Balint, Lajos; Dome, Peter; Daroczi, Gergely; Gonda, Xenia; Rihmer, Zoltan
2014-02-01
In the last century Hungary had astonishingly high suicide rates characterized by marked regional within-country inequalities, a spatial pattern which has been quite stable over time. To explain the above phenomenon at the level of micro-regions (n=175) in the period between 2005 and 2011. Our dependent variable was the age and gender standardized mortality ratio (SMR) for suicide while explanatory variables were factors which are supposed to influence suicide risk, such as measures of religious and political integration, travel time accessibility of psychiatric services, alcohol consumption, unemployment and disability pensionery. When applying the ordinary least squared regression model, the residuals were found to be spatially autocorrelated, which indicates the violation of the assumption on the independence of error terms and - accordingly - the necessity of application of a spatial autoregressive (SAR) model to handle this problem. According to our calculations the SARlag model was a better way (versus the SARerr model) of addressing the problem of spatial autocorrelation, furthermore its substantive meaning is more convenient. SMR was significantly associated with the "political integration" variable in a negative and with "lack of religious integration" and "disability pensionery" variables in a positive manner. Associations were not significant for the remaining explanatory variables. Several important psychiatric variables were not available at the level of micro-regions. We conducted our analysis on aggregate data. Our results may draw attention to the relevance and abiding validity of the classic Durkheimian suicide risk factors - such as lack of social integration - apropos of the spatial pattern of Hungarian suicides. © 2013 Published by Elsevier B.V.
Long-term demography of the Northern Goshawk in a variable environment
Richard T. Reynolds; Jeffrey S. Lambert; Curtis H. Flather; Gary C. White; Benjamin J. Bird; L. Scott Baggett; Carrie Lambert; Shelley Bayard De Bolo
2017-01-01
The Nearctic northern goshawk (Accipiter gentilis atricapillis) is a resident of conifer, broadleaf, and mixed forests from the boreal to the southwestern montane regions of North America. We report on a 20-year mark-recapture investigation (1991-2010) of the distribution and density of breeders, temporal and spatial variability in breeding, nestling sex ratios, local...
The Ocean's Role in Outlet Glacier Variability: A Case Study from Uummannaq, Greenland
NASA Astrophysics Data System (ADS)
Sutherland, D.; Catania, G. A.; Bartholomaus, T. C.; Nash, J. D.; Shroyer, E.; Walker, R. T.; Stearns, L. A.
2014-12-01
The dynamics controlling the coupling between fjord circulation and outlet glacier movement are poorly understood. Here, we use oceanographic data collected from 2013-2014 from two west Greenland fjords, Rink Isbrae and Kangerdlugssup Sermerssua, to constrain the spatial and temporal variability observed in fjord circulation. We aim to quantify the ocean's role, if any, in explaining the marked differences in glacier behavior from two systems that are in close proximity to one another. Combining time series data from a set of subsurface moorings with repeat transects in each fjord allows an unprecedented look at the temporal and spatial variability in circulation. We find significant differences in the variability in each fjord and discuss the implications for the glaciers.
Spatial characteristics of net methylmercury production hot spots in peatlands
Carl P.J. Mitchell; Brian A. Branfireun; Randall K. Kolka
2008-01-01
Many wetlands are sources of methylmercury (MeHg) to surface waters, yet little information exists about the distribution of MeHg within wetlands. Total mercury (THg) and MeHg in peat pore waters were studied in four peatlands in spring, summer, and fall 2005. Marked spatial variability in the distribution of MeHg, and %MeHg as a proxy for net MeHg production, was...
Burke, Ariane; Levavasseur, Guillaume; James, Patrick M A; Guiducci, Dario; Izquierdo, Manuel Arturo; Bourgeon, Lauriane; Kageyama, Masa; Ramstein, Gilles; Vrac, Mathieu
2014-08-01
The Last Glacial Maximum (LGM) was a global climate event, which had significant repercussions for the spatial distribution and demographic history of prehistoric populations. In Eurasia, the LGM coincides with a potential bottleneck for modern humans and may mark the divergence date for Asian and European populations (Keinan et al., 2007). In this research, the impact of climate variability on human populations in the Iberian Peninsula during the Last Glacial Maximum (LGM) is examined with the aid of downscaled high-resolution (16 × 16 km) numerical climate experiments. Human sensitivity to short time-scale (inter-annual) climate variability during this key time period, which follows the initial modern human colonisation of Eurasia and the extinction of the Neanderthals, is tested using the spatial distribution of archaeological sites. Results indicate that anatomically modern human populations responded to small-scale spatial patterning in climate variability, specifically inter-annual variability in precipitation levels as measured by the standard precipitation index. Climate variability at less than millennial scale, therefore, is shown to be an important component of ecological risk, one that played a role in regulating the spatial behaviour of prehistoric human populations and consequently affected their social networks. Copyright © 2014 Elsevier Ltd. All rights reserved.
Lebedev, Mikhail A; Pimashkin, Alexey; Ossadtchi, Alexei
2018-01-01
According to the currently prevailing theory, hippocampal formation constructs and maintains cognitive spatial maps. Most of the experimental evidence for this theory comes from the studies on navigation in laboratory rats and mice, typically male animals. While these animals exhibit a rich repertoire of behaviors associated with navigation, including locomotion, head movements, whisking, sniffing, raring and scent marking, the contribution of these behavioral patterns to the hippocampal spatially-selective activity has not been sufficiently studied. Instead, many publications have considered animal position in space as the major variable that affects the firing of hippocampal place cells and entorhinal grid cells. Here we argue that future work should focus on a more detailed examination of different behaviors exhibited during navigation to better understand the mechanism of spatial tuning in hippocampal neurons. As an inquiry in this direction, we have analyzed data from two datasets, shared online, containing recordings from rats navigating in square and round arenas. Our analyses revealed patchy navigation patterns, evident from the spatial maps of animal position, velocity and acceleration. Moreover, grid cells available in the datasets exhibited similar periodicity as the navigation parameters. These findings indicate that activity of grid cells could affect navigation parameters and/or vice versa. Additionally, we speculate that scent marks left by navigating animals could contribute to neuronal responses while rats and mice sniff their environment; the act of sniffing could modulate neuronal discharges even in virtual visual environments. Accordingly, we propose that future experiments should contain additional controls for navigation patterns, whisking, sniffing and maps composed of scent marks.
Gromov, V S
1997-01-01
Sex-age and seasonal variability of the ventral glands and different stereotypes of scent marking behaviour in four Meriones species (M. unguiculatus, M. meridianus, M. libycus, M. tamariscinus) have been studied in nature and under semi-natural conditions. Two major ways of olfactory marking are considered: by secretion of the ventral glands and by "signal heaps" with urine and feces. Intraspecific and inter-species variability of marking activity is investigated. The ventral glands start to function at the period of preparation of a generative system to reproduction. The peak of secretary activity of gland and maximum of two types of marking activity is observed in spring and early summer, i.e. the period of active reproduction. The maximum of two types of the marking activity is observed during this period. In M. tamariscinus and M. meridianus the marking by the ventral gland is prevailing mode of the territory scent marking, while Mongolian gerbils (M. unguiculatus) prefer to use "signal heaps" Libyan gerbils (M. libycus) in this relation take an intermediate position. At the non-productive period a level of marking activity is on 10-20 times lower than at the reproductive season. Besides hormonal, social factors were also important for regulation of marking activity. By influence of these factors the differences in the level of marking activity in high-rank and low-rank individuals and differences in patterns of a spatial distribution of scent marks in individuals of different hierarchical rank is explained. Functional significance of various ways of territory scent marking is discussed.
Nordey, Thibault; Léchaudel, Mathieu; Génard, Michel; Joas, Jacques
2014-11-01
Managing fruit quality is complex because many different attributes have to be taken into account, which are themselves subjected to spatial and temporal variations. Heterogeneous fruit quality has been assumed to be partly related to temperature and maturity gradients within the fruit. To test this assumption, we measured the spatial variability of certain mango fruit quality traits: colour of the peel and of the flesh, and sourness and sweetness, at different stages of fruit maturity using destructive methods as well as vis-NIR reflectance. The spatial variability of mango quality traits was compared to internal variations in thermal time, simulated by a physical model, and to internal variations in maturity, using ethylene content as an indicator. All the fruit quality indicators analysed showed significant spatial and temporal variations, regardless of the measurement method used. The heterogeneity of internal fruit quality traits was not correlated with the marked internal temperature gradient we modelled. However, variations in ethylene content revealed a strong internal maturity gradient which was correlated with the spatial variations in measured mango quality traits. Nonetheless, alone, the internal maturity gradient did not explain the variability of fruit quality traits, suggesting that other factors, such as gas, abscisic acid and water gradients, are also involved. Copyright © 2014 Elsevier GmbH. All rights reserved.
Liu, Gang; Mac Gabhann, Feilim; Popel, Aleksander S.
2012-01-01
The process of oxygen delivery from capillary to muscle fiber is essential for a tissue with variable oxygen demand, such as skeletal muscle. Oxygen distribution in exercising skeletal muscle is regulated by convective oxygen transport in the blood vessels, oxygen diffusion and consumption in the tissue. Spatial heterogeneities in oxygen supply, such as microvascular architecture and hemodynamic variables, had been observed experimentally and their marked effects on oxygen exchange had been confirmed using mathematical models. In this study, we investigate the effects of heterogeneities in oxygen demand on tissue oxygenation distribution using a multiscale oxygen transport model. Muscles are composed of different ratios of the various fiber types. Each fiber type has characteristic values of several parameters, including fiber size, oxygen consumption, myoglobin concentration, and oxygen diffusivity. Using experimentally measured parameters for different fiber types and applying them to the rat extensor digitorum longus muscle, we evaluated the effects of heterogeneous fiber size and fiber type properties on the oxygen distribution profile. Our simulation results suggest a marked increase in spatial heterogeneity of oxygen due to fiber size distribution in a mixed muscle. Our simulations also suggest that the combined effects of fiber type properties, except size, do not contribute significantly to the tissue oxygen spatial heterogeneity. However, the incorporation of the difference in oxygen consumption rates of different fiber types alone causes higher oxygen heterogeneity compared to control cases with uniform fiber properties. In contrast, incorporating variation in other fiber type-specific properties, such as myoglobin concentration, causes little change in spatial tissue oxygenation profiles. PMID:23028531
Schwartz, Charles C.; Haroldson, Mark A.; White, Gary C.; Harris, Richard B.; Cherry, Steve; Keating, Kim A.; Moody, Dave; Servheen, Christopher
2006-01-01
During the past 2 decades, the grizzly bear (Ursus arctos) population in the Greater Yellowstone Ecosystem (GYE) has increased in numbers and expanded in range. Understanding temporal, environmental, and spatial variables responsible for this change is useful in evaluating what likely influenced grizzly bear demographics in the GYE and where future management efforts might benefit conservation and management. We used recent data from radio-marked bears to estimate reproduction (1983–2002) and survival (1983–2001); these we combined into models to evaluate demographic vigor (lambda [λ]). We explored the influence of an array of individual, temporal, and spatial covariates on demographic vigor.
NASA Astrophysics Data System (ADS)
Fabris, L.; Malcolm, I.; Millidine, K. J.; Buddendorf, B.; Tetzlaff, D.; Soulsby, C.
2015-12-01
Wild Atlantic salmon populations in Scottish rivers constitute an important economic and recreational resource, as well as being a key component of biodiversity. Salmon have very specific habitat requirements at different life stages and their distribution is therefore strongly influenced by a complex suite of biological and physical controls. Previous research has shown that stream hydrodynamics and channel morphology have a strong influence on the distribution and density of juvenile salmon. Here, we utilise a unique 20 year data set of spatially distributed juvenile salmon densities derived from annual electro-fishing surveys in an upland Scottish river. We examine to what extent the spatial and temporal variability of in-stream hydraulics regulates the spatial and temporal variability in the performance and density of juvenile salmon. A 2-D hydraulic model (River2D) is used to simulate water velocity and water depth under different flow conditions for seven different electro-fishing sites. The selected sites represent different hydromorphological environments including plane-bed, step-pool and pool riffle reaches. The bathymetry of each site was characterised using a total station providing an accurate DTM of the bed, and hydraulic simulations were driven by 20 year stream flow records. Habitat suitability curves, based on direct observations during electro-fishing surveys, were produced for a range of hydraulic indices for juvenile salmon. The hydraulic simulations showed marked spatial differences in juvenile habitat quality both within and between reaches. They also showed marked differences both within and between years. This is most evident in extreme years with wet summers when salmon feeding opportunities may be constrained. Integration of hydraulic habitat models, with fish preference curves and the long term hydrological data allows us to assess whether long-term changes in hydroclimate may be affecting juvenile salmonid populations in the study stream.Wild Atlantic salmon populations in Scottish rivers constitute an important economic and recreational resource, as well as being a key component of biodiversity. Salmon have very specific habitat requirements at different life stages and their distribution is therefore strongly influenced by a complex suite of biological and physical controls. Previous research has shown that stream hydrodynamics and channel morphology have a strong influence on the distribution and density of juvenile salmon. Here, we utilise a unique 20 year data set of spatially distributed juvenile salmon densities derived from annual electro-fishing surveys in an upland Scottish river. We examine to what extent the spatial and temporal variability of in-stream hydraulics regulates the spatial and temporal variability in the performance and density of juvenile salmon. A 2-D hydraulic model (River2D) is used to simulate water velocity and water depth under different flow conditions for seven different electro-fishing sites. The selected sites represent different hydromorphological environments including plane-bed, step-pool and pool riffle reaches. The bathymetry of each site was characterised using a total station providing an accurate DTM of the bed, and hydraulic simulations were driven by 20 year stream flow records. Habitat suitability curves, based on direct observations during electro-fishing surveys, were produced for a range of hydraulic indices for juvenile salmon. The hydraulic simulations showed marked spatial differences in juvenile habitat quality both within and between reaches. They also showed marked differences both within and between years. This is most evident in extreme years with wet summers when salmon feeding opportunities may be constrained. Integration of hydraulic habitat models, with fish preference curves and the long term hydrological data allows us to assess whether long-term changes in hydroclimate may be affecting juvenile salmonid populations in the study stream.
Representation of vegetation by continental data sets derived from NOAA-AVHRR data
NASA Technical Reports Server (NTRS)
Justice, C. O.; Townshend, J. R. G.; Kalb, V. L.
1991-01-01
Images of the normalized difference vegetation index (NDVI) are examined with specific attention given to the effect of spatial scales on the understanding of surface phenomena. A scale variance analysis is conducted on NDVI annual and seasonal images of Africa taken from 1987 NOAA-AVHRR data at spatial scales ranging from 8-512 km. The scales at which spatial variation takes place are determined and the relative magnitude of the variations are considered. Substantial differences are demonstrated, notably an increase in spatial variation with coarsening spatial resolution. Different responses in scale variance as a function of spatial resolution are noted in an analysis of maximum value composites for February and September; the difference is most marked in areas with very seasonal vegetation. The spatial variation at different scales is attributed to different factors, and methods involving the averaging of areas of transition and surface heterogeneity can oversimplify surface conditions. The spatial characteristics and the temporal variability of areas should be considered to accurately apply satellite data to global models.
A comparison of small-area hospitalisation rates, estimated morbidity and hospital access.
Shulman, H; Birkin, M; Clarke, G P
2015-11-01
Published data on hospitalisation rates tend to reveal marked spatial variations within a city or region. Such variations may simply reflect corresponding variations in need at the small-area level. However, they might also be a consequence of poorer accessibility to medical facilities for certain communities within the region. To help answer this question it is important to compare these variable hospitalisation rates with small-area estimates of need. This paper first maps hospitalisation rates at the small-area level across the region of Yorkshire in the UK to show the spatial variations present. Then the Health Survey of England is used to explore the characteristics of persons with heart disease, using chi-square and logistic regression analysis. Using the most significant variables from this analysis the authors build a spatial microsimulation model of morbidity for heart disease for the Yorkshire region. We then compare these estimates of need with the patterns of hospitalisation rates seen across the region. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.
Santora, Jarrod A; Schroeder, Isaac D; Field, John C; Wells, Brian K; Sydeman, William J
Studies of predator–prey demographic responses and the physical drivers of such relationships are rare, yet essential for predicting future changes in the structure and dynamics of marine ecosystems. Here, we hypothesize that predator–prey relationships vary spatially in association with underlying physical ocean conditions, leading to observable changes in demographic rates, such as reproduction. To test this hypothesis, we quantified spatio-temporal variability in hydrographic conditions, krill, and forage fish to model predator (seabird) demographic responses over 18 years (1990–2007). We used principal component analysis and spatial correlation maps to assess coherence among ocean conditions, krill, and forage fish, and generalized additive models to quantify interannual variability in seabird breeding success relative to prey abundance. The first principal component of four hydrographic measurements yielded an index that partitioned “warm/weak upwelling” and “cool/strong upwelling” years. Partitioning of krill and forage fish time series among shelf and oceanic regions yielded spatially explicit indicators of prey availability. Krill abundance within the oceanic region was remarkably consistent between years, whereas krill over the shelf showed marked interannual fluctuations in relation to ocean conditions. Anchovy abundance varied on the shelf, and was greater in years of strong stratification, weak upwelling and warmer temperatures. Spatio-temporal variability of juvenile forage fish co-varied strongly with each other and with krill, but was weakly correlated with hydrographic conditions. Demographic responses between seabirds and prey availability revealed spatially variable associations indicative of the dynamic nature of “predator–habitat” relationships. Quantification of spatially explicit demographic responses, and their variability through time, demonstrate the possibility of delineating specific critical areas where the implementation of protective measures could maintain functions and productivity of central place foraging predators.
NASA Astrophysics Data System (ADS)
Encina Aulló-Maestro, María; Hunter, Peter; Spyrakos, Evangelos; Mercatoris, Pierre; Kovács, Attila; Horváth, Hajnalka; Preston, Tom; Présing, Mátyás; Torres Palenzuela, Jesús; Tyler, Andrew
2017-03-01
The development and validation of remote-sensing-based approaches for the retrieval of chromophoric dissolved organic matter (CDOM) concentrations requires a comprehensive understanding of the sources and magnitude of variability in the optical properties of dissolved material within lakes. In this study, spatial and seasonal variability in concentration and composition of CDOM and the origin of its variation was studied in Lake Balaton (Hungary), a large temperate shallow lake in central Europe. In addition, we investigated the effect of photobleaching on the optical properties of CDOM through in-lake incubation experiments. There was marked variability throughout the year in CDOM absorption in Lake Balaton (aCDOM(440) = 0. 06-9.01 m-1). The highest values were consistently observed at the mouth of the main inflow (Zala River), which drains humic-rich material from the adjoining Kis-Balaton wetland, but CDOM absorption decreased rapidly towards the east where it was consistently lower and less variable than in the westernmost lake basins. The spectral slope parameter for the interval of 350-500 nm (SCDOM(350-500)) was more variable with increasing distance from the inflow (observed range 0.0161-0.0181 nm-1 for the mouth of the main inflow and 0.0158-0.0300 nm-1 for waters closer to the outflow). However, spatial variation in SCDOM was more constant exhibiting a negative correlation with aCDOM(440). Dissolved organic carbon (DOC) was strongly positively correlated with aCDOM(440) and followed a similar seasonal trend but it demonstrated more variability than either aCDOM or SCDOM with distance through the system. Photobleaching resulting from a 7-day exposure to natural solar UV radiation resulted in a marked decrease in allochthonous CDOM absorption (7.04 to 3.36 m-1, 42 % decrease). Photodegradation also resulted in an increase in the spectral slope coefficient of dissolved material.
Observed Decrease of North American Winter Temperature Variability
NASA Astrophysics Data System (ADS)
Rhines, A. N.; Tingley, M.; McKinnon, K. A.; Huybers, P. J.
2015-12-01
There is considerable interest in determining whether temperature variability has changed in recent decades. Model ensembles project that extratropical land temperature variance will detectably decrease by 2070. We use quantile regression of station observations to show that decreasing variability is already robustly detectable for North American winter during 1979--2014. Pointwise trends from GHCND stations are mapped into a continuous spatial field using thin-plate spline regression, resolving small-scales while providing uncertainties accounting for spatial covariance and varying station density. We find that variability of daily temperatures, as measured by the difference between the 95th and 5th percentiles, has decreased markedly in winter for both daily minima and maxima. Composites indicate that the reduced spread of winter temperatures primarily results from Arctic amplification decreasing the meridional temperature gradient. Greater observed warming in the 5th relative to the 95th percentile stems from asymmetric effects of advection during cold versus warm days; cold air advection is generally from northerly regions that have experienced greater warming than western or southwestern regions that are generally sourced during warm days.
NASA Astrophysics Data System (ADS)
Llorens, Pilar; Garcia-Estringana, Pablo; Cayuela, Carles; Latron, Jérôme; Molina, Antonio; Gallart, Francesc
2015-04-01
Temporal and spatial variability of throughfall and stemflow patterns, due to differences in forest structure and seasonality of Mediterranean climate, may lead to significant changes in the volume of water that locally reaches the soil, with a potential effect on groundwater recharge and on hydrological response of forested hillslopes. Two forest stands in Mediterranean climatic conditions were studied to explore the role of vegetation on the temporal and spatial redistribution of rainfall. One is a Downy oak forest (Quercus pubescens) and the other is a Scots pine forest (Pinus sylvestris), both located in the Vallcebre research catchments (NE Spain, 42° 12'N, 1° 49'E). These plots are representative of Mediterranean mountain areas with spontaneous afforestation by Scots pine as a consequence of the abandonment of agricultural terraces, formerly covered by Downy oaks. The monitoring design of each plot consists of 20 automatic rain recorders to measuring throughfall, 7 stemflow rings connected to tipping-buckets and 40 automatic soil moisture probes. All data were recorded each 5 min. Bulk rainfall and meteorological conditions above both forest covers were also recorded, and canopy cover and biometric characteristics of the plots were measured. Results indicate a marked temporal stability of throughfall in both stands, and a lower persistence of spatial patterns in the leafless period than in the leafed one in the oaks stand. Moreover, in the oaks plot the ranks of gauges in the leafed and leafless periods were not significantly correlated, indicating different wet and dry hotspots in each season. The spatial distribution of throughfall varied significantly depending on rainfall volume, with small events having larger variability, whereas large events tended to homogenize the relative differences in point throughfall. Soil water content spatial variability increased with increasing soil water content, but direct dependence of soil water content variability on throughfall patterns is difficult to establish.
NASA Astrophysics Data System (ADS)
Smale, Dan A.; Barnes, David K. A.; Barnes, Richard S. K.; Smith, David J.; Suggett, David J.
2012-04-01
Tropical nearshore ecosystems represent global hotspots of marine biodiversity and endemism but are often poorly understood and impacted by human activities. The Seychelles Archipelago (Western Indian Ocean) sustains a wealth of marine life, much of which is threatened by rapid development associated with tourism and climate change. Six marine parks exist within the Archipelago, but their biodiversity value and ecological health are poorly known, especially with regards to non-fish and coral species. Here we investigate spatial patterns of littoral biodiversity on 6 islands, 5 of which were granitic and within marine parks, including the first surveys of Curieuse and Ile Cocos. Our surveys formed a nested sampling design, to facilitate an examination of variability in species richness, faunal abundance, taxonomic distinctness and assemblage composition at multiple spatial scales, from islands (> 100 s km) to quadrats (metres). We identified (mostly to species) and enumerated two target taxa, brachyuran decapod crustaceans and gastropod molluscs, and recorded over 8300 individuals belonging to over 150 species. Crabs and gastropods exhibited different patterns of spatial variability, as crab assemblages were generally more distinct between islands, while gastropod assemblages were markedly variable at the smallest spatial scales of 'patch' and 'quadrat'. Intertidal biodiversity was greatest on Curieuse Island and least at Desroches, the latter was being the only coral atoll we surveyed and thereby differing in its geological and ecological context. We discuss likely drivers of these biodiversity patterns and highlight urgently-needed research directions. Our assessment of the status of poorly-known invertebrate assemblages across the Seychelles will complement more extensive surveys of coral and fish assemblages and, in doing so, provide a useful baseline for monitoring the effects of key stressors in the region, such as coastal development and climate change.
NASA Astrophysics Data System (ADS)
Sycheva, Elena A.; Vasilev, Aleksandr S.; Lashmanov, Oleg U.; Korotaev, Valery V.
2017-06-01
The article is devoted to the optimization of optoelectronic systems of the spatial position of objects. Probabilistic characteristics of the detection of an active structured mark on a random noisy background are investigated. The developed computer model and the results of the study allow us to estimate the probabilistic characteristics of detection of a complex structured mark on a random gradient background, and estimate the error of spatial coordinates. The results of the study make it possible to improve the accuracy of measuring the coordinates of the object. Based on the research recommendations are given on the choice of parameters of the optimal mark structure for use in opticalelectronic systems for monitoring the spatial position of large-sized structures.
Li, Lianfa; Laurent, Olivier; Wu, Jun
2016-02-05
Epidemiological studies suggest that air pollution is adversely associated with pregnancy outcomes. Such associations may be modified by spatially-varying factors including socio-demographic characteristics, land-use patterns and unaccounted exposures. Yet, few studies have systematically investigated the impact of these factors on spatial variability of the air pollution's effects. This study aimed to examine spatial variability of the effects of air pollution on term birth weight across Census tracts and the influence of tract-level factors on such variability. We obtained over 900,000 birth records from 2001 to 2008 in Los Angeles County, California, USA. Air pollution exposure was modeled at individual level for nitrogen dioxide (NO2) and nitrogen oxides (NOx) using spatiotemporal models. Two-stage Bayesian hierarchical non-linear models were developed to (1) quantify the associations between air pollution exposure and term birth weight within each tract; and (2) examine the socio-demographic, land-use, and exposure-related factors contributing to the between-tract variability of the associations between air pollution and term birth weight. Higher air pollution exposure was associated with lower term birth weight (average posterior effects: -14.7 (95 % CI: -19.8, -9.7) g per 10 ppb increment in NO2 and -6.9 (95 % CI: -12.9, -0.9) g per 10 ppb increment in NOx). The variation of the association across Census tracts was significantly influenced by the tract-level socio-demographic, exposure-related and land-use factors. Our models captured the complex non-linear relationship between these factors and the associations between air pollution and term birth weight: we observed the thresholds from which the influence of the tract-level factors was markedly exacerbated or attenuated. Exacerbating factors might reflect additional exposure to environmental insults or lower socio-economic status with higher vulnerability, whereas attenuating factors might indicate reduced exposure or higher socioeconomic status with lower vulnerability. Our Bayesian models effectively combined a priori knowledge with training data to infer the posterior association of air pollution with term birth weight and to evaluate the influence of the tract-level factors on spatial variability of such association. This study contributes new findings about non-linear influences of socio-demographic factors, land-use patterns, and unaccounted exposures on spatial variability of the effects of air pollution.
Suzuki, Satoshi N; Kachi, Naoki; Suzuki, Jun-Ichirou
2008-09-01
During the development of an even-aged plant population, the spatial distribution of individuals often changes from a clumped pattern to a random or regular one. The development of local size hierarchies in an Abies forest was analysed for a period of 47 years following a large disturbance in 1959. In 1980 all trees in an 8 x 8 m plot were mapped and their height growth after the disturbance was estimated. Their mortality and growth were then recorded at 1- to 4-year intervals between 1980 and 2006. Spatial distribution patterns of trees were analysed by the pair correlation function. Spatial correlations between tree heights were analysed with a spatial autocorrelation function and the mark correlation function. The mark correlation function was able to detect a local size hierarchy that could not be detected by the spatial autocorrelation function alone. The small-scale spatial distribution pattern of trees changed from clumped to slightly regular during the 47 years. Mortality occurred in a density-dependent manner, which resulted in regular spacing between trees after 1980. The spatial autocorrelation and mark correlation functions revealed the existence of tree patches consisting of large trees at the initial stage. Development of a local size hierarchy was detected within the first decade after the disturbance, although the spatial autocorrelation was not negative. Local size hierarchies that developed persisted until 2006, and the spatial autocorrelation became negative at later stages (after about 40 years). This is the first study to detect local size hierarchies as a prelude to regular spacing using the mark correlation function. The results confirm that use of the mark correlation function together with the spatial autocorrelation function is an effective tool to analyse the development of a local size hierarchy of trees in a forest.
NASA Astrophysics Data System (ADS)
Westerberg, I.; Walther, A.; Guerrero, J.-L.; Coello, Z.; Halldin, S.; Xu, C.-Y.; Chen, D.; Lundin, L.-C.
2010-08-01
An accurate description of temporal and spatial precipitation variability in Central America is important for local farming, water supply and flood management. Data quality problems and lack of consistent precipitation data impede hydrometeorological analysis in the 7,500 km2 Choluteca River basin in central Honduras, encompassing the capital Tegucigalpa. We used precipitation data from 60 daily and 13 monthly stations in 1913-2006 from five local authorities and NOAA's Global Historical Climatology Network. Quality control routines were developed to tackle the specific data quality problems. The quality-controlled data were characterised spatially and temporally, and compared with regional and larger-scale studies. Two gap-filling methods for daily data and three interpolation methods for monthly and mean annual precipitation were compared. The coefficient-of-correlation-weighting method provided the best results for gap-filling and the universal kriging method for spatial interpolation. In-homogeneity in the time series was the main quality problem, and 22% of the daily precipitation data were too poor to be used. Spatial autocorrelation for monthly precipitation was low during the dry season, and correlation increased markedly when data were temporally aggregated from a daily time scale to 4-5 days. The analysis manifested the high spatial and temporal variability caused by the diverse precipitation-generating mechanisms and the need for an improved monitoring network.
A spatial mark–resight model augmented with telemetry data
Sollmann, Rachel; Gardner, Beth; Parsons, Arielle W.; Stocking, Jessica J.; McClintock, Brett T.; Simons, Theodore R.; Pollock, Kenneth H.; O’Connell, Allan F.
2013-01-01
Abundance and population density are fundamental pieces of information for population ecology and species conservation, but they are difficult to estimate for rare and elusive species. Mark-resight models are popular for estimating population abundance because they are less invasive and expensive than traditional mark-recapture. However, density estimation using mark-resight is difficult because the area sampled must be explicitly defined, historically using ad-hoc approaches. We develop a spatial mark-resight model for estimating population density that combines spatial resighting data and telemetry data. Incorporating telemetry data allows us to inform model parameters related to movement and individual location. Our model also allows 2. The model presented here will have widespread utility in future applications, especially for species that are not naturally marked.
NASA Astrophysics Data System (ADS)
Fathalli, Bilel; Pohl, Benjamin; Castel, Thierry; Safi, Mohamed Jomâa
2018-02-01
Temporal and spatial variability of rainfall over Tunisia (at 12 km spatial resolution) is analyzed in a multi-year (1992-2011) ten-member ensemble simulation performed using the WRF model, and a sample of regional climate hindcast simulations from Euro-CORDEX. RCM errors and skills are evaluated against a dense network of local rain gauges. Uncertainties arising, on the one hand, from the different model configurations and, on the other hand, from internal variability are furthermore quantified and ranked at different timescales using simple spread metrics. Overall, the WRF simulation shows good skill for simulating spatial patterns of rainfall amounts over Tunisia, marked by strong altitudinal and latitudinal gradients, as well as the rainfall interannual variability, in spite of systematic errors. Mean rainfall biases are wet in both DJF and JJA seasons for the WRF ensemble, while they are dry in winter and wet in summer for most of the used Euro-CORDEX models. The sign of mean annual rainfall biases over Tunisia can also change from one member of the WRF ensemble to another. Skills in regionalizing precipitation over Tunisia are season dependent, with better correlations and weaker biases in winter. Larger inter-member spreads are observed in summer, likely because of (1) an attenuated large-scale control on Mediterranean and Tunisian climate, and (2) a larger contribution of local convective rainfall to the seasonal amounts. Inter-model uncertainties are globally stronger than those attributed to model's internal variability. However, inter-member spreads can be of the same magnitude in summer, emphasizing the important stochastic nature of the summertime rainfall variability over Tunisia.
NASA Astrophysics Data System (ADS)
Liu, Shurong; Herbst, Michael; Bol, Roland; Gottselig, Nina; Pütz, Thomas; Weymann, Daniel; Wiekenkamp, Inge; Vereecken, Harry; Brüggemann, Nicolas
2016-04-01
Hydroxylamine (NH2OH), a reactive intermediate of several microbial nitrogen turnover processes, is a potential precursor of nitrous oxide (N2O) formation in the soil. However, the contribution of soil NH2OH to soil N2O emission rates in natural ecosystems is unclear. Here, we determined the spatial variability of NH2OH content and potential N2O emission rates of organic (Oh) and mineral (Ah) soil layers of a Norway spruce forest, using a recently developed analytical method for the determination of soil NH2OH content, combined with a geostatistical Kriging approach. Potential soil N2O emission rates were determined by laboratory incubations under oxic conditions, followed by gas chromatographic analysis and complemented by ancillary measurements of soil characteristics. Stepwise multiple regressions demonstrated that the potential N2O emission rates, NH2OH and nitrate (NO3-) content were spatially highly correlated, with hotspots for all three parameters observed in the headwater of a small creek flowing through the sampling area. In contrast, soil ammonium (NH4+) was only weakly correlated with potential N2O emission rates, and was excluded from the multiple regression models. While soil NH2OH content explained the potential soil N2O emission rates best for both layers, also NO3- and Mn content turned out to be significant parameters explaining N2O formation in both soil layers. The Kriging approach was improved markedly by the addition of the co-variable information of soil NH2OH and NO3- content. The results indicate that determination of soil NH2OH content could provide crucial information for the prediction of the spatial variability of soil N2O emissions.
Iordanova, B.; Rosenbaum, D.; Norman, D.; Weiner, M.; Studholme, C.
