. Remote sensing technologies have great potential to estimate both biodiversity and ecosystem function over large spatial scales. Here, we demonstrate the capacity of imaging spectroscopy to discriminate among genotypes of Populus tremuloides (trembling aspen), one of the most genetically diverse and widespread forest species in North America. We combine imaging spectroscopy (AVIRIS) data with genetic, phytochemical, microbial and biogeochemical data to determine how intraspecific plant genetic variation influences below-ground processes at landscape scales. We demonstrate that both canopy chemistry and below-ground processes vary over large spatial scales (continental) according to aspen genotype. Imaging spectrometer data distinguish aspen genotypes through variation in canopy spectral signature. In addition, foliar spectral variation correlates well with variation in canopy chemistry, especially condensed tannins. Variation in aspen canopy chemistry, in turn, is correlated with variation in below-ground processes. Variation in spectra also correlates well with variation in soil traits. These findings indicate that forest tree species can create spatial mosaics of ecosystem functioning across large spatial scales and that these patterns can be quantified via remote sensing techniques. Moreover, they demonstrate the utility of using optical properties as proxies for fine-scale measurements of biodiversity over large spatial scales. PMID:24733949

ANTIOXIDANT CAPACITY OF WYOMING BIG SAGEBRUSH (ARTEMISIA TRIDENTATA SSP. WYOMINGENSIS) VARIES SPATIALLY AND IS NOT RELATED TO THE PRESENCE OF A SAGEBRUSH DIETARY SPECIALIST

PubMed Central

Pu, Xinzhu; Lam, Lisa; Gehlken, Kristina; Ulappa, Amy C.; Rachlow, Janet L.; Forbey, Jennifer Sorensen

2015-01-01

Sagebrush (Artemisia spp.) in North America is an abundant native plant species that is ecologically and evolutionarily adapted to have a diverse array of biologically active chemicals. Several of these chemicals, specifically polyphenols, have antioxidant activity that may act as biomarkers of biotic or abiotic stress. This study investigated the spatial variation of antioxidant capacity, as well as the relationship between a mammalian herbivore and antioxidant capacity in Wyoming big sagebrush (Artemisia tridentata wyomingensis). We quantified and compared total polyphenols and antioxidant capacity of leaf extracts from sagebrush plants from different spatial scales and at different levels of browsing by a specialist mammalian herbivore, the pygmy rabbit (Brachylagus idahoensis). We found that antioxidant capacity of sagebrush extracts was positively correlated with total polyphenol content. Antioxidant capacity varied spatially within and among plants. Antioxidant capacity in sagebrush was not related to either browsing intensity or duration of association with rabbits. We propose that the patterns of antioxidant capacity observed in sagebrush may be a result of spatial variation in abiotic stress experienced by sagebrush. Antioxidants could therefore provide a biomarker of environmental stress for sagebrush that could aid in management and conservation of this plant in the threatened sagebrush steppe. PMID:26582971

Spatial heterogeneity of plant-soil feedback affects root interactions and interspecific competition.

PubMed

Hendriks, Marloes; Ravenek, Janneke M; Smit-Tiekstra, Annemiek E; van der Paauw, Jan Willem; de Caluwe, Hannie; van der Putten, Wim H; de Kroon, Hans; Mommer, Liesje

2015-08-01

Plant-soil feedback is receiving increasing interest as a factor influencing plant competition and species coexistence in grasslands. However, we do not know how spatial distribution of plant-soil feedback affects plant below-ground interactions. We investigated the way in which spatial heterogeneity of soil biota affects competitive interactions in grassland plant species. We performed a pairwise competition experiment combined with heterogeneous distribution of soil biota using four grassland plant species and their soil biota. Patches were applied as quadrants of 'own' and 'foreign' soils from all plant species in all pairwise combinations. To evaluate interspecific root responses, species-specific root biomass was quantified using real-time PCR. All plant species suffered negative soil feedback, but strength was species-specific, reflected by a decrease in root growth in own compared with foreign soil. Reduction in root growth in own patches by the superior plant competitor provided opportunities for inferior competitors to increase root biomass in these patches. These patterns did not cascade into above-ground effects during our experiment. We show that root distributions can be determined by spatial heterogeneity of soil biota, affecting plant below-ground competitive interactions. Thus, spatial heterogeneity of soil biota may contribute to plant species coexistence in species-rich grasslands. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

A Scalable Field Study Protocol and Rationale for Passive Ambient Air Sampling: A Spatial Phytosampling for Leaf Data Collection.

PubMed

Oyana, Tonny J; Lomnicki, Slawomir M; Guo, Chuqi; Cormier, Stephania A

2017-09-19

Stable, bioreactive, radicals known as environmentally persistent free radicals (EPFRs) have been found to exist on the surface of airborne PM 2.5 . These EPFRs have been found to form during many combustion processes, are present in vehicular exhaust, and persist in the environment for weeks and biological systems for up to 12 h. To measure EPFRs in PM samples, high volume samplers are required and measurements are less representative of community exposure; therefore, we developed a novel spatial phytosampling methodology to study the spatial patterns of EPFR concentrations using plants. Leaf samples for laboratory PM analysis were collected from 188 randomly drawn sampling sites within a 500-m buffer zone of pollution sources across a sampling grid measuring 32.9 × 28.4 km in Memphis, Tennessee. PM was isolated from the intact leaves and size fractionated, and EPFRs on PM quantified by electron paramagnetic resonance spectroscopy. The radical concentration was found to positively correlate with the EPFR g-value, thus indicating cumulative content of oxygen centered radicals in PM with higher EPFR load. Our spatial phytosampling approach reveals spatial variations and potential "hotspots" risk due to EPFR exposure across Memphis and provides valuable insights for identifying exposure and demographic differences for health studies.

Bacterial taxa–area and distance–decay relationships in marine environments

PubMed Central

Zinger, L; Boetius, A; Ramette, A

2014-01-01

The taxa–area relationship (TAR) and the distance–decay relationship (DDR) both describe spatial turnover of taxa and are central patterns of biodiversity. Here, we compared TAR and DDR of bacterial communities across different marine realms and ecosystems at the global scale. To obtain reliable global estimates for both relationships, we quantified the poorly assessed effects of sequencing depth, rare taxa removal and number of sampling sites. Slope coefficients of bacterial TARs were within the range of those of plants and animals, whereas slope coefficients of bacterial DDR were much lower. Slope coefficients were mostly affected by removing rare taxa and by the number of sampling sites considered in the calculations. TAR and DDR slope coefficients were overestimated at sequencing depth <4000 sequences per sample. Noticeably, bacterial TAR and DDR patterns did not correlate with each other both within and across ecosystem types, suggesting that (i) TAR cannot be directly derived from DDR and (ii) TAR and DDR may be influenced by different ecological factors. Nevertheless, we found marine bacterial TAR and DDR to be steeper in ecosystems associated with high environmental heterogeneity or spatial isolation, namely marine sediments and coastal environments compared with pelagic ecosystems. Hence, our study provides information on macroecological patterns of marine bacteria, as well as methodological and conceptual insights, at a time when biodiversity surveys increasingly make use of high-throughput sequencing technologies. PMID:24460915

Mobile Platforms for Continuous Spatial Measurements of Urban Trace Gases and Criteria Pollutants

NASA Astrophysics Data System (ADS)

Fasoli, B.; Mitchell, L.; Bares, R.; Crosman, E.; Bush, S. E.; Horel, J.; Lin, J. C.; Bowling, D. R.; Ehleringer, J. R.