2007-01-01
BACKGROUND AND PURPOSE Brain volumetry is widely used for evaluating tissue degeneration; however, the parcellation methods are rarely validated and use arbitrary planes to mark boundaries of brain regions. The goal of this study was to develop, validate, and apply an MR imaging tracing method for the parcellation of 3 major gyri of the frontal lobe, which uses only local landmarks intrinsic to the structures of interest, without the need for global reorientation or the use of dividing planes or lines. METHODS Studies were performed on 25 subjects—healthy controls and subjects diagnosed with Lewy body dementia and Alzheimer disease—with significant variation in the underlying gyral anatomy and state of atrophy. The protocol was evaluated by using multiple observers tracing scans of subjects diagnosed with neurodegenerative disease and those aging normally, and the results were compared by spatial overlap agreement. To confirm the results, observers marked the same locations in different brains. We illustrated the variabilities of the key boundaries that pose the greatest challenge to defining consistent parcellations across subjects. RESULTS The resulting gyral volumes were evaluated, and their consistency across raters was used as an additional assessment of the validity of our marking method. The agreement on a scale of 0–1 was found to be 0.83 spatial and 0.90 volumetric for the same rater and 0.85 spatial and 0.90 volumetric for 2 different raters. The results revealed that the protocol remained consistent across different neurodegenerative conditions. CONCLUSION Our method provides a simple and reliable way for the volumetric evaluation of frontal lobe neurodegeneration and can be used as a resource for larger comparative studies as well as a validation procedure of automated algorithms. PMID:16971629
Analysis of Pollution Hazard Intensity: A Spatial Epidemiology Case Study of Soil Pb Contamination
Ha, Hoehun; Rogerson, Peter A.; Olson, James R.; Han, Daikwon; Bian, Ling; Shao, Wanyun
2016-01-01
Heavy industrialization has resulted in the contamination of soil by metals from anthropogenic sources in Anniston, Alabama. This situation calls for increased public awareness of the soil contamination issue and better knowledge of the main factors contributing to the potential sources contaminating residential soil. The purpose of this spatial epidemiology research is to describe the effects of physical factors on the concentration of lead (Pb) in soil in Anniston AL, and to determine the socioeconomic and demographic characteristics of those residing in areas with higher soil contamination. Spatial regression models are used to account for spatial dependencies using these explanatory variables. After accounting for covariates and multicollinearity, results of the analysis indicate that lead concentration in soils varies markedly in the vicinity of a specific foundry (Foundry A), and that proximity to railroads explained a significant amount of spatial variation in soil lead concentration. Moreover, elevated soil lead levels were identified as a concern in industrial sites, neighborhoods with a high density of old housing, a high percentage of African American population, and a low percent of occupied housing units. The use of spatial modelling allows for better identification of significant factors that are correlated with soil lead concentrations. PMID:27649221
Moreno-Pino, Mario; De la Iglesia, Rodrigo; Valdivia, Nelson; Henríquez-Castilo, Carlos; Galán, Alexander; Díez, Beatriz; Trefault, Nicole
2016-07-01
Spatial environmental heterogeneity influences diversity of organisms at different scales. Environmental filtering suggests that local environmental conditions provide habitat-specific scenarios for niche requirements, ultimately determining the composition of local communities. In this work, we analyze the spatial variation of microbial communities across environmental gradients of sea surface temperature, salinity and photosynthetically active radiation and spatial distance in Fildes Bay, King George Island, Antarctica. We hypothesize that environmental filters are the main control of the spatial variation of these communities. Thus, strong relationships between community composition and environmental variation and weak relationships between community composition and spatial distance are expected. Combining physical characterization of the water column, cell counts by flow cytometry, small ribosomal subunit genes fingerprinting and next generation sequencing, we contrast the abundance and composition of photosynthetic eukaryotes and heterotrophic bacterial local communities at a submesoscale. Our results indicate that the strength of the environmental controls differed markedly between eukaryotes and bacterial communities. Whereas eukaryotic photosynthetic assemblages responded weakly to environmental variability, bacteria respond promptly to fine-scale environmental changes in this polar marine system. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Analysis of Pollution Hazard Intensity: A Spatial Epidemiology Case Study of Soil Pb Contamination.
Ha, Hoehun; Rogerson, Peter A; Olson, James R; Han, Daikwon; Bian, Ling; Shao, Wanyun
2016-09-14
Heavy industrialization has resulted in the contamination of soil by metals from anthropogenic sources in Anniston, Alabama. This situation calls for increased public awareness of the soil contamination issue and better knowledge of the main factors contributing to the potential sources contaminating residential soil. The purpose of this spatial epidemiology research is to describe the effects of physical factors on the concentration of lead (Pb) in soil in Anniston AL, and to determine the socioeconomic and demographic characteristics of those residing in areas with higher soil contamination. Spatial regression models are used to account for spatial dependencies using these explanatory variables. After accounting for covariates and multicollinearity, results of the analysis indicate that lead concentration in soils varies markedly in the vicinity of a specific foundry (Foundry A), and that proximity to railroads explained a significant amount of spatial variation in soil lead concentration. Moreover, elevated soil lead levels were identified as a concern in industrial sites, neighborhoods with a high density of old housing, a high percentage of African American population, and a low percent of occupied housing units. The use of spatial modelling allows for better identification of significant factors that are correlated with soil lead concentrations.
Application of a liquid crystal spatial light modulator to laser marking.
Parry, Jonathan P; Beck, Rainer J; Shephard, Jonathan D; Hand, Duncan P
2011-04-20
Laser marking is demonstrated using a nanosecond (ns) pulse duration laser in combination with a liquid crystal spatial light modulator to generate two-dimensional patterns directly onto thin films and bulk metal surfaces. Previous demonstrations of laser marking with such devices have been limited to low average power lasers. Application in the ns regime enables more complex, larger scale marks to be generated with more widely available and industrially proven laser systems. The dynamic nature of the device is utilized to improve mark quality by reducing the impact of the inherently speckled intensity distribution across the generated image and reduce thermal effects in the marked surface. © 2011 Optical Society of America
J.E. Lundquist; R.M. Reich; M. Tuffly
2012-01-01
The amber-marked birch leafminer has caused severe infestations of birch species in Anchorage, AK, since 2002. Its spatial distribution has been monitored since 2006 and summarized using interpolated surfaces based on simple kriging. In this study, we developed methods of assessing and describing spatial distribution of the leafminer as they vary from year to year, and...
NASA Astrophysics Data System (ADS)
Montelli, A.; Dowdeswell, J. A.; Ottesen, D.; Johansen, S. E.
2017-12-01
An extensive three-dimensional seismic dataset is used to investigate the sedimentary processes and morphological evolution of the mid-Norwegian continental slope through the Quaternary. These data reveal hundreds of buried landforms, including channels and debris flows of variable morphology, as well as gullies, iceberg ploughmarks, slide scars and sediment waves. Slide scars, turbidity currents and debris flows comprise slope systems controlled by local slope morphology, showing the spatial variability of high-latitude sedimentation. Channels dominate the Early Pleistocene ( 2.7-0.8 Ma) morphological record of the mid-Norwegian slope. During Early Plesitocene, glacimarine sedimentation on the slope was influenced by dense bottom-water flow and turbidity currents. Glacigenic debris-flows appear within the Middle-Late Pleistocene ( 0.8-0 Ma) succession. Their abundance increases on Late Pleistocene palaeo-surfaces, marking a paleo-environmental change characterised by decreasing role for channelized turbidity currents and dense water flows. This transition coincides with the gradual shift to full-glacial ice-sheet conditions marked by the appearance of the first erosive fast-flowing ice streams and an associated increase in sediment flux to the shelf edge, emphasizing first-order climate control on the temporal variability of high-latitude sedimentary slope records.
Large scale patterns in vertical distribution and behaviour of mesopelagic scattering layers
NASA Astrophysics Data System (ADS)
Klevjer, T. A.; Irigoien, X.; Røstad, A.; Fraile-Nuez, E.; Benítez-Barrios, V. M.; Kaartvedt., S.
2016-01-01
Recent studies suggest that previous estimates of mesopelagic biomasses are severely biased, with the new, higher estimates underlining the need to unveil behaviourally mediated coupling between shallow and deep ocean habitats. We analysed vertical distribution and diel vertical migration (DVM) of mesopelagic acoustic scattering layers (SLs) recorded at 38 kHz across oceanographic regimes encountered during the circumglobal Malaspina expedition. Mesopelagic SLs were observed in all areas covered, but vertical distributions and DVM patterns varied markedly. The distribution of mesopelagic backscatter was deepest in the southern Indian Ocean (weighted mean daytime depth: WMD 590 m) and shallowest at the oxygen minimum zone in the eastern Pacific (WMD 350 m). DVM was evident in all areas covered, on average ~50% of mesopelagic backscatter made daily excursions from mesopelagic depths to shallow waters. There were marked differences in migrating proportions between the regions, ranging from ~20% in the Indian Ocean to ~90% in the Eastern Pacific. Overall the data suggest strong spatial gradients in mesopelagic DVM patterns, with implied ecological and biogeochemical consequences. Our results suggest that parts of this spatial variability can be explained by horizontal patterns in physical-chemical properties of water masses, such as oxygen, temperature and turbidity.
Large scale patterns in vertical distribution and behaviour of mesopelagic scattering layers.
Klevjer, T A; Irigoien, X; Røstad, A; Fraile-Nuez, E; Benítez-Barrios, V M; Kaartvedt, S
2016-01-27
Recent studies suggest that previous estimates of mesopelagic biomasses are severely biased, with the new, higher estimates underlining the need to unveil behaviourally mediated coupling between shallow and deep ocean habitats. We analysed vertical distribution and diel vertical migration (DVM) of mesopelagic acoustic scattering layers (SLs) recorded at 38 kHz across oceanographic regimes encountered during the circumglobal Malaspina expedition. Mesopelagic SLs were observed in all areas covered, but vertical distributions and DVM patterns varied markedly. The distribution of mesopelagic backscatter was deepest in the southern Indian Ocean (weighted mean daytime depth: WMD 590 m) and shallowest at the oxygen minimum zone in the eastern Pacific (WMD 350 m). DVM was evident in all areas covered, on average ~50% of mesopelagic backscatter made daily excursions from mesopelagic depths to shallow waters. There were marked differences in migrating proportions between the regions, ranging from ~20% in the Indian Ocean to ~90% in the Eastern Pacific. Overall the data suggest strong spatial gradients in mesopelagic DVM patterns, with implied ecological and biogeochemical consequences. Our results suggest that parts of this spatial variability can be explained by horizontal patterns in physical-chemical properties of water masses, such as oxygen, temperature and turbidity.
Tufto, Jarle; Lande, Russell; Ringsby, Thor-Harald; Engen, Steinar; Saether, Bernt-Erik; Walla, Thomas R; DeVries, Philip J
2012-07-01
1. We develop a Bayesian method for analysing mark-recapture data in continuous habitat using a model in which individuals movement paths are Brownian motions, life spans are exponentially distributed and capture events occur at given instants in time if individuals are within a certain attractive distance of the traps. 2. The joint posterior distribution of the dispersal rate, longevity, trap attraction distances and a number of latent variables representing the unobserved movement paths and time of death of all individuals is computed using Gibbs sampling. 3. An estimate of absolute local population density is obtained simply by dividing the Poisson counts of individuals captured at given points in time by the estimated total attraction area of all traps. Our approach for estimating population density in continuous habitat avoids the need to define an arbitrary effective trapping area that characterized previous mark-recapture methods in continuous habitat. 4. We applied our method to estimate spatial demography parameters in nine species of neotropical butterflies. Path analysis of interspecific variation in demographic parameters and mean wing length revealed a simple network of strong causation. Larger wing length increases dispersal rate, which in turn increases trap attraction distance. However, higher dispersal rate also decreases longevity, thus explaining the surprising observation of a negative correlation between wing length and longevity. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.
Referential shift in Nicaraguan Sign Language: a transition from lexical to spatial devices
Kocab, Annemarie; Pyers, Jennie; Senghas, Ann
2015-01-01
Even the simplest narratives combine multiple strands of information, integrating different characters and their actions by expressing multiple perspectives of events. We examined the emergence of referential shift devices, which indicate changes among these perspectives, in Nicaraguan Sign Language (NSL). Sign languages, like spoken languages, mark referential shift grammatically with a shift in deictic perspective. In addition, sign languages can mark the shift with a point or a movement of the body to a specified spatial location in the three-dimensional space in front of the signer, capitalizing on the spatial affordances of the manual modality. We asked whether the use of space to mark referential shift emerges early in a new sign language by comparing the first two age cohorts of deaf signers of NSL. Eight first-cohort signers and 10 second-cohort signers watched video vignettes and described them in NSL. Narratives were coded for lexical (use of words) and spatial (use of signing space) devices. Although the cohorts did not differ significantly in the number of perspectives represented, second-cohort signers used referential shift devices to explicitly mark a shift in perspective in more of their narratives. Furthermore, while there was no significant difference between cohorts in the use of non-spatial, lexical devices, there was a difference in spatial devices, with second-cohort signers using them in significantly more of their narratives. This suggests that spatial devices have only recently increased as systematic markers of referential shift. Spatial referential shift devices may have emerged more slowly because they depend on the establishment of fundamental spatial conventions in the language. While the modality of sign languages can ultimately engender the syntactic use of three-dimensional space, we propose that a language must first develop systematic spatial distinctions before harnessing space for grammatical functions. PMID:25713541
Referential shift in Nicaraguan Sign Language: a transition from lexical to spatial devices.
Kocab, Annemarie; Pyers, Jennie; Senghas, Ann
2014-01-01
Even the simplest narratives combine multiple strands of information, integrating different characters and their actions by expressing multiple perspectives of events. We examined the emergence of referential shift devices, which indicate changes among these perspectives, in Nicaraguan Sign Language (NSL). Sign languages, like spoken languages, mark referential shift grammatically with a shift in deictic perspective. In addition, sign languages can mark the shift with a point or a movement of the body to a specified spatial location in the three-dimensional space in front of the signer, capitalizing on the spatial affordances of the manual modality. We asked whether the use of space to mark referential shift emerges early in a new sign language by comparing the first two age cohorts of deaf signers of NSL. Eight first-cohort signers and 10 second-cohort signers watched video vignettes and described them in NSL. Narratives were coded for lexical (use of words) and spatial (use of signing space) devices. Although the cohorts did not differ significantly in the number of perspectives represented, second-cohort signers used referential shift devices to explicitly mark a shift in perspective in more of their narratives. Furthermore, while there was no significant difference between cohorts in the use of non-spatial, lexical devices, there was a difference in spatial devices, with second-cohort signers using them in significantly more of their narratives. This suggests that spatial devices have only recently increased as systematic markers of referential shift. Spatial referential shift devices may have emerged more slowly because they depend on the establishment of fundamental spatial conventions in the language. While the modality of sign languages can ultimately engender the syntactic use of three-dimensional space, we propose that a language must first develop systematic spatial distinctions before harnessing space for grammatical functions.
Abidin, Tommy Rowel; Alexander, Neal; Brock, Paddy; Grigg, Matthew J.; Murphy, Amanda; William, Timothy; Menon, Jayaram; Drakeley, Chris J.; Cox, Jonathan
2016-01-01
The zoonotic malaria species Plasmodium knowlesi has become the main cause of human malaria in Malaysian Borneo. Deforestation and associated environmental and population changes have been hypothesized as main drivers of this apparent emergence. We gathered village-level data for P. knowlesi incidence for the districts of Kudat and Kota Marudu in Sabah state, Malaysia, for 2008–2012. We adjusted malaria records from routine reporting systems to reflect the diagnostic uncertainty of microscopy for P. knowlesi. We also developed negative binomial spatial autoregressive models to assess potential associations between P. knowlesi incidence and environmental variables derived from satellite-based remote-sensing data. Marked spatial heterogeneity in P. knowlesi incidence was observed, and village-level numbers of P. knowlesi cases were positively associated with forest cover and historical forest loss in surrounding areas. These results suggest the likelihood that deforestation and associated environmental changes are key drivers in P. knowlesi transmission in these areas. PMID:26812373
Expressive writing in people with traumatic brain injury and learning disability.
Wheeler, Lisa; Nickerson, Sherry; Long, Kayla; Silver, Rebecca
2014-01-01
There is a dearth of systematic studies of expressive writing disorder (EWD) in persons with Traumatic Brain Injury (TBI). It is unclear if TBI survivors' written expression differs significantly from that experienced by persons with learning disabilities. It is also unclear which cognitive or neuropsychological variables predict problems with expressive writing (EW) or the EWD. This study investigated the EW skill, and the EWD in adults with mild traumatic brain injuries (TBI) relative to those with learning disabilities (LD). It also determined which of several cognitive variables predicted EW and EWD. Principle Component Analysis (PCA) of writing samples from 28 LD participants and 28 TBI survivors revealed four components of expressive writing skills: Reading Ease, Sentence Fluency, Grammar and Spelling, and Paragraph Fluency. There were no significant differences between the LD and TBI groups on any of the expressive writing components. Several neuropsychological variables predicted skills of written expression. The best predictors included measures of spatial perception, verbal IQ, working memory, and visual memory. TBI survivors and persons with LD do not differ markedly in terms of expressive writing skill. Measures of spatial perception, visual memory, verbal intelligence, and working memory predict writing skill in both groups. Several therapeutic interventions are suggested that are specifically designed to improve deficits in expressive writing skills in individuals with TBI and LD.
Rocket measurements of electron density irregularities during MAC/SINE
NASA Technical Reports Server (NTRS)
Ulwick, J. C.
1989-01-01
Four Super Arcas rockets were launched at the Andoya Rocket Range, Norway, as part of the MAC/SINE campaign to measure electron density irregularities with high spatial resolution in the cold summer polar mesosphere. They were launched as part of two salvos: the turbulent/gravity wave salvo (3 rockets) and the EISCAT/SOUSY radar salvo (one rocket). In both salvos meteorological rockets, measuring temperature and winds, were also launched and the SOUSY radar, located near the launch site, measured mesospheric turbulence. Electron density irregularities and strong gradients were measured by the rocket probes in the region of most intense backscatter observed by the radar. The electron density profiles (8 to 4 on ascent and 4 on descent) show very different characteristics in the peak scattering region and show marked spatial and temporal variability. These data are intercompared and discussed.
A public hedonic analysis of environmental attributes in an open space preservation program
NASA Astrophysics Data System (ADS)
Nordman, Erik E.
The Town of Brookhaven, on Long Island, NY, has implemented an open space preservation program to protect natural areas, and the ecosystem services they provide, from suburban growth. I used a public hedonic model of Brookhaven's open space purchases to estimate implicit prices for various environmental attributes, locational variables and spatial metrics. I also measured the correlation between cost per acre and non-monetary environmental benefit scores and tested whether including cost data, as opposed to non-monetary environmental benefit score alone, would change the prioritization ranks of acquired properties. The mean acquisition cost per acre was 82,501. I identified the key on-site environmental and locational variables using stepwise regression for four functional forms. The log-log specification performed best ( R2adj= 0.727). I performed a second stepwise regression (log-log form) which included spatial metrics, calculated from a high-resolution land cover classification, in addition to the environmental and locational variables. This markedly improved the model's performance ( R2adj=0.866). Statistically significant variables included the property size, location in the Pine Barrens Compatible Growth Area, location in a FEMA flood zone, adjacency to public land, and several other environmental dummy variables. The single significant spatial metric, the fractal dimension of the tree cover class, had the largest elasticity of any variable. Of the dummy variables, location within the Compatible Growth Area had the largest implicit price (298,792 per acre). The priority rank for the two methods, non-monetary environmental benefit score alone and the ratio of non-monetary environmental benefit score to acquisition cost were significantly positively correlated. This suggests that, despite the lack of cost data in their ranking method, Brookhaven does not suffer from efficiency losses. The economics literature encourages using both environmental benefits and acquisition costs to ensure cost-effective conservation programs. I recommend that Brookhaven consider acquisition costs in addition to environmental benefits to avert potential efficiency losses in future open space purchases. This dissertation shows that the addition of spatial metrics can enhance the performance of hedonic models. It also provides a baseline valuation for the environmental attributes of Brookhaven' open spaces and shows that location is critical when dealing with open space preservation programs.
NASA Astrophysics Data System (ADS)
Villate, Fernando; Uriarte, Ibon; Olivar, M. Pilar; Maynou, Francesc; Emelianov, Mikhail; Ameztoy, Iban
2014-11-01
The abundance, composition and mesoscale variability of the microplankton (53-200 μm) and the mesoplankton (0.2-2 mm) fractions in relation to oceanographic factors and phytoplankton biomass were compared off the Catalan coast (NW Mediterranean) during the summer stratification (June) and autumn mixing (November) periods in 2005. This work aims to determine whether the two plankton fractions that more contribute to fish larval diet respond to a common variable environment, and this study constitutes the first attempt to analyse, in parallel, the spatial structure of both fractions in this area. From June to November microplankton abundance increased mainly by the increase of dinoflagellates, tintinnids and radiolarians, and mesoplankton decreased due mainly to the decrease of long-horned dinoflagellates, cladocerans, doliolids and appendicularians. Plankton mesoscale variability in relation to environmental variables showed higher complexity in June, where environmental horizontal and vertical gradients were more marked than in November. In June, the major mode of variability of the microplankton was mainly accounted by the patchy distribution of several tintinnid species dominated by Rhabdonella spiralis associated to the subsurface phytoplankton biomass. The main mode of variability of the mesoplankton was related to the intrusion of the Ebro river plume and the related aggregation of doliolids and cladocerans, dominated by Evadne spinifera. In November, the major variability pattern in both fractions was a combination of inshore-offshore and eastern-western gradients in taxa distributions shaped mainly by the course of the Catalan Current along the shelf-break. Spatial differences in planktonic food pathways in each period are discussed on the basis of literature on plankton feeding habits and types, and on the diet of fish larvae of the main species from the same surveys.
NASA Astrophysics Data System (ADS)
Béjar, M.; Vericat, D.; Batalla, R. J.; Gibbins, C. N.
2018-06-01
The temporal and spatial variability of water and sediment loads of rivers is controlled by a suite of factors whose individual effects are often difficult to disentangle. While land use changes and localised human activities such as instream mining and hydropeaking alter water and sediment transfer, tributaries naturally contribute to discharge and sediment load of mainstem rivers, and so may help compensate upstream anthropogenic factors. The work presented here aimed to assess water and the sediment transfer in a river reach affected by gravel extraction and hydropeaking, set against a backdrop of changes to the supply of water and sediment from tributaries. Discharge and suspended sediment transport were monitored during two average hydrological years at three cross-sections along a 10-km reach of the upper River Cinca, in the Southern Pyrenees. Water and sediment loads differed substantially between the reaches. The upper reach showed a largely torrential discharge regime, controlled mainly by floods, and had high but variable water and sediment loads. The middle reach was influenced markedly by hydropeaking and tributary inflows, which increased its annual water yield four-fold. Suspended sediment load in this reach increased by only 25% compared to upstream, indicating that dilution predominated. In the lowermost section, while discharge remained largely unaltered, sediment load increased appreciably as a result of changes to sediment availability from instream mining and inputs from tributaries. At the reach scale, snowmelt and summer and autumn thunderstorms were responsible for most of the water yield, while flood flows determined the magnitude and transport of the sediment load. The study highlights that a combination of natural and human factors control the spatial and temporal transfer of water and sediment in river channels and that, depending on their geographic location and effect-size, can result in marked variability even over short downstream distances.
A multiscale analysis of nest predation on Least Bell's Vireos (Vireo bellii pusillus)
Kus, Barbara E.; Peterson, Bonnie L.; Deutschman, Douglas H.
2008-01-01
We examined variables influencing nest predation on the endangered Least Bell's Vireo (Vireo bellii pusillus) at three spatial scales to determine what nest-site, habitat, or landscape characteristics affect the likelihood of nest predation and to determine the spatial distribution of predation risk and the variables influencing it. We used MARK to calculate daily survival rates of Least Bell's Vireo nests and applied an information-theoretic approach to evaluate support for logistic regression models of the effect of habitat variables on predation risk. Analysis of data for 195 nests collected during 1999 and 2000 at the San Luis Rey River and Pilgrim Creek in southern California revealed no effect of fine-scale factors, including nest height, supporting plant species, and three measures of nest concealment, on the likelihood of predation. At the intermediate scale, distances to the riparian-habitat edge and to internal gaps in the canopy were unrelated to nest survival. Surrounding land-use type was a poor predictor of predation risk, with the exception of proximity to golf course–park habitat and wetland. Nests within 400 m of golf course–park were only 20% as likely to avoid predation as nests >400 m from this habitat, and nests near wetland were more than twice as likely to survive as nests distant from wetland. Spatially, predation appeared to be random throughout the site, with localized clustering evident in the vicinity of golf course–park and wetland. Our results suggest that the landscape may be the most appropriate scale at which to manage nest predation in this system.
NASA Astrophysics Data System (ADS)
Legave, Jean Michel; Blanke, Michael; Christen, Danilo; Giovannini, Daniela; Mathieu, Vincent; Oger, Robert
2013-03-01
In the current context of global warming, an analysis is required of spatially-extensive and long-term blooming data in fruit trees to make up for insufficient information on regional-scale blooming changes and determinisms that are key to the phenological adaptation of these species. We therefore analysed blooming dates over long periods at climate-contrasted sites in Western Europe, focusing mainly on the Golden Delicious apple that is grown worldwide. On average, blooming advances were more pronounced in northern continental (10 days) than in western oceanic (6-7 days) regions, while the shortest advance was found on the Mediterranean coastline. Temporal trends toward blooming phase shortenings were also observed in continental regions. These regional differences in temporal variability across Western Europe resulted in a decrease in spatial variability, i.e. shorter time intervals between blooming dates in contrasted regions (8-10-day decrease for full bloom between Mediterranean and continental regions). Fitted sequential models were used to reproduce phenological changes. Marked trends toward shorter simulated durations of forcing period (bud growth from dormancy release to blooming) and high positive correlations between these durations and observed blooming dates support the notion that blooming advances and shortenings are mainly due to faster satisfaction of the heating requirement. However, trends toward later dormancy releases were also noted in oceanic and Mediterranean regions. This could tend toward blooming delays and explain the shorter advances in these regions despite similar or greater warming. The regional differences in simulated chilling and forcing periods were consistent with the regional differences in temperature increases.
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.
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
Large scale patterns in vertical distribution and behaviour of mesopelagic scattering layers
Klevjer, T. A.; Irigoien, X.; Røstad, A.; Fraile-Nuez, E.; Benítez-Barrios, V. M.; Kaartvedt., S.
2016-01-01
Recent studies suggest that previous estimates of mesopelagic biomasses are severely biased, with the new, higher estimates underlining the need to unveil behaviourally mediated coupling between shallow and deep ocean habitats. We analysed vertical distribution and diel vertical migration (DVM) of mesopelagic acoustic scattering layers (SLs) recorded at 38 kHz across oceanographic regimes encountered during the circumglobal Malaspina expedition. Mesopelagic SLs were observed in all areas covered, but vertical distributions and DVM patterns varied markedly. The distribution of mesopelagic backscatter was deepest in the southern Indian Ocean (weighted mean daytime depth: WMD 590 m) and shallowest at the oxygen minimum zone in the eastern Pacific (WMD 350 m). DVM was evident in all areas covered, on average ~50% of mesopelagic backscatter made daily excursions from mesopelagic depths to shallow waters. There were marked differences in migrating proportions between the regions, ranging from ~20% in the Indian Ocean to ~90% in the Eastern Pacific. Overall the data suggest strong spatial gradients in mesopelagic DVM patterns, with implied ecological and biogeochemical consequences. Our results suggest that parts of this spatial variability can be explained by horizontal patterns in physical-chemical properties of water masses, such as oxygen, temperature and turbidity. PMID:26813333
Al-Chokhachy, R.; Budy, P.; Conner, M.
2009-01-01
Using empirical field data for bull trout (Salvelinus confluentus), we evaluated the trade-off between power and sampling effort-cost using Monte Carlo simulations of commonly collected mark-recapture-resight and count data, and we estimated the power to detect changes in abundance across different time intervals. We also evaluated the effects of monitoring different components of a population and stratification methods on the precision of each method. Our results illustrate substantial variability in the relative precision, cost, and information gained from each approach. While grouping estimates by age or stage class substantially increased the precision of estimates, spatial stratification of sampling units resulted in limited increases in precision. Although mark-resight methods allowed for estimates of abundance versus indices of abundance, our results suggest snorkel surveys may be a more affordable monitoring approach across large spatial scales. Detecting a 25% decline in abundance after 5 years was not possible, regardless of technique (power = 0.80), without high sampling effort (48% of study site). Detecting a 25% decline was possible after 15 years, but still required high sampling efforts. Our results suggest detecting moderate changes in abundance of freshwater salmonids requires considerable resource and temporal commitments and highlight the difficulties of using abundance measures for monitoring bull trout populations.
Mesa, Matthew G.; Duke, S.D.; Ward, David L.
1990-01-01
Population data for smallmouth bass Micropterus dolomieui in 20,235 ha John Day Reservoir on the Columbia River were used to (1) determine whether Proportional Stock Density (PSD) and Relative Weight (Wr) varied spatially and temporally in two areas of the reservoir with established smallmouth bass fisheries; (2) explore possible causes of any observed variation; and (3) discuss some management implications and recommendations. Both PSD and Wr varied spatially and monthly in all years examined. On an annual basis, PSD varied at one area but not at the other, whereas Wr showed little variation. Possible explanations for the variation in PSD and Wr are differences in growth, mortality, recruitment, and exploitation. Our data suggested that regulations established or changed on a reservoir-wide basis may have different effects on the fishery, depending on location in the reservoir. Also, pooling data from various areas within a reservoir to yield point estimates of structural indices may not represent the variation present in the population as a whole. The significant temporal variability reflects the importance of determining the proper time to sample fish to yield representative estimates of the variable of interest. In areas with valuable fisheries or markedly different population structures, we suggest that an area-specific approach be made to reservoir fishery management, and that efforts be made toward effecting consistent harvest regulations in interstate waters.
Monitoring of oceanographic properties of Glacier Bay, Alaska 2004
Madison, Erica N.; Etherington, Lisa L.
2005-01-01
Glacier Bay is a recently (300 years ago) deglaciated fjord estuarine system that has multiple sills, very deep basins, tidewater glaciers, and many streams. Glacier Bay experiences a large amount of runoff, high sedimentation, and large tidal variations. High freshwater discharge due to snow and ice melt and the presence of the tidewater glaciers makes the bay extremely cold. There are many small- and large-scale mixing and upwelling zones at sills, glacial faces, and streams. The complex topography and strong currents lead to highly variable salinity, temperature, sediment, primary productivity, light penetration, stratification levels, and current patterns within a small area. The oceanographic patterns within Glacier Bay drive a large portion of the spatial and temporal variability of the ecosystem. It has been widely recognized by scientists and resource managers in Glacier Bay that a program to monitor oceanographic patterns is essential for understanding the marine ecosystem and to differentiate between anthropogenic disturbance and natural variation. This year’s sampling marks the 12th continuous year of monitoring the oceanographic conditions at 23 stations along the primary axes within Glacier Bay, AK, making this a very unique and valuable data set in terms of its spatial and temporal coverage.
An example of fisheries oceanography: Walleye pollock in Alaskan waters
NASA Astrophysics Data System (ADS)
Schumacher, Jim; Kendall, Arthur W.
1995-07-01
A major area of research in fisheries oceanography examines relationships between recruitment dynamics of fish populations and the marine environment. A primary goal is to understand the natural causes of variability in year-class strength of commercially valuable species and apply this knowledge to management [Perry, 1994]. The paradigm that the majority of mortality occurs during transport of early life history stages from spawning to nursery grounds [Rothschild, 1986; Houde, 1987] provides an initial temporal focus for most research. The spatial domain includes the region occupied by early life history stages. Since global climate variability impacts regional ecosystem dynamics, however, the spatial domain often must be expanded. The relative importance and manifestation of biological factors [starvation and predation] that limit survival varies each year. Marked interannual and longer period variations in temperature (an influence on metabolic rates and behavior), transport of planktonic stages, and turbulence can exert an influence on both survival of early life history stages, and distribution of juveniles and adults. To understand how these environmental factors influence reproductive success of fish stocks also requires knowledge of the impact of these factors on predators and prey throughout the food web.
Rhodes, Matthew K; Fant, Jeremie B; Skogen, Krissa A
2014-01-01
Identifying factors that shape the spatial distribution of genetic variation is crucial to understanding many population- and landscape-level processes. In this study, we explore fine-scale spatial genetic structure in Oenothera harringtonii (Onagraceae), an insect-pollinated, gravity-dispersed herb endemic to the grasslands of south-central and southeastern Colorado, USA. We genotyped 315 individuals with 11 microsatellite markers and utilized a combination of spatial autocorrelation analyses and landscape genetic models to relate life history traits and landscape features to dispersal processes. Spatial genetic structure was consistent with theoretical expectations of isolation by distance, but this pattern was weak (Sp = 0.00374). Anisotropic analyses indicated that spatial genetic structure was markedly directional, in this case consistent with increased dispersal along prominent slopes. Landscape genetic models subsequently confirmed that spatial genetic variation was significantly influenced by local topographic heterogeneity, specifically that geographic distance, elevation and aspect were important predictors of spatial genetic structure. Among these variables, geographic distance was ~68% more important than elevation in describing spatial genetic variation, and elevation was ~42% more important than aspect after removing the effect of geographic distance. From these results, we infer a mechanism of hydrochorous seed dispersal along major drainages aided by seasonal monsoon rains. Our findings suggest that landscape features may shape microevolutionary processes at much finer spatial scales than typically considered, and stress the importance of considering how particular dispersal vectors are influenced by their environmental context. © The American Genetic Association 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Spatial variability of Chinook salmon spawning distribution and habitat preferences
Cram, Jeremy M.; Torgersen, Christian E.; Klett, Ryan S.; Pess, George R.; May, Darran; Pearsons, Todd N.; Dittman, Andrew H.
2017-01-01
We investigated physical habitat conditions associated with the spawning sites of Chinook Salmon Oncorhynchus tshawytscha and the interannual consistency of spawning distribution across multiple spatial scales using a combination of spatially continuous and discrete sampling methods. We conducted a census of aquatic habitat in 76 km of the upper main-stem Yakima River in Washington and evaluated spawning site distribution using redd survey data from 2004 to 2008. Interannual reoccupation of spawning areas was high, ranging from an average Pearson’s correlation of 0.62 to 0.98 in channel subunits and 10-km reaches, respectively. Annual variance in the interannual correlation of spawning distribution was highest in channel units and subunits, but it was low at reach scales. In 13 of 15 models developed for individual years (2004–2008) and reach lengths (800 m, 3 km, 6 km), stream power and depth were the primary predictors of redd abundance. Multiple channels and overhead cover were patchy but were important secondary and tertiary predictors of reach-scale spawning site selection. Within channel units and subunits, pool tails and thermal variability, which may be associated with hyporheic exchange, were important predictors of spawning. We identified spawning habitat preferences within reaches and channel units that are relevant for salmonid habitat restoration planning. We also identified a threshold (i.e., 2-km reaches) beyond which interannual spawning distribution was markedly consistent, which may be informative for prioritizing habitat restoration or conservation. Management actions may be improved through enhanced understanding of spawning habitat preferences and the consistency with which Chinook Salmon reoccupy spawning areas at different spatial scales.
DOT National Transportation Integrated Search
2010-11-01
Previous research on pavement markings from a safety perspective tackled various issues such as pavement marking retroreflectivity : variability, relationship between pavement marking retroreflectivity and driver visibility, or pavement marking impro...
NASA Astrophysics Data System (ADS)
Ólafsson, Haraldur; Cataldi, Maxime; Zehouf, Hafsa; Pálmason, Bolli
2014-05-01
Short wave radiation has been observed at several locations in Iceland in recent years. The observations reveal that there is large spatial variability in the incoming radiation. There are indications of a coast-to-inland gradient and there is much greater radiation at central-inland locations than further west as well in the far east. The results are in line with Markús Á. Einarsson's reports where estimation of radiation was based on manned cloud observations shortly after the middle of the 20th century. Values of radiation retrieved from the operational simulations of the European Centre for Medium-range Weather Forecasts (ECMWF) compare in general well with the observations.
Effect of fertility on secondary sex ratio and twinning rate in Sweden, 1749-1870.
Fellman, Johan; Eriksson, Aldur W
2015-02-01
We analyzed the effect of total fertility rate (TFR) and crude birth rate (CBR) on the number of males per 100 females at birth, also called the secondary sex ratio (SR), and on the twinning rate (TWR). Earlier studies have noted regional variations in TWR and racial differences in the SR. Statistical analyses have shown that comparisons between SRs demand large data sets because random fluctuations in moderate data are marked. Consequently, reliable results presuppose national birth data. Here, we analyzed historical demographic data and their regional variations between counties in Sweden. We built spatial models for the TFR in 1860 and the CBR in 1751-1870, and as regressors we used geographical coordinates for the provincial capitals of the counties. For both variables, we obtained significant spatial variations, albeit of different patterns and power. The SR among the live-born in 1749-1869 and the TWR in 1751-1860 showed slight spatial variations. The influence of CBR and TFR on the SR and TWR was examined and statistical significant effects were found.
Davis, Doreen E.
2018-01-01
Background Few studies of edge effects on wildlife objectively identify habitat edges or explore non-linear responses. In this paper, we build on ground beetle (Coleoptera: Carabidae) research that has begun to address these domains by using triangulation wombling to identify boundaries in beetle community structure and composition at the edges of forest patches with residential developments. We hypothesized that edges are characterized by boundaries in environmental variables that correspond to marked discontinuities in vegetation structure between maintained yards and forest. We expected environmental boundaries to be associated with beetle boundaries. Methods We collected beetles and measured environmental variables in 200 m by 200 m sampling grids centered at the edges of three forest patches, each with a rural, suburban, or urban context, in Charlotte, North Carolina, USA. We identified boundaries within each grid at two spatial scales and tested their significance and overlap using boundary statistics and overlap statistics, respectively. We complemented boundary delineation with k-means clustering. Results Boundaries in environmental variables, such as temperature, grass cover, and leaf litter depth, occurred at or near the edges of all three sites, in many cases at both scales. The beetle variables that exhibited the most pronounced boundary structure in relation to edges were total species evenness, generalist abundance, generalist richness, generalist evenness, and Agonum punctiforme abundance. Environmental and beetle boundaries also occurred within forest patches and residential developments, indicating substantial localized spatial variation on either side of edges. Boundaries in beetle and environmental variables that displayed boundary structure at edges significantly overlapped, as did boundaries on either side of edges. The comparison of boundaries and clusters revealed that boundaries formed parts of the borders of patches of similar beetle or environmental condition. Discussion We show that edge effects on ground beetle community structure and composition and environmental variation at the intersection of forest patches and residential developments can be described by boundaries and that these boundaries overlap in space. However, our results also highlight the complexity of edge effects in our system: environmental boundaries were located at or near edges whereas beetle boundaries related to edges could be spatially disjunct from them; boundaries incompletely delineated edges such that only parts of edges were well-described by sharp transitions in beetle and/or environmental variables; and the occurrence of boundaries related to edges was apparently influenced by individual property management practices, site-specific characteristics such as development geometry, and spatial scale. PMID:29333346
Davis, Doreen E; Gagné, Sara A
2018-01-01
Few studies of edge effects on wildlife objectively identify habitat edges or explore non-linear responses. In this paper, we build on ground beetle (Coleoptera: Carabidae) research that has begun to address these domains by using triangulation wombling to identify boundaries in beetle community structure and composition at the edges of forest patches with residential developments. We hypothesized that edges are characterized by boundaries in environmental variables that correspond to marked discontinuities in vegetation structure between maintained yards and forest. We expected environmental boundaries to be associated with beetle boundaries. We collected beetles and measured environmental variables in 200 m by 200 m sampling grids centered at the edges of three forest patches, each with a rural, suburban, or urban context, in Charlotte, North Carolina, USA. We identified boundaries within each grid at two spatial scales and tested their significance and overlap using boundary statistics and overlap statistics, respectively. We complemented boundary delineation with k -means clustering. Boundaries in environmental variables, such as temperature, grass cover, and leaf litter depth, occurred at or near the edges of all three sites, in many cases at both scales. The beetle variables that exhibited the most pronounced boundary structure in relation to edges were total species evenness, generalist abundance, generalist richness, generalist evenness, and Agonum punctiforme abundance. Environmental and beetle boundaries also occurred within forest patches and residential developments, indicating substantial localized spatial variation on either side of edges. Boundaries in beetle and environmental variables that displayed boundary structure at edges significantly overlapped, as did boundaries on either side of edges. The comparison of boundaries and clusters revealed that boundaries formed parts of the borders of patches of similar beetle or environmental condition. We show that edge effects on ground beetle community structure and composition and environmental variation at the intersection of forest patches and residential developments can be described by boundaries and that these boundaries overlap in space. However, our results also highlight the complexity of edge effects in our system: environmental boundaries were located at or near edges whereas beetle boundaries related to edges could be spatially disjunct from them; boundaries incompletely delineated edges such that only parts of edges were well-described by sharp transitions in beetle and/or environmental variables; and the occurrence of boundaries related to edges was apparently influenced by individual property management practices, site-specific characteristics such as development geometry, and spatial scale.
Cronin, Adam L; Loeuille, Nicolas; Monnin, Thibaud
2016-02-05
Offspring investment strategies vary markedly between and within taxa, and much of this variation is thought to stem from the trade-off between offspring size and number. While producing larger offspring can increase their competitive ability, this often comes at a cost to their colonization ability. This competition-colonization trade-off (CCTO) is thought to be an important mechanism supporting coexistence of alternative strategies in a wide range of taxa. However, the relative importance of an alternative and possibly synergistic mechanism-spatial structuring of the environment-remains the topic of some debate. In this study, we explore the influence of these mechanisms on metacommunity structure using an agent-based model built around variable life-history traits. Our model combines explicit resource competition and spatial dynamics, allowing us to tease-apart the influence of, and explore the interaction between, the CCTO and the spatial structure of the environment. We test our model using two reproductive strategies which represent extremes of the CCTO and are common in ants. Our simulations show that colonisers outperform competitors in environments subject to higher temporal and spatial heterogeneity and are favoured when agents mature late and invest heavily in reproduction, whereas competitors dominate in low-disturbance, high resource environments and when maintenance costs are low. Varying life-history parameters has a marked influence on coexistence conditions and yields evolutionary stable strategies for both modes of reproduction. Nonetheless, we show that these strategies can coexist over a wide range of life-history and environmental parameter values, and that coexistence can in most cases be explained by a CCTO. By explicitly considering space, we are also able to demonstrate the importance of the interaction between dispersal and landscape structure. The CCTO permits species employing different reproductive strategies to coexist over a wide range of life-history and environmental parameters, and is likely to be an important factor in structuring ant communities. Our consideration of space highlights the importance of dispersal, which can limit the success of low-dispersers through kin competition, and enhance coexistence conditions for different strategies in spatially structured environments.
NASA Astrophysics Data System (ADS)
Moura, Y. M.; Hilker, T.; Galvão, L. S.; Santos, J. R.; Lyapustin, A.; Sousa, C. H. R. D.; McAdam, E.
2014-12-01
The sensitivity of the Amazon rainforests to climate change has received great attention by the scientific community due to the important role that this vegetation plays in the global carbon, water and energy cycle. The spatial and temporal variability of tropical forests across Amazonia, and their phenological, ecological and edaphic cycles are still poorly understood. The objective of this work was to infer seasonal and spatial variability of forest structure in the Brazilian Amazon based on anisotropy of multi-angle satellite observations. We used observations from the Moderate Resolution Imaging Spectroradiometer (MODIS/Terra and Aqua) processed by a new Multi-Angle Implementation Atmospheric Correction Algorithm (MAIAC) to investigate how multi-angular spectral response from satellite imagery can be used to analyze structural variability of Amazon rainforests. We calculated differences acquired from forward and backscatter reflectance by modeling the bi-directional reflectance distribution function to infer seasonal and spatial changes in vegetation structure. Changes in anisotropy were larger during the dry season than during the wet season, suggesting intra-annual changes in vegetation structure and density. However, there were marked differences in timing and amplitude depending on forest type. For instance differences between reflectance hotspot and darkspot showed more anisotropy in the open Ombrophilous forest than in the dense Ombrophilous forest. Our results show that multi-angle data can be useful for analyzing structural differences in various forest types and for discriminating different seasonal effects within the Amazon basin. Also, multi-angle data could help solve uncertainties about sensitivity of different tropical forest types to light versus rainfall. In conclusion, multi-angular information, as expressed by the anisotropy of spectral reflectance, may complement conventional studies and provide significant improvements over approaches that are based on vegetation indices alone.
The relationship between the spatial scaling of biodiversity and ecosystem stability
Delsol, Robin; Loreau, Michel; Haegeman, Bart
2018-01-01
Aim Ecosystem stability and its link with biodiversity have mainly been studied at the local scale. Here we present a simple theoretical model to address the joint dependence of diversity and stability on spatial scale, from local to continental. Methods The notion of stability we use is based on the temporal variability of an ecosystem-level property, such as primary productivity. In this way, our model integrates the well-known species–area relationship (SAR) with a recent proposal to quantify the spatial scaling of stability, called the invariability–area relationship (IAR). Results We show that the link between the two relationships strongly depends on whether the temporal fluctuations of the ecosystem property of interest are more correlated within than between species. If fluctuations are correlated within species but not between them, then the IAR is strongly constrained by the SAR. If instead individual fluctuations are only correlated by spatial proximity, then the IAR is unrelated to the SAR. We apply these two correlation assumptions to explore the effects of species loss and habitat destruction on stability, and find a rich variety of multi-scale spatial dependencies, with marked differences between the two assumptions. Main conclusions The dependence of ecosystem stability on biodiversity across spatial scales is governed by the spatial decay of correlations within and between species. Our work provides a point of reference for mechanistic models and data analyses. More generally, it illustrates the relevance of macroecology for ecosystem functioning and stability. PMID:29651225
Wojciulik, E; Rorden, C; Clarke, K; Husain, M; Driver, J
2004-09-01
Visual neglect is a relatively common deficit after brain damage, particularly strokes. Cancellation tests provide standard clinical measures of neglect severity and deficits in daily life. A recent single-case study introduced a new variation on standard cancellation. Instead of making a visible mark on each target found, the patient made invisible marks (recorded with carbon paper underneath, for later scoring). Such invisible cancellation was found to reveal more neglect than cancellation with visible marks. Here we test the generality of this. Twenty three successive cases with suspected neglect each performed cancellation with visible or invisible marks. Neglect of contralesional targets was more pronounced with invisible marks. Indeed, about half of the patients only showed neglect in this version. For cases showing more neglect with invisible marks, stronger neglect of contralesional targets correlated with more revisits to ipsilesional targets for making additional invisible marks upon them. These results indicate that cancellation with invisible marks can reveal more neglect than standard cancellation with visible marks, while still providing a practical bedside test. Our observations may be consistent with recent proposals that demands on spatial working memory (required to keep track of previously found items only when marked invisibly) can exacerbate spatial neglect.
Deribe, Kebede; Brooker, Simon J; Pullan, Rachel L; Hailu, Asrat; Enquselassie, Fikre; Reithinger, Richard; Newport, Melanie; Davey, Gail
2013-01-01
An up-to-date and reliable map of podoconiosis is needed to design geographically targeted and cost-effective intervention in Ethiopia. Identifying the ecological correlates of the distribution of podoconiosis is the first step for distribution and risk maps. The objective of this study was to investigate the spatial distribution and ecological correlates of podoconiosis using historical and contemporary survey data. Data on the observed prevalence of podoconiosis were abstracted from published and unpublished literature into a standardized database, according to strict inclusion and exclusion criteria. In total, 10 studies conducted between 1969 and 2012 were included, and data were available for 401,674 individuals older than 15 years of age from 229 locations. A range of high resolution environmental factors were investigated to determine their association with podoconiosis prevalence, using logistic regression. The prevalence of podoconiosis in Ethiopia was estimated at 3.4% (95% CI 3.3%-3.4%) with marked regional variation. We identified significant associations between mean annual Land Surface Temperature (LST), mean annual precipitation, topography of the land and fine soil texture and high prevalence of podoconiosis. The derived maps indicate both widespread occurrence of podoconiosis and a marked variability in prevalence of podoconiosis, with prevalence typically highest at altitudes >1500 m above sea level (masl), with >1500 mm annual rainfall and mean annual LST of 19-21°C. No (or very little) podoconiosis occurred at altitudes <1225 masl, with annual rainfall <900 mm, and mean annual LST of >24°C. Podoconiosis remains a public health problem in Ethiopia over considerable areas of the country, but exhibits marked geographical variation associated in part with key environmental factors. This is work in progress and the results presented here will be refined in future work.
NASA Astrophysics Data System (ADS)
Philippe, Morgane; Tison, Jean-Louis; Fjøsne, Karen; Hubbard, Bryn; Kjær, Helle A.; Lenaerts, Jan T. M.; Drews, Reinhard; Sheldon, Simon G.; De Bondt, Kevin; Claeys, Philippe; Pattyn, Frank
2016-10-01
Ice cores provide temporal records of surface mass balance (SMB). Coastal areas of Antarctica have relatively high and variable SMB, but are under-represented in records spanning more than 100 years. Here we present SMB reconstruction from a 120 m-long ice core drilled in 2012 on the Derwael Ice Rise, coastal Dronning Maud Land, East Antarctica. Water stable isotope (δ18O and δD) stratigraphy is supplemented by discontinuous major ion profiles and continuous electrical conductivity measurements. The base of the ice core is dated to AD 1759 ± 16, providing a climate proxy for the past ˜ 250 years. The core's annual layer thickness history is combined with its gravimetric density profile to reconstruct the site's SMB history, corrected for the influence of ice deformation. The mean SMB for the core's entire history is 0.47 ± 0.02 m water equivalent (w.e.) a-1. The time series of reconstructed annual SMB shows high variability, but a general increase beginning in the 20th century. This increase is particularly marked during the last 50 years (1962-2011), which yields mean SMB of 0.61 ± 0.01 m w.e. a-1. This trend is compared with other reported SMB data in Antarctica, generally showing a high spatial variability. Output of the fully coupled Community Earth System Model (CESM) suggests that, although atmospheric circulation is the main factor influencing SMB, variability in sea surface temperatures and sea ice cover in the precipitation source region also explain part of the variability in SMB. Local snow redistribution can also influence interannual variability but is unlikely to influence long-term trends significantly. This is the first record from a coastal ice core in East Antarctica to show an increase in SMB beginning in the early 20th century and particularly marked during the last 50 years.
Ozgul, Arpat; Armitage, Kenneth B; Blumstein, Daniel T; Oli, Madan K
2006-04-01
Spatiotemporal variation in age-specific survival rates can profoundly influence population dynamics, but few studies of vertebrates have thoroughly investigated both spatial and temporal variability in age-specific survival rates. We used 28 years (1976-2003) of capture-mark-recapture (CMR) data from 17 locations to parameterize an age-structured Cormack-Jolly-Seber model, and investigated spatial and temporal variation in age-specific annual survival rates of yellow-bellied marmots (Marmota flaviventris). Survival rates varied both spatially and temporally, with survival of younger animals exhibiting the highest degree of variation. Juvenile survival rates varied from 0.52 +/- 0.05 to 0.78 +/- 0.10 among sites and from 0.15 +/- 0.14 to 0.89 +/- 0.06 over time. Adult survival rates varied from 0.62 +/- 0.09 to 0.80 +/- 0.03 among sites, but did not vary significantly over time. We used reverse-time CMR models to estimate the realized population growth rate (lamda), and to investigate the influence of the observed variation in age-specific survival rates on lamda. The realized growth rate of the population closely covaried with, and was significantly influenced by, spatiotemporal variation in juvenile survival rate. High variability in juvenile survival rates over space and time clearly influenced the dynamics of our study population and is also likely to be an important determinant of the spatiotemporal variation in the population dynamics of other mammals with similar life history characteristics.
Intensity of Territorial Marking Predicts Wolf Reproduction: Implications for Wolf Monitoring
García, Emilio J.
2014-01-01
Background The implementation of intensive and complex approaches to monitor large carnivores is resource demanding, restricted to endangered species, small populations, or small distribution ranges. Wolf monitoring over large spatial scales is difficult, but the management of such contentious species requires regular estimations of abundance to guide decision-makers. The integration of wolf marking behaviour with simple sign counts may offer a cost-effective alternative to monitor the status of wolf populations over large spatial scales. Methodology/Principal Findings We used a multi-sampling approach, based on the collection of visual and scent wolf marks (faeces and ground scratching) and the assessment of wolf reproduction using howling and observation points, to test whether the intensity of marking behaviour around the pup-rearing period (summer-autumn) could reflect wolf reproduction. Between 1994 and 2007 we collected 1,964 wolf marks in a total of 1,877 km surveyed and we searched for the pups' presence (1,497 howling and 307 observations points) in 42 sampling sites with a regular presence of wolves (120 sampling sites/year). The number of wolf marks was ca. 3 times higher in sites with a confirmed presence of pups (20.3 vs. 7.2 marks). We found a significant relationship between the number of wolf marks (mean and maximum relative abundance index) and the probability of wolf reproduction. Conclusions/Significance This research establishes a real-time relationship between the intensity of wolf marking behaviour and wolf reproduction. We suggest a conservative cutting point of 0.60 for the probability of wolf reproduction to monitor wolves on a regional scale combined with the use of the mean relative abundance index of wolf marks in a given area. We show how the integration of wolf behaviour with simple sampling procedures permit rapid, real-time, and cost-effective assessments of the breeding status of wolf packs with substantial implications to monitor wolves at large spatial scales. PMID:24663068
Measurement Effects in Studying Reactions to Spatial Invasions.
ERIC Educational Resources Information Center
Becker, Franklin D.; Mayo, Clara
Two concepts predominate in studies of spatial invasion: territoriality (personalization and defense of a fixed spatial area) and personal space (a portable area surrounding the individual, which is responsive to environmental change). Spatial invasions were carried out by occupying a marked seat (invade condition), and adjacent seat (adjacent…
Rapid Effects of Marine Reserves via Larval Dispersal
Cudney-Bueno, Richard; Lavín, Miguel F.; Marinone, Silvio G.; Raimondi, Peter T.; Shaw, William W.
2009-01-01
Marine reserves have been advocated worldwide as conservation and fishery management tools. It is argued that they can protect ecosystems and also benefit fisheries via density-dependent spillover of adults and enhanced larval dispersal into fishing areas. However, while evidence has shown that marine reserves can meet conservation targets, their effects on fisheries are less understood. In particular, the basic question of if and over what temporal and spatial scales reserves can benefit fished populations via larval dispersal remains unanswered. We tested predictions of a larval transport model for a marine reserve network in the Gulf of California, Mexico, via field oceanography and repeated density counts of recently settled juvenile commercial mollusks before and after reserve establishment. We show that local retention of larvae within a reserve network can take place with enhanced, but spatially-explicit, recruitment to local fisheries. Enhancement occurred rapidly (2 yrs), with up to a three-fold increase in density of juveniles found in fished areas at the downstream edge of the reserve network, but other fishing areas within the network were unaffected. These findings were consistent with our model predictions. Our findings underscore the potential benefits of protecting larval sources and show that enhancement in recruitment can be manifested rapidly. However, benefits can be markedly variable within a local seascape. Hence, effects of marine reserve networks, positive or negative, may be overlooked when only focusing on overall responses and not considering finer spatially-explicit responses within a reserve network and its adjacent fishing grounds. Our results therefore call for future research on marine reserves that addresses this variability in order to help frame appropriate scenarios for the spatial management scales of interest. PMID:19129910
Sedinger, James S.; Chelgren, Nathan; Lindberg, Mark S.; Obritchkewitch, Tim; Kirk, Morgan T.; Martin, Philip D.; Anderson, Betty A.; Ward, David H.
2002-01-01
We used capture-recapture methods to estimate adult survival rates for adult female Black Brant (Branta bernicla nigricans; hereafter “brant”) from three colonies in Alaska, two on the Yukon-Kuskokwim Delta, and one on Alaska's Arctic coast. Costs of migration and reproductive effort varied among those colonies, enabling us to examine variation in survival in relation to variation in these other variables. We used the Barker model in program MARK to estimate true annual survival for brant from the three colonies. Models allowing for spatial variation in survival were among the most parsimonious models but were indistinguishable from a model with no spatial variation. Point estimates of annual survival were slightly higher for brant from the Arctic (0.90 ± 0.036) than for brant from either Tutakoke River (0.85 ± 0.004) or Kokechik Bay (0.86 ± 0.011). Thus, our survival estimates do not support a hypothesis that the cost of longer migrations or harvest experienced by brant from the Arctic reduced their annual survival relative to brant from the Yukon-Kuskokwim Delta. Spatial variation in survival provides weak support for life-history theory because brant from the region with lower reproductive investment had slightly higher survival.
Steger, Doris; Berry, David; Haider, Susanne; Horn, Matthias; Wagner, Michael; Stocker, Roman; Loy, Alexander
2011-01-01
The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained. This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias. Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization.
Haider, Susanne; Horn, Matthias; Wagner, Michael; Stocker, Roman; Loy, Alexander
2011-01-01
Background The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained. Methodology/Principal Findings This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias. Conclusions Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization. PMID:21858215
Zimmermann, N.E.; Edwards, T.C.; Moisen, Gretchen G.; Frescino, T.S.; Blackard, J.A.
2007-01-01
1. Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. 2. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. 3. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. 4. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. 5. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. ?? 2007 The Authors.
ZIMMERMANN, N E; EDWARDS, T C; MOISEN, G G; FRESCINO, T S; BLACKARD, J A
2007-01-01
Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. PMID:18642470
NLDAS Views of North American 2011 Extreme Events
NASA Technical Reports Server (NTRS)
Rui, Hualan; Teng, William L.; Vollmer, Bruce; Mocko, David; Lei, Guang-Dih
2014-01-01
2011 was marked as one of the most extreme years in recent history. Over the course of the year, weather-related extreme events, such as floods, heat waves, blizzards, tornadoes, and wildfires, caused tremendous loss of human life and property. The North American Land Data Assimilation System (NLDAS, http:ldas.gsfc.nasa.govnldas) data set, with high spatial and temporal resolutions (0.125 x 0.125, hourly) and various water- and energy-related variables, is an excellent data source for case studies of extreme events. This presentation illustrates some extreme events from 2011 in North America, including the Groundhog Day Blizzard, the July heat wave, Hurricane Irene, and Tropical Storm Lee, all utilizing NLDAS Phase 2 (NLDAS-2) data.
Variable features on Mars. VII - Dark filamentary markings on Mars
NASA Technical Reports Server (NTRS)
Veverka, J.
1976-01-01
The paper discusses the location, variability, and possible nature of well-developed patterns of dark filamentary markings in the Mariner 9 photographic records. Although not common on Mars, the markings are concentrated in at least two areas: Depressio Hellespontica and Cerberus/Trivium Charontis. In certain localities, strong winds are required to bring these markings into prominence. The dark filamentary markings seem to be true albedo features controlled by local topography, it being unlikely that they are free linear dunes. The distinctive criss-cross pattern seen in many of the pictures suggests that jointing provides the controlling topographic grid. At this stage it cannot be inferred whether the markings are erosional or depositional in character.
Regions of pollution with particulate matter in Poland
NASA Astrophysics Data System (ADS)
Rawicki, Kacper; Czarnecka, Małgorzata; Nidzgorska-Lencewicz, Jadwiga
2018-01-01
The study presents the temporal and spatial variability of particulate matter concentration in Poland in the calendar winter season (December-February). The basis for the study were the hourly and daily values of particulate matter PM10 concentration from the period 2005/06 - 2014/15, obtained from 33 air pollution monitoring stations. In Poland, the obligation to monitor the concentration of the finer fraction of particles smaller than 2.5µm in aerodynamic diameter was introduced only in 2010. Consequently, data on PM2.5 concentration refer to a shorter period, i.e. 2009/10 - 2014/15, and were obtained from 23 stations. Using the cluster analysis (k-means method), three regions of comparable variability of particulate matter concentration were delineated. The largest region, i.e. Region I, comprises the northern and eastern central area of Poland, and its southern boundary is along the line Gorzów Wlkp-Bydgoszcz-Konin-Łódź-Kielce-Lublin. Markedly smaller Region II is located to the south of Region I. By far the smallest area was designated to Region III which covers the south west area of Poland. The delineated regions show a marked variability in terms of mean concentration of both PM fractions in winter (PM10: region I - 33 µg·m-3, region II - 55 µg·m-3, region III - 83 µg·m-3; PM2,5: region I - 35 µg·m-3, region II - 50 µg·m-3, region III - 60 µg·m-3) and, in the case of PM10, the frequency of excessive daily limit value.
Spatial Characteristics of Tree Diameter Distributions in a Temperate Old-Growth Forest
Zhao, Xiuhai; von Gadow, Klaus
2013-01-01
This contribution identifies spatial characteristics of tree diameter in a temperate forest in north-eastern China, based on a fully censused observational study area covering 500×600 m. Mark correlation analysis with three null hypothesis models was used to determine departure from expectations at different neighborhood distances. Tree positions are clumped at all investigated scales in all 37 studied species, while the diameters of most species are spatially negatively correlated, especially at short distances. Interestingly, all three cases showing short-distance attraction of dbh marks are associated with light-demanding shrub species. The short-distance attraction of dbh marks indicates spatially aggregated cohorts of stems of similar size. The percentage of species showing significant dbh suppression peaked at a 4 m distance under the heterogeneous Poisson model. At scales exceeding the peak distance, the percentage of species showing significant dbh suppression decreases sharply with increasing distances. The evidence from this large observational study shows that some of the variation of the spatial characteristics of tree diameters is related variations of topography and soil chemistry. However, an obvious interpretation of this result is still lacking. Thus, removing competitors surrounding the target trees is an effective way to avoid neighboring competition effects reducing the growth of valuable target trees in forest management practice. PMID:23527066
Spatial characteristics of tree diameter distributions in a temperate old-growth forest.
Zhang, Chunyu; Wei, Yanbo; Zhao, Xiuhai; von Gadow, Klaus
2013-01-01
This contribution identifies spatial characteristics of tree diameter in a temperate forest in north-eastern China, based on a fully censused observational study area covering 500×600 m. Mark correlation analysis with three null hypothesis models was used to determine departure from expectations at different neighborhood distances. Tree positions are clumped at all investigated scales in all 37 studied species, while the diameters of most species are spatially negatively correlated, especially at short distances. Interestingly, all three cases showing short-distance attraction of dbh marks are associated with light-demanding shrub species. The short-distance attraction of dbh marks indicates spatially aggregated cohorts of stems of similar size. The percentage of species showing significant dbh suppression peaked at a 4 m distance under the heterogeneous Poisson model. At scales exceeding the peak distance, the percentage of species showing significant dbh suppression decreases sharply with increasing distances. The evidence from this large observational study shows that some of the variation of the spatial characteristics of tree diameters is related variations of topography and soil chemistry. However, an obvious interpretation of this result is still lacking. Thus, removing competitors surrounding the target trees is an effective way to avoid neighboring competition effects reducing the growth of valuable target trees in forest management practice.
NASA Astrophysics Data System (ADS)
Masoud, Alaa A.; El-Horiny, Mohamed M.; Atwia, Mohamed G.; Gemail, Khaled S.; Koike, Katsuaki
2018-06-01
Salinization of groundwater and soil resources has long been a serious environmental hazard in arid regions. This study was conducted to investigate and document the factors controlling such salinization and their inter-relationships in the Dakhla Oasis (Egypt). To accomplish this, 60 groundwater samples and 31 soil samples were collected in February 2014. Factor analysis (FA) and hierarchical cluster analysis (HCA) were integrated with geostatistical analyses to characterize the chemical properties of groundwater and soil and their spatial patterns, identify the factors controlling the pattern variability, and clarify the salinization mechanism. Groundwater quality standards revealed emergence of salinization (av. 885.8 mg/L) and extreme occurrences of Fe2+ (av. 17.22 mg/L) and Mn2+ (av. 2.38 mg/L). Soils were highly salt-affected (av. 15.2 dS m-1) and slightly alkaline (av. pH = 7.7). Evaporation and ion-exchange processes governed the evolution of two main water types: Na-Cl (52%) and Ca-Mg-Cl (47%), respectively. Salinization leads the chemical variability of both resources. Distinctive patterns of slight salinization marked the northern part and intense salinization marked the middle and southern parts. Congruence in the resources clusters confirmed common geology, soil types, and urban and agricultural practices. Minimizing the environmental and socioeconomic impacts of the resources salinization urges the need for better understanding of the hydrochemical characteristics and prediction of quality changes.
Interexaminer variation of minutia markup on latent fingerprints.
Ulery, Bradford T; Hicklin, R Austin; Roberts, Maria Antonia; Buscaglia, JoAnn
2016-07-01
Latent print examiners often differ in the number of minutiae they mark during analysis of a latent, and also during comparison of a latent with an exemplar. Differences in minutia counts understate interexaminer variability: examiners' markups may have similar minutia counts but differ greatly in which specific minutiae were marked. We assessed variability in minutia markup among 170 volunteer latent print examiners. Each provided detailed markup documenting their examinations of 22 latent-exemplar pairs of prints randomly assigned from a pool of 320 pairs. An average of 12 examiners marked each latent. The primary factors associated with minutia reproducibility were clarity, which regions of the prints examiners chose to mark, and agreement on value or comparison determinations. In clear areas (where the examiner was "certain of the location, presence, and absence of all minutiae"), median reproducibility was 82%; in unclear areas, median reproducibility was 46%. Differing interpretations regarding which regions should be marked (e.g., when there is ambiguity in the continuity of a print) contributed to variability in minutia markup: especially in unclear areas, marked minutiae were often far from the nearest minutia marked by a majority of examiners. Low reproducibility was also associated with differences in value or comparison determinations. Lack of standardization in minutia markup and unfamiliarity with test procedures presumably contribute to the variability we observed. We have identified factors accounting for interexaminer variability; implementing standards for detailed markup as part of documentation and focusing future training efforts on these factors may help to facilitate transparency and reduce subjectivity in the examination process. Published by Elsevier Ireland Ltd.
Spatiotemporal variation in reproductive parameters of yellow-bellied marmots.
Ozgul, Arpat; Oli, Madan K; Olson, Lucretia E; Blumstein, Daniel T; Armitage, Kenneth B
2007-11-01
Spatiotemporal variation in reproductive rates is a common phenomenon in many wildlife populations, but the population dynamic consequences of spatial and temporal variability in different components of reproduction remain poorly understood. We used 43 years (1962-2004) of data from 17 locations and a capture-mark-recapture (CMR) modeling framework to investigate the spatiotemporal variation in reproductive parameters of yellow-bellied marmots (Marmota flaviventris), and its influence on the realized population growth rate. Specifically, we estimated and modeled breeding probabilities of two-year-old females (earliest age of first reproduction), >2-year-old females that have not reproduced before (subadults), and >2-year-old females that have reproduced before (adults), as well as the litter sizes of two-year old and >2-year-old females. Most reproductive parameters exhibited spatial and/or temporal variation. However, reproductive parameters differed with respect to their relative influence on the realized population growth rate (lambda). Litter size had a stronger influence than did breeding probabilities on both spatial and temporal variations in lambda. Our analysis indicated that lambda was proportionately more sensitive to survival than recruitment. However, the annual fluctuation in litter size, abetted by the breeding probabilities, accounted for most of the temporal variation in lambda.
The tropical Pacific as a key pacemaker of the variable rates of global warming
NASA Astrophysics Data System (ADS)
Kosaka, Yu; Xie, Shang-Ping
2016-09-01
Global mean surface temperature change over the past 120 years resembles a rising staircase: the overall warming trend was interrupted by the mid-twentieth-century big hiatus and the warming slowdown since about 1998. The Interdecadal Pacific Oscillation has been implicated in modulations of global mean surface temperatures, but which part of the mode drives the variability in warming rates is unclear. Here we present a successful simulation of the global warming staircase since 1900 with a global ocean-atmosphere coupled model where tropical Pacific sea surface temperatures are forced to follow the observed evolution. Without prescribed tropical Pacific variability, the same model, on average, produces a continual warming trend that accelerates after the 1960s. We identify four events where the tropical Pacific decadal cooling markedly slowed down the warming trend. Matching the observed spatial and seasonal fingerprints we identify the tropical Pacific as a key pacemaker of the warming staircase, with radiative forcing driving the overall warming trend. Specifically, tropical Pacific variability amplifies the first warming epoch of the 1910s-1940s and determines the timing when the big hiatus starts and ends. Our method of removing internal variability from the observed record can be used for real-time monitoring of anthropogenic warming.
Acoustooptic Processing of Two Dimensional Signals Using Temporal and Spatial Integration
1989-05-12
AND SPATIAL INTEGRATION Demetri Psaltis, John Hong, Scott Hudson, Jeff Yu Fai Mok, Mark Neifeld, and Nabeel Riza, Dave Brady V 13U7101 4 NS7urtn-a...Jeff Yu Fai Mok, Mark Neifeld, and Nabeel Riza, Dave Brady DTIC Grant AFOSR-85-0332 ELECTE Submitted to: S J’ Dr. Lee Giles Air Force Office of...In addition we examine the capacity when the filter is binarized. Vector-matrix multipliers are fundamental components of many signal processing sys
Spatial Variability of Snowpack Properties On Small Slopes
NASA Astrophysics Data System (ADS)
Pielmeier, C.; Kronholm, K.; Schneebeli, M.; Schweizer, J.
The spatial variability of alpine snowpacks is created by a variety of parameters like deposition, wind erosion, sublimation, melting, temperature, radiation and metamor- phism of the snow. Spatial variability is thought to strongly control the avalanche initi- ation and failure propagation processes. Local snowpack measurements are currently the basis for avalanche warning services and there exist contradicting hypotheses about the spatial continuity of avalanche active snow layers and interfaces. Very little about the spatial variability of the snowpack is known so far, therefore we have devel- oped a systematic and objective method to measure the spatial variability of snowpack properties, layering and its relation to stability. For a complete coverage, the analysis of the spatial variability has to entail all scales from mm to km. In this study the small to medium scale spatial variability is investigated, i.e. the range from centimeters to tenths of meters. During the winter 2000/2001 we took systematic measurements in lines and grids on a flat snow test field with grid distances from 5 cm to 0.5 m. Fur- thermore, we measured systematic grids with grid distances between 0.5 m and 2 m in undisturbed flat fields and on small slopes above the tree line at the Choerbschhorn, in the region of Davos, Switzerland. On 13 days we measured the spatial pattern of the snowpack stratigraphy with more than 110 snow micro penetrometer measure- ments at slopes and flat fields. Within this measuring grid we placed 1 rutschblock and 12 stuffblock tests to measure the stability of the snowpack. With the large num- ber of measurements we are able to use geostatistical methods to analyse the spatial variability of the snowpack. Typical correlation lengths are calculated from semivari- ograms. Discerning the systematic trends from random spatial variability is analysed using statistical models. Scale dependencies are shown and recurring scaling patterns are outlined. The importance of the small and medium scale spatial variability for the larger (kilometer) scale spatial variability as well as for the avalanche formation are discussed. Finally, an outlook on spatial models for the snowpack variability is given.
Valdivia, Nelson; Díaz, María J.; Holtheuer, Jorge; Garrido, Ignacio; Huovinen, Pirjo; Gómez, Iván
2014-01-01
Understanding the variation of biodiversity along environmental gradients and multiple spatial scales is relevant for theoretical and management purposes. Hereby, we analysed the spatial variability in diversity and structure of intertidal and subtidal macrobenthic Antarctic communities along vertical environmental stress gradients and across multiple horizontal spatial scales. Since biotic interactions and local topographic features are likely major factors for coastal assemblages, we tested the hypothesis that fine-scale processes influence the effects of the vertical environmental stress gradients on the macrobenthic diversity and structure. We used nested sampling designs in the intertidal and subtidal habitats, including horizontal spatial scales ranging from few centimetres to 1000s of metres along the rocky shore of Fildes Peninsula, King George Island. In both intertidal and subtidal habitats, univariate and multivariate analyses showed a marked vertical zonation in taxon richness and community structure. These patterns depended on the horizontal spatial scale of observation, as all analyses showed a significant interaction between height (or depth) and the finer spatial scale analysed. Variance and pseudo-variance components supported our prediction for taxon richness, community structure, and the abundance of dominant species such as the filamentous green alga Urospora penicilliformis (intertidal), the herbivore Nacella concinna (intertidal), the large kelp-like Himantothallus grandifolius (subtidal), and the red crustose red alga Lithothamnion spp. (subtidal). We suggest that in coastal ecosystems strongly governed by physical factors, fine-scale processes (e.g. biotic interactions and refugia availability) are still relevant for the structuring and maintenance of the local communities. The spatial patterns found in this study serve as a necessary benchmark to understand the dynamics and adaptation of natural assemblages in response to observed and predicted environmental changes in Antarctica. PMID:24956114
Camera traps and mark-resight models: The value of ancillary data for evaluating assumptions
Parsons, Arielle W.; Simons, Theodore R.; Pollock, Kenneth H.; Stoskopf, Michael K.; Stocking, Jessica J.; O'Connell, Allan F.