2015-12-01

Surface-based observations of atmospheric trace gases and criteria pollutants provide critical data on how emissions and pollutant concentrations vary over time. However, traditional stationary measurement sites only quantify concentrations at a single point in space, limiting our ability to understand spatial patterns. Using trace gas instrumentation capable of making continuous high-frequency (~1s) measurements, we have developed mobile platforms to complement stationary observation sites in order to better constrain the heterogeneity and complexities of urban emissions. These compact trace gas and criteria pollutant measurement systems are capable of precisely measuring CO2, CH4 PM2.5, O3, NOx, and several meteorological parameters on TRAX, Salt Lake City's light-rail system, and in a van-based mobile laboratory. Using case study observations, we discuss mobile measurement methodologies and the practical applications of mobile trace gas sampling platforms.

NO2 DOAS Measurements of Traffic Emissions by Chasing Cars

NASA Astrophysics Data System (ADS)

Zhu, Ying; Lipkowitsch, Ivo; Chan, Ka Lok; Bräu, Melanie; Wenig, Mark

2016-04-01

On this poster we present NO2 measurements using a Cavity-Enhanced DOAS on a measurement bus which we used to chase other vehicles to measure their NO2 emissions. Emissions of nitrogen oxides from on-road vehicles have received highly attention recently due to the increasing trend of ambient NOx level. It is particularly important to identify and quantify the direct emission and secondary formation of NO2 contributed by traffic emissions, in order to study the impact to the local air quality. We sampled on-road emissions in different environments and different driving conditions (e.g. urban, highway, different speeds). We analyse the data set in terms of spatial and temporal variability to search for temporal and spatial patterns. We present mean values sorted for different vehicle types, distance to the target car and travelling speeds to provide an emission data base from this measurement study.

disLocate: tools to rapidly quantify local intermolecular structure to assess two-dimensional order in self-assembled systems.

PubMed

Bumstead, Matt; Liang, Kunyu; Hanta, Gregory; Hui, Lok Shu; Turak, Ayse

2018-01-24

Order classification is particularly important in photonics, optoelectronics, nanotechnology, biology, and biomedicine, as self-assembled and living systems tend to be ordered well but not perfectly. Engineering sets of experimental protocols that can accurately reproduce specific desired patterns can be a challenge when (dis)ordered outcomes look visually similar. Robust comparisons between similar samples, especially with limited data sets, need a finely tuned ensemble of accurate analysis tools. Here we introduce our numerical Mathematica package disLocate, a suite of tools to rapidly quantify the spatial structure of a two-dimensional dispersion of objects. The full range of tools available in disLocate give different insights into the quality and type of order present in a given dispersion, accessing the translational, orientational and entropic order. The utility of this package allows for researchers to extract the variation and confidence range within finite sets of data (single images) using different structure metrics to quantify local variation in disorder. Containing all metrics within one package allows for researchers to easily and rapidly extract many different parameters simultaneously, allowing robust conclusions to be drawn on the order of a given system. Quantifying the experimental trends which produce desired morphologies enables engineering of novel methods to direct self-assembly.

Quantifying Contemporary Terrestrial Carbon Sources and Sinks in the Conterminous United States

NASA Astrophysics Data System (ADS)

Liu, S.; Loveland, T.

2003-12-01

U.S. land likely accounts for a significant portion of the unidentified global carbon sink, although the magnitude is highly uncertain. The ultimate goal of this study is to quantify the contemporary temporal and spatial patterns of carbon sources and sinks in the conterminous United States from the early 1970s to 2000, and to explain the mechanisms that cause the variability and changes. Because of the difficulty and massive cost for developing land cover change databases for the conterminous United States, we adopt an ecoregion-based sampling approach. Carbon dynamics within thousands of 20 km by 20 km or 10 km by 10 km sampling blocks, stratified by Omernik Level III ecoregions, are simulated using the General Ensemble Biogeochemical Modeling System at the spatial resolution of 60 m by 60 m. The land use change data, providing unprecedented accuracy and consistency, are derived from Landsat imagery for five time points (nominally 1972, 1980, 1986, 1992, and 2000). Mechanisms have been implemented to assimilate data from key national benchmark databases (including the USDA Forest Service­_s Forest Inventory and Analysis data and the USDA­_s agricultural census data). The dynamics of carbon stocks in vegetation, soil, and harvested wood materials are quantified. Results from three ecoregions (i.e., Southeastern Plains, Piedmont, and Northern Piedmont) indicated that the carbon sink strength has been decreasing from the 1970s to 2000. The relative contribution of biomass accumulation to the sink decreased during this period, while those of soil organic carbon and harvested wood materials increased.

Spatial analysis of fractured rock around fault zones based on photogrammetric data

NASA Astrophysics Data System (ADS)

Deckert, H.; Gessner, K.; Drews, M.; Wellmann, J. F.

2009-04-01

The location of hydrocarbon, geothermal or hydrothermal fluids is often bound to fault zones. The fracture systems along these faults play an important role in providing pathways to fluids in the Earth's crust. Thus an evaluation of the change in permeability due to rock deformation is of particular interest in these zones. Recent advances in digital imaging using modern techniques like photogrammetry provide new opportunities to view, analyze and present high resolution geological data in three dimensions. Our method is an extension of the one-dimensional scan-line approach to quantify discontinuities in rock outcrops. It has the advantage to take into account a larger amount of spatial data than conventional manual measurement methods. It enables to recover the entity of spatial information of a 3D fracture pattern, i.e. position, orientation, extent and frequency of fractures. We present examples of outcrop scale datasets in granitic and sedimentary rocks and analyse changes in fracture patterns across fault zones from the host rock to the damage zone. We also present a method to generate discontinuity density maps from 3D surface models generated by digital photogrammetry methods. This methodology has potential for application in rock mass characterization, structural and tectonic studies, the formation of hydrothermal mineral deposits, oil and gas migration, and hydrogeology. Our analysis methods represent important steps towards developing a toolkit to automatically detect and interpret spatial rock characteristics, by taking advantage of the large amount of data that can be collected by photogrammetric methods. This acquisition of parameters defining a 3D fracture pattern allows the creation of synthetic fracture networks following these constraints. The mathematical description of such a synethtical network can be implemented into numerical simulation tools for modeling fluid flow in fracture media. We give an outline of current and future applications of photogrammetry in rock mechanics, petroleum geology, hydrogeology, and structural geology.