2015-01-01
Unbiased estimators of abundance and density are fundamental to the study of animal ecology and critical for making sound management decisions. Capture–recapture models are generally considered the most robust approach for estimating these parameters but rely on a number of assumptions that are often violated but rarely validated. Mark-resight models, a form of capture–recapture, are well suited for use with noninvasive sampling methods and allow for a number of assumptions to be relaxed. We used ancillary data from continuous video and radio telemetry to evaluate the assumptions of mark-resight models for abundance estimation on a barrier island raccoon (Procyon lotor) population using camera traps. Our island study site was geographically closed, allowing us to estimate real survival and in situ recruitment in addition to population size. We found several sources of bias due to heterogeneity of capture probabilities in our study, including camera placement, animal movement, island physiography, and animal behavior. Almost all sources of heterogeneity could be accounted for using the sophisticated mark-resight models developed by McClintock et al. (2009b) and this model generated estimates similar to a spatially explicit mark-resight model previously developed for this population during our study. Spatially explicit capture–recapture models have become an important tool in ecology and confer a number of advantages; however, non-spatial models that account for inherent individual heterogeneity may perform nearly as well, especially where immigration and emigration are limited. Non-spatial models are computationally less demanding, do not make implicit assumptions related to the isotropy of home ranges, and can provide insights with respect to the biological traits of the local population.
NASA Astrophysics Data System (ADS)
Zerbini, S.; Raicich, F.; Richter, B.; Gorini, V.; Errico, M.
2010-04-01
This work describes a study of GPS heights, gravity and hydrological time series collected by stations located in northeastern Italy. During the last 12 years, changes in the long-term behaviors of the GPS heights and gravity time series are observed. In particular, starting in 2004-2005, a height increase is observed over the whole area. The temporal and spatial variability of these parameters has been studied as well as those of key hydrological variables, namely precipitation, hydrological balance and water table by using the Empirical Orthogonal Functions (EOF) analysis. The coupled variability between the GPS heights and the hydrological balance and precipitation data has been investigated by means of the Singular Value Decomposition (SVD) approach. Significant common patterns in the spatial and temporal variability of these parameters have been recognized. In particular, hydrology-induced variations are clearly observable starting in 2002-2003 in the southern part of the Po Plain for the longest time series, and from 2004-2005 over the whole area. These findings, obtained by means of purely mathematical approaches, are supported by sound physical interpretation suggesting that the climate-related fluctuations in the regional/local hydrological regime are one of the main contributors to the observed variations. A regional scale signal has been identified in the GPS station heights; it is characterized by the opposite behavior of the southern and northern stations in response to the hydrological forcing. At Medicina, in the southern Po Plain, the EOF analysis has shown a marked common signal between the GPS heights and the Superconducting Gravimeter (SG) data both over the long and the short period.
Precipitation phase partitioning variability across the Northern Hemisphere
NASA Astrophysics Data System (ADS)
Jennings, K. S.; Winchell, T. S.; Livneh, B.; Molotch, N. P.
2017-12-01
Precipitation phase drives myriad hydrologic, climatic, and biogeochemical processes. Despite its importance, many of the land surface models used to simulate such processes and their sensitivity to climate warming rely on simple, spatially uniform air temperature thresholds to partition rainfall and snowfall. Our analysis of a 29-year dataset with 18.7 million observations of precipitation phase from 12,143 stations across the Northern Hemisphere land surface showed marked spatial variability in the near-surface air temperature at which precipitation is equally likely to fall as rain and snow, the 50% rain-snow threshold. This value averaged 1.0°C and ranged from -0.4°C to 2.4°C for 95% of the stations analyzed. High-elevation continental areas such as the Rocky Mountains of the western U.S. and the Tibetan Plateau of central Asia generally exhibited the warmest thresholds, in some cases exceeding 3.0°C. Conversely, the coldest thresholds were observed on the Pacific Coast of North America, the southeast U.S., and parts of Eurasia, with values dropping below -0.5°C. Analysis of the meteorological conditions during storm events showed relative humidity exerted the strongest control on phase partitioning, with surface pressure playing a secondary role. Lower relative humidity and surface pressure were both associated with warmer 50% rain-snow thresholds. Additionally, we trained a binary logistic regression model on the observations to classify rain and snow events and found including relative humidity as a predictor variable significantly increased model performance between 0.6°C and 3.8°C when phase partitioning is most uncertain. We then used the optimized model and a spatially continuous reanalysis product to map the 50% rain-snow threshold across the Northern Hemisphere. The map reproduced patterns in the observed thresholds with a mean bias of 0.5°C relative to the station data. The above results suggest land surface models could be improved by incorporating relative humidity into their precipitation phase prediction schemes or by using a spatially variable, optimized rain-snow temperature threshold. This is particularly important for climate warming simulations where misdiagnosing a shift from snow to rain or inaccurately quantifying snowfall fraction would likely lead to biased results.
NASA Astrophysics Data System (ADS)
Houben, Peter
2008-10-01
Agricultural landscapes with a millennial-scale history of cultivation are common in many loess areas of central Europe. Over time, patterns of erosion and sedimentation have been continually modified via the variable imposition of anthropogenic discontinuities and linkages on fragmented hillslope sediment cascades, which eventually caused the complicated soilscape pattern. These field records challenge topographically oriented models of hillslope erosion and simple predictions of longer-term change of spatial soilscape by cultivation activities. A thorough understanding how soilscape patterns form in the long-term, however, is essential to develop spatial concepts of the sediment budget, particularly for the spatial modeling of anthropogenic hillslope sediment flux using GIS. In this study I used extensive datasets of anthropogenic soil truncation and burial in a typical undulating loess watershed in southern Germany (10 km 2, Wetterau Basin, N of Frankfurt a.M.). Spatial soilscape properties and historic sediment flux, as caused by cultivation over seven millennia, were evaluated by these data. The soilscape pattern on the low-gradient hillslopes of the study area was found to be marked by a statistical near-random pattern of varying depth (thickness) of truncation and overthickened burial. Moreover, it was shown that truncation and burial had developed independently from each other and did not correlate with either hillslope gradient or downslope curvature. Hence, in the field any combination of (few) nearly preserved, severely truncated or completely removed soil profiles with either no, some or a thick sediment cover is present, thereby lacking an obvious spatial pattern. Here, I suggest putting long-term change of the soilscape into a contextual anthropogeomorphic systems perspective, that accommodates components of human-induced soil erosion operating at different spatial scales to interpret the longer-term spatial consequences at the hillslope-system level. In the study area, system scale linkages are marked by the spatial intersection of a finer-scaled managed field system with a broader hillslope-scale framework of 'natural' erosion controls. In the low-gradient study area, field borders exert control over the spatial reference of soil erosion and sedimentation sites. Over time, this brought about a growing historical and spatial contingency change to the soilscape, because of arbitrary spatial changes of the field system which are inherent in its socio-agricultural maintenance. Thus, the very low-gradient and low-erosivity setting of the study area have singled out the agency of human-induced spatial and connectivity controls and contingency for long-term spatial hillslope sediment flux. Although these findings may be less true for different settings, they allow for deriving a generic conceptual model of the linkages between 'natural' and anthropogenic subsystems to interpret the effects of long-term human-induced sediment flux. Accordingly, the resulting balance between on-hillslope net storage and net delivery to streams is scaling with basic physiographic properties of erosivity and sedimentation as well as the degree of anthropogenic hillslope fragmentation. For loess areas in Europe variable fields are fundamental anthropogeomorphic units that determine appropriate system scaling for historic sediment flux analysis and constrain retrodiction and prediction of changing fluxes at a point and a time at watershed scales. Methodical implications address adequate sampling strategies to record soilscape change, as a result of which a critical review of the applicability of the catena concept to long-cultivated hillslopes in central Europe was included. Finally, the suggested refined generic model of long-term, human-controlled sediment flux involves a number of research opportunities, particularly for linking modeling approaches to long-term field records of cultivation-related change in the soilscape.
Ghosh, Subimal; Vittal, H.; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K. S.; Dhanesh, Y.; Sudheer, K. P.; Gunthe, S. S.
2016-01-01
India’s agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins. PMID:27463092
Ghosh, Subimal; Vittal, H; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K S; Dhanesh, Y; Sudheer, K P; Gunthe, S S
2016-01-01
India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins.
NASA Astrophysics Data System (ADS)
Beekman, F.; Hardebol, N.; Cloetingh, S.; Tesauro, M.
2006-12-01
Better understanding of 3D rheological heterogeneity of the European Lithosphere provide the key to tie the recorded intraplate deformation pattern to stress fields transmitted into plate interior from plate boundary forces. The first order strain patterns result from stresses transmitted through the European lithosphere that is marked by a patchwork of high strength variability from inherited structural and compositional heterogeneities and upper mantle thermal perturbations. As the lithospheric rheology depends primarily on its spatial structure, composition and thermal estate, the 3D strength model for the European lithosphere relies on a 3D compositional model that yields the compositional heterogeneities and an iteratively calculated thermal cube using Fouriers law for heat conduction. The accurate appraisal of spatial strength variability results from proper mapping and integration of the geophysical compositional and thermal input parameters. Therefore, much attention has been paid to a proper description of first order structural and tectonic features that facilitate compilation of the compositional and thermal input models. As such, the 3D strength model reflects the thermo-mechanical structure inherited from the Europeans polyphase deformation history. Major 3D spatial mechanical strength variability has been revealed. The East-European and Fennoscandian Craton to the NE exhibit high strength (30-50 1012 N/m) from low mantle temperatures and surface heatflow of 35-60 mW/m2 while central and western Europe reflect a polyphase Phanerozoic thermo- tectonic history. Here, regions with high rigidity are formed primarily by patches of thermally stabilized Variscan Massifs (e.g. Rhenish, Armorican, Bohemian, and Iberian Massif) with low heatflow and lithospheric thickness values (50-65 mW/m2; 110-150 km) yielding strengths of ~15-25 1012 N/m. In contrast, major axis of weakened lithosphere coincides with Cenozoic Rift System (e.g. Upper and Lower Rhine Grabens, Pannonian Basin and Massif Central) attributed to the presence of tomographically imaged plumes. This study has elucidated the memory of the present-days Europeans lithosphere induced by compositional and thermal heterogeneities. The resulting lateral strength variations has a clear signature of the pst lithospheres polyphase deformation and also entails active tectonics, tectonically induced topography and surface processes.
NASA Astrophysics Data System (ADS)
Freire, J.; González-Gurriarán, E.; Olaso, I.
1992-12-01
Geostatistical methodology was used to analyse spatial structure and distribution of the epibenthic crustaceans Munida intermedia and M. sarsi within sets of data which had been collected during three survey cruises carried out on the Galician continental shelf (1983 and 1984). This study investigates the feasibility of using geostatistics for data collected according to traditional methods and of enhancing such methodology. The experimental variograms were calculated (pooled variance minus spatial covariance between samples taken one pair at a time vs. distance) and fitted to a 'spherical' model. The spatial structure model was used to estimate the abundance and distribution of the populations studied using the technique of kriging. The species display spatial structures, which are well marked during high density periods and in some areas (especially northern shelf). Geostatistical analysis allows identification of the density gradients in space as well as the patch grain along the continental shelf of 16-25 km diameter for M. intermedia and 12-20 km for M. sarsi. Patches of both species have a consistent location throughout the different cruises. As in other geographical areas, M. intermedia and M. sarsi usually appear at depths ranging from 200 to 500 m, with the highest densities in the continental shelf area located between Fisterra and Estaca de Bares. Althouh sampling was not originally designed specifically for geostatistics, this assay provides a measurement of spatial covariance, and shows variograms with variable structure depending on population density and geographical area. These ideas are useful in improving the design of future sampling cruises.
Circulation controls of the spatial structure of maximum daily precipitation over Poland
NASA Astrophysics Data System (ADS)
Stach, Alfred
2015-04-01
Among forecasts made on the basis of global and regional climatic models is one of a high probability of an increase in the frequency and intensity of extreme precipitation events. Learning the regularities underlying the recurrence and spatial extent of extreme precipitation is obviously of great importance, both economic and social. The main goal of the study was to analyse regularities underlying spatial and temporal variations in monthly Maximum Daily Precipitation Totals (MDPTs) observed in Poland over the years 1956-1980. These data are specific because apart from being spatially discontinuous, which is typical of precipitation, they are also non-synchronic. The main aim of the study was accomplished via several detailed goals: • identification and typology of the spatial structure of monthly MDPTs, • determination of the character and probable origin of events generating MDPTs, and • quantitative assessment of the contribution of the particular events to the overall MDPT figures. The analysis of the spatial structure of MDPTs was based on 300 models of spatial structure, one for each of the analysed sets of monthly MDPTs. The models were built on the basis of empirical anisotropic semivariograms of normalised data. In spite of their spatial discontinuity and asynchronicity, the MDPT data from Poland display marked regularities in their spatial pattern that yield readily to mathematical modelling. The MDPT field in Poland is usually the sum of the outcomes of three types of processes operating at various spatial scales: local (<10-20 km), regional (50-150 km), and supra-regional (>200 km). The spatial scales are probably connected with a convective/ orographic, a frontal and a 'planetary waves' genesis of high precipitation. Their contributions are highly variable. Generally predominant, however, are high daily precipitation totals with a spatial extent of 50 to 150 km connected with mesoscale phenomena and the migration of atmospheric fronts (35-38%). The spatial extent of areas of high local-scale precipitation usually varies at random, especially in the warm season. At supra-local scales, structures of repetitive size predominate. Eight types of anisotropic structures of monthly MDPTs were distinguished. To identify them, an analysis was made of semivariance surface similarities. The types differ not only in the level and direction of anisotropy, but also in the number and type of elementary components, which is evidence of genetic differences in precipitation. Their appearance shows a significant seasonal variability, so the most probable supposition was that temporal variations in the MDPT pattern were connected with circulation conditions: the type and direction of inflow of air masses. This hypothesis was validated by testing differences in the frequency of occurrence of Grosswetterlagen circulation situations in the months belonging to the distinguished types of the spatial MDPT pattern.
NLDAS Views of North American 2011 Extreme Events
NASA Technical Reports Server (NTRS)
Rui, Hualan; Teng, William; Vollmer, Bruce; Mocko, David; Lei, Guang-Dih
2012-01-01
2011 was marked as one of the most extreme years in recent history. Over the course of the year, weather-related extreme events, such as floods, heat waves, blizzards, tornadoes, and wildfires, caused tremendous loss of human life and property. The North American Land Data Assimilation System (NLDAS, http://ldas.gsfc.nasa.gov/nldas/) data set, with high spatial and temporal resolutions (0.125? x 0.125?, hourly) and various water- and energy-related variables, is an excellent data source for case studies of extreme events. This presentation illustrates some extreme events from 2011 in North America, including the Groundhog Day Blizzard, the July heat wave, Hurricane Irene, and Tropical Storm Lee, all utilizing NLDAS Phase 2 (NLDAS-2) data.
NASA Technical Reports Server (NTRS)
Williams, D. J.; Frank, L. A.
1980-01-01
On November 20, 1977, at 0230-0300 UT, ISEE 1 encountered unusual charged particle distributions within the magnetosphere. The three-dimensional distribution observations for energetic (greater than 24 keV) ions and plasma show the development of field-aligned asymmetries in the energetic ion distributions simultaneously with a marked change in plasma flow. It is concluded that the most likely explanation for these observations is that ISEE 1 encountered open magnetospheric field lines at its position within the magnetosphere (1030 LT and 1200 plus or minus 300 km from the magnetopause). Field lines were open near the geomagnetic equator, and the geometry was spatially or temporally variable. Other features of the field line topology are presented.
In-vivo RGB marking and multicolour single-cell tracking in the adult brain
Gomez-Nicola, Diego; Riecken, Kristoffer; Fehse, Boris; Perry, V. Hugh
2014-01-01
In neuroscience it is a technical challenge to identify and follow the temporal and spatial distribution of cells as they differentiate. We hypothesised that RGB marking, the tagging of individual cells with unique hues resulting from simultaneous expression of the three basic colours red, green and blue, provides a convenient toolbox for the study of the CNS anatomy at the single-cell level. Using γ-retroviral and lentiviral vector sets we describe for the first time the in-vivo multicolour RGB marking of neurons in the adult brain. RGB marking also enabled us to track the spatial and temporal fate of neural stem cells in the adult brain. The application of different viral envelopes and promoters provided a useful approach to track the generation of neurons vs. glial cells at the neurogenic niche, allowing the identification of the prominent generation of new astrocytes to the striatum. Multicolour RGB marking could serve as a universal and reproducible method to study and manipulate the CNS at the single-cell level, in both health and disease. PMID:25531807
Bonanno, Angelo; Giannoulaki, Marianna; Barra, Marco; Basilone, Gualtiero; Machias, Athanassios; Genovese, Simona; Goncharov, Sergey; Popov, Sergey; Rumolo, Paola; Di Bitetto, Massimiliano; Aronica, Salvatore; Patti, Bernardo; Fontana, Ignazio; Giacalone, Giovanni; Ferreri, Rosalia; Buscaino, Giuseppa; Somarakis, Stylianos; Pyrounaki, Maria-Myrto; Tsoukali, Stavroula; Mazzola, Salvatore
2014-01-01
A number of scientific papers in the last few years singled out the influence of environmental conditions on the spatial distribution of fish species, highlighting the need for the fisheries scientific community to investigate, besides biomass estimates, also the habitat selection of commercially important fish species. The Mediterranean Sea, although generally oligotrophic, is characterized by high habitat variability and represents an ideal study area to investigate the adaptive behavior of small pelagics under different environmental conditions. In this study the habitat selection of European anchovy Engraulis encrasicolus and European sardine Sardina pilchardus is analyzed in two areas of the Mediterranean Sea that largely differentiate in terms of environmental regimes: the Strait of Sicily and the North Aegean Sea. A number of environmental parameters were used to investigate factors influencing anchovy and sardine habitat selection. Acoustic surveys data, collected during the summer period 2002–2010, were used for this purpose. The quotient analysis was used to identify the association between high density values and environmental variables; it was applied to the entire dataset in each area in order to identify similarities or differences in the “mean” spatial behavioral pattern for each species. Principal component analysis was applied to selected environmental variables in order to identify those environmental regimes which drive each of the two ecosystems. The analysis revealed the effect of food availability along with bottom depth selection on the spatial distribution of both species. Furthermore PCA results highlighted that observed selectivity for shallower waters is mainly associated to specific environmental processes that locally increase productivity. The common trends in habitat selection of the two species, as observed in the two regions although they present marked differences in hydrodynamics, seem to be driven by the oligotrophic character of the study areas, highlighting the role of areas where the local environmental regimes meet ‘the ocean triad hypothesis’. PMID:24992576
Lifestyle and nutrition related to male longevity in Sardinia: an ecological study.
Pes, G M; Tolu, F; Poulain, M; Errigo, A; Masala, S; Pietrobelli, A; Battistini, N C; Maioli, M
2013-03-01
A demographic analysis in the Mediterranean island of Sardinia revealed marked differences in extreme longevity across the 377 municipalities and particularly identified a mountain inner area where the proportion of oldest subjects among male population has one of the highest validated value worldwide. The cause(s) of this unequal distribution of male longevity may be attributed to a concurrence of environmental, lifestyle and genetic factors. In this study we focussed on some lifestyle and nutrition variables recorded in the island's population in early decades of 20th century, when agricultural and pastoral economy was still prevalent, and try to verify through ecological spatial models if they may account for the variability in male longevity. By computing the Extreme Longevity Index (the proportion of newborns in a given municipality who reach age 100) the island's territory was divided in two areas with relatively higher and lower level of population longevity. Most nutritional variables do not show any significant difference between these two areas whereas a significant difference was found with respect to pastoralism (P = 0.0001), physical activity estimated by the average slope of the territory in each municipality (P = 0.0001), and average daily distance required by the active population to reach the usual workplace (P = 0.0001). Overall, these findings suggest that factors affecting the average energy expenditure of male population such as occupational activity and geographic characteristics of the area where the population mainly resides, are important in explaining the spatial variation of Sardinian extreme longevity. Copyright © 2011 Elsevier B.V. All rights reserved.
Kelsey, Katharine C.; Wickland, Kimberly P.; Striegl, Robert G.; Neff, Jason C.
2012-01-01
Carbon dynamics of high-latitude regions are an important and highly uncertain component of global carbon budgets, and efforts to constrain estimates of soil-atmosphere carbon exchange in these regions are contingent on accurate representations of spatial and temporal variability in carbon fluxes. This study explores spatial and temporal variability in soilatmosphere carbon dynamics at both fine and coarse spatial scales in a high-elevation, permafrost-dominated boreal black spruce forest. We evaluate the importance of landscape-level investigations of soil-atmosphere carbon dynamics by characterizing seasonal trends in soil-atmosphere carbon exchange, describing soil temperature-moisture-respiration relations, and quantifying temporal and spatial variability at two spatial scales: the plot scale (0–5 m) and the landscape scale (500–1000 m). Plot-scale spatial variability (average variation on a given measurement day) in soil CO2 efflux ranged from a coefficient of variation (CV) of 0.25 to 0.69, and plot-scale temporal variability (average variation of plots across measurement days) in efflux ranged from a CV of 0.19 to 0.36. Landscape-scale spatial and temporal variability in efflux was represented by a CV of 0.40 and 0.31, respectively, indicating that plot-scale spatial variability in soil respiration is as great as landscape-scale spatial variability at this site. While soil respiration was related to soil temperature at both the plot- and landscape scale, landscape-level descriptions of soil moisture were necessary to define soil respiration-moisture relations. Soil moisture variability was also integral to explaining temporal variability in soil respiration. Our results have important implications for research efforts in high-latitude regions where remote study sites make landscape-scale field campaigns challenging.
Logistic regression for southern pine beetle outbreaks with spatial and temporal autocorrelation
M. L. Gumpertz; C.-T. Wu; John M. Pye
2000-01-01
Regional outbreaks of southern pine beetle (Dendroctonus frontalis Zimm.) show marked spatial and temporal patterns. While these patterns are of interest in themselves, we focus on statistical methods for estimating the effects of underlying environmental factors in the presence of spatial and temporal autocorrelation. The most comprehensive available information on...
Long and spatially variable Neolithic Demographic Transition in the North American Southwest
Kohler, Timothy A.; Reese, Kelsey M.
2014-01-01
In many places of the world, a Neolithic Demographic Transition (NDT) is visible as a several-hundred-year period of increased birth rates coupled with stable mortality rates, resulting in dramatic population growth that is eventually curtailed by increased mortality. Similar processes can be reconstructed in particular detail for the North American Southwest, revealing an anomalously long and spatially variable NDT. Irrigation-dependent societies experienced relatively low birth rates but were quick to achieve a high degree of sociopolitical complexity, whereas societies dependent on dry or rainfed farming experienced higher birth rates but less initial sociopolitical complexity. Low birth rates after A.D. 1200 mark the beginning of the decline of the Hohokam. Overall in the Southwest, birth rates increased slowly from 1100 B.C. to A.D. 500, and remained at high levels with some fluctuation until decreasing rapidly beginning A.D. 1300. Life expectancy at 15 increased slowly from 900 B.C. to A.D. 700, and then increased rapidly for 200 y before fluctuating and then declining after A.D. 1400. Life expectancy at birth, on the other hand, generally declined from 1100 B.C. to A.D. 1100/1200, before rebounding. Farmers took two millennia (∼1100 B.C. to ∼A.D. 1000) to reach the carrying capacity of the agricultural niche in the Southwest. PMID:24982134
Miskell, Georgia; Salmond, Jennifer A; Williams, David E
2018-04-01
Portable low-cost instruments have been validated and used to measure ambient nitrogen dioxide (NO 2 ) at multiple sites over a small urban area with 20min time resolution. We use these results combined with land use regression (LUR) and rank correlation methods to explore the effects of traffic, urban design features, and local meteorology and atmosphere chemistry on small-scale spatio-temporal variations. We measured NO 2 at 45 sites around the downtown area of Vancouver, BC, in spring 2016, and constructed four different models: i) a model based on averaging concentrations observed at each site over the whole measurement period, and separate temporal models for ii) morning, iii) midday, and iv) afternoon. Redesign of the temporal models using the average model predictors as constants gave three 'hybrid' models that used both spatial and temporal variables. These accounted for approximately 50% of the total variation with mean absolute error±5ppb. Ranking sites by concentration and by change in concentration across the day showed a shift of high NO 2 concentrations across the central city from morning to afternoon. Locations could be identified in which NO 2 concentration was determined by the geography of the site, and others as ones in which the concentration changed markedly from morning to afternoon indicating the importance of temporal controls. Rank correlation results complemented LUR in identifying significant urban design variables that impacted NO 2 concentration. High variability across a relatively small space was partially described by predictor variables related to traffic (bus stop density, speed limits, traffic counts, distance to traffic lights), atmospheric chemistry (ozone, dew point), and environment (land use, trees). A high-density network recording continuously would be needed fully to capture local variations. Copyright © 2017 Elsevier B.V. All rights reserved.
Climate variability in the subarctic area for the last 2 millennia
NASA Astrophysics Data System (ADS)
Nicolle, Marie; Debret, Maxime; Massei, Nicolas; Colin, Christophe; deVernal, Anne; Divine, Dmitry; Werner, Johannes P.; Hormes, Anne; Korhola, Atte; Linderholm, Hans W.
2018-01-01
To put recent climate change in perspective, it is necessary to extend the instrumental climate records with proxy data from paleoclimate archives. Arctic climate variability for the last 2 millennia has been investigated using statistical and signal analyses from three regionally averaged records from the North Atlantic, Siberia and Alaska based on many types of proxy data archived in the Arctic 2k database v1.1.1. In the North Atlantic and Alaska, the major climatic trend is characterized by long-term cooling interrupted by recent warming that started at the beginning of the 19th century. This cooling is visible in the Siberian region at two sites, warming at the others. The cooling of the Little Ice Age (LIA) was identified from the individual series, but it is characterized by wide-range spatial and temporal expression of climate variability, in contrary to the Medieval Climate Anomaly. The LIA started at the earliest by around AD 1200 and ended at the latest in the middle of the 20th century. The widespread temporal coverage of the LIA did not show regional consistency or particular spatial distribution and did not show a relationship with archive or proxy type either. A focus on the last 2 centuries shows a recent warming characterized by a well-marked warming trend parallel with increasing greenhouse gas emissions. It also shows a multidecadal variability likely due to natural processes acting on the internal climate system on a regional scale. A ˜ 16-30-year cycle is found in Alaska and seems to be linked to the Pacific Decadal Oscillation, whereas ˜ 20-30- and ˜ 50-90-year periodicities characterize the North Atlantic climate variability, likely in relation with the Atlantic Multidecadal Oscillation. These regional features are probably linked to the sea ice cover fluctuations through ice-temperature positive feedback.
Spatially explicit models for inference about density in unmarked or partially marked populations
Chandler, Richard B.; Royle, J. Andrew
2013-01-01
Recently developed spatial capture–recapture (SCR) models represent a major advance over traditional capture–recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5–10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19–1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating that neither spatial independence nor individual recognition is needed to estimate population density—rather, spatial dependence can be informative about individual distribution and density.
Space-Time Variability in River Flow Regimes of Northeast Turkey
NASA Astrophysics Data System (ADS)
Saris, F.; Hannah, D. M.; Eastwood, W. J.
2011-12-01
The northeast region of Turkey is characterised by relatively high annual precipitation totals and river flow. It is a mountainous region with high ecological status and also it is of prime interest to the energy sector. These characteristics make this region an important area for a hydroclimatology research in terms of future availability and management of water resources. However, there is not any previous research identifying hydroclimatological variability across the region. This study provides first comprehensive and detailed information on river flow regimes of northeast Turkey which is delimited by two major river basins namely East Black Sea (EBS) and Çoruh River (ÇRB) basins. A novel river flow classification is used that yields a large-scale perspective on hydroclimatology patterns of the region and allows interpretations regarding the controlling factors on river flow variability. River flow regimes are classified (with respect to timing and magnitude of flow) to examine spatial variability based on long-term average regimes, and also by grouping annual regimes for each station-year to identify temporal (between-year) variability. Results indicate that rivers in northeast Turkey are characterised by marked seasonal flow variation with an April-May-June maximum flow period. Spatial variability in flow regime seasonality is dependent largely on the topography of the study area. The EBS Basin, for which the North Anatolian Mountains cover the eastern part, is characterised by a May-June peak; whereas the ÇRB is defined by an April-May flow peak. The timing of river flows indicates that snowmelt is an important process and contributor of river flow maxima for both basins. The low flow season is January and February. Intermediate and low regime magnitude classes dominate in ÇRB and EBS basins, respectively, while high flow magnitude class is observed for one station only across the region. Result of regime stability analysis (year-to-year variation) shows that April-May and May-June peak shape classes together with low and intermediate magnitude classes are the most frequent and persistent flow regimes. This research has advanced understanding of hydroclimatological processes in northeast Turkey by identifying river flow regimes and together with explanations regarding the controlling factors on river flow variability.
Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre
2014-12-05
Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the spatial variation did not depend on the soil environmental variability for certain species. This finding could indicate the influence of contagious biotic interactions, stochastic factors, or unmeasured relevant soil environmental variables.
Jackson, Grant; Roddick, John F.; Bull, C. Michael
2016-01-01
Individual movement influences the spatial and social structuring of a population. Animals regularly use the same paths to move efficiently to familiar places, or to patrol and mark home ranges. We found that Australian sleepy lizards (Tiliqua rugosa), a monogamous species with stable pair-bonds, repeatedly used the same paths within their home ranges and investigated whether path re-use functions as a scent-marking behaviour, or whether it is influenced by site familiarity. Lizards can leave scent trails on the substrate when moving through the environment and have a well-developed vomeronasal system to detect and respond to those scents. Path re-use would allow sleepy lizards to concentrate scent marks along these well-used trails, advertising their presence. Hypotheses of mate attraction and mating competition predict that sleepy lizard males, which experience greater intra-sexual competition, mark more strongly. Consistent with those hypotheses, males re-used their paths more than females, and lizards that showed pairing behaviour with individuals of the opposite sex re-used paths more than unpaired lizards, particularly among females. Hinterland marking is most economic when home ranges are large and mobility is low, as is the case in the sleepy lizard. Consistent with this strategy, re-used paths were predominantly located in the inner 50% home range areas. Together, our detailed movement analyses suggest that path re-use is a scent marking behaviour in the sleepy lizard. We also investigated but found less support for alternative explanations of path re-use behaviour, such as site familiarity and spatial knowledge. Lizards established the same number of paths, and used them as often, whether they had occupied their home ranges for one or for more years. We discuss our findings in relation to maintenance of the monogamous mating system of this species, and the spatial and social structuring of the population. PMID:27019790
Leu, Stephan T; Jackson, Grant; Roddick, John F; Bull, C Michael
2016-01-01
Individual movement influences the spatial and social structuring of a population. Animals regularly use the same paths to move efficiently to familiar places, or to patrol and mark home ranges. We found that Australian sleepy lizards (Tiliqua rugosa), a monogamous species with stable pair-bonds, repeatedly used the same paths within their home ranges and investigated whether path re-use functions as a scent-marking behaviour, or whether it is influenced by site familiarity. Lizards can leave scent trails on the substrate when moving through the environment and have a well-developed vomeronasal system to detect and respond to those scents. Path re-use would allow sleepy lizards to concentrate scent marks along these well-used trails, advertising their presence. Hypotheses of mate attraction and mating competition predict that sleepy lizard males, which experience greater intra-sexual competition, mark more strongly. Consistent with those hypotheses, males re-used their paths more than females, and lizards that showed pairing behaviour with individuals of the opposite sex re-used paths more than unpaired lizards, particularly among females. Hinterland marking is most economic when home ranges are large and mobility is low, as is the case in the sleepy lizard. Consistent with this strategy, re-used paths were predominantly located in the inner 50% home range areas. Together, our detailed movement analyses suggest that path re-use is a scent marking behaviour in the sleepy lizard. We also investigated but found less support for alternative explanations of path re-use behaviour, such as site familiarity and spatial knowledge. Lizards established the same number of paths, and used them as often, whether they had occupied their home ranges for one or for more years. We discuss our findings in relation to maintenance of the monogamous mating system of this species, and the spatial and social structuring of the population.
China's Air Quality and Respiratory Disease Mortality Based on the Spatial Panel Model.
Cao, Qilong; Liang, Ying; Niu, Xueting
2017-09-18
Background : Air pollution has become an important factor restricting China's economic development and has subsequently brought a series of social problems, including the impact of air pollution on the health of residents, which is a topical issue in China. Methods : Taking into account this spatial imbalance, the paper is based on the spatial panel data model PM 2.5 . Respiratory disease mortality in 31 Chinese provinces from 2004 to 2008 is taken as the main variable to study the spatial effect and impact of air quality and respiratory disease mortality on a large scale. Results : It was found that there is a spatial correlation between the mortality of respiratory diseases in Chinese provinces. The spatial correlation can be explained by the spatial effect of PM 2.5 pollutions in the control of other variables. Conclusions : Compared with the traditional non-spatial model, the spatial model is better for describing the spatial relationship between variables, ensuring the conclusions are scientific and can measure the spatial effect between variables.
Barton, James C; Chen, Wen-Pin; Emond, Mary J; Phatak, Pradyumna D; Subramaniam, V Nathan; Adams, Paul C; Gurrin, Lyle C; Anderson, Gregory J; Ramm, Grant A; Powell, Lawrie W; Allen, Katrina J; Phillips, John D; Parker, Charles J; McLaren, Gordon D; McLaren, Christine E
2017-03-01
GNPAT p.D519G positivity is significantly increased in HFE p.C282Y homozygotes with markedly increased iron stores. We sought to determine associations of p.D519G and iron-related variables with iron stores in p.C282Y homozygotes. We defined markedly increased iron stores as serum ferritin >2247pmol/L (>1000μg/L) and either hepatic iron >236μmol/g dry weight or iron >10g by induction phlebotomy (men and women). We defined normal or mildly elevated iron stores as serum ferritin <674.1pmol/L (<300μg/L) or either age≥40y with iron ≤2.5g iron by induction phlebotomy or age≥50y with ≤3.0g iron by induction phlebotomy (men only). We compared participant subgroups using univariate methods. Using multivariable logistic regression, we evaluated associations of markedly increased iron stores with these variables: age; iron supplement use (dichotomous); whole blood units donated; erythrocyte units received as transfusion; daily alcohol consumption, g; and p.D519G positivity (heterozygosity or homozygosity). The mean age of 56 participants (94.6% men) was 55±10 (SD) y; 41 had markedly increased iron stores. Prevalences of swollen/tender 2nd/3rd metacarpophalangeal joints and elevated aspartate or alanine aminotransferase were significantly greater in participants with markedly increased iron stores. Only participants with markedly increased iron stores had cirrhosis. In multivariable analyses, p.D519G positivity was the only exposure variable significantly associated with markedly increased iron stores (odds ratio 9.9, 95% CI [1.6, 60.3], p=0.0126). GNPAT p.D519G is strongly associated with markedly increased iron stores in p.C282Y homozygotes after correction for age, iron-related variables, and alcohol consumption. Copyright © 2016 Elsevier Inc. All rights reserved.