Multiscale comparison of GPM radar and passive microwave precipitation fields over oceans and land: effective resolution and global/regional/local diagnostics for improving retrieval algorithms

NASA Astrophysics Data System (ADS)

Guilloteau, C.; Foufoula-Georgiou, E.; Kummerow, C.; Kirstetter, P. E.

2017-12-01

A multiscale approach is used to compare precipitation fields retrieved from GMI using the last version of the GPROF algorithm (GPROF-2017) to the DPR fields all over the globe. Using a wavelet-based spectral analysis, which renders the multi-scale decompositions of the original fields independent of each other spatially and across scales, we quantitatively assess the various scales of variability of the retrieved fields, and thus define the spatially-variable "effective resolution" (ER) of the retrievals. Globally, a strong agreement is found between passive microwave and radar patterns at scales coarser than 80km. Over oceans the patterns match down to the 20km scale. Over land, comparison statistics are spatially heterogeneous. In most areas a strong discrepancy is observed between passive microwave and radar patterns at scales finer than 40-80km. The comparison is also supported by ground-based observations over the continental US derived from the NOAA/NSSL MRMS suite of products. While larger discrepancies over land than over oceans are classically explained by land complex surface emissivity perturbing the passive microwave retrieval, other factors are investigated here, such as intricate differences in the storm structure over oceans and land. Differences in term of statistical properties (PDF of intensities and spatial organization) of precipitation fields over land and oceans are assessed from radar data, as well as differences in the relation between the 89GHz brightness temperature and precipitation. Moreover, the multiscale approach allows quantifying the part of discrepancies caused by miss-match of the location of intense cells and instrument-related geometric effects. The objective is to diagnose shortcomings of current retrieval algorithms such that targeted improvements can be made to achieve over land the same retrieval performance as over oceans.

[Distribution patterns of canopy and understory tree species at local scale in a Tierra Firme forest, the Colombian Amazonia].

PubMed

Barreto-Silva, Juan Sebastian; López, Dairon Cárdenas; Montoya, Alvaro Javier Duque

2014-03-01

The effect of environmental variation on the structure of tree communities in tropical forests is still under debate. There is evidence that in landscapes like Tierra Firme forest, where the environmental gradient decreases at a local level, the effect of soil on the distribution patterns of plant species is minimal, happens to be random or is due to biological processes. In contrast, in studies with different kinds of plants from tropical forests, a greater effect on floristic composition of varying soil and topography has been reported. To assess this, the current study was carried out in a permanent plot of ten hectares in the Amacayacu National Park, Colombian Amazonia. To run the analysis, floristic and environmental variations were obtained according to tree species abundance categories and growth forms. In order to quantify the role played by both environmental filtering and dispersal limitation, the variation of the spatial configuration was included. We used Detrended Correspondence Analysis and Canonical Correspondence Analysis, followed by a variation partitioning, to analyze the species distribution patterns. The spatial template was evaluated using the Principal Coordinates of Neighbor Matrix method. We recorded 14 074 individuals from 1 053 species and 80 families. The most abundant families were Myristicaceae, Moraceae, Meliaceae, Arecaceae and Lecythidaceae, coinciding with other studies from Northwest Amazonia. Beta diversity was relatively low within the plot. Soils were very poor, had high aluminum concentration and were predominantly clayey. The floristic differences explained along the ten hectares plot were mainly associated to biological processes, such as dispersal limitation. The largest proportion of community variation in our dataset was unexplained by either environmental or spatial data. In conclusion, these results support random processes as the major drivers of the spatial variation of tree species at a local scale on Tierra Firme forests of Amacayacu National Park, and suggest reserve's size as a key element to ensure the conservation of plant diversity at both regional and local levels.

Midpoint attractors and species richness: Modelling the interaction between environmental drivers and geometric constraints.

PubMed

Colwell, Robert K; Gotelli, Nicholas J; Ashton, Louise A; Beck, Jan; Brehm, Gunnar; Fayle, Tom M; Fiedler, Konrad; Forister, Matthew L; Kessler, Michael; Kitching, Roger L; Klimes, Petr; Kluge, Jürgen; Longino, John T; Maunsell, Sarah C; McCain, Christy M; Moses, Jimmy; Noben, Sarah; Sam, Katerina; Sam, Legi; Shapiro, Arthur M; Wang, Xiangping; Novotny, Vojtech

2016-09-01

We introduce a novel framework for conceptualising, quantifying and unifying discordant patterns of species richness along geographical gradients. While not itself explicitly mechanistic, this approach offers a path towards understanding mechanisms. In this study, we focused on the diverse patterns of species richness on mountainsides. We conjectured that elevational range midpoints of species may be drawn towards a single midpoint attractor - a unimodal gradient of environmental favourability. The midpoint attractor interacts with geometric constraints imposed by sea level and the mountaintop to produce taxon-specific patterns of species richness. We developed a Bayesian simulation model to estimate the location and strength of the midpoint attractor from species occurrence data sampled along mountainsides. We also constructed midpoint predictor models to test whether environmental variables could directly account for the observed patterns of species range midpoints. We challenged these models with 16 elevational data sets, comprising 4500 species of insects, vertebrates and plants. The midpoint predictor models generally failed to predict the pattern of species midpoints. In contrast, the midpoint attractor model closely reproduced empirical spatial patterns of species richness and range midpoints. Gradients of environmental favourability, subject to geometric constraints, may parsimoniously account for elevational and other patterns of species richness. © 2016 John Wiley & Sons Ltd/CNRS.

Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models

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

Kravitz, Ben; Lynch, Cary; Hartin, Corinne

Pattern scaling is a well-established method for approximating modeled spatial distributions of changes in temperature by assuming a time-invariant pattern that scales with changes in global mean temperature. We compare two methods of pattern scaling for annual mean precipitation (regression and epoch difference) and evaluate which method is better in particular circumstances by quantifying their robustness to interpolation/extrapolation in time, inter-model variations, and inter-scenario variations. Both the regression and epoch-difference methods (the two most commonly used methods of pattern scaling) have good absolute performance in reconstructing the climate model output, measured as an area-weighted root mean square error. We decomposemore » the precipitation response in the RCP8.5 scenario into a CO 2 portion and a non-CO 2 portion. Extrapolating RCP8.5 patterns to reconstruct precipitation change in the RCP2.6 scenario results in large errors due to violations of pattern scaling assumptions when this CO 2-/non-CO 2-forcing decomposition is applied. As a result, the methodologies discussed in this paper can help provide precipitation fields to be utilized in other models (including integrated assessment models or impacts assessment models) for a wide variety of scenarios of future climate change.« less

Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models

DOE PAGES

Kravitz, Ben; Lynch, Cary; Hartin, Corinne; ...