Annual precipitation in the Yellowstone National Park region since AD 1173
Gray, Stephen T.; Graumlich, Lisa J.; Betancourt, Julio L.
2007-01-01
Cores and cross sections from 133 limber pine (Pinus flexilis James) and Douglas fir (Pseudotsuga menziesii (Mirbel) Franco) at four sites were used to estimate annual (July to June) precipitation in the Yellowstone National Park region for the period from AD 1173 to 1998. Examination of the long-term record shows that the early 20th century was markedly wet compared to the previous 700 yr. Extreme wet and dry years within the instrumental period fall within the range of past variability, and the magnitude of the worst-case droughts of the 20th century (AD 1930s and 1950s) was likely equaled or exceeded on numerous occasions before AD 1900. Spectral analysis showed significant decadal to multidecadal precipitation variability. At times this lower frequency variability produces strong regime-like behavior in regional precipitation, with the potential for rapid, high-amplitude switching between predominately wet and predominately dry conditions. Over multiple time scales, strong Yellowstone region precipitation anomalies were almost always associated with spatially extensive events spanning various combinations of the central and southern U.S. Rockies, the northern U.S.-Southern Canadian Rockies and the Pacific Northwest.
Annual precipitation in the Yellowstone National Park region since AD 1173
Gray, S.T.; Graumlich, L.J.; Betancourt, J.L.
2007-01-01
Cores and cross sections from 133 limber pine (Pinus flexilis James) and Douglas fir (Pseudotsuga menziesii (Mirbel) Franco) at four sites were used to estimate annual (July to June) precipitation in the Yellowstone National Park region for the period from AD 1173 to 1998. Examination of the long-term record shows that the early 20th century was markedly wet compared to the previous 700??yr. Extreme wet and dry years within the instrumental period fall within the range of past variability, and the magnitude of the worst-case droughts of the 20th century (AD 1930s and 1950s) was likely equaled or exceeded on numerous occasions before AD 1900. Spectral analysis showed significant decadal to multidecadal precipitation variability. At times this lower frequency variability produces strong regime-like behavior in regional precipitation, with the potential for rapid, high-amplitude switching between predominately wet and predominately dry conditions. Over multiple time scales, strong Yellowstone region precipitation anomalies were almost always associated with spatially extensive events spanning various combinations of the central and southern U.S. Rockies, the northern U.S.-Southern Canadian Rockies and the Pacific Northwest. ?? 2007 University of Washington.
A Skew-t space-varying regression model for the spectral analysis of resting state brain activity.
Ismail, Salimah; Sun, Wenqi; Nathoo, Farouk S; Babul, Arif; Moiseev, Alexader; Beg, Mirza Faisal; Virji-Babul, Naznin
2013-08-01
It is known that in many neurological disorders such as Down syndrome, main brain rhythms shift their frequencies slightly, and characterizing the spatial distribution of these shifts is of interest. This article reports on the development of a Skew-t mixed model for the spatial analysis of resting state brain activity in healthy controls and individuals with Down syndrome. Time series of oscillatory brain activity are recorded using magnetoencephalography, and spectral summaries are examined at multiple sensor locations across the scalp. We focus on the mean frequency of the power spectral density, and use space-varying regression to examine associations with age, gender and Down syndrome across several scalp regions. Spatial smoothing priors are incorporated based on a multivariate Markov random field, and the markedly non-Gaussian nature of the spectral response variable is accommodated by the use of a Skew-t distribution. A range of models representing different assumptions on the association structure and response distribution are examined, and we conduct model selection using the deviance information criterion. (1) Our analysis suggests region-specific differences between healthy controls and individuals with Down syndrome, particularly in the left and right temporal regions, and produces smoothed maps indicating the scalp topography of the estimated differences.
Estimating black bear density using DNA data from hair snares
Gardner, B.; Royle, J. Andrew; Wegan, M.T.; Rainbolt, R.E.; Curtis, P.D.
2010-01-01
DNA-based mark-recapture has become a methodological cornerstone of research focused on bear species. The objective of such studies is often to estimate population size; however, doing so is frequently complicated by movement of individual bears. Movement affects the probability of detection and the assumption of closure of the population required in most models. To mitigate the bias caused by movement of individuals, population size and density estimates are often adjusted using ad hoc methods, including buffering the minimum polygon of the trapping array. We used a hierarchical, spatial capturerecapture model that contains explicit components for the spatial-point process that governs the distribution of individuals and their exposure to (via movement), and detection by, traps. We modeled detection probability as a function of each individual's distance to the trap and an indicator variable for previous capture to account for possible behavioral responses. We applied our model to a 2006 hair-snare study of a black bear (Ursus americanus) population in northern New York, USA. Based on the microsatellite marker analysis of collected hair samples, 47 individuals were identified. We estimated mean density at 0.20 bears/km2. A positive estimate of the indicator variable suggests that bears are attracted to baited sites; therefore, including a trap-dependence covariate is important when using bait to attract individuals. Bayesian analysis of the model was implemented in WinBUGS, and we provide the model specification. The model can be applied to any spatially organized trapping array (hair snares, camera traps, mist nests, etc.) to estimate density and can also account for heterogeneity and covariate information at the trap or individual level. ?? The Wildlife Society.
Microscopic saw mark analysis: an empirical approach.
Love, Jennifer C; Derrick, Sharon M; Wiersema, Jason M; Peters, Charles
2015-01-01
Microscopic saw mark analysis is a well published and generally accepted qualitative analytical method. However, little research has focused on identifying and mitigating potential sources of error associated with the method. The presented study proposes the use of classification trees and random forest classifiers as an optimal, statistically sound approach to mitigate the potential for error of variability and outcome error in microscopic saw mark analysis. The statistical model was applied to 58 experimental saw marks created with four types of saws. The saw marks were made in fresh human femurs obtained through anatomical gift and were analyzed using a Keyence digital microscope. The statistical approach weighed the variables based on discriminatory value and produced decision trees with an associated outcome error rate of 8.62-17.82%. © 2014 American Academy of Forensic Sciences.
Community-wide spatial and temporal discordances of seed-seedling shadows in a tropical rainforest.
Rother, Débora Cristina; Pizo, Marco Aurélio; Siqueira, Tadeu; Rodrigues, Ricardo Ribeiro; Jordano, Pedro
2015-01-01
Several factors decrease plant survival throughout their lifecycles. Among them, seed dispersal limitation may play a major role by resulting in highly aggregated (contagious) seed and seedling distributions entailing increased mortality. The arrival of seeds, furthermore, may not match suitable environments for seed survival and, consequently, for seedling establishment. In this study, we investigated spatio-temporal patterns of seed and seedling distribution in contrasting microhabitats (bamboo and non-bamboo stands) from the Brazilian Atlantic Forest. Spatial distribution patterns, spatial concordance between seed rain and seedling recruitment between subsequent years in two fruiting seasons (2004-2005 and 2007-2009), and the relation between seeds and seedlings with environmental factors were examined within a spatially-explicit framework. Density and species richness of both seeds and seedlings were randomly distributed in non-bamboo stands, but showed significant clustering in bamboo stands. Seed and seedling distributions showed across-year inconsistency, suggesting a marked spatial decoupling of the seed and seedling stages. Generalized linear mixed effects models indicated that only seed density and seed species richness differed between stand types while accounting for variation in soil characteristics. Our analyses provide evidence of marked recruitment limitation as a result of the interplay between biotic and abiotic factors. Because bamboo stands promote heterogeneity in the forest, they are important components of the landscape. However, at high densities, bamboos may limit recruitment for the plant community by imposing marked discordances of seed arrival and early seedling recruitment.
Fully Resolved Simulations of Particle-Bed-Turbulence Interactions in Oscillatory Flows
NASA Astrophysics Data System (ADS)
Apte, S.; Ghodke, C.
2017-12-01
Particle-resolved direct numerical simulations (DNS) are performed to investigate the behavior of an oscillatory flow field over a bed of closely packed fixed spherical particles for a range of Reynolds numbers in transitional and rough turbulent flow regime. Presence of roughness leads to a substantial modification of the underlying boundary layer mechanism resulting in increased bed shear stress, reduction in the near-bed anisotropy, modification of the near-bed sweep and ejection motions along with marked changes in turbulent energy transport mechanisms. Characterization of such resulting flow field is performed by studying statistical descriptions of the near-bed turbulence for different roughness parameters. A double-averaging technique is employed to reveal spatial inhomogeneities at the roughness scale that provide alternate paths of energy transport in the turbulent kinetic energy (TKE) budget. Spatio-temporal characteristics of unsteady particle forces by studying their spatial distribution, temporal auto-correlations, frequency spectra, cross-correlations with near-bed turbulent flow variables and intermittency intermittency in the forces using the concept of impulse are investigated in detail. These first principle simulations provide substantial insights into the modeling of incipient motion of sediments.
How does spatial variability of climate affect catchment streamflow predictions?
Spatial variability of climate can negatively affect catchment streamflow predictions if it is not explicitly accounted for in hydrologic models. In this paper, we examine the changes in streamflow predictability when a hydrologic model is run with spatially variable (distribute...
Influences of Phonological Context on Tense Marking in Spanish-English Dual Language Learners
ERIC Educational Resources Information Center
Combiths, Philip N.; Barlow, Jessica A.; Potapova, Irina; Pruitt-Lord, Sonja
2017-01-01
Purpose: The emergence of tense-morpheme marking during language acquisition is highly variable, which confounds the use of tense marking as a diagnostic indicator of language impairment in linguistically diverse populations. In this study, we seek to better understand tense-marking patterns in young bilingual children by comparing phonological…
Touyarot, K; Venero, C; Sandi, C
2004-02-01
Although chronic stress has been reported to induce deleterious effects on hippocampal structure and function, the possible existence of individual differences in the vulnerability to develop stress-induced cognitive alterations was hypothesized. This study was designed to evaluate (i) whether individual variability in behavioural reactivity to novelty could be related to a differential vulnerability to show spatial learning deficits after chronic stress in young adult rats, and (ii) to what extent, could individual differences in stress-induced cognitive alterations be related to alterations in specific neurobiological substrates. Four month-old Wistar male rats were classified according to their locomotor reactivity to a novel environment, as either low (LR) or highly (HR) reactive, and then either submitted to psychosocial stress for 21-days (consisting of the daily cohabitation of each young adult rat with a new middle-aged rat) or left undisturbed. The results showed that psychosocial stress induced a marked deficit in spatial learning in the water maze in HR, but not in LR, rats. Then, a second experiment investigated the possible differential expression of corticosteroid receptors (MR and GR) and cell adhesion molecules (NCAM and L1) in the hippocampus of HR and LR rats, both under basal conditions and after exposure to chronic social stress. Although chronic stress induced a reduction on the hippocampal expression of MRs and the NCAM-140 isoform, the levels of these molecules did not differ between stressed rats with and without spatial learning impairments; i.e., between HR- and LR-stressed rats, respectively. Nevertheless, it should be noted that the reduction of the hippocampal expression of NCAM-140 induced by psychosocial stress was particularly marked in HR stressed rats. However, the expression of GRs, NCAM-120 and NCAM-180 isoforms, and L1, was not affected by stress, regardless of the reactivity of the animals. Therefore, although we failed to find a neurobiological substrate that specifically correlated with the differential cognitive vulnerability to chronic stress shown by animals with a different novelty reactivity, this study confirms the hypothesis that rats differ in their susceptibility to display stress-induced impairments in hippocampus-dependent spatial learning tasks. In addition, it provides a model to further search for the neurobiological substrate(s) involved in the differential susceptibility to develop stress-induced cognitive impairments.
NASA Astrophysics Data System (ADS)
Cristiano, Elena; ten Veldhuis, Marie-claire; van de Giesen, Nick
2017-07-01
In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.
Spatial and seasonal dynamics of brook trout populations inhabiting a central Appalachian watershed
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.
Isermann, D.A.; Bettoli, P.W.; Sammons, S.M.; Churchill, T.N.
2002-01-01
Initial poststocking mortality, oxytetracycline mark persistence, and year-class contribution were evaluated for black-nosed crappies, a morphological variant of the black crappie Pomoxis nigromaculatus, stocked into Tennessee reservoirs during 1997-1999. Average initial poststocking mortality was low (x?? = 13%, N = 44). Lake temperature and the difference between lake and hauling tank water temperatures were significant in explaining variability in arcsine-transformed mortality estimates; however, the variability explained by these factors was low (R2 = 0.15). Oxytetracycline immersion was a highly effective marking tool; 97-100% of all crappies treated were marked, and 99% of the marks were visible 36-110 weeks after marking. All control otoliths were correctly scored as unmarked during the evaluation, and mortality rates did not differ between marked and unmarked crappies. Year-class contribution was variable across reservoirs and was highest in Normandy Reservoir (34-93% at ages 1-3). Contribution at ages 1 and 2 was 11-24% in Woods Reservoir. Stocking did not supplement the crappie population in Lake Graham. Black-nosed crappies made up a significant portion (>50%) of the crappies harvested by anglers in Center Hill Reservoir 3 years after stocking was initiated. Conversely, black-nosed crappies made up a relatively small percentage (???12%) of the crappies harvested in Cherokee Reservoir in the 4 years after initial stocking.
NASA Astrophysics Data System (ADS)
Christianson, D. S.; Kaufman, C. G.; Kueppers, L. M.; Harte, J.
2013-12-01
Sampling limitations and current modeling capacity justify the common use of mean temperature values in summaries of historical climate and future projections. However, a monthly mean temperature representing a 1-km2 area on the landscape is often unable to capture the climate complexity driving organismal and ecological processes. Estimates of variability in addition to mean values are more biologically meaningful and have been shown to improve projections of range shifts for certain species. Historical analyses of variance and extreme events at coarse spatial scales, as well as coarse-scale projections, show increasing temporal variability in temperature with warmer means. Few studies have considered how spatial variance changes with warming, and analysis for both temporal and spatial variability across scales is lacking. It is unclear how the spatial variability of fine-scale conditions relevant to plant and animal individuals may change given warmer coarse-scale mean values. A change in spatial variability will affect the availability of suitable habitat on the landscape and thus, will influence future species ranges. By characterizing variability across both temporal and spatial scales, we can account for potential bias in species range projections that use coarse climate data and enable improvements to current models. In this study, we use temperature data at multiple spatial and temporal scales to characterize spatial and temporal variability under a warmer climate, i.e., increased mean temperatures. Observational data from the Sierra Nevada (California, USA), experimental climate manipulation data from the eastern and western slopes of the Rocky Mountains (Colorado, USA), projected CMIP5 data for California (USA) and observed PRISM data (USA) allow us to compare characteristics of a mean-variance relationship across spatial scales ranging from sub-meter2 to 10,000 km2 and across temporal scales ranging from hours to decades. Preliminary spatial analysis at fine-spatial scales (sub-meter to 10-meter) shows greater temperature variability with warmer mean temperatures. This is inconsistent with the inherent assumption made in current species distribution models that fine-scale variability is static, implying that current projections of future species ranges may be biased -- the direction and magnitude requiring further study. While we focus our findings on the cross-scaling characteristics of temporal and spatial variability, we also compare the mean-variance relationship between 1) experimental climate manipulations and observed conditions and 2) temporal versus spatial variance, i.e., variability in a time-series at one location vs. variability across a landscape at a single time. The former informs the rich debate concerning the ability to experimentally mimic a warmer future. The latter informs space-for-time study design and analyses, as well as species persistence via a combined spatiotemporal probability of suitable future habitat.
Spatio-Temporal Variability of Groundwater Storage in India
NASA Technical Reports Server (NTRS)
Bhanja, Soumendra; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit
2016-01-01
Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Ground water storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent).In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.
Spatio-temporal variability of groundwater storage in India.
Bhanja, Soumendra N; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit
2017-01-01
Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Groundwater storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent). In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.
Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis
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
China’s Air Quality and Respiratory Disease Mortality Based on the Spatial Panel Model
Cao, Qilong; Liang, Ying; Niu, Xueting
2017-01-01
Background: Air pollution has become an important factor restricting China’s economic development and has subsequently brought a series of social problems, including the impact of air pollution on the health of residents, which is a topical issue in China. Methods: Taking into account this spatial imbalance, the paper is based on the spatial panel data model PM2.5. Respiratory disease mortality in 31 Chinese provinces from 2004 to 2008 is taken as the main variable to study the spatial effect and impact of air quality and respiratory disease mortality on a large scale. Results: It was found that there is a spatial correlation between the mortality of respiratory diseases in Chinese provinces. The spatial correlation can be explained by the spatial effect of PM2.5 pollutions in the control of other variables. Conclusions: Compared with the traditional non-spatial model, the spatial model is better for describing the spatial relationship between variables, ensuring the conclusions are scientific and can measure the spatial effect between variables. PMID:28927016
Baldissera, Ronei; Rodrigues, Everton N L; Hartz, Sandra M
2012-01-01
The distribution of beta diversity is shaped by factors linked to environmental and spatial control. The relative importance of both processes in structuring spider metacommunities has not yet been investigated in the Atlantic Forest. The variance explained by purely environmental, spatially structured environmental, and purely spatial components was compared for a metacommunity of web spiders. The study was carried out in 16 patches of Atlantic Forest in southern Brazil. Field work was done in one landscape mosaic representing a slight gradient of urbanization. Environmental variables encompassed plot- and patch-level measurements and a climatic matrix, while principal coordinates of neighbor matrices (PCNMs) acted as spatial variables. A forward selection procedure was carried out to select environmental and spatial variables influencing web-spider beta diversity. Variation partitioning was used to estimate the contribution of pure environmental and pure spatial effects and their shared influence on beta-diversity patterns, and to estimate the relative importance of selected environmental variables. Three environmental variables (bush density, land use in the surroundings of patches, and shape of patches) and two spatial variables were selected by forward selection procedures. Variation partitioning revealed that 15% of the variation of beta diversity was explained by a combination of environmental and PCNM variables. Most of this variation (12%) corresponded to pure environmental and spatially environmental structure. The data indicated that (1) spatial legacy was not important in explaining the web-spider beta diversity; (2) environmental predictors explained a significant portion of the variation in web-spider composition; (3) one-third of environmental variation was due to a spatial structure that jointly explains variation in species distributions. We were able to detect important factors related to matrix management influencing the web-spider beta-diversity patterns, which are probably linked to historical deforestation events.
Shifts of environmental and phytoplankton variables in a regulated river: A spatial-driven analysis.
Sabater-Liesa, Laia; Ginebreda, Antoni; Barceló, Damià
2018-06-18
The longitudinal structure of the environmental and phytoplankton variables was investigated in the Ebro River (NE Spain), which is heavily affected by water abstraction and regulation. A first exploration indicated that the phytoplankton community did not resist the impact of reservoirs and barely recovered downstream of them. The spatial analysis showed that the responses of the phytoplankton and environmental variables were not uniform. The two set of variables revealed spatial variability discontinuities and river fragmentation upstream and downstream from the reservoirs. Reservoirs caused the replacement of spatially heterogeneous habitats by homogeneous spatially distributed water bodies, these new environmental conditions downstream benefiting the opportunist and cosmopolitan algal taxa. The application of a spatial auto-regression model to algal biomass (chlorophyll-a) permitted to capture the relevance and contribution of extra-local influences in the river ecosystem. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
Net ecosystem metabolism (NEM) is becoming a commonly used ecological indicator of estuarine ecosystem metabolic rates. Estuarine ecosystem processes are spatially and temporally variable, but the corresponding variability in NEM has not been properly assessed. Spatial and temp...
Children’s Marking of Verbal –s by Nonmainstream English Dialect and Clinical Status
Cleveland, Lesli H.; Oetting, Janna B.
2015-01-01
Purpose Children’s marking of verbal –s was examined by their dialect (African American English [AAE] vs. Southern White English [SWE]) and clinical status (specific language impairment [SLI] vs. typically developing [TD]) and as a function of 4 linguistic variables (verb regularity, negation, expression of a habitual activity, and expression of historical present tense). Method The data were language samples from 57 six-year-olds who varied by their dialect and clinical status (AAE: SLI = 14, TD = 12; SWE: SLI = 12, TD = 19). Results The AAE groups produced lower rates of marking than did the SWE groups, and the SWE SLI group produced lower rates of marking than did the SWE TD group. Although low numbers of verb contexts made it difficult to evaluate the linguistic variables, there was evidence of their influence, especially for verb regularity and negation. The direction and magnitude of the effects were often (but not always) consistent with what has been described in the adult dialect literature. Conclusion Verbal –s can be used to help distinguish children with and without SLI in SWE but not in AAE. Clinicians can apply these findings to other varieties of AAE and SWE and other dialects by considering rates of marking and the effects of linguistic variables on marking. PMID:23813205
NASA Astrophysics Data System (ADS)
Sonam, Sonam; Jain, Vikrant
2017-04-01
River long profile is one of the fundamental geomorphic parameters which provides a platform to study interaction of geological and geomorphic processes at different time scales. Long profile shape is governed by geological processes at 10 ^ 5 - 10 ^ 6 years' time scale and it controls the modern day (10 ^ 0 - 10 ^ 1 years' time scale) fluvial processes by controlling the spatial variability of channel slope. Identification of an appropriate model for river long profile may provide a tool to analyse the quantitative relationship between basin geology, profile shape and its geomorphic effectiveness. A systematic analysis of long profiles has been carried for the Himalayan tributaries of the Ganga River basin. Long profile shape and stream power distribution pattern is derived using SRTM DEM data (90 m spatial resolution). Peak discharge data from 34 stations is used for hydrological analysis. Lithological variability and major thrusts are marked along the river long profile. The best fit of long profile is analysed for power, logarithmic and exponential function. Second order exponential function provides the best representation of long profiles. The second order exponential equation is Z = K1*exp(-β1*L) + K2*exp(-β2*L), where Z is elevation of channel long profile, L is the length, K and β are coefficients of the exponential function. K1 and K2 are the proportion of elevation change of the long profile represented by β1 (fast) and β2 (slow) decay coefficients of the river long profile. Different values of coefficients express the variability in long profile shapes and is related with the litho-tectonic variability of the study area. Channel slope of long profile is estimated taking the derivative of exponential function. Stream power distribution pattern along long profile is estimated by superimposing the discharge and long profile slope. Sensitivity analysis of stream power distribution with decay coefficients of the second order exponential equation is evaluated for a range of coefficient values. Our analysis suggests that the amplitude of stream power peak value is dependent on K1, the proportion of elevation change coming under the fast decay exponent and the location of stream power peak is dependent of the long profile decay coefficient (β1). Different long profile shapes owing to litho-tectonic variability across the Himalayas are responsible for spatial variability of stream power distribution pattern. Most of the stream power peaks lie in the Higher Himalaya. In general, eastern rivers have higher stream power in hinterland area and low stream power in the alluvial plains. This is responsible for, 1) higher erosion rate and sediment supply in hinterland of eastern rivers, 2) the incised and stable nature of channels in the western alluvial plains and 3) aggrading channels with dynamic nature in the eastern alluvial plains. Our study shows that the spatial variability of litho-units defines the coefficients of long profile function which in turn controls the position and magnitude of stream power maxima and hence the geomorphic variability in a fluvial system.
Using Predictions Based on Geostatistics to Monitor Trends in Aspergillus flavus Strain Composition.
Orum, T V; Bigelow, D M; Cotty, P J; Nelson, M R
1999-09-01
ABSTRACT Aspergillus flavus is a soil-inhabiting fungus that frequently produces aflatoxins, potent carcinogens, in cottonseed and other seed crops. A. flavus S strain isolates, characterized on the basis of sclerotial morphology, are highly toxigenic. Spatial and temporal characteristics of the percentage of the A. flavus isolates that are S strain (S strain incidence) were used to predict patterns across areas of more than 30 km(2). Spatial autocorrelation in S strain incidence in Yuma County, AZ, was shown to extend beyond field boundaries to adjacent fields. Variograms revealed both short-range (2 to 6 km) and long-range (20 to 30 km) spatial structure in S strain incidence. S strain incidence at 36 locations sampled in July 1997 was predicted with a high correlation between expected and observed values (R = 0.85, P = 0.0001) by kriging data from July 1995 and July 1996. S strain incidence at locations sampled in October 1997 and March 1998 was markedly less than predicted by kriging data from the same months in prior years. Temporal analysis of four locations repeatedly sampled from April 1995 through July 1998 also indicated a major reduction in S strain incidence in the Texas Hill area after July 1997. Surface maps generated by kriging point data indicated a similarity in the spatial pattern of S strain incidence among all sampling dates despite temporal changes in the overall S strain incidence. Geostatistics provided useful descriptions of variability in S strain incidence over space and time.
Tedoldi, Damien; Chebbo, Ghassan; Pierlot, Daniel; Branchu, Philippe; Kovacs, Yves; Gromaire, Marie-Christine
2017-02-01
Stormwater runoff infiltration brings about some concerns regarding its potential impact on both soil and groundwater quality; besides, the fate of contaminants in source-control devices somewhat suffers from a lack of documentation. The present study was dedicated to assessing the spatial distribution of three heavy metals (copper, lead, zinc) in the surface soil of ten small-scale infiltration facilities, along with several physical parameters (soil moisture, volatile matter, variable thickness of the upper horizon). High-resolution samplings and in-situ measurements were undertaken, followed by X-ray fluorescence analyses and spatial interpolation. Highest metal accumulation was found in a relatively narrow area near the water inflow zone, from which concentrations markedly decreased with increasing distance. Maximum enrichment ratios amounted to >20 in the most contaminated sites. Heavy metal patterns give a time-integrated vision of the non-uniform infiltration fluxes, sedimentation processes and surface flow pathways within the devices. This element indicates that the lateral extent of contamination is mainly controlled by hydraulics. The evidenced spatial structure of soil concentrations restricts the area where remediation measures would be necessary in these systems, and suggests possible optimization of their hydraulic functioning towards an easier maintenance. Heterogeneous upper boundary conditions should be taken into account when studying the fate of micropollutants in infiltration facilities with either mathematical modeling or soil coring field surveys. Copyright © 2016 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Lercari, D.; Defeo, O.
1999-10-01
Sandy beaches are ecosystems which are heavily affected by human activities. An example of this is freshwater discharges, which are known to change salinity, temperature and nutrient regimes and degrade nearshore environments. However, the effects of this kind of disturbance on sandy beach fauna have been little studied. This paper reports the spatial effects of a man-made freshwater canal discharge on the population structure, abundance and reproductive characteristics of the sandy beach mole crab Emerita brasiliensis. Along the 22 km of sandy beach sampled, the mole crab showed a marked longshore variability in population structure and abundance. Abundance of different population components (juveniles, males, females and ovigerous females) significantly decreased towards the canal. Population structure by sex and size, individual weight, fecundity and female maturity patterns at size also displayed a non-linear response to the distance from the freshwater discharge. Only the size structure of males did not follow this pattern. For males, spatial heterogeneity enhanced the detection of density-dependence at less disturbed sites. The authors conclude that artificial freshwater discharges could significantly influence the distribution, abundance and life-history traits of the biota of sandy beaches, and that further study of these ecosystems should include human activities as important factors affecting spatial and temporal trends. The need to consider different spatial and temporal scales in order to detect the effect of anthropogenically-driven impacts in sandy beach populations is stressed.
Spatial pattern analysis of Cu, Zn and Ni and their interpretation in the Campania region (Italy)
NASA Astrophysics Data System (ADS)
Petrik, Attila; Albanese, Stefano; Jordan, Gyozo; Rolandi, Roberto; De Vivo, Benedetto
2017-04-01
The uniquely abundant Campanian topsoil dataset enabled us to perform a spatial pattern analysis on 3 potentially toxic elements of Cu, Zn and Ni. This study is focusing on revealing the spatial texture and distribution of these elements by spatial point pattern and image processing analysis such as lineament density and spatial variability index calculation. The application of these methods on geochemical data provides a new and efficient tool to understand the spatial variation of concentrations and their background/baseline values. The determination and quantification of spatial variability is crucial to understand how fast the change in concentration is in a certain area and what processes might govern the variation. The spatial variability index calculation and image processing analysis including lineament density enables us to delineate homogenous areas and analyse them with respect to lithology and land use. Identification of spatial outliers and their patterns were also investigated by local spatial autocorrelation and image processing analysis including the determination of local minima and maxima points and singularity index analysis. The spatial variability of Cu and Zn reveals the highest zone (Cu: 0.5 MAD, Zn: 0.8-0.9 MAD, Median Deviation Index) along the coast between Campi Flegrei and the Sorrento Peninsula with the vast majority of statistically identified outliers and high-high spatial clustered points. The background/baseline maps of Cu and Zn reveals a moderate to high variability (Cu: 0.3 MAD, Zn: 0.4-0.5 MAD) NW-SE oriented zone including disrupted patches from Bisaccia to Mignano following the alluvial plains of Appenine's rivers. This zone has high abundance of anomaly concentrations identified using singularity analysis and it also has a high density of lineaments. The spatial variability of Ni shows the highest variability zone (0.6-0.7 MAD) around Campi Flegrei where the majority of low outliers are concentrated. The variability of background/baseline map of Ni reveals a shift to the east in case of highest variability zones coinciding with limestone outcrops. The high segmented area between Mignano and Bisaccia partially follows the alluvial plains of Appenine's rivers which seem to be playing a crucial role in the distribution and redistribution pattern of Cu, Zn and Ni in Campania. The high spatial variability zones of the later elements are located in topsoils on volcanoclastic rocks and are mostly related to cultivation and urbanised areas.
Sakamoto, Manabu; Ruta, Marcello
2012-01-01
Background Studies of biological shape evolution are greatly enhanced when framed in a phylogenetic perspective. Inclusion of fossils amplifies the scope of macroevolutionary research, offers a deep-time perspective on tempo and mode of radiations, and elucidates life-trait changes. We explore the evolution of skull shape in felids (cats) through morphometric analyses of linear variables, phylogenetic comparative methods, and a new cladistic study of saber-toothed cats. Methodology/Principal Findings A new phylogenetic analysis supports the monophyly of saber-toothed cats (Machairodontinae) exclusive of Felinae and some basal felids, but does not support the monophyly of various saber-toothed tribes and genera. We quantified skull shape variation in 34 extant and 18 extinct species using size-adjusted linear variables. These distinguish taxonomic group membership with high accuracy. Patterns of morphospace occupation are consistent with previous analyses, for example, in showing a size gradient along the primary axis of shape variation and a separation between large and small-medium cats. By combining the new phylogeny with a molecular tree of extant Felinae, we built a chronophylomorphospace (a phylogeny superimposed onto a two-dimensional morphospace through time). The evolutionary history of cats was characterized by two major episodes of morphological divergence, one marking the separation between saber-toothed and modern cats, the other marking the split between large and small-medium cats. Conclusions/Significance Ancestors of large cats in the ‘Panthera’ lineage tend to occupy, at a much later stage, morphospace regions previously occupied by saber-toothed cats. The latter radiated out into new morphospace regions peripheral to those of extant large cats. The separation between large and small-medium cats was marked by considerable morphologically divergent trajectories early in feline evolution. A chronophylomorphospace has wider applications in reconstructing temporal transitions across two-dimensional trait spaces, can be used in ecophenotypical and functional diversity studies, and may reveal novel patterns of morphospace occupation. PMID:22792186
NASA Astrophysics Data System (ADS)
Arístegui, Javier; Montero, María F.
2005-02-01
The temporal and spatial variabilities in the abundance and respiratory activity of plankton communities (<200 μm) were studied during three seasonal cruises around Gran Canaria Island (Canary Islands), a region of high mesoscale variability. Marked seasonal changes in respiratory activity, plankton community structure, and the ratio of heterotrophic to autotrophic biomass can be largely explained by hydrographic changes at the mesoscale level. Wind/current shearing at the flanks of the island enhances plankton respiration, presumably as the consequence of an increase in turbulence. Counter-paired cyclonic and anticyclonic eddies generated downstream of the island act as a two-way biological pump, increasing plankton production by nutrient pumping into the euphotic zone and accelerating the transport of organic matter into the aphotic zone, respectively. Coastal upwelling waters invading the Canary region in the form of filaments can transport either water with low plankton respiration and large phytoplankton cells or water with high respiratory rates associated with small cells. Plankton respiration was closely related to the abundance of Synechococcus type cyanobacteria and heterotrophic nanoflagellates during the three periods, but was only correlated with chlorophyll during the most fertile season, suggesting that respiration was mainly linked to microbial food web processes. Size-fractionated studies showed that 51-67% of the respiratory activity was due to picoplankton cells (<2 μm). Respiration rates (average values: 113±18 to 187±87 mmol C m -2 d -1) matched primary production rates during the fertile period, but were up to one order of magnitude higher during the rest of the year. Substantial inputs of organic matter from the coastal upwelling would be necessary to balance the large annual heterotrophic deficit in the region of study.
Simulating maize yield and biomass with spatial variability of soil field capacity
USDA-ARS?s Scientific Manuscript database
Spatial variability in field soil water and other properties is a challenge for system modelers who use only representative values for model inputs, rather than their distributions. In this study, we compared simulation results from a calibrated model with spatial variability of soil field capacity ...
Automatic marker for photographic film
NASA Technical Reports Server (NTRS)
Gabbard, N. M.; Surrency, W. M.
1974-01-01
Commercially-produced wire-marking machine is modified to title or mark film rolls automatically. Machine is used with film drive mechanism which is powered with variable-speed, 28-volt dc motor. Up to 40 frames per minute can be marked, reducing time and cost of process.
Modelling space of spread Dengue Hemorrhagic Fever (DHF) in Central Java use spatial durbin model
NASA Astrophysics Data System (ADS)
Ispriyanti, Dwi; Prahutama, Alan; Taryono, Arkadina PN
2018-05-01
Dengue Hemorrhagic Fever is one of the major public health problems in Indonesia. From year to year, DHF causes Extraordinary Event in most parts of Indonesia, especially Central Java. Central Java consists of 35 districts or cities where each region is close to each other. Spatial regression is an analysis that suspects the influence of independent variables on the dependent variables with the influences of the region inside. In spatial regression modeling, there are spatial autoregressive model (SAR), spatial error model (SEM) and spatial autoregressive moving average (SARMA). Spatial Durbin model is the development of SAR where the dependent and independent variable have spatial influence. In this research dependent variable used is number of DHF sufferers. The independent variables observed are population density, number of hospitals, residents and health centers, and mean years of schooling. From the multiple regression model test, the variables that significantly affect the spread of DHF disease are the population and mean years of schooling. By using queen contiguity and rook contiguity, the best model produced is the SDM model with queen contiguity because it has the smallest AIC value of 494,12. Factors that generally affect the spread of DHF in Central Java Province are the number of population and the average length of school.
Mary M. Conner; John J. Keane; Claire V. Gallagher; Thomas E. Munton; Paula A. Shaklee
2016-01-01
Monitoring studies often use marked animals to estimate population abundance at small spatial scales. However, at smaller scales, occupancy sampling, which uses detection/nondetection data, may be useful where sites are approximately territories, and occupancy dynamics should be strongly correlated with population dynamics. Occupancy monitoring has advantages...