2017-05-12

Pattern scaling is a well-established method for approximating modeled spatial distributions of changes in temperature by assuming a time-invariant pattern that scales with changes in global mean temperature. We compare two methods of pattern scaling for annual mean precipitation (regression and epoch difference) and evaluate which method is better in particular circumstances by quantifying their robustness to interpolation/extrapolation in time, inter-model variations, and inter-scenario variations. Both the regression and epoch-difference methods (the two most commonly used methods of pattern scaling) have good absolute performance in reconstructing the climate model output, measured as an area-weighted root mean square error. We decomposemore » the precipitation response in the RCP8.5 scenario into a CO 2 portion and a non-CO 2 portion. Extrapolating RCP8.5 patterns to reconstruct precipitation change in the RCP2.6 scenario results in large errors due to violations of pattern scaling assumptions when this CO 2-/non-CO 2-forcing decomposition is applied. As a result, the methodologies discussed in this paper can help provide precipitation fields to be utilized in other models (including integrated assessment models or impacts assessment models) for a wide variety of scenarios of future climate change.« less

COMPARISON OF SPATIAL PATTERNS OF POLLUTANT DISTRIBUTION WITH CMAQ PREDICTIONS

EPA Science Inventory

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

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Spatial and Temporal Patterns of SMAP Brightness Temperatures for Use in Level 1 TB Characterization

NASA Astrophysics Data System (ADS)

Kim, E. J.

2015-12-01

1. IntroductionThe recent launch of NASA's Soil Moisture Active Passive (SMAP) mission [Entekhabi, et al] has opened the door to improved brightness temperature (TB) calibration of satellite L-band microwave radiometers, through the use of SMAP's lower noise performance and better immunity to man-made interference (vs. ESA's Soil Moisture Ocean Salinity (SMOS) mission [Kerr, et al]), better spatial resolution (vs. NASA's Aquarius sea surface salinity mission [Le Vine, et al]), and cleaner antenna pattern (vs. SMOS). All three radiometers use/used large homogeneous places on Earth's surface as calibration targets—parts of the ocean, Antarctica, and tropical forests. Despite the recent loss of Aquarius data, there is still hope for creating a longer-term L-band data set that spans the timeframe of all 3 missions. 2. Description of Analyses and Expected Results In this paper, we analyze SMAP brightness temperature data to quantify the spatial and temporal characteristics of external target areas in the oceans, Antarctica, forests, and other areas. Existing analyses have examined these targets in terms of averages, standard deviations, and other basic statistics (for Aquarius & SMOS as well). This paper will approach the problem from a signal processing perspective. Coupled with the use of SMAP's novel RFI-mitigated TBs, and the aforementioned lower noise and cleaner antenna pattern, it is expected that of the 3 L-band missions, SMAP should do the best job of characterizing such external targets. The resulting conclusions should be useful to extract the best possible TB calibration from all 3 missions, helping to inter-compare the TB from the 3 missions, and to eventually inter-calibrate the TBs into a single long-term dataset.

Prey Patch Patterns Predict Habitat Use by Top Marine Predators with Diverse Foraging Strategies

PubMed Central

Benoit-Bird, Kelly J.; Battaile, Brian C.; Heppell, Scott A.; Hoover, Brian; Irons, David; Jones, Nathan; Kuletz, Kathy J.; Nordstrom, Chad A.; Paredes, Rosana; Suryan, Robert M.; Waluk, Chad M.; Trites, Andrew W.

2013-01-01

Spatial coherence between predators and prey has rarely been observed in pelagic marine ecosystems. We used measures of the environment, prey abundance, prey quality, and prey distribution to explain the observed distributions of three co-occurring predator species breeding on islands in the southeastern Bering Sea: black-legged kittiwakes (Rissa tridactyla), thick-billed murres (Uria lomvia), and northern fur seals (Callorhinus ursinus). Predictions of statistical models were tested using movement patterns obtained from satellite-tracked individual animals. With the most commonly used measures to quantify prey distributions - areal biomass, density, and numerical abundance - we were unable to find a spatial relationship between predators and their prey. We instead found that habitat use by all three predators was predicted most strongly by prey patch characteristics such as depth and local density within spatial aggregations. Additional prey patch characteristics and physical habitat also contributed significantly to characterizing predator patterns. Our results indicate that the small-scale prey patch characteristics are critical to how predators perceive the quality of their food supply and the mechanisms they use to exploit it, regardless of time of day, sampling year, or source colony. The three focal predator species had different constraints and employed different foraging strategies – a shallow diver that makes trips of moderate distance (kittiwakes), a deep diver that makes trip of short distances (murres), and a deep diver that makes extensive trips (fur seals). However, all three were similarly linked by patchiness of prey rather than by the distribution of overall biomass. This supports the hypothesis that patchiness may be critical for understanding predator-prey relationships in pelagic marine systems more generally. PMID:23301063

Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using Satellite Soil Moisture Data, GRACE Water Storage and Precipitation Observations

NASA Astrophysics Data System (ADS)

A, G.; Velicogna, I.; Kimball, J. S.; Du, J.; Kim, Y.; Njoku, E. G.; Colliander, A.

2016-12-01

We combine soil moisture (SM) data from AMSR-E, AMSR-2 and SMAP, terrestrial water storage (TWS) changes from GRACE and precipitation measurements from GPCP to delineate and characterize drought and water supply pattern and its impact on vegetation growth. GRACE TWS provides spatially continuous observations of total terrestrial water storage changes and regional drought extent, persistence and severity, while satellite derived soil moisture estimates provide enhanced delineation of plant-available soil moisture. Together these data provide complementary metrics quantifying available plant water supply and have important implications for water resource management. We use these data to investigate the supply changes from different water components in relation to satellite based vegetation productivity metrics from MODIS, before, during and following the major drought events observed in the continental US during the past 13 years. We observe consistent trends and significant correlations between monthly time series of TWS, SM, and vegetation productivity. In Texas and surrounding semi-arid areas, we find that the spatial pattern of the vegetation-moisture relation follows the gradient in mean annual precipitation. In Texas, GRACE TWS and surface SM show strong coupling and similar characteristic time scale in relatively normal years, while during the 2011 onward hydrological drought, GRACE TWS manifests a longer time scale than that of surface SM, implying stronger drought persistence in deeper water storage. In the Missouri watershed, we find a spatially varying vegetation-moisture relationship where in the drier northwestern portion of the basin, the inter-annual variability in summer vegetation productivity is closely associated with changes in carry-on GRACE TWS from spring, whereas in the moist southeastern portion of the basin, summer precipitation is the dominant controlling factor on vegetation growth.