Past Tense Marking by African American English–Speaking Children Reared in Poverty
Pruitt, Sonja; Oetting, Janna
2012-01-01
Purpose This study examined past tense marking by African American English (AAE)-speaking children from low- and middle-income backgrounds to determine if poverty affects children’s marking of past tense in ways that mirror the clinical condition of specific language impairment (SLI). Method Participants were 15 AAE-speaking 6-year-olds from low-income backgrounds, 15 AAE-speaking 6-year-olds from middle-income backgrounds who served as age-matched controls, and 15 AAE-speaking 5-year-olds from middle-income backgrounds who served as language-matched controls. Data were drawn from language samples and probes. Results Results revealed high rates of regular marking, variable rates of irregular marking, high rates of over-regularizations, and absence of dialect-inappropriate errors of commission. For some analyses, marking was affected by the phonological characteristics of the items and the children’s ages, but none of the analyses revealed effects for the children’s socioeconomic level. Conclusions Within AAE, poverty status as a variable affects past tense marking in ways that are different from the clinical condition of SLI. PMID:18695014
Tense Marking in Black English. A Linguistic and Social Analysis. Urban Language Series, No. 8.
ERIC Educational Resources Information Center
Fasold, Ralph W.
In recent years a considerable amount of interest has developed in language variability and in the educational problems connected with it. This volume is a report of linguistic research on the variable language behavior in a community of American English speakers, specifically on some aspects of tense marking in Black English. The following topics…
Spatio-temporal characteristics of PM10 concentration across Malaysia
NASA Astrophysics Data System (ADS)
Juneng, Liew; Latif, Mohd Talib; Tangang, Fredolin T.; Mansor, Haslina
The recurrence of forest fires in Southeast Asia and associated biomass burning, has contributed markedly to the problem of trans-boundary haze and the long-range movement of pollutants in the region. Air pollutants, specifically particulate matter in the atmosphere, have received extensive attention, mainly because of their adverse effect on people's health. In this study, the spatial and temporal variability of the PM10 concentration across Malaysia was analyzed by means of the rotated principal component analysis. The results suggest that the variability of the PM10 concentration can be decomposed into four dominant modes, each characterizing different spatial and temporal variations. The first mode characterizes the southwest coastal region of the Malaysian Peninsular with the PM10 showing a peak concentration during the summer monsoon i.e. when the winds are predominantly southerlies or southwesterlies, and a minimal concentration during the winter monsoon. The second mode features the region of western Borneo with the PM10 exhibiting a concentration surge in August-September, which is likely to be the result of the northward shift of the Inter Tropical Convergence Zone (ITCZ) and the subsequent rapid arrival of the rainy season. The third mode delineates the northern region of the Malaysian Peninsular with strong bimodality in the PM10 concentration. Seasonally, this component exhibits two concentration maxima during the late winter and summer monsoons, as well as two minima during the inter-monsoon periods. The fourth dominant mode characterizes the northern Borneo region which exhibits weaker seasonality of the PM10 concentration. Generally, the seasonal fluctuation of the PM10 concentration is largely associated with the seasonal variation of rainfall in the country. However, in addition to this, the PM10 concentration also fluctuates markedly in two timescale bands i.e. 10-20 days quasi-biweekly (QBW) and 30-60 days lower frequency (LF) band of the intra-seasonal timescales. These intra-seasonal fluctuations show strong seasonality with the largest fraction of variance occurring during the boreal summer and the weakest variance during the winter. Generally, the LF intra-seasonal oscillation is stronger compared to the QBW intra-seasonal band.
Extracting spatial information from large aperture exposures of diffuse sources
NASA Technical Reports Server (NTRS)
Clarke, J. T.; Moos, H. W.
1981-01-01
The spatial properties of large aperture exposures of diffuse emission can be used both to investigate spatial variations in the emission and to filter out camera noise in exposures of weak emission sources. Spatial imaging can be accomplished both parallel and perpendicular to dispersion with a resolution of 5-6 arc sec, and a narrow median filter running perpendicular to dispersion across a diffuse image selectively filters out point source features, such as reseaux marks and fast particle hits. Spatial information derived from observations of solar system objects is presented.
NASA Astrophysics Data System (ADS)
Hanke, John R.; Fischer, Mark P.; Pollyea, Ryan M.
2018-03-01
In this study, the directional semivariogram is deployed to investigate the spatial variability of map-scale fracture network attributes in the Paradox Basin, Utah. The relative variability ratio (R) is introduced as the ratio of integrated anisotropic semivariogram models, and R is shown to be an effective metric for quantifying the magnitude of spatial variability for any two azimuthal directions. R is applied to a GIS-based data set comprising roughly 1200 fractures, in an area which is bounded by a map-scale anticline and a km-scale normal fault. This analysis reveals that proximity to the fault strongly influences the magnitude of spatial variability for both fracture intensity and intersection density within 1-2 km. Additionally, there is significant anisotropy in the spatial variability, which is correlated with trends of the anticline and fault. The direction of minimum spatial correlation is normal to the fault at proximal distances, and gradually rotates and becomes subparallel to the fold axis over the same 1-2 km distance away from the fault. We interpret these changes to reflect varying scales of influence of the fault and the fold on fracture network development: the fault locally influences the magnitude and variability of fracture network attributes, whereas the fold sets the background level and structure of directional variability.
Spatial patterns of throughfall isotopic composition at the event and seasonal timescales
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...
Short-term rainfall: its scaling properties over Portugal
NASA Astrophysics Data System (ADS)
de Lima, M. Isabel P.
2010-05-01
The characterization of rainfall at a variety of space- and time-scales demands usually that data from different origins and resolution are explored. Different tools and methodologies can be used for this purpose. In regions where the spatial variation of rain is marked, the study of the scaling structure of rainfall can lead to a better understanding of the type of events affecting that specific area, which is essential for many engineering applications. The relevant factors affecting rain variability, in time and space, can lead to contrasting statistics which should be carefully taken into account in design procedures and decision making processes. One such region is Mainland Portugal; the territory is located in the transitional region between the sub-tropical anticyclone and the subpolar depression zones and is characterized by strong north-south and east-west rainfall gradients. The spatial distribution and seasonal variability of rain are particularly influenced by the characteristics of the global circulation. One specific feature is the Atlantic origin of many synoptic disturbances in the context of the regional geography (e.g. latitude, orography, oceanic and continental influences). Thus, aiming at investigating the statistical signature of rain events of different origins, resulting from the large number of mechanisms and factors affecting the rainfall climate over Portugal, scale-invariant analyses of the temporal structure of rain from several locations in mainland Portugal were conducted. The study used short-term rainfall time series. Relevant scaling ranges were identified and characterized that help clarifying the small-scale behaviour and statistics of this process.
Wilk, John A.; Kramer, Andrea T.; Ashley, Mary V.
2009-01-01
Background and Aims Many plants reproduce both clonally and sexually, and the balance between the two modes of reproduction will vary among populations. Clonal reproduction was characterized in three populations of the wild strawberry, Fragaria virginiana, to determine the extent that reproductive mode varied locally between sites. The study sites were fragmented woodlands in Cook County, Illinois, USA. Methods A total of 95 strawberry ramets were sampled from the three sites via transects. Ramets were mapped and genotyped at five variable microsatellite loci. The variability at these five loci was sufficient to assign plants to clones with high confidence, and the spatial pattern of genets was mapped at each site. Key Results A total of 27 distinct multilocus genotypes were identified. Of these, 18 genotypes were detected only once, with the remaining nine detected in multiple ramets. The largest clone was identified in 16 ramets. No genets were shared between sites, and each site exhibited markedly different clonal and sexual recruitment patterns, ranging from two non-overlapping and widespread genets to 19 distinct genets. Only one flowering genet was female; the remainder were hermaphrodites. Conclusions Local population history or fine-scale ecological differences can result in dramatically different reproductive patterns at small spatial scales. This finding may be fairly widespread among clonal plant species, and studies that aim to characterize reproductive modes in species capable of asexual reproduction need to evaluate reproductive modes in multiple populations and sites. PMID:19797422
The Footprint of Continental-Scale Ocean Currents on the Biogeography of Seaweeds
Wernberg, Thomas; Thomsen, Mads S.; Connell, Sean D.; Russell, Bayden D.; Waters, Jonathan M.; Zuccarello, Giuseppe C.; Kraft, Gerald T.; Sanderson, Craig; West, John A.; Gurgel, Carlos F. D.
2013-01-01
Explaining spatial patterns of biological organisation remains a central challenge for biogeographic studies. In marine systems, large-scale ocean currents can modify broad-scale biological patterns by simultaneously connecting environmental (e.g. temperature, salinity and nutrients) and biological (e.g. amounts and types of dispersed propagules) properties of adjacent and distant regions. For example, steep environmental gradients and highly variable, disrupted flow should lead to heterogeneity in regional communities and high species turnover. In this study, we investigated the possible imprint of the Leeuwin (LC) and East Australia (EAC) Currents on seaweed communities across ~7,000 km of coastline in temperate Australia. These currents flow poleward along the west and east coasts of Australia, respectively, but have markedly different characteristics. We tested the hypothesis that, regional seaweed communities show serial change in the direction of current flow and that, because the LC is characterised by a weaker temperature gradient and more un-interrupted along-shore flow compared to the EAC, then coasts influenced by the LC have less variable seaweed communities and lower species turnover across regions than the EAC. This hypothesis was supported. We suggest that this pattern is likely caused by a combination of seaweed temperature tolerances and current-driven dispersal. In conclusion, our findings support the idea that the characteristics of continental-scale currents can influence regional community organisation, and that the coupling of ocean currents and marine biological structure is a general feature that transcends taxa and spatial scales. PMID:24260352
Chapter 9: Marking and assessing forest heterogeneity
M. North; J. Sherlock
2012-01-01
Marking guidelines commonly use stocking level, crown class, and species preferences to meet management objectives. Traditionally, these guidelines were applied across the extent of the stand. Current marking guidelines are more flexible, responding to within-stand variability with different stocking level, crown class, and species preference guidelines in...
Empirical spatial econometric modelling of small scale neighbourhood
NASA Astrophysics Data System (ADS)
Gerkman, Linda
2012-07-01
The aim of the paper is to model small scale neighbourhood in a house price model by implementing the newest methodology in spatial econometrics. A common problem when modelling house prices is that in practice it is seldom possible to obtain all the desired variables. Especially variables capturing the small scale neighbourhood conditions are hard to find. If there are important explanatory variables missing from the model, the omitted variables are spatially autocorrelated and they are correlated with the explanatory variables included in the model, it can be shown that a spatial Durbin model is motivated. In the empirical application on new house price data from Helsinki in Finland, we find the motivation for a spatial Durbin model, we estimate the model and interpret the estimates for the summary measures of impacts. By the analysis we show that the model structure makes it possible to model and find small scale neighbourhood effects, when we know that they exist, but we are lacking proper variables to measure them.
TBI-Induced Formation of Toxic Tau and Its Biochemical Similarities to Tau in AD Brains
2016-10-01
onto wild-type mice markedly reduces 1) memory including contextual fear memory and spatial memory, and 2) long-term potentiation, a type of...TERMS Tau, contextual fear memory, spatial memory, synaptic plasticity, traumatic brain injury, Alzheimer’s disease 16. SECURITY CLASSIFICATION OF: 17...mechanism leading to TBI and AD. 2 KEYWORDS Tau, contextual fear memory, spatial memory, synaptic plasticity, traumatic brain injury, Alzheimer’s
Plethodontid salamander population ecology in managed forest headwaters in the Oregon coast range
Matthew R. Kluber; Deanna H. Olson
2013-01-01
We examined temporal and spatial patterns of terrestrial amphibian species abundances and individual movements in western Oregon managed headwater forest stands using artifi cial cover object (ACO) arrays. Using mark-recapture methods, we estimated the eff ects of species and seasonality on apparent survival rates and recapture probabilities. We captured, marked, and...
Crawford, John T; Loken, Luke C; Casson, Nora J; Smith, Colin; Stone, Amanda G; Winslow, Luke A
2015-01-06
Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h(-1)) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial-aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.
Crawford, John T.; Loken, Luke C.; Casson, Nora J.; Smith, Collin; Stone, Amanda G.; Winslow, Luke A.
2015-01-01
Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h–1) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial–aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.
The underlying processes of a soil mite metacommunity on a small scale.
Dong, Chengxu; Gao, Meixiang; Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin
2017-01-01
Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran's eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale.
The underlying processes of a soil mite metacommunity on a small scale
Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin
2017-01-01
Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran’s eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale. PMID:28481906
Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R
2015-04-01
Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for epidemiological surveillance.
NASA Astrophysics Data System (ADS)
Garousi Nejad, I.; He, S.; Tang, Q.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Tarboton, D. G.; Ohara, N.; Lin, H.
2017-12-01
Spatial scale is one of the main considerations in hydrological modeling of snowmelt in mountainous areas. The size of model elements controls the degree to which variability can be explicitly represented versus what needs to be parameterized using effective properties such as averages or other subgrid variability parameterizations that may degrade the quality of model simulations. For snowmelt modeling terrain parameters such as slope, aspect, vegetation and elevation play an important role in the timing and quantity of snowmelt that serves as an input to hydrologic runoff generation processes. In general, higher resolution enhances the accuracy of the simulation since fine meshes represent and preserve the spatial variability of atmospheric and surface characteristics better than coarse resolution. However, this increases computational cost and there may be a scale beyond which the model response does not improve due to diminishing sensitivity to variability and irreducible uncertainty associated with the spatial interpolation of inputs. This paper examines the influence of spatial resolution on the snowmelt process using simulations of and data from the Animas River watershed, an alpine mountainous area in Colorado, USA, using an unstructured distributed physically based hydrological model developed for a parallel computing environment, ADHydro. Five spatial resolutions (30 m, 100 m, 250 m, 500 m, and 1 km) were used to investigate the variations in hydrologic response. This study demonstrated the importance of choosing the appropriate spatial scale in the implementation of ADHydro to obtain a balance between representing spatial variability and the computational cost. According to the results, variation in the input variables and parameters due to using different spatial resolution resulted in changes in the obtained hydrological variables, especially snowmelt, both at the basin-scale and distributed across the model mesh.
Hiding in Plain Sight: A Case for Cryptic Metapopulations in Brook Trout (Salvelinus fontinalis)
Kazyak, David C.; Hilderbrand, Robert H.; King, Tim L.; Keller, Stephen R.; Chhatre, Vikram E.
2016-01-01
A fundamental issue in the management and conservation of biodiversity is how to define a population. Spatially contiguous fish occupying a stream network have often been considered to represent a single, homogenous population. However, they may also represent multiple discrete populations, a single population with genetic isolation-by-distance, or a metapopulation. We used microsatellite DNA and a large-scale mark-recapture study to assess population structure in a spatially contiguous sample of Brook Trout (Salvelinus fontinalis), a species of conservation concern. We found evidence for limited genetic exchange across small spatial scales and in the absence of barriers to physical movement. Mark-recapture and stationary passive integrated transponder antenna records demonstrated that fish from two tributaries very seldom moved into the opposite tributary, but movements between the tributaries and mainstem were more common. Using Bayesian genetic clustering, we identified two genetic groups that exhibited significantly different growth rates over three years of study, yet survival rates were very similar. Our study highlights the importance of considering the possibility of multiple genetically distinct populations occurring within spatially contiguous habitats, and suggests the existence of a cryptic metapopulation: a spatially continuous distribution of organisms exhibiting metapopulation-like behaviors. PMID:26730588
Hiding in Plain Sight: A Case for Cryptic Metapopulations in Brook Trout (Salvelinus fontinalis).
Kazyak, David C; Hilderbrand, Robert H; King, Tim L; Keller, Stephen R; Chhatre, Vikram E
2016-01-01
A fundamental issue in the management and conservation of biodiversity is how to define a population. Spatially contiguous fish occupying a stream network have often been considered to represent a single, homogenous population. However, they may also represent multiple discrete populations, a single population with genetic isolation-by-distance, or a metapopulation. We used microsatellite DNA and a large-scale mark-recapture study to assess population structure in a spatially contiguous sample of Brook Trout (Salvelinus fontinalis), a species of conservation concern. We found evidence for limited genetic exchange across small spatial scales and in the absence of barriers to physical movement. Mark-recapture and stationary passive integrated transponder antenna records demonstrated that fish from two tributaries very seldom moved into the opposite tributary, but movements between the tributaries and mainstem were more common. Using Bayesian genetic clustering, we identified two genetic groups that exhibited significantly different growth rates over three years of study, yet survival rates were very similar. Our study highlights the importance of considering the possibility of multiple genetically distinct populations occurring within spatially contiguous habitats, and suggests the existence of a cryptic metapopulation: a spatially continuous distribution of organisms exhibiting metapopulation-like behaviors.
Multi-Scale Approach for Predicting Fish Species Distributions across Coral Reef Seascapes
Pittman, Simon J.; Brown, Kerry A.
2011-01-01
Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5–300 m radii) surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT) and Maximum Entropy Species Distribution Modelling (MaxEnt). The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided ‘outstanding’ model predictions (AUC = >0.9) for three of five fish species. MaxEnt provided ‘outstanding’ model predictions for two of five species, with the remaining three models considered ‘excellent’ (AUC = 0.8–0.9). In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy) than BRT (68% map accuracy). We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support conservation prioritization in marine protected area design, zoning in marine spatial planning, and ecosystem-based fisheries management. PMID:21637787
Multi-scale approach for predicting fish species distributions across coral reef seascapes.
Pittman, Simon J; Brown, Kerry A
2011-01-01
Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5-300 m radii) surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT) and Maximum Entropy Species Distribution Modelling (MaxEnt). The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided 'outstanding' model predictions (AUC = >0.9) for three of five fish species. MaxEnt provided 'outstanding' model predictions for two of five species, with the remaining three models considered 'excellent' (AUC = 0.8-0.9). In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy) than BRT (68% map accuracy). We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support conservation prioritization in marine protected area design, zoning in marine spatial planning, and ecosystem-based fisheries management.
Benson, Thomas J; Ward, Michael P; Lampman, Richard L; Raim, Arlo; Weatherhead, Patrick J
2012-10-01
The arrival of West Nile virus (WNV) in North America has led to interest in the interaction between birds, the amplification hosts of WNV, and Culex mosquitoes, the primary WNV vectors. American robins (Turdus migratorius) are particularly important amplification hosts of WNV, and because the vector Culex mosquitoes are primarily nocturnal and feed on roosting birds, robin communal roosting behavior may play an important role in the transmission ecology of WNV. Using data from 43 radio-tracked individuals, we determined spatial and temporal patterns of robin roosting behavior, and how these patterns related to the distribution of WNV-infected mosquitoes. Use of the communal roost and fidelity to foraging areas was highly variable both within and among individual robins, and differed markedly from patterns documented in a previous study of robin roosting. Although there were clear seasonal patterns to both robin roosting and WNV occurrence, there was no significant relationship between communal roosting by robins and temporal or spatial patterns of WNV-positive mosquitoes. Our results suggest that, although robins may be important as WNV hosts, communal roosts are not necessarily important for WNV amplification. Other factors, including the availability and distribution of high-quality mosquito habitat and favorable weather for mosquito reproduction, may influence the importance of robin roosts for local WNV amplification and transmission.
Localized Hotspots Drive Continental Geography of Abnormal Amphibians on U.S. Wildlife Refuges
Reeves, Mari K.; Medley, Kimberly A.; Pinkney, Alfred E.; Holyoak, Marcel; Johnson, Pieter T. J.; Lannoo, Michael J.
2013-01-01
Amphibians with missing, misshapen, and extra limbs have garnered public and scientific attention for two decades, yet the extent of the phenomenon remains poorly understood. Despite progress in identifying the causes of abnormalities in some regions, a lack of knowledge about their broader spatial distribution and temporal dynamics has hindered efforts to understand their implications for amphibian population declines and environmental quality. To address this data gap, we conducted a nationwide, 10-year assessment of 62,947 amphibians on U.S. National Wildlife Refuges. Analysis of a core dataset of 48,081 individuals revealed that consistent with expected background frequencies, an average of 2% were abnormal, but abnormalities exhibited marked spatial variation with a maximum prevalence of 40%. Variance partitioning analysis demonstrated that factors associated with space (rather than species or year sampled) captured 97% of the variation in abnormalities, and the amount of partitioned variance decreased with increasing spatial scale (from site to refuge to region). Consistent with this, abnormalities occurred in local to regional hotspots, clustering at scales of tens to hundreds of kilometers. We detected such hotspot clusters of high-abnormality sites in the Mississippi River Valley, California, and Alaska. Abnormality frequency was more variable within than outside of hotspot clusters. This is consistent with dynamic phenomena such as disturbance or natural enemies (pathogens or predators), whereas similarity of abnormality frequencies at scales of tens to hundreds of kilometers suggests involvement of factors that are spatially consistent at a regional scale. Our characterization of the spatial and temporal variation inherent in continent-wide amphibian abnormalities demonstrates the disproportionate contribution of local factors in predicting hotspots, and the episodic nature of their occurrence. PMID:24260103
Spatial Variability of Dissolved Organic Carbon in Headwater Wetlands in Central Pennsylvania
NASA Astrophysics Data System (ADS)
Reichert-Eberhardt, A. J.; Wardrop, D.; Boyer, E. W.
2011-12-01
Dissolved organic carbon (DOC) is known to be of an important factor in many microbially mediated biochemical processes, such as denitrification, that occur in wetlands. The spatial variability of DOC within a wetland could impact the microbes that fuel these processes, which in turn can affect the ecosystem services provided by wetlands. However, the amount of spatial variability of DOC in wetlands is generally unknown. Furthermore, it is unknown how disturbance to wetlands can affect spatial variability of DOC. Previous research in central Pennsylvania headwater wetland soils has shown that wetlands with increased human disturbance had decreased heterogeneity in soil biochemistry. To address groundwater chemical variability 20 monitoring wells were installed in a random pattern in a 400 meter squared plot in a low-disturbance headwater wetland and a high-disturbance headwater wetland in central Pennsylvania. Water samples from these wells will be analyzed for DOC, dissolved inorganic carbon, nitrate, ammonia, and sulfate concentrations, as well as pH, conductivity, and temperature on a seasonal basis. It is hypothesized that there will be greater spatial variability of groundwater chemistry in the low disturbance wetland than the high disturbance wetland. This poster will present the initial data concerning DOC spatial variability in both the low and high impact headwater wetlands.
NASA Technical Reports Server (NTRS)
Brunet, Y.; Vauclin, M.
1985-01-01
The correct interpretation of thermal and hydraulic soil parameters infrared from remotely sensed data (thermal infrared, microwaves) implies a good understanding of the causes of their temporal and spatial variability. Given this necessity, the sensitivity of the surface variables (temperature, moisture) to the spatial variability of hydraulic soil properties is tested with a numerical model of heat and mass transfer between bare soil and atmosphere. The spatial variability of hydraulic soil properties is taken into account in terms of the scaling factor. For a given soil, the knowledge of its frequency distribution allows a stochastic use of the model. The results are treated statistically, and the part of the variability of soil surface parameters due to that of soil hydraulic properties is evaluated quantitatively.
Lisa M. Ellsworth; Creighton M. Litton; Andrew D. Taylor; J. Boone Kauffman
2013-01-01
Frequent wildfires in tropical landscapes dominated by non-native invasive grasses threaten surrounding ecosystems and developed areas. To better manage fire, accurate estimates of the spatial and temporal variability in fuels are urgently needed. We quantified the spatial variability in live and dead fine fuel loads and moistures at four guinea grass (...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Halvorson, J.J.; Smith, J.L.; Bolton, H. Jr.
1995-09-01
Geostatistics are often calculated for a single variable at a time, even though many natural phenomena are functions of several variables. The objective of this work was to demonstrate a nonparametric approach for assessing the spatial characteristics of multiple-variable phenomena. Specifically, we analyzed the spatial characteristics of resource islands in the soil under big sagebrush (Artemisia tridentala Nutt.), a dominant shrub in the intermountain western USA. For our example, we defined resource islands as a function of six soil variables representing concentrations of soil resources, populations of microorganisms, and soil microbial physiological variables. By collectively evaluating the indicator transformations ofmore » these individual variables, we created a new data set, termed a multiple-variable indicator transform or MVIT. Alternate MVITs were obtained by varying the selection criteria. Each MVIT was analyzed with variography to characterize spatial continuity, and with indicator kriging to predict the combined probability of their occurrence at unsampled locations in the landscape. Simple graphical analysis and variography demonstrated spatial dependence for all individual soil variables. Maps derived from ordinary kriging of MVITs suggested that the combined probabilities for encountering zones of above-median resources were greatest near big sagebrush. 51 refs., 5 figs., 1 tab.« less
Floodplain complexity and surface metrics: influences of scale and geomorphology
Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.
2015-01-01
Many studies of fluvial geomorphology and landscape ecology examine a single river or landscape, thus lack generality, making it difficult to develop a general understanding of the linkages between landscape patterns and larger-scale driving variables. We examined the spatial complexity of eight floodplain surfaces in widely different geographic settings and determined how patterns measured at different scales relate to different environmental drivers. Floodplain surface complexity is defined as having highly variable surface conditions that are also highly organised in space. These two components of floodplain surface complexity were measured across multiple sampling scales from LiDAR-derived DEMs. The surface character and variability of each floodplain were measured using four surface metrics; namely, standard deviation, skewness, coefficient of variation, and standard deviation of curvature from a series of moving window analyses ranging from 50 to 1000 m in radius. The spatial organisation of each floodplain surface was measured using spatial correlograms of the four surface metrics. Surface character, variability, and spatial organisation differed among the eight floodplains; and random, fragmented, highly patchy, and simple gradient spatial patterns were exhibited, depending upon the metric and window size. Differences in surface character and variability among the floodplains became statistically stronger with increasing sampling scale (window size), as did their associations with environmental variables. Sediment yield was consistently associated with differences in surface character and variability, as were flow discharge and variability at smaller sampling scales. Floodplain width was associated with differences in the spatial organization of surface conditions at smaller sampling scales, while valley slope was weakly associated with differences in spatial organisation at larger scales. A comparison of floodplain landscape patterns measured at different scales would improve our understanding of the role that different environmental variables play at different scales and in different geomorphic settings.
Nijhof, Carl O P; Huijbregts, Mark A J; Golsteijn, Laura; van Zelm, Rosalie
2016-04-01
We compared the influence of spatial variability in environmental characteristics and the uncertainty in measured substance properties of seven chemicals on freshwater fate factors (FFs), representing the residence time in the freshwater environment, and on exposure factors (XFs), representing the dissolved fraction of a chemical. The influence of spatial variability was quantified using the SimpleBox model in which Europe was divided in 100 × 100 km regions, nested in a regional (300 × 300 km) and supra-regional (500 × 500 km) scale. Uncertainty in substance properties was quantified by means of probabilistic modelling. Spatial variability and parameter uncertainty were expressed by the ratio k of the 95%ile and 5%ile of the FF and XF. Our analysis shows that spatial variability ranges in FFs of persistent chemicals that partition predominantly into one environmental compartment was up to 2 orders of magnitude larger compared to uncertainty. For the other (less persistent) chemicals, uncertainty in the FF was up to 1 order of magnitude larger than spatial variability. Variability and uncertainty in freshwater XFs of the seven chemicals was negligible (k < 1.5). We found that, depending on the chemical and emission scenario, accounting for region-specific environmental characteristics in multimedia fate modelling, as well as accounting for parameter uncertainty, can have a significant influence on freshwater fate factor predictions. Therefore, we conclude that it is important that fate factors should not only account for parameter uncertainty, but for spatial variability as well, as this further increases the reliability of ecotoxicological impacts in LCA. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Pricope, Narcisa Gabriela
This dissertation addresses changes in land and resource availability occurring as a result of climate, water variability and changes in fire regimes in a semi-arid savanna region in Southern Africa. The research combines geospatial analyses of climatological and hydrologic data and various remotely-sensed datasets to create measures of ecosystem variability and adaptability to natural and anthropogenic changes in sensitive ecosystems. The study area is the Chobe River Basin (CRB), a watershed shared between Botswana and Namibia situated at the heart of one of the world.s largest transfrontier conservation areas, where different land-use management strategies and economic policies affect both the ecosystem and the livelihoods support system differentially. The southern African savanna is a highly variable environment and people have adapted to its harshness through the generations. However, in light of past and ongoing environmental changes, their ability to adapt may become threatened. By mapping and then analyzing the spatial and temporal variability of two important factors, namely flooding and fires, in conjunction with indices of vegetation health and productivity, the findings of this research can ultimately contribute to enhancing our understanding of local adaptation mechanisms to future environmental change. This is the first reconstruction of the spatial and temporal patterns of inundation for the last 25 years in the CRB, a transboundary basin with an unusual hydrologic regime and an important water resource for both human and wildlife populations. In the context of increasing temperatures, decreasing precipitation trends and increasing frequencies and intensities of El Nino episodes in southern Africa (Boko et al., 2007), I also investigated changes in fire incidences and marked shifts in fire seasonality both within and outside of protected areas of central Kavango Zambezi Transfrontier Conservation Area (KAZA TFCA). These changes are likely to have a series of strong impacts on other components of fire regimes in semi-arid ecosystems that will, in turn, affect their ecology, structure, and function. This dissertation contributes to the field of land use and land change science by proposing a novel spatial coincidence analysis framework for analyzing how the interand intra-annual extents of inundation and fire are correlated with both annual patterns of vegetation productivity and multi-date changes in vegetation productivity. (Full text of this dissertation may be available via the University of Florida Libraries web site. Please check http://www.uflib.ufl.edu/etd.html)
Approach to spatial information security based on digital certificate
NASA Astrophysics Data System (ADS)
Cong, Shengri; Zhang, Kai; Chen, Baowen
2005-11-01
With the development of the online applications of geographic information systems (GIS) and the spatial information services, the spatial information security becomes more important. This work introduced digital certificates and authorization schemes into GIS to protect the crucial spatial information combining the techniques of the role-based access control (RBAC), the public key infrastructure (PKI) and the privilege management infrastructure (PMI). We investigated the spatial information granularity suited for sensitivity marking and digital certificate model that fits the need of GIS security based on the semantics analysis of spatial information. It implements a secure, flexible, fine-grained data access based on public technologies in GIS in the world.
Wu, Naicheng; Qu, Yueming; Guse, Björn; Makarevičiūtė, Kristė; To, Szewing; Riis, Tenna; Fohrer, Nicola
2018-03-01
There has been increasing interest in algae-based bioassessment, particularly, trait-based approaches are increasingly suggested. However, the main drivers, especially the contribution of hydrological variables, of species composition, trait composition, and beta diversity of algae communities are less studied. To link species and trait composition to multiple factors (i.e., hydrological variables, local environmental variables, and spatial factors) that potentially control species occurrence/abundance and to determine their relative roles in shaping species composition, trait composition, and beta diversities of pelagic algae communities, samples were collected from a German lowland catchment, where a well-proven ecohydrological modeling enabled to predict long-term discharges at each sampling site. Both trait and species composition showed significant correlations with hydrological, environmental, and spatial variables, and variation partitioning revealed that the hydrological and local environmental variables outperformed spatial variables. A higher variation of trait composition (57.0%) than species composition (37.5%) could be explained by abiotic factors. Mantel tests showed that both species and trait-based beta diversities were mostly related to hydrological and environmental heterogeneity with hydrological contributing more than environmental variables, while purely spatial impact was less important. Our findings revealed the relative importance of hydrological variables in shaping pelagic algae community and their spatial patterns of beta diversities, emphasizing the need to include hydrological variables in long-term biomonitoring campaigns and biodiversity conservation or restoration. A key implication for biodiversity conservation was that maintaining the instream flow regime and keeping various habitats among rivers are of vital importance. However, further investigations at multispatial and temporal scales are greatly needed.
NASA Astrophysics Data System (ADS)
Cabral, Mariza Castanheira De Moura Da Costa
In the fifty-two years since Robert Horton's 1945 pioneering quantitative description of channel network planform (or plan view morphology), no conclusive findings have been presented that permit inference of geomorphological processes from any measures of network planform. All measures of network planform studied exhibit limited geographic variability across different environments. Horton (1945), Langbein et al. (1947), Schumm (1956), Hack (1957), Melton (1958), and Gray (1961) established various "laws" of network planform, that is, statistical relationships between different variables which have limited variability. A wide variety of models which have been proposed to simulate the growth of channel networks in time over a landsurface are generally also in agreement with the above planform laws. An explanation is proposed for the generality of the channel network planform laws. Channel networks must be space filling, that is, they must extend over the landscape to drain every hillslope, leaving no large undrained areas, and with no crossing of channels, often achieving a roughly uniform drainage density in a given environment. It is shown that the space-filling constraint can reduce the sensitivity of planform variables to different network growth models, and it is proposed that this constraint may determine the planform laws. The "Q model" of network growth of Van Pelt and Verwer (1985) is used to generate samples of networks. Sensitivity to the model parameter Q is markedly reduced when the networks generated are required to be space filling. For a wide variety of Q values, the space-filling networks are in approximate agreement with the various channel network planform laws. Additional constraints, including of energy efficiency, were not studied but may further reduce the variability of planform laws. Inference of model parameter Q from network topology is successful only in networks not subject to spatial constraints. In space-filling networks, for a wide range of Q values, the maximal-likelihood Q parameter value is generally in the vicinity of 1/2, which yields topological randomness. It is proposed that space filling originates the appearance of randomness in channel network topology, and may cause difficulties to geomorphological inference from network planform.
Gutzwiller, Kevin J.; Barrow, Wylie C.; White, Joseph D.; Johnson-Randall, Lori; Cade, Brian S.; Zygo, Lisa M.
2010-01-01
1. Organism–environment models are used widely in conservation. The degree to which they are useful for informing conservation decisions – the conservation relevance of these relations – is important because lack of relevance may lead to misapplication of scarce conservation resources or failure to resolve important conservation dilemmas. Even when models perform well based on model fit and predictive ability, conservation relevance of associations may not be clear without also knowing the magnitude and variability of predicted changes in response variables. 2. We introduce a method for evaluating the conservation relevance of organism–environment relations that employs confidence intervals for predicted changes in response variables. The confidence intervals are compared to a preselected magnitude of change that marks a threshold (trigger) for conservation action. To demonstrate the approach, we used a case study from the Chihuahuan Desert involving relations between avian richness and broad-scale patterns of shrubland. We considered relations for three winters and two spatial extents (1- and 2-km-radius areas) and compared predicted changes in richness to three thresholds (10%, 20% and 30% change). For each threshold, we examined 48 relations. 3. The method identified seven, four and zero conservation-relevant changes in mean richness for the 10%, 20% and 30% thresholds respectively. These changes were associated with major (20%) changes in shrubland cover, mean patch size, the coefficient of variation for patch size, or edge density but not with major changes in shrubland patch density. The relative rarity of conservation-relevant changes indicated that, overall, the relations had little practical value for informing conservation decisions about avian richness. 4. The approach we illustrate is appropriate for various response and predictor variables measured at any temporal or spatial scale. The method is broadly applicable across ecological environments, conservation objectives, types of statistical predictive models and levels of biological organization. By focusing on magnitudes of change that have practical significance, and by using the span of confidence intervals to incorporate uncertainty of predicted changes, the method can be used to help improve the effectiveness of conservation efforts.
[Cognitive disorders in patients with chronic mercury intoxication].
Katamanova, E V; Shevchenko, O I; Lakhman, O L; Denisova, I A
2014-01-01
To assess severity of cognitive disorders in chronic mercury intoxication, the authors performed claster and discrimination analysis of neuropsychologic and neurophysiologic research data from workers exposed to mercury during long length of service, from patients with early and marked stages of chronic mercurial intoxication. Cognitive disorders in chronic mercurial intoxication have three severity degrees, in the light degree disorders patients demonstrate lower amplitude of cognitive evoked potentials, poor long-term memory and associative thinking. Moderate cognitive disorders are characterized by decreased visual, long-term memory, concentration of attention, poor optic and spatial gnosis. Marked cognitive disorders with chronic mercurial intoxication present with more decreased long-term, short-term, picturesque memory, poor intellect, optic and spatial gnosis and associative thinking.
Effects of Verb Familiarity on Finiteness Marking in Children With Specific Language Impairment
Rice, Mabel L.; Bontempo, Daniel E.
2015-01-01
Purpose Children with specific language impairment (SLI) have known deficits in the verb lexicon and finiteness marking. This study investigated a potential relationship between these 2 variables in children with SLI and 2 control groups considering predictions from 2 different theoretical perspectives, morphosyntactic versus morphophonological. Method Children with SLI, age-equivalent, and language-equivalent (LE) control children (n = 59) completed an experimental sentence imitation task that generated estimates of children's finiteness accuracy under 2 levels of verb familiarity—familiar real verbs versus unfamiliar real verbs—in clausal sites marked for finiteness. Imitations were coded and analyzed for overall accuracy as well as finiteness marking and verb root imitation accuracy. Results Statistical comparisons revealed that children with SLI did not differ from LE children and were less accurate than age-equivalent children on all dependent variables: overall imitation, finiteness marking imitation, and verb root imitation accuracy. A significant Group × Condition interaction for finiteness marking revealed lower levels of accuracy on unfamiliar verbs for the SLI and LE groups only. Conclusions Findings indicate a relationship between verb familiarity and finiteness marking in children with SLI and younger controls and help clarify the roles of morphosyntax, verb lexicon, and morphophonology. PMID:25611349
Multifractal analyis of soil invertebrates along a transect under different land uses
NASA Astrophysics Data System (ADS)
Machado Siqueira, Glécio; Alves Silva, Raimunda; Vidal-Vázquez, Eva; Paz-González, Antonio
2017-04-01
Soil fauna play a central role in many essential ecosystem processes. Land use and management can have a dramatic effect upon soil invertebrate community. Indices based on soil invertebrates abundance and diversity are fundamental for soil quality assessment. Many soil properties and attributes have been shown to exhibit spatial variabilityThe aim of this study was to analyze the scaling heterogeneity of the soil invertebrate community sampled using pitfall traps across a transect. The field study was conducted at Mata Roma municipality, Maranhão State, Brazil. Transects were marked under seven different agricultural/forestry land uses (millet, soybean, maize, eucalyptus, pasture, secondary savannah and native savannah). Native vegetation was considered as a reference, whereas the agricultural fields showed a range of soil use intensities. Along these transects 130 pitfall per land use were installed. First, differences in community assemblages and composition under different land use systems were evaluated using classical indices. Then, the spatial distribution of soil fauna trapped by pitfall techniques, characterized through generalized dimension, Dq, and singularity spectra, f(α) - α, showed a well-defined multifractal structure. Differences in scaling heterogeneity and other multifractal characteristics were examined in relation to land use intensification.
Application of satellite products and hydrological modelling for flood early warning
NASA Astrophysics Data System (ADS)
Koriche, Sifan A.; Rientjes, Tom H. M.
2016-06-01
Floods have caused devastating impacts to the environment and society in Awash River Basin, Ethiopia. Since flooding events are frequent, this marks the need to develop tools for flood early warning. In this study, we propose a satellite based flood index to identify the runoff source areas that largely contribute to extreme runoff production and floods in the basin. Satellite based products used for development of the flood index are CMORPH (Climate Prediction Center MORPHing technique: 0.25° by 0.25°, daily) product for calculation of the Standard Precipitation Index (SPI) and a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) for calculation of the Topographic Wetness Index (TWI). Other satellite products used in this study are for rainfall-runoff modelling to represent rainfall, potential evapotranspiration, vegetation cover and topography. Results of the study show that assessment of spatial and temporal rainfall variability by satellite products may well serve in flood early warning. Preliminary findings on effectiveness of the flood index developed in this study indicate that the index is well suited for flood early warning. The index combines SPI and TWI, and preliminary results illustrate the spatial distribution of likely runoff source areas that cause floods in flood prone areas.
Can APEX Represent In-Field Spatial Variability and Simulate Its Effects On Crop Yields?
USDA-ARS?s Scientific Manuscript database
Precision agriculture, from variable rate nitrogen application to precision irrigation, promises improved management of resources by considering the spatial variability of topography and soil properties. Hydrologic models need to simulate the effects of this variability if they are to inform about t...
Drive by Soil Moisture Measurement: A Citizen Science Project
NASA Astrophysics Data System (ADS)
Senanayake, I. P.; Willgoose, G. R.; Yeo, I. Y.; Hancock, G. R.
2017-12-01
Two of the common attributes of soil moisture are that at any given time it varies quite markedly from point to point, and that there is a significant deterministic pattern that underlies this spatial variation and which is typically 50% of the spatial variability. The spatial variation makes it difficult to determine the time varying catchment average soil moisture using field measurements because any individual measurement is unlikely to be equal to the average for the catchment. The traditional solution to this is to make many measurements (e.g. with soil moisture probes) spread over the catchment, which is very costly and manpower intensive, particularly if we need a time series of soil moisture variation across a catchment. An alternative approach, explored in this poster is to use the deterministic spatial pattern of soil moisture to calibrate one site (e.g. a permanent soil moisture probe at a weather station) to the spatial pattern of soil moisture over the study area. The challenge is then to determine the spatial pattern of soil moisture. This poster will present results from a proof of concept project, where data was collected by a number of undergraduate engineering students, to estimate the spatial pattern. The approach was to drive along a series of roads in a catchment and collect soil moisture measurements at the roadside using field portable soil moisture probes. This drive was repeated a number of times over the semester, and the time variation and spatial persistence of the soil moisture pattern were examined. Provided that the students could return to exactly the same location on each collection day there was a strong persistent pattern in the soil moisture, even while the average soil moisture varied temporally as a result of preceding rainfall. The poster will present results and analysis of the student data, and compare these results with several field sites where we have spatially distributed permanently installed soil moisture probes. The poster will also outline an experimental design, based on our experience, that will underpin a proposed citizen science project involving community environment and farming groups, and high school students.
2017-01-01
The magnitude of diffusive carbon dioxide (CO2) and methane (CH4) emission from man-made reservoirs is uncertain because the spatial variability generally is not well-represented. Here, we examine the spatial variability and its drivers for partial pressure, gas-exchange velocity (k), and diffusive flux of CO2 and CH4 in three tropical reservoirs using spatially resolved measurements of both gas concentrations and k. We observed high spatial variability in CO2 and CH4 concentrations and flux within all three reservoirs, with river inflow areas generally displaying elevated CH4 concentrations. Conversely, areas close to the dam are generally characterized by low concentrations and are therefore not likely to be representative for the whole system. A large share (44–83%) of the within-reservoir variability of gas concentration was explained by dissolved oxygen, pH, chlorophyll, water depth, and within-reservoir location. High spatial variability in k was observed, and kCH4 was persistently higher (on average, 2.5 times more) than kCO2. Not accounting for the within-reservoir variability in concentrations and k may lead to up to 80% underestimation of whole-system diffusive emission of CO2 and CH4. Our findings provide valuable information on how to develop field-sampling strategies to reliably capture the spatial heterogeneity of diffusive carbon fluxes from reservoirs. PMID:29257874
Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl
2016-01-01
The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.
Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl
2016-01-01
The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858
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.
Three dimensional simulation of spatial and temporal variability of stratospheric hydrogen chloride
NASA Technical Reports Server (NTRS)
Kaye, Jack A.; Rood, Richard B.; Jackman, Charles H.; Allen, Dale J.; Larson, Edmund M.
1989-01-01
Spatial and temporal variability of atmospheric HCl columns are calculated for January 1979 using a three-dimensional chemistry-transport model designed to provide the best possible representation of stratospheric transport. Large spatial and temporal variability of the HCl columns is shown to be correlated with lower stratospheric potential vorticity and thus to be of dynamical origin. Systematic longitudinal structure is correlated with planetary wave structure. These results can help place spatially and temporally isolated column and profile measurements in a regional and/or global perspective.
Glynn, P.D.
2003-01-01
One-dimensional (1D) geochemical transport modeling is used to demonstrate the effects of speciation and sorption reactions on the ground-water transport of Np and Pu, two redox-sensitive elements. Earlier 1D simulations (Reardon, 1981) considered the kinetically limited dissolution of calcite and its effect on ion-exchange reactions (involving 90Sr, Ca, Na, Mg and K), and documented the spatial variation of a 90Sr partition coefficient under both transient and steady-state chemical conditions. In contrast, the simulations presented here assume local equilibrium for all reactions, and consider sorption on constant potential, rather than constant charge, surfaces. Reardon's (1981) seminal findings on the spatial and temporal variability of partitioning (of 90Sr) are reexamined and found partially caused by his assumption of a kinetically limited reaction. In the present work, sorption is assumed the predominant retardation process controlling Pu and Np transport, and is simulated using a diffuse-double-layer-surface-complexation (DDLSC) model. Transport simulations consider the infiltration of Np- and Pu-contaminated waters into an initially uncontaminated environment, followed by the cleanup of the resultant contamination with uncontaminated water. Simulations are conducted using different spatial distributions of sorption capacities (with the same total potential sorption capacity, but with different variances and spatial correlation structures). Results obtained differ markedly from those that would be obtained in transport simulations using constant Kd, Langmuir or Freundlich sorption models. When possible, simulation results (breakthrough curves) are fitted to a constant K d advection-dispersion transport model and compared. Functional differences often are great enough that they prevent a meaningful fit of the simulation results with a constant K d (or even a Langmuir or Freundlich) model, even in the case of Np, a weakly sorbed radionuclide under the simulation conditions. Functional behaviors that cannot be fit include concentration trend reversals and radionuclide desorption spikes. Other simulation results are fit successfully but the fitted parameters (Kd and dispersivity) vary significantly depending on simulation conditions (e.g. "infiltration" vs. "cleanup" conditions). Notably, an increase in the variance of the specified sorption capacities results in a marked increase in the dispersion of the radionuclides. The results presented have implications for the simulation of radionuclide migration in performance assessments of nuclear waste-disposal sites, for the future monitoring of those sites, and more generally for modeling contaminant transport in ground-water environments. ?? 2003 Published by Elsevier Science Ltd.
Peixoto, Roberta B.; Machado-Silva, Fausto; Marotta, Humberto; Enrich-Prast, Alex; Bastviken, David
2015-01-01
Inland waters (lakes, rivers and reservoirs) are now understood to contribute large amounts of methane (CH4) to the atmosphere. However, fluxes are poorly constrained and there is a need for improved knowledge on spatiotemporal variability and on ways of optimizing sampling efforts to yield representative emission estimates for different types of aquatic ecosystems. Low-latitude floodplain lakes and wetlands are among the most high-emitting environments, and here we provide a detailed investigation of spatial and day-to-day variability in a shallow floodplain lake in the Pantanal in Brazil over a five-day period. CH4 flux was dominated by frequent and ubiquitous ebullition. A strong but predictable spatial variability (decreasing flux with increasing distance to the shore or to littoral vegetation) was found, and this pattern can be addressed by sampling along transects from the shore to the center. Although no distinct day-to-day variability were found, a significant increase in flux was identified from measurement day 1 to measurement day 5, which was likely attributable to a simultaneous increase in temperature. Our study demonstrates that representative emission assessments requires consideration of spatial variability, but also that spatial variability patterns are predictable for lakes of this type and may therefore be addressed through limited sampling efforts if designed properly (e.g., fewer chambers may be used if organized along transects). Such optimized assessments of spatial variability are beneficial by allowing more of the available sampling resources to focus on assessing temporal variability, thereby improving overall flux assessments. PMID:25860229
NASA Astrophysics Data System (ADS)
Veiga, P.; Rubal, M.; Vieira, R.; Arenas, F.; Sousa-Pinto, I.
2013-03-01
Natural assemblages are variable in space and time; therefore, quantification of their variability is imperative to identify relevant scales for investigating natural or anthropogenic processes shaping these assemblages. We studied the variability of intertidal macroalgal assemblages on the North Portuguese coast, considering three spatial scales (from metres to 10 s of kilometres) following a hierarchical design. We tested the hypotheses that (1) spatial pattern will be invariant at all the studied scales and (2) spatial variability of macroalgal assemblages obtained by using species will be consistent with that obtained using functional groups. This was done considering as univariate variables: total biomass and number of taxa as well as biomass of the most important species and functional groups and as multivariate variables the structure of macroalgal assemblages, both considering species and functional groups. Most of the univariate results confirmed the first hypothesis except for the total number of taxa and foliose macroalgae that showed significant variability at the scale of site and area, respectively. In contrast, when multivariate patterns were examined, the first hypothesis was rejected except at the scale of 10 s of kilometres. Both uni- and multivariate results indicated that variation was larger at the smallest scale, and thus, small-scale processes seem to have more effect on spatial variability patterns. Macroalgal assemblages, both considering species and functional groups as surrogate, showed consistent spatial patterns, and therefore, the second hypothesis was confirmed. Consequently, functional groups may be considered a reliable biological surrogate to study changes on macroalgal assemblages at least along the investigated Portuguese coastline.
NASA Astrophysics Data System (ADS)
Fourment, Mercedes; Ferrer, Milka; González-Neves, Gustavo; Barbeau, Gérard; Bonnardot, Valérie; Quénol, Hervé
2017-09-01
Spatial variability of temperature was studied in relation to the berry basic composition and secondary compounds of the Tannat cultivar at harvest from vineyards located in Canelones and Montevideo, the most important wine region of Uruguay. Monitoring of berries and recording of temperature were performed in 10 commercial vineyards of Tannat situated in the southern coastal wine region of the country for three vintages (2012, 2013, and 2014). Results from a multivariate correlation analysis between berry composition and temperature over the three vintages showed that (1) Tannat responses to spatial variability of temperature were different over the vintages, (2) correlations between secondary metabolites and temperature were higher than those between primary metabolites, and (3) correlation values between berry composition and climate variables increased when ripening occurred under dry conditions (below average rainfall). For a particular studied vintage (2013), temperatures explained 82.5% of the spatial variability of the berry composition. Daily thermal amplitude was found to be the most important spatial mode of variability with lower values recorded at plots nearest to the sea and more exposed to La Plata River. The highest levels in secondary compounds were found in berries issued from plots situated as far as 18.3 km from La Plata River. The increasing knowledge of temperature spatial variability and its impact on grape berry composition contributes to providing possible issues to adapt grapevine to climate change.
Parsons, Jessica E; Cain, Charles A; Fowlkes, J Brian
2007-03-01
Spatial variability in acoustic backscatter is investigated as a potential feedback metric for assessment of lesion morphology during cavitation-mediated mechanical tissue disruption ("histotripsy"). A 750-kHz annular array was aligned confocally with a 4.5 MHz passive backscatter receiver during ex vivo insonation of porcine myocardium. Various exposure conditions were used to elicit a range of damage morphologies and backscatter characteristics [pulse duration = 14 micros, pulse repetition frequency (PRF) = 0.07-3.1 kHz, average I(SPPA) = 22-44 kW/cm2]. Variability in backscatter spatial localization was quantified by tracking the lag required to achieve peak correlation between sequential RF A-lines received. Mean spatial variability was observed to be significantly higher when damage morphology consisted of mechanically disrupted tissue homogenate versus mechanically intact coagulation necrosis (2.35 +/- 1.59 mm versus 0.067 +/- 0.054 mm, p < 0.025). Statistics from these variability distributions were used as the basis for selecting a threshold variability level to identify the onset of homogenate formation via an abrupt, sustained increase in spatially dynamic backscatter activity. Specific indices indicative of the state of the homogenization process were quantified as a function of acoustic input conditions. The prevalence of backscatter spatial variability was observed to scale with the amount of homogenate produced for various PRFs and acoustic intensities.
Predictor variable resolution governs modeled soil types
USDA-ARS?s Scientific Manuscript database
Soil mapping identifies different soil types by compressing a unique suite of spatial patterns and processes across multiple spatial scales. It can be quite difficult to quantify spatial patterns of soil properties with remotely sensed predictor variables. More specifically, matching the right scale...
NASA Astrophysics Data System (ADS)
Wang, Jun; Wang, Yang; Zeng, Hui
2016-01-01
A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.
Emma Vakili; Chad M. Hoffman; Robert E. Keane; Wade T. Tinkham; Yvette Dickinson
2016-01-01
There is growing consensus that spatial variability in fuel loading at scales down to 0.5 m may govern fire behaviour and effects. However, there remains a lack of understanding of how fuels vary through space in wildland settings. This study quantifies surface fuel loading and its spatial variability in ponderosa pine sites before and after fuels treatment in the...
Lejiang Yu; Shiyuan Zhong; Xindi Bian; Warren E. Heilman
2015-01-01
This study examines the spatial and temporal variability of wind speed at 80m above ground (the average hub height of most modern wind turbines) in the contiguous United States using Climate Forecast System Reanalysis (CFSR) data from 1979 to 2011. The mean 80-m wind exhibits strong seasonality and large spatial variability, with higher (lower) wind speeds in the...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mutaf, Yildirim D.; Yi, Byong Yong; Prado, Karl
Purpose: A dedicated stereotactic gamma irradiation device, the GammaPod Trade-Mark-Sign from Xcision Medical Systems, was developed specifically to treat small breast cancers. This study presents the first evaluation of dosimetric and geometric characteristics from the initial prototype installed at University of Maryland Radiation Oncology Department. Methods: The GammaPod Trade-Mark-Sign stereotactic radiotherapy device is an assembly of a hemi-spherical source carrier containing 36 {sup 60}Co sources, a tungsten collimator, a dynamically controlled patient support table, and the breast immobilization system which also functions as a stereotactic frame. The source carrier contains the sources in six columns spaced longitudinally at 60 Degree-Signmore » intervals and it rotates together with the variable-size collimator to form 36 noncoplanar, concentric arcs focused at the isocenter. The patient support table enables motion in three dimensions to position the patient tumor at the focal point of the irradiation. The table moves continuously in three cardinal dimensions during treatment to provide dynamic shaping of the dose distribution. The breast is immobilized using a breast cup applying a small negative pressure, where the immobilization cup is embedded with fiducials also functioning as the stereotactic frame for the breast. Geometric and dosimetric evaluations of the system as well as a protocol for absorbed dose calibration are provided. Dosimetric verifications of dynamically delivered patient plans are performed for seven patients using radiochromic films in hypothetical preop, postop, and target-in-target treatment scenarios. Results: Loaded with 36 {sup 60}Co sources with cumulative activity of 4320 Ci, the prototype GammaPod Trade-Mark-Sign unit delivers 5.31 Gy/min at the isocenter using the largest 2.5 cm diameter collimator. Due to the noncoplanar beam arrangement and dynamic dose shaping features, the GammaPod Trade-Mark-Sign device is found to deliver uniform doses to targets with good conformity. The spatial accuracy of the device to locate the radiation isocenter is determined to be less than 1 mm. Single shot profiles with 2.5 cm collimator are measured with radiochromic film and found to be in good agreement with respect to the Monte Carlo based calculations (congruence of FWHM less than 1 mm). Dosimetric verifications corresponding to all hypothetical treatment plans corresponding to three target scenarios for each of the seven patients demonstrated good agreement with gamma index pass rates of better than 97% (99.0%{+-} 0.7%). Conclusions: Dosimetric evaluation of the first GammaPod Trade-Mark-Sign stereotactic breast radiotherapy unit was performed and the dosimetric and spatial accuracy of this novel technology is found to be feasible with respect to clinical radiotherapy standards. The observed level of agreement between the treatment planning system calculations and dosimetric measurements has confirmed that the system can deliver highly complex treatment plans with remarkable geometric and dosimetric accuracy.« less
Hongqing Wanga; Charles A.S. Halla; Frederick N. Scatenab; Ned Fetcherc; Wei Wua
2003-01-01
There are few studies that have examined the spatial variability of forest productivity over an entire tropical forested landscape. In this study, we used a spatially-explicit forest productivity model, TOPOPROD, which is based on the FORESTBGC model, to simulate spatial patterns of gross primary productivity (GPP), net primary productivity (NPP), and respiration over...
J. Rojas-Sandoval; E. J. Melendez-Ackerman; NO-VALUE
2013-01-01
Aims The spatial distribution of biotic and abiotic factors may play a dominant role in determining the distribution and abundance of plants in arid and semiarid environments. In this study, we evaluated how spatial patterns of microhabitat variables and the degree of spatial dependence of these variables influence the distribution and abundance of the endangered...
Acoustooptic Processing of Two Dimensional Signals Using Temporal and Spatial Integration.
1987-05-29
DIMENSIONAL SIGNALS USING N TEMPORAL AND SPATIAL INTEGRATION TM 00 Demetri Psaltis, John Hong, Scott Hudson, Fai ’Mok, MNyark Neifeld, and - Nabeel Riza ELECTE...DIMENSIONAL SIGNALS USING TEMPORAL AND SPATIAL INTEGRATION Demetri Psaltis, John Hong, Scott Hudson, Fai Mok, Mark Neifeld, and Nabeel Riza DTIC ELECTE...Induced Radar Imaging, IEEE Trans. Aero. and Elect. Sys .,AES-16,2,(1980). i31 Prickett,M.J. and Chen,C.C., Principles of Inverse Synthetic Aperture Radar
Strecker, Angela L; Casselman, John M; Fortin, Marie-Josée; Jackson, Donald A; Ridgway, Mark S; Abrams, Peter A; Shuter, Brian J
2011-07-01
Species present in communities are affected by the prevailing environmental conditions, and the traits that these species display may be sensitive indicators of community responses to environmental change. However, interpretation of community responses may be confounded by environmental variation at different spatial scales. Using a hierarchical approach, we assessed the spatial and temporal variation of traits in coastal fish communities in Lake Huron over a 5-year time period (2001-2005) in response to biotic and abiotic environmental factors. The association of environmental and spatial variables with trophic, life-history, and thermal traits at two spatial scales (regional basin-scale, local site-scale) was quantified using multivariate statistics and variation partitioning. We defined these two scales (regional, local) on which to measure variation and then applied this measurement framework identically in all 5 study years. With this framework, we found that there was no change in the spatial scales of fish community traits over the course of the study, although there were small inter-annual shifts in the importance of regional basin- and local site-scale variables in determining community trait composition (e.g., life-history, trophic, and thermal). The overriding effects of regional-scale variables may be related to inter-annual variation in average summer temperature. Additionally, drivers of fish community traits were highly variable among study years, with some years dominated by environmental variation and others dominated by spatially structured variation. The influence of spatial factors on trait composition was dynamic, which suggests that spatial patterns in fish communities over large landscapes are transient. Air temperature and vegetation were significant variables in most years, underscoring the importance of future climate change and shoreline development as drivers of fish community structure. Overall, a trait-based hierarchical framework may be a useful conservation tool, as it highlights the multi-scaled interactive effect of variables over a large landscape.
Zhang, Houxi; Zhuang, Shunyao; Qian, Haiyan; Wang, Feng; Ji, Haibao
2015-01-01
Understanding the spatial variability of soil organic carbon (SOC) must be enhanced to improve sampling design and to develop soil management strategies in terrestrial ecosystems. Moso bamboo (Phyllostachys pubescens Mazel ex Houz.) forests have a high SOC storage potential; however, they also vary significantly spatially. This study investigated the spatial variability of SOC (0-20 cm) in association with other soil properties and with spatial variables in the Moso bamboo forests of Jian’ou City, which is a typical bamboo hometown in China. 209 soil samples were collected from Moso bamboo stands and then analyzed for SOC, bulk density (BD), pH, cation exchange capacity (CEC), and gravel content (GC) based on spatial distribution. The spatial variability of SOC was then examined using geostatistics. A Kriging map was produced through ordinary interpolation and required sample numbers were calculated by classical and Kriging methods. An aggregated boosted tree (ABT) analysis was also conducted. A semivariogram analysis indicated that ln(SOC) was best fitted with an exponential model and that it exhibited moderate spatial dependence, with a nugget/sill ratio of 0.462. SOC was significantly and linearly correlated with BD (r = −0.373**), pH (r = −0.429**), GC (r = −0.163*), CEC (r = 0.263**), and elevation (r = 0.192**). Moreover, the Kriging method requires fewer samples than the classical method given an expected standard error level as per a variance analysis. ABT analysis indicated that the physicochemical variables of soil affected SOC variation more significantly than spatial variables did, thus suggesting that the SOC in Moso bamboo forests can be strongly influenced by management practices. Thus, this study provides valuable information in relation to sampling strategy and insight into the potential of adjustments in agronomic measure, such as in fertilization for Moso bamboo production. PMID:25789615
Resistance evolution to Bt crops: predispersal mating of European corn borers.
Dalecky, Ambroise; Ponsard, Sergine; Bailey, Richard I; Pélissier, Céline; Bourguet, Denis
2006-06-01
Over the past decade, the high-dose refuge (HDR) strategy, aimed at delaying the evolution of pest resistance to Bacillus thuringiensis (Bt) toxins produced by transgenic crops, became mandatory in the United States and is being discussed for Europe. However, precopulatory dispersal and the mating rate between resident and immigrant individuals, two features influencing the efficiency of this strategy, have seldom been quantified in pests targeted by these toxins. We combined mark-recapture and biogeochemical marking over three breeding seasons to quantify these features directly in natural populations of Ostrinia nubilalis, a major lepidopteran corn pest. At the local scale, resident females mated regardless of males having dispersed beforehand or not, as assumed in the HDR strategy. Accordingly, 0-67% of resident females mating before dispersal did so with resident males, this percentage depending on the local proportion of resident males (0% to 67.2%). However, resident males rarely mated with immigrant females (which mostly arrived mated), the fraction of females mating before dispersal was variable and sometimes substantial (4.8% to 56.8%), and there was no evidence for male premating dispersal being higher. Hence, O. nubilalis probably mates at a more restricted spatial scale than previously assumed, a feature that may decrease the efficiency of the HDR strategy under certain circumstances, depending for example on crop rotation practices.
Ndiath, Mansour M; Cisse, Badara; Ndiaye, Jean Louis; Gomis, Jules F; Bathiery, Ousmane; Dia, Anta Tal; Gaye, Oumar; Faye, Babacar
2015-11-18
In Senegal, considerable efforts have been made to reduce malaria morbidity and mortality during the last decade. This resulted in a marked decrease of malaria cases. With the decline of malaria cases, transmission has become sparse in most Senegalese health districts. This study investigated malaria hotspots in Keur Soce sites by using geographically-weighted regression. Because of the occurrence of hotspots, spatial modelling of malaria cases could have a considerable effect in disease surveillance. This study explored and analysed the spatial relationships between malaria occurrence and socio-economic and environmental factors in small communities in Keur Soce, Senegal, using 6 months passive surveillance. Geographically-weighted regression was used to explore the spatial variability of relationships between malaria incidence or persistence and the selected socio-economic, and human predictors. A model comparison of between ordinary least square and geographically-weighted regression was also explored. Vector dataset (spatial) of the study area by village levels and statistical data (non-spatial) on malaria confirmed cases, socio-economic status (bed net use), population data (size of the household) and environmental factors (temperature, rain fall) were used in this exploratory analysis. ArcMap 10.2 and Stata 11 were used to perform malaria hotspots analysis. From Jun to December, a total of 408 confirmed malaria cases were notified. The explanatory variables-household size, housing materials, sleeping rooms, sheep and distance to breeding site returned significant t values of -0.25, 2.3, 4.39, 1.25 and 2.36, respectively. The OLS global model revealed that it explained about 70 % (adjusted R(2) = 0.70) of the variation in malaria occurrence with AIC = 756.23. The geographically-weighted regression of malaria hotspots resulted in coefficient intercept ranging from 1.89 to 6.22 with a median of 3.5. Large positive values are distributed mainly in the southeast of the district where hotspots are more accurate while low values are mainly found in the centre and in the north. Geographically-weighted regression and OLS showed important risks factors of malaria hotspots in Keur Soce. The outputs of such models can be a useful tool to understand occurrence of malaria hotspots in Senegal. An understanding of geographical variation and determination of the core areas of the disease may provide an explanation regarding possible proximal and distal contributors to malaria elimination in Senegal.
ERIC Educational Resources Information Center
Edwards, Richard; Tracy, Fran; Jordan, Katy
2011-01-01
While much attention has been given to the changing spaces of education introduced by new technologies, the impact of spatial theory on the discussion of such education is less well developed. Drawing upon empirical evidence from the Ensemble research project, this article examines spatially some of the possibilities and constraints that arise in…
Relevance of anisotropy and spatial variability of gas diffusivity for soil-gas transport
NASA Astrophysics Data System (ADS)
Schack-Kirchner, Helmer; Kühne, Anke; Lang, Friederike
2017-04-01
Models of soil gas transport generally do not consider neither direction dependence of gas diffusivity, nor its small-scale variability. However, in a recent study, we could provide evidence for anisotropy favouring vertical gas diffusion in natural soils. We hypothesize that gas transport models based on gas diffusion data measured with soil rings are strongly influenced by both, anisotropy and spatial variability and the use of averaged diffusivities could be misleading. To test this we used a 2-dimensional model of soil gas transport to under compacted wheel tracks to model the soil-air oxygen distribution in the soil. The model was parametrized with data obtained from soil-ring measurements with its central tendency and variability. The model includes vertical parameter variability as well as variation perpendicular to the elongated wheel track. Different parametrization types have been tested: [i)]Averaged values for wheel track and undisturbed. em [ii)]Random distribution of soil cells with normally distributed variability within the strata. em [iii)]Random distributed soil cells with uniformly distributed variability within the strata. All three types of small-scale variability has been tested for [j)] isotropic gas diffusivity and em [jj)]reduced horizontal gas diffusivity (constant factor), yielding in total six models. As expected the different parametrizations had an important influence to the aeration state under wheel tracks with the strongest oxygen depletion in case of uniformly distributed variability and anisotropy towards higher vertical diffusivity. The simple simulation approach clearly showed the relevance of anisotropy and spatial variability in case of identical central tendency measures of gas diffusivity. However, until now it did not consider spatial dependency of variability, that could even aggravate effects. To consider anisotropy and spatial variability in gas transport models we recommend a) to measure soil-gas transport parameters spatially explicit including different directions and b) to use random-field stochastic models to assess the possible effects for gas-exchange models.
Regional model simulations of New Zealand climate
NASA Astrophysics Data System (ADS)
Renwick, James A.; Katzfey, Jack J.; Nguyen, Kim C.; McGregor, John L.
1998-03-01
Simulation of New Zealand climate is examined through the use of a regional climate model nested within the output of the Commonwealth Scientific and Industrial Research Organisation nine-level general circulation model (GCM). R21 resolution GCM output is used to drive a regional model run at 125 km grid spacing over the Australasian region. The 125 km run is used in turn to drive a simulation at 50 km resolution over New Zealand. Simulations with a full seasonal cycle are performed for 10 model years. The focus is on the quality of the simulation of present-day climate, but results of a doubled-CO2 run are discussed briefly. Spatial patterns of mean simulated precipitation and surface temperatures improve markedly as horizontal resolution is increased, through the better resolution of the country's orography. However, increased horizontal resolution leads to a positive bias in precipitation. At 50 km resolution, simulated frequency distributions of daily maximum/minimum temperatures are statistically similar to those of observations at many stations, while frequency distributions of daily precipitation appear to be statistically different to those of observations at most stations. Modeled daily precipitation variability at 125 km resolution is considerably less than observed, but is comparable to, or exceeds, observed variability at 50 km resolution. The sensitivity of the simulated climate to changes in the specification of the land surface is discussed briefly. Spatial patterns of the frequency of extreme temperatures and precipitation are generally well modeled. Under a doubling of CO2, the frequency of precipitation extremes changes only slightly at most locations, while air frosts become virtually unknown except at high-elevation sites.
NASA Astrophysics Data System (ADS)
Baniasadi, Neda; Wang, Mengyu; Wang, Hui; Jin, Qingying; Mahd, Mufeed; Elze, Tobias
2017-02-01
Purpose: To evaluate the effects of four anatomical parameters (angle between superior and inferior temporal retinal arteries [inter-artery angle, IAA], optic disc [OD] rotation, retinal curvature, and central retinal vessel trunk entry point location [CRVTL]) on retinal nerve fiber layer thickness (RNFLT) abnormality marks by OCT machines. Methods: Cirrus OCT circumpapillary RNFLT measurements and Humphrey visual fields (HVF 24-2) of 421 patients from a large glaucoma clinic were included. Ellipses were fitted to the OD borders. Ellipse rotation relative to the vertical axis defined OD rotation. CRVTL was manually marked on the horizontal axis of the ellipse on the OCT fundus image. IAA was calculated between manually marked retinal artery locations at the 1.73mm radius around OD. Retinal curvature was determined by the inner limiting membrane on the horizontal B-scan closest to the OD center. For each location on the circumpapillary scanning area, logistic regression was used to determine if each of the four parameters had a significant impact on RNFLT abnormality marks independent of disease severity. The results are presented on spatial maps of the entire scanning area. Results: Variations in IAA significantly influenced abnormality marks on 38.8% of the total scanning area, followed by CRVTL (19.2%) and retinal curvature (18.7%). The effect of OD rotation was negligible (<1%). Conclusions: A natural variation in IAA, retinal curvature, and CRVTL can affect OCT abnormality ratings, which may bias clinical diagnosis. Our spatial maps may help OCT manufacturers to introduce location specific norms to ensure that abnormality marks indicate ocular disease instead of variations in eye anatomy.
Spatial Distribution of Black Bear Incident Reports in Michigan
McFadden-Hiller, Jamie E.; Beyer, Dean E.; Belant, Jerrold L.
2016-01-01
Interactions between humans and carnivores have existed for centuries due to competition for food and space. American black bears are increasing in abundance and populations are expanding geographically in many portions of its range, including areas that are also increasing in human density, often resulting in associated increases in human-bear conflict (hereafter, bear incidents). We used public reports of bear incidents in Michigan, USA, from 2003–2011 to assess the relative contributions of ecological and anthropogenic variables in explaining the spatial distribution of bear incidents and estimated the potential risk of bear incidents. We used weighted Normalized Difference Vegetation Index mean as an index of primary productivity, region (i.e., Upper Peninsula or Lower Peninsula), primary and secondary road densities, and percentage land cover type within 6.5-km2 circular buffers around bear incidents and random points. We developed 22 a priori models and used generalized linear models and Akaike’s Information Criterion (AIC) to rank models. The global model was the best compromise between model complexity and model fit (w = 0.99), with a ΔAIC 8.99 units from the second best performing model. We found that as deciduous forest cover increased, the probability of bear incident occurrence increased. Among the measured anthropogenic variables, cultivated crops and primary roads were the most important in our AIC-best model and were both positively related to the probability of bear incident occurrence. The spatial distribution of relative bear incident risk varied markedly throughout Michigan. Forest cover fragmented with agriculture and other anthropogenic activities presents an environment that likely facilitates bear incidents. Our map can help wildlife managers identify areas of bear incident occurrence, which in turn can be used to help develop strategies aimed at reducing incidents. Researchers and wildlife managers can use similar mapping techniques to assess locations of specific conflict types or to address human impacts on endangered species. PMID:27119344
Spatial Distribution of Black Bear Incident Reports in Michigan.