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

Valous, Nektarios A.; Lahrmann, Bernd; Halama, Niels

Purpose: The interactions of neoplastic cells with each other and the microenvironment are complex. To understand intratumoral heterogeneity, subtle differences should be quantified. Main factors contributing to heterogeneity include the gradient ischemic level within neoplasms, action of microenvironment, mechanisms of intercellular transfer of genetic information, and differential mechanisms of modifications of genetic material/proteins. This may reflect on the expression of biomarkers in the context of prognosis/stratification. Hence, a rigorous approach for assessing the spatial intratumoral heterogeneity of histological biomarker expression with accuracy and reproducibility is required, since patterns in immunohistochemical images can be challenging to identify and describe. Methods: Amore » quantitative method that is useful for characterizing complex irregular structures is lacunarity; it is a multiscale technique that exhaustively samples the image, while the decay of its index as a function of window size follows characteristic patterns for different spatial arrangements. In histological images, lacunarity provides a useful measure for the spatial organization of a biomarker when a sampling scheme is employed and relevant features are computed. The proposed approach quantifies the segmented proliferative cells and not the textural content of the histological slide, thus providing a more realistic measure of heterogeneity within the sample space of the tumor region. The aim is to investigate in whole sections of primary pancreatic neuroendocrine neoplasms (pNENs), using whole-slide imaging and image analysis, the spatial intratumoral heterogeneity of Ki-67 immunostains. Unsupervised learning is employed to verify that the approach can partition the tissue sections according to distributional heterogeneity. Results: The architectural complexity of histological images has shown that single measurements are often insufficient. Inhomogeneity of distribution depends not only on percentage content of proliferation phase but also on how the phase fills the space. Lacunarity curves demonstrate variations in the sampled image sections. Since the spatial distribution of proliferation in each case is different, the width of the curves changes too. Image sections that have smaller numerical variations in the computed features correspond to neoplasms with spatially homogeneous proliferation, while larger variations correspond to cases where proliferation shows various degrees of clumping. Grade 1 (uniform/nonuniform: 74%/26%) and grade 3 (uniform: 100%) pNENs demonstrate a more homogeneous proliferation with grade 1 neoplasms being more variant, while grade 2 tumor regions render a more diverse landscape (50%/50%). Hence, some cases show an increased degree of spatial heterogeneity comparing to others with similar grade. Whether this is a sign of different tumor biology and an association with a more benign/malignant clinical course needs to be investigated further. The extent and range of spatial heterogeneity has the potential to be evaluated as a prognostic marker. Conclusions: The association with tumor grade as well as the rationale that the methodology reflects true tumor architecture supports the technical soundness of the method. This reflects a general approach which is relevant to other solid tumors and biomarkers. Drawing upon the merits of computational biomedicine, the approach uncovers salient features for use in future studies of clinical relevance.« less

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

USGS Publications Warehouse

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

2017-01-01

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

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

EPA Science Inventory

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

National spatial and temporal patterns of notified dengue cases, Colombia 2007-2010.

PubMed

Restrepo, Angela Cadavid; Baker, Peter; Clements, Archie C A

2014-07-01

To explore the variation in the spatial distribution of notified dengue cases in Colombia from January 2007 to December 2010 and examine associations between the disease and selected environmental risk factors. Data on the number of notified dengue cases in Colombia were obtained from the National Institute of Health (Instituto Nacional de Salud - INS) for the period 1 January 2007 through 31 December 2010. Data on environmental factors were collected from the Worldclim website. A Bayesian spatio-temporal conditional autoregressive model was used to quantify the relationship between monthly dengue cases and temperature, precipitation and elevation. Monthly dengue counts decreased by 18% (95% credible interval (CrI): 17-19%) in 2008 and increased by 30% (95% CrI: 28-31%) and 326% (95% CrI: 322-331%) in 2009 and 2010, respectively, compared to 2007. Additionally, there was a significant, nonlinear effect of monthly average precipitation. The results highlight the role of environmental risk factors in determining the spatial of dengue and show how these factors can be used to develop and refine preventive approaches for dengue in Colombia. © 2014 John Wiley & Sons Ltd.

The HTM Spatial Pooler-A Neocortical Algorithm for Online Sparse Distributed Coding.

PubMed

Cui, Yuwei; Ahmad, Subutai; Hawkins, Jeff

2017-01-01

Hierarchical temporal memory (HTM) provides a theoretical framework that models several key computational principles of the neocortex. In this paper, we analyze an important component of HTM, the HTM spatial pooler (SP). The SP models how neurons learn feedforward connections and form efficient representations of the input. It converts arbitrary binary input patterns into sparse distributed representations (SDRs) using a combination of competitive Hebbian learning rules and homeostatic excitability control. We describe a number of key properties of the SP, including fast adaptation to changing input statistics, improved noise robustness through learning, efficient use of cells, and robustness to cell death. In order to quantify these properties we develop a set of metrics that can be directly computed from the SP outputs. We show how the properties are met using these metrics and targeted artificial simulations. We then demonstrate the value of the SP in a complete end-to-end real-world HTM system. We discuss the relationship with neuroscience and previous studies of sparse coding. The HTM spatial pooler represents a neurally inspired algorithm for learning sparse representations from noisy data streams in an online fashion.

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.

Effects of population succession on demographic and genetic processes: predictions and tests in the daylily Hemerocallis thunbergii (Liliaceae).

PubMed

Chung, Mi Yoon; Nason, John D; Chung, Myong Gi

2007-07-01

Spatial genetic structure within plant populations is influenced by variation in demographic processes through space and time, including a population's successional status. To determine how demographic structure and fine-scale genetic structure (FSGS) change with stages in a population's successional history, we studied Hemerocallis thunbergii (Liliaceae), a nocturnal flowering and hawkmoth-pollinated herbaceous perennial with rapid population turnover dynamics. We examined nine populations assigned to three successive stages of population succession: expansion, maturation, and senescence. We developed stage-specific expectations for within-population demographic and genetic structure, and then for each population quantified the spatial aggregation of individuals and genotypes using spatial autocorrelation methods (nonaccumulative O-ring and kinship statistics, respectively), and at the landscape level measured inbreeding and genetic structure using Wright's F-statistics. Analyses using the O-ring statistic revealed significant aggregation of individuals at short spatial scales in expanding and senescing populations, in particular, which may reflect restricted seed dispersal around maternal individuals combined with relatively low local population densities at these stages. Significant FSGS was found for three of four expanding, no mature, and only one senescing population, a pattern generally consistent with expectations of successional processes. Although allozyme genetic diversity was high within populations (mean %P = 78.9 and H(E) = 0.281), landscape-level differentiation among sites was also high (F(ST) = 0.166) and all populations exhibited a significant deficit of heterozygotes relative to Hardy-Weinberg expectations (range F = 0.201-0.424, mean F(IS) = 0.321). Within populations, F was not correlated with the degree of FSGS, thus suggesting inbreeding due primarily to selfing as opposed to mating among close relatives in spatially structured populations. Our results demonstrate considerable variation in the spatial distribution of individuals and patterns and magnitude of FSGS in H. thunbergii populations across the landscape. This variation is generally consistent with succession-stage-specific differences in ecological processes operating within these populations.

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.

Sunlight Modulates Fruit Metabolic Profile and Shapes the Spatial Pattern of Compound Accumulation within the Grape Cluster.

PubMed

Reshef, Noam; Walbaum, Natasha; Agam, Nurit; Fait, Aaron

2017-01-01

Vineyards are characterized by their large spatial variability of solar irradiance (SI) and temperature, known to effectively modulate grape metabolism. To explore the role of sunlight in shaping fruit composition and cluster uniformity, we studied the spatial pattern of incoming irradiance, fruit temperature and metabolic profile within individual grape clusters under three levels of sunlight exposure. The experiment was conducted in a vineyard of Cabernet Sauvignon cv. located in the Negev Highlands, Israel, where excess SI and midday temperatures are known to degrade grape quality. Filtering SI lowered the surface temperature of exposed fruits and increased the uniformity of irradiance and temperature in the cluster zone. SI affected the overall levels and patterns of accumulation of sugars, organic acids, amino acids and phenylpropanoids, across the grape cluster. Increased exposure to sunlight was associated with lower accumulation levels of malate, aspartate, and maleate but with higher levels of valine, leucine, and serine, in addition to the stress-related proline and GABA. Flavan-3-ols metabolites showed a negative response to SI, whereas flavonols were highly induced. The overall levels of anthocyanins decreased with increased sunlight exposure; however, a hierarchical cluster analysis revealed that the members of this family were grouped into three distinct accumulation patterns, with malvidin anthocyanins and cyanidin-glucoside showing contrasting trends. The flavonol-glucosides, quercetin and kaempferol, exhibited a logarithmic response to SI, leading to improved cluster uniformity under high-light conditions. Comparing the within-cluster variability of metabolite accumulation highlighted the stability of sugars, flavan-3-ols, and cinnamic acid metabolites to SI, in contrast to the plasticity of flavonols. A correlation-based network analysis revealed that extended exposure to SI modified metabolic coordination, increasing the number of negative correlations between metabolites in both pulp and skin. This integrated study of micrometeorology and metabolomics provided insights into the grape-cluster pattern of accumulation of 70 primary and secondary metabolites as a function of spatial variations in SI. Studying compound-specific responses against an extended gradient of quantified conditions improved our knowledge regarding the modulation of berry metabolism by SI, with the aim of using sunlight regulation to accurately modulate fruit composition in warm and arid/semi-arid regions.

Sunlight Modulates Fruit Metabolic Profile and Shapes the Spatial Pattern of Compound Accumulation within the Grape Cluster

PubMed Central

Reshef, Noam; Walbaum, Natasha; Agam, Nurit; Fait, Aaron

2017-01-01

Vineyards are characterized by their large spatial variability of solar irradiance (SI) and temperature, known to effectively modulate grape metabolism. To explore the role of sunlight in shaping fruit composition and cluster uniformity, we studied the spatial pattern of incoming irradiance, fruit temperature and metabolic profile within individual grape clusters under three levels of sunlight exposure. The experiment was conducted in a vineyard of Cabernet Sauvignon cv. located in the Negev Highlands, Israel, where excess SI and midday temperatures are known to degrade grape quality. Filtering SI lowered the surface temperature of exposed fruits and increased the uniformity of irradiance and temperature in the cluster zone. SI affected the overall levels and patterns of accumulation of sugars, organic acids, amino acids and phenylpropanoids, across the grape cluster. Increased exposure to sunlight was associated with lower accumulation levels of malate, aspartate, and maleate but with higher levels of valine, leucine, and serine, in addition to the stress-related proline and GABA. Flavan-3-ols metabolites showed a negative response to SI, whereas flavonols were highly induced. The overall levels of anthocyanins decreased with increased sunlight exposure; however, a hierarchical cluster analysis revealed that the members of this family were grouped into three distinct accumulation patterns, with malvidin anthocyanins and cyanidin-glucoside showing contrasting trends. The flavonol-glucosides, quercetin and kaempferol, exhibited a logarithmic response to SI, leading to improved cluster uniformity under high-light conditions. Comparing the within-cluster variability of metabolite accumulation highlighted the stability of sugars, flavan-3-ols, and cinnamic acid metabolites to SI, in contrast to the plasticity of flavonols. A correlation-based network analysis revealed that extended exposure to SI modified metabolic coordination, increasing the number of negative correlations between metabolites in both pulp and skin. This integrated study of micrometeorology and metabolomics provided insights into the grape-cluster pattern of accumulation of 70 primary and secondary metabolites as a function of spatial variations in SI. Studying compound-specific responses against an extended gradient of quantified conditions improved our knowledge regarding the modulation of berry metabolism by SI, with the aim of using sunlight regulation to accurately modulate fruit composition in warm and arid/semi-arid regions. PMID:28203242

Mapping forest structure, species gradients and growth in an urban area using lidar and hyperspectral imagery

NASA Astrophysics Data System (ADS)

Gu, Huan

Urban forests play an important role in the urban ecosystem by providing a range of ecosystem services. Characterization of forest structure, species variation and growth in urban forests is critical for understanding the status, function and process of urban ecosystems, and helping maximize the benefits of urban ecosystems through management. The development of methods and applications to quantify urban forests using remote sensing data has lagged the study of natural forests due to the heterogeneity and complexity of urban ecosystems. In this dissertation, I quantify and map forest structure, species gradients and forest growth in an urban area using discrete-return lidar, airborne imaging spectroscopy and thermal infrared data. Specific objectives are: (1) to demonstrate the utility of leaf-off lidar originally collected for topographic mapping to characterize and map forest structure and associated uncertainties, including aboveground biomass, basal area, diameter, height and crown size; (2) to map species gradients using forest structural variables estimated from lidar and foliar functional traits, vegetation indices derived from AVIRIS hyperspectral imagery in conjunction with field-measured species data; and (3) to identify factors related to relative growth rates in aboveground biomass in the urban forests, and assess forest growth patterns across areas with varying degree of human interactions. The findings from this dissertation are: (1) leaf-off lidar originally acquired for topographic mapping provides a robust, potentially low-cost approach to quantify spatial patterns of forest structure and carbon stock in urban areas; (2) foliar functional traits and vegetation indices from hyperspectral data capture gradients of species distributions in the heterogeneous urban landscape; (3) species gradients, stand structure, foliar functional traits and temperature are strongly related to forest growth in the urban forests; and (4) high uncertainties in our ability to map forest structure, species gradient and growth rate occur in residential neighborhoods and along forest edges. Maps generated from this dissertation provide estimates of broad-scale spatial variations in forest structure, species distributions and growth to the city forest managers. The associated maps of uncertainty help managers understand the limitations of the maps and identify locations where the maps are more reliable and where more data are needed.

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.

Investigating the performance of reconstruction methods used in structured illumination microscopy as a function of the illumination pattern's modulation frequency

NASA Astrophysics Data System (ADS)

Shabani, H.; Sánchez-Ortiga, E.; Preza, C.

2016-03-01

Surpassing the resolution of optical microscopy defined by the Abbe diffraction limit, while simultaneously achieving optical sectioning, is a challenging problem particularly for live cell imaging of thick samples. Among a few developing techniques, structured illumination microscopy (SIM) addresses this challenge by imposing higher frequency information into the observable frequency band confined by the optical transfer function (OTF) of a conventional microscope either doubling the spatial resolution or filling the missing cone based on the spatial frequency of the pattern when the patterned illumination is two-dimensional. Standard reconstruction methods for SIM decompose the low and high frequency components from the recorded low-resolution images and then combine them to reach a high-resolution image. In contrast, model-based approaches rely on iterative optimization approaches to minimize the error between estimated and forward images. In this paper, we study the performance of both groups of methods by simulating fluorescence microscopy images from different type of objects (ranging from simulated two-point sources to extended objects). These simulations are used to investigate the methods' effectiveness on restoring objects with various types of power spectrum when modulation frequency of the patterned illumination is changing from zero to the incoherent cut-off frequency of the imaging system. Our results show that increasing the amount of imposed information by using a higher modulation frequency of the illumination pattern does not always yield a better restoration performance, which was found to be depended on the underlying object. Results from model-based restoration show performance improvement, quantified by an up to 62% drop in the mean square error compared to standard reconstruction, with increasing modulation frequency. However, we found cases for which results obtained with standard reconstruction methods do not always follow the same trend.

Regional patterns of genetic diversity in swine influenza A viruses in the United States from 2010 to 2016.

PubMed

Walia, Rasna R; Anderson, Tavis K; Vincent, Amy L

2018-04-06

Regular spatial and temporal analyses of the genetic diversity and evolutionary patterns of influenza A virus (IAV) in swine informs control efforts and improves animal health. Initiated in 2009, the USDA passively surveils IAV in U.S. swine, with a focus on subtyping clinical respiratory submissions, sequencing at minimum the hemagglutinin (HA) and neuraminidase (NA) genes, and sharing these data publicly. In this study, our goal was to quantify and describe regional and national patterns in the genetic diversity and evolution of IAV in U.S. swine from 2010 to 2016. A comprehensive phylogenetic and epidemiological analysis of publicly available HA and NA genes generated by the USDA surveillance system collected from January 2010 to December 2016 was conducted. The dominant subtypes and genetic clades detected during the study period were H1N1 (H1-γ/1A.3.3.3, N1-classical, 29%), H1N2 (H1-δ1/1B.2.2, N2-2002, 27%), and H3N2 (H3-IV-A, N2-2002, 15%), but many other minor clades were also maintained. Year-round circulation was observed, with a primary epidemic peak in October-November and a secondary epidemic peak in March-April. Partitioning these data into 5 spatial zones revealed that genetic diversity varied regionally and was not correlated with aggregated national patterns of HA/NA diversity. These data suggest that vaccine composition and control efforts should consider IAV diversity within swine production regions in addition to aggregated national patterns. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Complex responses of spring alpine vegetation phenology to snow cover dynamics over the Tibetan Plateau, China.

PubMed

Wang, Siyuan; Wang, Xiaoyue; Chen, Guangsheng; Yang, Qichun; Wang, Bin; Ma, Yuanxu; Shen, Ming

2017-09-01

Snow cover dynamics are considered to play a key role on spring phenological shifts in the high-latitude, so investigating responses of spring phenology to snow cover dynamics is becoming an increasingly important way to identify and predict global ecosystem dynamics. In this study, we quantified the temporal trends and spatial variations of spring phenology and snow cover across the Tibetan Plateau by calibrating and analyzing time series of the NOAA AVHRR-derived normalized difference vegetation index (NDVI) during 1983-2012. We also examined how snow cover dynamics affect the spatio-temporal pattern of spring alpine vegetation phenology over the plateau. Our results indicated that 52.21% of the plateau experienced a significant advancing trend in the beginning of vegetation growing season (BGS) and 34.30% exhibited a delaying trend. Accordingly, the snow cover duration days (SCD) and snow cover melt date (SCM) showed similar patterns with a decreasing trend in the west and an increasing trend in the southeast, but the start date of snow cover (SCS) showed an opposite pattern. Meanwhile, the spatial patterns of the BGS, SCD, SCS and SCM varied in accordance with the gradients of temperature, precipitation and topography across the plateau. The response relationship of spring phenology to snow cover dynamics varied within different climate, terrain and alpine plant community zones, and the spatio-temporal response patterns were primarily controlled by the long-term local heat-water conditions and topographic conditions. Moreover, temperature and precipitation played a profound impact on diverse responses of spring phenology to snow cover dynamics. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2013-01-01

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

A cross-shelf gradient in δ15N stable isotope values of krill and pollock indicates seabird foraging patterns in the Bering Sea

NASA Astrophysics Data System (ADS)

Jones, Nathan M.; Hoover, Brian A.; Heppell, Scott A.; Kuletz, Kathy J.

2014-11-01

Concurrent measurements of predator and prey δ15N isotope values demonstrated that a cross-shelf isotopic gradient can propagate through a marine food web from forage species to top-tier predators and indicate foraging areas at a scale of tens of kilometers. We measured δ13C and δ15N in muscle tissues of thick-billed murres (Uria lomvia) and black-legged kittiwakes (Rissa tridactyla), and in whole body tissues of walleye pollock (Gadus chalcogrammus) and krill (Thysanoessa spp), sampled across the continental shelf break in the Bering Sea in 2008 and in 2009. We found significant basin-shelf differences at fine scales (<100 km) in δ15N among murres but not kittiwakes, and no such differences in δ13C in either seabird species at that scale. We then quantified the multi-trophic signal and spatial structure of a basin-shelf δ15Nitrogen gradient in the central and southern Bering Sea, and used it to contrast foraging patterns of thick-billed murres and kittiwakes on the open ocean. Seabird muscle δ15N values were compared to baselines created from measurements in krill and pollock tissues sampled concurrently throughout the study area. Krill, pollock, and murre tissues from northern, shallow, shelf habitat (<200 m) were enriched 1-2‰ in δ15N relative to samples taken from deeper habitats (>200 m) to the south and west. Krill δ15N baseline values predicted 35-42% of the variability in murre tissue values. Patterns between kittiwakes and prey were less coherent. The persistence of strong spatial autocorrelation among sample values, and a congruence of geospatial patterns in δ15N among murre and prey tissues, suggest that murres forage repeatedly in specific areas. Murre isotope values showed distinct geospatial stratification, coincident with the spatial distribution of three colonies: St. Paul, St. George, and Bogoslof. This suggests some degree of foraging habitat partitioning among colonies.

The cross wavelet and wavelet coherence analysis of spatio-temporal rainfall-groundwater system in Pingtung plain, Taiwan

NASA Astrophysics Data System (ADS)

Lin, Yuan-Chien; Yu, Hwa-Lung

2013-04-01

The increasing frequency and intensity of extreme rainfall events has been observed recently in Taiwan. Particularly, Typhoon Morakot, Typhoon Fanapi, and Typhoon Megi consecutively brought record-breaking intensity and magnitude of rainfalls to different locations of Taiwan in these two years. However, records show the extreme rainfall events did not elevate the amount of annual rainfall accordingly. Conversely, the increasing frequency of droughts has also been occurring in Taiwan. The challenges have been confronted by governmental agencies and scientific communities to come up with effective adaptation strategies for natural disaster reduction and sustainable environment establishment. Groundwater has long been a reliable water source for a variety of domestic, agricultural, and industrial uses because of its stable quantity and quality. In Taiwan, groundwater accounts for the largest proportion of all water resources for about 40%. This study plans to identify and quantify the nonlinear relationship between precipitation and groundwater recharge, find the non-stationary time-frequency relations between the variations of rainfall and groundwater levels to understand the phase difference of time series. Groundwater level data and over-50-years hourly rainfall records obtained from 20 weather stations in Pingtung Plain, Taiwan has been collected. Extract the space-time pattern by EOF method, which is a decomposition of a signal or data set in terms of orthogonal basis functions determined from the data for both time series and spatial patterns, to identify the important spatial pattern of groundwater recharge and using cross wavelet and wavelet coherence method to identify the relationship between rainfall and groundwater levels. Results show that EOF method can specify the spatial-temporal patterns which represents certain geological characteristics and other mechanisms of groundwater, and the wavelet coherence method can identify general correlation between rainfall and groundwater signal at low frequency and high frequency relationship at some certain extreme rainfall events. Keywords: extreme rainfall, groundwater, EOF, wavelet coherence

Curvature by design and on demand in liquid crystal elastomers

NASA Astrophysics Data System (ADS)

Kowalski, B. A.; Mostajeran, C.; Godman, N. P.; Warner, M.; White, T. J.

2018-01-01

The shape of liquid crystalline elastomers (LCEs) with spatial variation in the director orientation can be transformed by exposure to a stimulus. Here, informed by previously reported analytical treatments, we prepare complex spiral patterns imprinted into LCEs and quantify the resulting shape transformation. Quantification of the stimuli-induced shapes reveals good agreement between predicted and experimentally observed curvatures. We conclude this communication by reporting a design strategy to allow LCE films to be anchored at their external boundaries onto rigid substrates without incurring internal, mechanical-mismatch stresses upon actuation, a critical advance to the realization of shape transformation of LCEs in practical device applications.

The resolution capability of an irregularly sampled dataset: With application to Geosat altimeter data

NASA Technical Reports Server (NTRS)

Chelton, Dudley B.; Schlax, Michael G.

1994-01-01

A formalism is presented for determining the wavenumber-frequency transfer function associated with an irregularly sampled multidimensional dataset. This transfer function reveals the filtering characteristics and aliasing patterns inherent in the sample design. In combination with information about the spectral characteristics of the signal, the transfer function can be used to quantify the spatial and temporal resolution capability of the dataset. Application of the method to idealized Geosat altimeter data (i.e., neglecting measurement errors and data dropouts) concludes that the Geosat orbit configuration is capable of resolving scales of about 3 deg in latitude and longitude by about 30 days.

Temporal and spatial patterns of wetland extent influence variability of surface water connectivity in the Prairie Pothole Region, United States

USGS Publications Warehouse

Vanderhoof, Melanie; Alexander, Laurie C.; Todd, Jason

2016-01-01

Context. Quantifying variability in landscape-scale surface water connectivity can help improve our understanding of the multiple effects of wetlands on downstream waterways. Objectives. We examined how wetland merging and the coalescence of wetlands with streams varied both spatially (among ecoregions) and interannually (from drought to deluge) across parts of the Prairie Pothole Region. Methods. Wetland extent was derived over a time series (1990-2011) using Landsat imagery. Changes in landscape-scale connectivity, generated by the physical coalescence of wetlands with other surface water features, were quantified by fusing static wetland and stream datasets with Landsat-derived wetland extent maps, and related to multiple wetness indices. The usage of Landsat allows for decadal-scale analysis, but limits the types of surface water connections that can be detected. Results. Wetland extent correlated positively with the merging of wetlands and wetlands with streams. Wetness conditions, as defined by drought indices and runoff, were positively correlated with wetland extent, but less consistently correlated with measures of surface water connectivity. The degree of wetland-wetland merging was found to depend less on total wetland area or density, and more on climate conditions, as well as the threshold for how wetland/upland was defined. In contrast, the merging of wetlands with streams was positively correlated with stream density, and inversely related to wetland density. Conclusions. Characterizing the degree of surface water connectivity within the Prairie Pothole Region in North America requires consideration of 1) climate-driven variation in wetness conditions and 2) within-region variation in wetland and stream spatial arrangements.

The Transcriptional Regulator CBP Has Defined Spatial Associations within Interphase Nuclei

PubMed Central

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

2006-01-01

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

Spatial distribution of enzyme activities along the root and in the rhizosphere of different plants

NASA Astrophysics Data System (ADS)

Razavi, Bahar S.; Zarebanadkouki, Mohsen; Blagodatskaya, Evgenia; Kuzyakov, Yakov

2015-04-01

Extracellular enzymes are important for decomposition of many biological macromolecules abundant in soil such as cellulose, hemicelluloses and proteins. Activities of enzymes produced by both plant roots and microbes are the primary biological drivers of organic matter decomposition and nutrient cycling. So far acquisition of in situ data about local activity of different enzymes in soil has been challenged. That is why there is an urgent need in spatially explicit methods such as 2-D zymography to determine the variation of enzymes along the roots in different plants. Here, we developed further the zymography technique in order to quantitatively visualize the enzyme activities (Spohn and Kuzyakov, 2013), with a better spatial resolution We grew Maize (Zea mays L.) and Lentil (Lens culinaris) in rhizoboxes under optimum conditions for 21 days to study spatial distribution of enzyme activity in soil and along roots. We visualized the 2D distribution of the activity of three enzymes:β-glucosidase, leucine amino peptidase and phosphatase, using fluorogenically labelled substrates. Spatial resolution of fluorescent images was improved by direct application of a substrate saturated membrane to the soil-root system. The newly-developed direct zymography shows different pattern of spatial distribution of enzyme activity along roots and soil of different plants. We observed a uniform distribution of enzyme activities along the root system of Lentil. However, root system of Maize demonstrated inhomogeneity of enzyme activities. The apical part of an individual root (root tip) in maize showed the highest activity. The activity of all enzymes was the highest at vicinity of the roots and it decreased towards the bulk soil. Spatial patterns of enzyme activities as a function of distance from the root surface were enzyme specific, with highest extension for phosphatase. We conclude that improved zymography is promising in situ technique to analyze, visualize and quantify spatial distribution of enzyme activities in the rhizosphere hotspots. References Spohn, M., Kuzyakov, Y., 2013. Phosphorus mineralization can be driven by microbial need for carbon. Soil Biology & Biochemistry 61: 69-75