McFadden-Hiller, Jamie E; Beyer, Dean E; Belant, Jerrold L
2016-01-01
Interactions between humans and carnivores have existed for centuries due to competition for food and space. American black bears are increasing in abundance and populations are expanding geographically in many portions of its range, including areas that are also increasing in human density, often resulting in associated increases in human-bear conflict (hereafter, bear incidents). We used public reports of bear incidents in Michigan, USA, from 2003-2011 to assess the relative contributions of ecological and anthropogenic variables in explaining the spatial distribution of bear incidents and estimated the potential risk of bear incidents. We used weighted Normalized Difference Vegetation Index mean as an index of primary productivity, region (i.e., Upper Peninsula or Lower Peninsula), primary and secondary road densities, and percentage land cover type within 6.5-km2 circular buffers around bear incidents and random points. We developed 22 a priori models and used generalized linear models and Akaike's Information Criterion (AIC) to rank models. The global model was the best compromise between model complexity and model fit (w = 0.99), with a ΔAIC 8.99 units from the second best performing model. We found that as deciduous forest cover increased, the probability of bear incident occurrence increased. Among the measured anthropogenic variables, cultivated crops and primary roads were the most important in our AIC-best model and were both positively related to the probability of bear incident occurrence. The spatial distribution of relative bear incident risk varied markedly throughout Michigan. Forest cover fragmented with agriculture and other anthropogenic activities presents an environment that likely facilitates bear incidents. Our map can help wildlife managers identify areas of bear incident occurrence, which in turn can be used to help develop strategies aimed at reducing incidents. Researchers and wildlife managers can use similar mapping techniques to assess locations of specific conflict types or to address human impacts on endangered species.
Geoelectrical characterisation of basement aquifers: the case of Iberekodo, southwestern Nigeria
NASA Astrophysics Data System (ADS)
Aizebeokhai, Ahzegbobor P.; Oyeyemi, Kehinde D.
2018-03-01
Basement aquifers, which occur within the weathered and fractured zones of crystalline bedrocks, are important groundwater resources in tropical and subtropical regions. The development of basement aquifers is complex owing to their high spatial variability. Geophysical techniques are used to obtain information about the hydrologic characteristics of the weathered and fractured zones of the crystalline basement rocks, which relates to the occurrence of groundwater in the zones. The spatial distributions of these hydrologic characteristics are then used to map the spatial variability of the basement aquifers. Thus, knowledge of the spatial variability of basement aquifers is useful in siting wells and boreholes for optimal and perennial yield. Geoelectrical resistivity is one of the most widely used geophysical methods for assessing the spatial variability of the weathered and fractured zones in groundwater exploration efforts in basement complex terrains. The presented study focuses on combining vertical electrical sounding with two-dimensional (2D) geoelectrical resistivity imaging to characterise the weathered and fractured zones in a crystalline basement complex terrain in southwestern Nigeria. The basement aquifer was delineated, and the nature, extent and spatial variability of the delineated basement aquifer were assessed based on the spatial variability of the weathered and fractured zones. The study shows that a multiple-gradient array for 2D resistivity imaging is sensitive to vertical and near-surface stratigraphic features, which have hydrological implications. The integration of resistivity sounding with 2D geoelectrical resistivity imaging is efficient and enhances near-surface characterisation in basement complex terrain.
Exploring the spatial variability of soil properties in an Alfisol Catena
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rosemary, F.; Vitharana, U. W. A.; Indraratne, S. P.
Detailed digital soil maps showing the spatial heterogeneity of soil properties consistent with the landscape are required for site-specific management of plant nutrients, land use planning and process-based environmental modeling. We characterized the short-scale spatial heterogeneity of soil properties in an Alfisol catena in a tropical landscape of Sri Lanka. The impact of different land-uses (paddy, vegetable and un-cultivated) was examined to assess the impact of anthropogenic activities on the variability of soil properties at the catenary level. Conditioned Latin hypercube sampling was used to collect 58 geo-referenced topsoil samples (0–30 cm) from the study area. Soil samples were analyzedmore » for pH, electrical conductivity (EC), organic carbon (OC), cation exchange capacity (CEC) and texture. The spatial correlation between soil properties was analyzed by computing crossvariograms and subsequent fitting of theoretical model. Spatial distribution maps were developed using ordinary kriging. The range of soil properties, pH: 4.3–7.9; EC: 0.01–0.18 dS m –1 ; OC: 0.1–1.37%; CEC: 0.44– 11.51 cmol (+) kg –1 ; clay: 1.5–25% and sand: 59.1–84.4% and their coefficient of variations indicated a large variability in the study area. Electrical conductivity and pH showed a strong spatial correlation which was reflected by the cross-variogram close to the hull of the perfect correlation. Moreover, cross-variograms calculated for EC and Clay, CEC and OC, CEC and clay and CEC and pH indicated weak positive spatial correlation between these properties. Relative nugget effect (RNE) calculated from variograms showed strongly structured spatial variability for pH, EC and sand content (RNE < 25%) while CEC, organic carbon and clay content showed moderately structured spatial variability (25% < RNE < 75%). Spatial dependencies for examined soil properties ranged from 48 to 984 m. The mixed effects model fitting followed by Tukey's post-hoc test showed significant effect of land use on the spatial variability of EC. Our study revealed a structured variability of topsoil properties in the selected tropical Alfisol catena. Except for EC, observed variability was not modified by the land uses. Investigated soil properties showed distinct spatial structures at different scales and magnitudes of strength. Our results will be useful for digital soil mapping, site specific management of soil properties, developing appropriate land use plans and quantifying anthropogenic impacts on the soil system.« less
The spatial pattern of suicide in the US in relation to deprivation, fragmentation and rurality.
Congdon, Peter
2011-01-01
Analysis of geographical patterns of suicide and psychiatric morbidity has demonstrated the impact of latent ecological variables (such as deprivation, rurality). Such latent variables may be derived by conventional multivariate techniques from sets of observed indices (for example, by principal components), by composite variable methods or by methods which explicitly consider the spatial framework of areas and, in particular, the spatial clustering of latent risks and outcomes. This article considers a latent random variable approach to explaining geographical contrasts in suicide in the US; and it develops a spatial structural equation model incorporating deprivation, social fragmentation and rurality. The approach allows for such latent spatial constructs to be correlated both within and between areas. Potential effects of area ethnic mix are also included. The model is applied to male and female suicide deaths over 2002–06 in 3142 US counties.
NASA Astrophysics Data System (ADS)
Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.
2017-12-01
Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.
Schmidt, Joachim; Böhner, Jürgen; Brandl, Roland; Opgenoorth, Lars
2017-01-01
Mass elevation and lee effects markedly influence snow lines and tree lines in high mountain systems. However, their impact on other phenomena or groups of organisms has not yet been quantified. Here we quantitatively studied their influence in the Himalaya–Tibet orogen on the distribution of ground beetles as model organisms, specifically whether the ground beetle distribution increases from the outer to the inner parts of the orogen, against latitudinal effects. We also tested whether July temperature and solar radiation are predictors of the beetle’s elevational distribution ranges. Finally, we discussed the general importance of these effects for the distributional and evolutionary history of the biota of High Asia. We modelled spatially explicit estimates of variables characterizing temperature and solar radiation and correlated the variables with the respective lower elevational range of 118 species of ground beetles from 76 high-alpine locations. Both July temperature and solar radiation significantly positively correlated with the elevational ranges of high-alpine beetles. Against the latitudinal trend, the median elevation of the respective species distributions increased by 800 m from the Himalayan south face north to the Transhimalaya. Our results indicate that an increase in seasonal temperature due to mass elevation and lee effects substantially impact the regional distribution patterns of alpine ground beetles of the Himalaya–Tibet orogen and are likely to affect also other soil biota there and in mountain ranges worldwide. Since these effects must have changed during orogenesis, their potential impact must be considered when biogeographic scenarios based on geological models are derived. As this has not been the practice, we believe that large biases likely exist in many paleoecological and evolutionary studies dealing with the biota from the Himalaya-Tibet orogen and mountain ranges worldwide. PMID:28339461
Van Wynsberge, Simon; Andréfouët, Serge; Gaertner-Mazouni, Nabila; Remoissenet, Georges
2018-02-01
Despite actions to manage sustainably tropical Pacific Ocean reef fisheries, managers have faced failures and frustrations because of unpredicted mass mortality events triggered by climate variability. The consequences of these events on the long-term population dynamics of living resources need to be better understood for better management decisions. Here, we use a giant clam (Tridacna maxima) spatially explicit population model to compare the efficiency of several management strategies under various scenarios of natural mortality, including mass mortality due to climatic anomalies. The model was parameterized by in situ estimations of growth and mortality and fishing effort, and was validated by historical and new in situ surveys of giant clam stocks in two French Polynesia lagoons. Projections on the long run (100 years) suggested that the best management strategy was a decrease of fishing pressure through quota implementation, regardless of the mortality regime considered. In contrast, increasing the minimum legal size of catch and closing areas to fishing were less efficient. When high mortality occurred due to climate variability, the efficiency of all management scenarios decreased markedly. Simulating El Niño Southern Oscillation event by adding temporal autocorrelation in natural mortality rates increased the natural variability of stocks, and also decreased the efficiency of management. These results highlight the difficulties that managers in small Pacific islands can expect in the future in the face of global warming, climate anomalies and new mass mortalities. Copyright © 2017 Elsevier Inc. All rights reserved.
Dementia of frontal lobe type.
Neary, D; Snowden, J S; Northen, B; Goulding, P
1988-01-01
A significant proportion of patients with presenile dementia due to primary cerebral atrophy do not have Alzheimer's disease. One form of non-Alzheimer dementia may be designated as dementia of frontal lobe type (DFT), on the basis of a characteristic neuropsychological picture suggestive of frontal lobe disorder, confirmed by findings on single photon emission tomography. The case histories of seven patients exemplify the disorder: a presentation of social misconduct and personality change, unconcern and disinhibition, in the presence of physical well-being and few neurological signs. Assessment revealed economic and concrete speech with verbal stereotypes, variable memory impairment, and marked abnormalities on tasks sensitive to frontal lobe function. Visuo-spatial disorder was invariably absent. Comparisons of DFT and Alzheimer patients revealed qualitative differences in clinical presentation, neurological signs, profile of psychological disability, electroencephalography, single photon emission tomography and demography. DFT, which may represent forms of Pick's disease, may be more common than is often recognised. PMID:3258902
Robustness of plasmon phased array nanoantennas to disorder
Arango, Felipe Bernal; Thijssen, Rutger; Brenny, Benjamin; Coenen, Toon; Koenderink, A. Femius
2015-01-01
We present cathodoluminescence experiments that quantify the response of plasmonic Yagi-Uda antennas fabricated on one-dimensional silicon nitride waveguides as function of electron beam excitation position and emission wavelength. At the near-infrared antenna design wavelength cathodoluminescence signal robustly is strongest when exciting the antenna at the reflector element. Yet at just slightly shorter wavelengths the signal is highly variable from antenna to antenna and wavelength to wavelength. Hypothesizing that fabrication randomness is at play, we analyze the resilience of plasmon Yagi-Uda antennas to varations in element size of just 5 nm. While in our calculations the appearance of directivity is robust, both the obtained highest directivity and the wavelength at which it occurs vary markedly between realizations. The calculated local density of states is invariably high at the reflector for the design wavelength, but varies dramatically in spatial distribution for shorter wavelengths, consistent with the cathodoluminescence experiments. PMID:26038871
Lagrangian Assimilation of Satellite Data for Climate Studies in the Arctic
NASA Technical Reports Server (NTRS)
Lindsay, Ronald W.; Zhang, Jin-Lun; Stern, Harry
2004-01-01
Under this grant we have developed and tested a new Lagrangian model of sea ice. A Lagrangian model keeps track of material parcels as they drift in the model domain. Besides providing a natural framework for the assimilation of Lagrangian data, it has other advantages: 1) a model that follows material elements is well suited for a medium such as sea ice in which an element retains its identity for a long period of time; 2) model cells can be added or dropped as needed, allowing the spatial resolution to be increased in areas of high variability or dense observations; 3) ice from particular regions, such as the marginal seas, can be marked and traced for a long time; and 4) slip lines in the ice motion are accommodated more naturally because there is no internal grid. Our work makes use of these strengths of the Lagrangian formulation.
Cloud Feedback Key to Marine Heatwave off Baja California
NASA Astrophysics Data System (ADS)
Myers, Timothy A.; Mechoso, Carlos R.; Cesana, Gregory V.; DeFlorio, Michael J.; Waliser, Duane E.
2018-05-01
Between 2013 and 2015, the northeast Pacific Ocean experienced the warmest surface temperature anomalies in the modern observational record. This "marine heatwave" marked a shift of Pacific decadal variability to its warm phase and was linked to significant impacts on marine species as well as exceptionally arid conditions in western North America. Here we show that the subtropical signature of this warming, off Baja California, was associated with a record deficit in the spatial coverage of co-located marine boundary layer clouds. This deficit coincided with a large increase in downwelling solar radiation that dominated the anomalous energy budget of the upper ocean, resulting in record-breaking warm sea surface temperature anomalies. Our observation-based analysis suggests that a positive cloud-surface temperature feedback was key to the extreme intensity of the heatwave. The results demonstrate the extent to which boundary layer clouds can contribute to regional variations in climate.
Johnston, R E; Bhorade, A
1998-09-01
Hamsters preferentially remember or value the top scent of a scent over-mark. What cues do they use to do this? Using habituation-discrimination techniques, we exposed male golden hamsters (Mesocricetus auratus) on 3 to 4 trials to genital over-marks from 2 females and then tested subjects for their familiarity with these 2 scents compared with that of a novel female's secretion. Preferential memory for 1 of the 2 individuals' scents did not occur if the 2 marks did not overlap or did not overlap but differed in age, but it did occur if a region of overlap existed or 1 mark apparently occluded another (but did not overlap it). Thus, hamsters use regions of overlap and the spatial configuration of scents to evaluate over-marks. These phenomena constitute evidence for previously unsuspected perceptual abilities, including olfactory scene analysis, which is analogous to visual and auditory scene analysis.
Variability of the raindrop size distribution at small spatial scales
NASA Astrophysics Data System (ADS)
Berne, A.; Jaffrain, J.
2010-12-01
Because of the interactions between atmospheric turbulence and cloud microphysics, the raindrop size distribution (DSD) is strongly variable in space and time. The spatial variability of the DSD at small spatial scales (below a few km) is not well documented and not well understood, mainly because of a lack of adequate measurements at the appropriate resolutions. A network of 16 disdrometers (Parsivels) has been designed and set up over EPFL campus in Lausanne, Switzerland. This network covers a typical operational weather radar pixel of 1x1 km2. The question of the significance of the variability of the DSD at such small scales is relevant for radar remote sensing of rainfall because the DSD is often assumed to be uniform within a radar sample volume and because the Z-R relationships used to convert the measured radar reflectivity Z into rain rate R are usually derived from point measurements. Thanks to the number of disdrometers, it was possible to quantify the spatial variability of the DSD at the radar pixel scale and to show that it can be significant. In this contribution, we show that the variability of the total drop concentration, of the median volume diameter and of the rain rate are significant, taking into account the sampling uncertainty associated with disdrometer measurements. The influence of this variability on the Z-R relationship can be non-negligible. Finally, the spatial structure of the DSD is quantified using a geostatistical tool, the variogram, and indicates high spatial correlation within a radar pixel.
NASA Astrophysics Data System (ADS)
Libonati, Renata; DaCamara, Carlos; Setzer, Alberto
2016-04-01
Although Cerrado is a fire-dependent biome, current agriculture practices have significantly modified the native fire regime. Moreover, over the last decades, climate conditions, such as intensive droughts, have contributed to enhance the effects of anthropogenic activities, and consequently fire, over the region. For instance, during the 2010 extreme drought there was an increase of 100% in the number of fire pixels detected by just one polar orbiting satellite (information online at http://www.cptec.inpe.br/queimadas). A better characterization of spatial and temporal fire patterns over Cerrado is therefore crucial to uncover both climate and anthropogenic influences in this ecosystem. Additionally, information about the extent, location and time of burned areas (BA) over Cerrado is especially useful to a wide range of users, from government agencies, research groups and ecologists, to fire managers and NGOs. Instruments on-board satellites are the only available operational means to collect BA data at appropriated spatial and temporal scales and in a cost-effective way. Several global BA products derived from remote sensed information have been developed over the last years using a variety of techniques based on different spatial, spectral and temporal resolutions. Although presenting similar inter-annual variability, there are marked differences among the products both in magnitude and location of the area burnt. The development of regional algorithms which take into account local characteristics such as vegetation type, soil and climate is therefore an added value to the existing information. We present a monthly BA product (AQM) for Brazil based on information from MODIS 1km. The algorithm was specifically designed for ecosystems in Brazil and the procedure represents the first initiative of an automated method for BA monitoring using remote sensing information in the country. The product relies on an algorithm that takes advantage of the ability of MIR reflectances to discriminate BA. Validation over Cerrado biome indicates that the product is in accordance with BA maps from reference data, making the product suitable for applications in fire emission studies and ecosystem management. The AQM regional database covers the 11-year period 2005-2015 over Cerrado and allows analyzing the overall temporal and spatial distribution patterns of BA for the last decade. The highest monthly mean amount is observed in September, followed by October, and March presents the lowest amount. The most severe year is 2007, followed by 2005 and 2010; 2006 and 2009 are the years with less area burned, followed by 2008. The spatial pattern of BA shows that the north region of Cerrado presents the highest frequency of occurrence. The intra and inter-annual variability of BA over Cerrado are closely related to variability of precipitation but it is worth emphasizing that, despite the major role played by climate conditions, the human factor has also a prominent role on fire dynamics in this region and cannot be disregarded.
Submesoscale Sea Surface Temperature Variability from UAV and Satellite Measurements
NASA Astrophysics Data System (ADS)
Castro, S. L.; Emery, W. J.; Tandy, W., Jr.; Good, W. S.
2017-12-01
Technological advances in spatial resolution of observations have revealed the importance of short-lived ocean processes with scales of O(1km). These submesoscale processes play an important role for the transfer of energy from the meso- to small scales and for generating significant spatial and temporal intermittency in the upper ocean, critical for the mixing of the oceanic boundary layer. Submesoscales have been observed in sea surface temperatures (SST) from satellites. Satellite SST measurements are spatial averages over the footprint of the satellite. When the variance of the SST distribution within the footprint is small, the average value is representative of the SST over the whole pixel. If the variance is large, the spatial heterogeneity is a source of uncertainty in satellite derived SSTs. Here we show evidence that the submesoscale variability in SSTs at spatial scales of 1km is responsible for the spatial variability within satellite footprints. Previous studies of the spatial variability in SST, using ship-based radiometric data suggested that variability at scales smaller than 1 km is significant and affects the uncertainty of satellite-derived skin SSTs. We examine data collected by a calibrated thermal infrared radiometer, the Ball Experimental Sea Surface Temperature (BESST), flown on a UAV over the Arctic Ocean and compare them with coincident measurements from the MODIS spaceborne radiometer to assess the spatial variability of SST within 1 km pixels. By taking the standard deviation of all the BESST measurements within individual MODIS pixels we show that significant spatial variability exists within the footprints. The distribution of the surface variability measured by BESST shows a peak value of O(0.1K) with 95% of the pixels showing σ < 0.45K. More importantly, high-variability pixels are located at density fronts in the marginal ice zone, which are a primary source of submesoscale intermittency near the surface in the Arctic Ocean. Wavenumber spectra of the BESST SSTs indicate a spectral slope of -2, consistent with the presence of submesoscale processes. Furthermore, not only is the BESST wavenumber spectra able to match the MODIS SST spectra well, but also extends the spectral slope of -2 by 2 decades relative to MODIS, from wavelengths of 8km to 0.08km.
The Variability of Neural Responses to Naturalistic Videos Change with Age and Sex.
Petroni, Agustin; Cohen, Samantha S; Ai, Lei; Langer, Nicolas; Henin, Simon; Vanderwal, Tamara; Milham, Michael P; Parra, Lucas C
2018-01-01
Neural development is generally marked by an increase in the efficiency and diversity of neural processes. In a large sample ( n = 114) of human children and adults with ages ranging from 5 to 44 yr, we investigated the neural responses to naturalistic video stimuli. Videos from both real-life classroom settings and Hollywood feature films were used to probe different aspects of attention and engagement. For all stimuli, older ages were marked by more variable neural responses. Variability was assessed by the intersubject correlation of evoked electroencephalographic responses. Young males also had less-variable responses than young females. These results were replicated in an independent cohort ( n = 303). When interpreted in the context of neural maturation, we conclude that neural function becomes more variable with maturity, at least during the passive viewing of real-world stimuli.
NASA Astrophysics Data System (ADS)
Sicard, Emeline; Sabatier, Robert; Niel, HéLèNe; Cadier, Eric
2002-12-01
The objective of this paper is to implement an original method for spatial and multivariate data, combining a method of three-way array analysis (STATIS) with geostatistical tools. The variables of interest are the monthly amounts of rainfall in the Nordeste region of Brazil, recorded from 1937 to 1975. The principle of the technique is the calculation of a linear combination of the initial variables, containing a large part of the initial variability and taking into account the spatial dependencies. It is a promising method that is able to analyze triple variability: spatial, seasonal, and interannual. In our case, the first component obtained discriminates a group of rain gauges, corresponding approximately to the Agreste, from all the others. The monthly variables of July and August strongly influence this separation. Furthermore, an annual study brings out the stability of the spatial structure of components calculated for each year.
Cloern, James E.; Jassby, Alan D.; Schraga, Tara; Kress, Erica S.; Martin, Charles A.
2017-01-01
The salinity gradient of estuaries plays a unique and fundamental role in structuring spatial patterns of physical properties, biota, and biogeochemical processes. We use variability along the salinity gradient of San Francisco Bay to illustrate some lessons about the diversity of spatial structures in estuaries and their variability over time. Spatial patterns of dissolved constituents (e.g., silicate) can be linear or nonlinear, depending on the relative importance of river-ocean mixing and internal sinks (diatom uptake). Particles have different spatial patterns because they accumulate in estuarine turbidity maxima formed by the combination of sinking and estuarine circulation. Some constituents have weak or no mean spatial structure along the salinity gradient, reflecting spatially distributed sources along the estuary (nitrate) or atmospheric exchanges that buffer spatial variability of ecosystem metabolism (dissolved oxygen). The density difference between freshwater and seawater establishes stratification in estuaries stronger than the thermal stratification of lakes and oceans. Stratification is strongest around the center of the salinity gradient and when river discharge is high. Spatial distributions of motile organisms are shaped by species-specific adaptations to different salinity ranges (shrimp) and by behavioral responses to environmental variability (northern anchovy). Estuarine spatial patterns change over time scales of events (intrusions of upwelled ocean water), seasons (river inflow), years (annual weather anomalies), and between eras separated by ecosystem disturbances (a species introduction). Each of these lessons is a piece in the puzzle of how estuarine ecosystems are structured and how they differ from the river and ocean ecosystems they bridge.
Spatial heterogeneity of within-stream methane concentrations
NASA Astrophysics Data System (ADS)
Crawford, John T.; Loken, Luke C.; West, William E.; Crary, Benjamin; Spawn, Seth A.; Gubbins, Nicholas; Jones, Stuart E.; Striegl, Robert G.; Stanley, Emily H.
2017-05-01
Streams, rivers, and other freshwater features may be significant sources of CH4 to the atmosphere. However, high spatial and temporal variabilities hinder our ability to understand the underlying processes of CH4 production and delivery to streams and also challenge the use of scaling approaches across large areas. We studied a stream having high geomorphic variability to assess the underlying scale of CH4 spatial variability and to examine whether the physical structure of a stream can explain the variation in surface CH4. A combination of high-resolution CH4 mapping, a survey of groundwater CH4 concentrations, quantitative analysis of methanogen DNA, and sediment CH4 production potentials illustrates the spatial and geomorphic controls on CH4 emissions to the atmosphere. We observed significant spatial clustering with high CH4 concentrations in organic-rich stream reaches and lake transitions. These sites were also enriched in the methane-producing mcrA gene and had highest CH4 production rates in the laboratory. In contrast, mineral-rich reaches had significantly lower concentrations and had lesser abundances of mcrA. Strong relationships between CH4 and the physical structure of this aquatic system, along with high spatial variability, suggest that future investigations will benefit from viewing streams as landscapes, as opposed to ecosystems simply embedded in larger terrestrial mosaics. In light of such high spatial variability, we recommend that future workers evaluate stream networks first by using similar spatial tools in order to build effective sampling programs.
Nitrogen attenuation along delivery pathways in agricultural catchments
NASA Astrophysics Data System (ADS)
McAleer, Eoin; Mellander, Per-Erik; Coxon, Catherine; Richards, Karl G.
2014-05-01
Hillslope hydrologic systems and in particular near-stream saturated zones are active sites of nitrogen (N) biogeochemical dynamics. The efficiency of N removal and the ratio of reaction products (nitrous oxide and dinitrogen) in groundwater is highly variable and depends upon aquifer hydrology, mineralogy, dissolved oxygen, energy sources and redox chemistry. There are large uncertainties in the closing of N budgets in agricultural catchments. Spatial and temporal variability in groundwater physico-chemistry, catchment hydrology and land-use gives rise to hotspots and hot moments of N attenuation. In addition the production, consumption and movement of denitrification products remains poorly understood. The focus of this study is to develop a holistic understanding of N dynamics in groundwater as it moves from the top of the hillslope to the stream. This includes saturated groundwater flow, exchange at the groundwater-surface water interface and hyporheic zone flow. This project is being undertaken in two ca. 10km2 Irish catchments, characterised by permeable soils. One catchment is dominated by arable land overlying slate bedrock and the other by grassland overlying sandstone. Multi-level monitoring wells have been installed at the upslope, midslope and bottom of each hillslope. The piezometers are screened to intercept the subsoil, weathered bedrock and competent bedrock zones. Groundwater samples for nitrate (NO3-N) nitrite (NO2-N), ammonium (NH4-N) and total nitrogen are collected on a monthly basis while dissolved gas concentrations are collected seasonally. Groundwater NO3-N profiles from monitoring data to date in both catchments differ markedly. Although the two catchments had similar 3 year mean concentrations of 6.89 mg/L (arable) and 6.24 mg/L (grassland), the grassland catchment had higher spatial and temporal variation. The arable catchment showed relatively homogenous NO3-N concentrations in all layers and zones (range: 1.2 - 12.13 mg/L, SD = 1.60 mg/L). Whereas in the grassland catchment NO3-N concentrations ranged from 0.001 - 23.9 mg/L (SD = 4.40 mg/L) with elevated concentrations in the midslope and upslope zones and groundwater at the hillslope bottom which were consistently close to the limits of detection, indicating a potential denitrifying zone. Using a combination of groundwater flow modelling (Visual Modflow-Flex), high density spatial and temporal sampling and push pull tracer techniques; it is aimed to contribute to the wider understanding of N dynamics in terms of the individual environmental parameters affecting N attenuation, spatial and temporal variability in denitrification rates and gaseous emissions along the hillslope flow path.
Examining Impulse-Variability in Kicking.
Chappell, Andrew; Molina, Sergio L; McKibben, Jonathon; Stodden, David F
2016-07-01
This study examined variability in kicking speed and spatial accuracy to test the impulse-variability theory prediction of an inverted-U function and the speed-accuracy trade-off. Twenty-eight 18- to 25-year-old adults kicked a playground ball at various percentages (50-100%) of their maximum speed at a wall target. Speed variability and spatial error were analyzed using repeated-measures ANOVA with built-in polynomial contrasts. Results indicated a significant inverse linear trajectory for speed variability (p < .001, η2= .345) where 50% and 60% maximum speed had significantly higher variability than the 100% condition. A significant quadratic fit was found for spatial error scores of mean radial error (p < .0001, η2 = .474) and subject-centroid radial error (p < .0001, η2 = .453). Findings suggest variability and accuracy of multijoint, ballistic skill performance may not follow the general principles of impulse-variability theory or the speed-accuracy trade-off.
The role of plant phenology in stomatal ozone flux modeling.
Anav, Alessandro; Liu, Qiang; De Marco, Alessandra; Proietti, Chiara; Savi, Flavia; Paoletti, Elena; Piao, Shilong
2018-01-01
Plant phenology plays a pivotal role in the climate system as it regulates the gas exchange between the biosphere and the atmosphere. The uptake of ozone by forest is estimated through several meteorological variables and a specific function describing the beginning and the termination of plant growing season; actually, in many risk assessment studies, this function is based on a simple latitude and topography model. In this study, using two satellite datasets, we apply and compare six methods to estimate the start and the end dates of the growing season across a large region covering all Europe for the year 2011. Results show a large variability between the green-up and dormancy dates estimated using the six different methods, with differences greater than one month. However, interestingly, all the methods display a common spatial pattern in the uptake of ozone by forests with a marked change in the magnitude, up to 1.9 TgO 3 /year, and corresponding to a difference of 25% in the amount of ozone that enters the leaves. Our results indicate that improved estimates of ozone fluxes require a better representation of plant phenology in the models used for O 3 risk assessment. © 2017 John Wiley & Sons Ltd.
Stepping over obstacles: anticipatory modifications in children with and without Down syndrome.
Virji-Babul, Naznin; Brown, Michelle
2004-12-01
The purpose of this study was to explore the mechanism of anticipatory control of gait in relation to the perception of an obstacle. Typically developing (TD) children (4-7 years of age) and children with Down syndrome (5-6 years of age) walked and stepped over obstacles of two different heights-a "subtle" obstacle that was placed at a very low distance from the floor (1% of total body height) and an "obvious" obstacle that was placed at a much higher distance from the floor (15% of total body height). Spatial and temporal measures of the gait cycle were analyzed. TD children showed increased variability in pre-obstacle step lengths only in response to the higher obstacle. Children with DS showed a decrease in variability in response to the higher obstacle and marked qualitative changes in their gait cycle. Both groups of children were able to scale toe clearance with obstacle height. These results show that TD young children can make task-specific anticipatory adjustments by modulating step length and toe clearance. Children with DS show appropriate scaling of toe clearance and are beginning to show the emergence of anticipatory responses under specific environmental conditions.
Modeling the Spatial Dynamics of International Tuna Fleets
2016-01-01
We developed an iterative sequential random utility model to investigate the social and environmental determinants of the spatiotemporal decision process of tuna purse-seine fishery fishing effort in the eastern Pacific Ocean. Operations of the fishing gear mark checkpoints in a continuous complex decision-making process. Individual fisher behavior is modeled by identifying diversified choices over decision-space for an entire fishing trip, which allows inclusion of prior and current vessel locations and conditions among the explanatory variables. Among these factors are vessel capacity; departure and arrival port; duration of the fishing trip; daily and cumulative distance travelled, which provides a proxy for operation costs; expected revenue; oceanographic conditions; and tons of fish on board. The model uses a two-step decision process to capture the probability of a vessel choosing a specific fishing region for the first set and the probability of switching to (or staying in) a specific region to fish before returning to its landing port. The model provides a means to anticipate the success of marine resource management, and it can be used to evaluate fleet diversity in fisher behavior, the impact of climate variability, and the stability and resilience of complex coupled human and natural systems. PMID:27537545
Memory Effects on Movement Behavior in Animal Foraging
Bracis, Chloe; Gurarie, Eliezer; Van Moorter, Bram; Goodwin, R. Andrew
2015-01-01
An individual’s choices are shaped by its experience, a fundamental property of behavior important to understanding complex processes. Learning and memory are observed across many taxa and can drive behaviors, including foraging behavior. To explore the conditions under which memory provides an advantage, we present a continuous-space, continuous-time model of animal movement that incorporates learning and memory. Using simulation models, we evaluate the benefit memory provides across several types of landscapes with variable-quality resources and compare the memory model within a nested hierarchy of simpler models (behavioral switching and random walk). We find that memory almost always leads to improved foraging success, but that this effect is most marked in landscapes containing sparse, contiguous patches of high-value resources that regenerate relatively fast and are located in an otherwise devoid landscape. In these cases, there is a large payoff for finding a resource patch, due to size, value, or locational difficulty. While memory-informed search is difficult to differentiate from other factors using solely movement data, our results suggest that disproportionate spatial use of higher value areas, higher consumption rates, and consumption variability all point to memory influencing the movement direction of animals in certain ecosystems. PMID:26288228
Memory Effects on Movement Behavior in Animal Foraging.
Bracis, Chloe; Gurarie, Eliezer; Van Moorter, Bram; Goodwin, R Andrew
2015-01-01
An individual's choices are shaped by its experience, a fundamental property of behavior important to understanding complex processes. Learning and memory are observed across many taxa and can drive behaviors, including foraging behavior. To explore the conditions under which memory provides an advantage, we present a continuous-space, continuous-time model of animal movement that incorporates learning and memory. Using simulation models, we evaluate the benefit memory provides across several types of landscapes with variable-quality resources and compare the memory model within a nested hierarchy of simpler models (behavioral switching and random walk). We find that memory almost always leads to improved foraging success, but that this effect is most marked in landscapes containing sparse, contiguous patches of high-value resources that regenerate relatively fast and are located in an otherwise devoid landscape. In these cases, there is a large payoff for finding a resource patch, due to size, value, or locational difficulty. While memory-informed search is difficult to differentiate from other factors using solely movement data, our results suggest that disproportionate spatial use of higher value areas, higher consumption rates, and consumption variability all point to memory influencing the movement direction of animals in certain ecosystems.
Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé
2016-01-01
The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes.
Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé
2016-01-01
The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes. PMID:27074044
Multi-scale Homogenization of Caddisfly Metacomminities in Human-modified Landscapes
NASA Astrophysics Data System (ADS)
Simião-Ferreira, Juliana; Nogueira, Denis Silva; Santos, Anna Claudia; De Marco, Paulo; Angelini, Ronaldo
2018-04-01
The multiple scale of stream networks spatial organization reflects the hierarchical arrangement of streams habitats with increasingly levels of complexity from sub-catchments until entire hydrographic basins. Through these multiple spatial scales, local stream habitats form nested subsets of increasingly landscape scale and habitat size with varying contributions of both alpha and beta diversity for the regional diversity. Here, we aimed to test the relative importance of multiple nested hierarchical levels of spatial scales while determining alpha and beta diversity of caddisflies in regions with different levels of landscape degradation in a core Cerrado area in Brazil. We used quantitative environmental variables to test the hypothesis that landscape homogenization affects the contribution of alpha and beta diversity of caddisflies to regional diversity. We found that the contribution of alpha and beta diversity for gamma diversity varied according to landscape degradation. Sub-catchments with more intense agriculture had lower diversity at multiple levels, markedly alpha and beta diversities. We have also found that environmental predictors mainly associated with water quality, channel size, and habitat integrity (lower scores indicate stream degradation) were related to community dissimilarity at the catchment scale. For an effective management of the headwater biodiversity of caddisfly, towards the conservation of these catchments, heterogeneous streams with more pristine riparian vegetation found within the river basin need to be preserved in protected areas. Additionally, in the most degraded areas the restoration of riparian vegetation and size increase of protected areas will be needed to accomplish such effort.
Spatial patterns of development drive water use
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.
Measuring spatial variability in soil characteristics
Hoskinson, Reed L.; Svoboda, John M.; Sawyer, J. Wayne; Hess, John R.; Hess, J. Richard
2002-01-01
The present invention provides systems and methods for measuring a load force associated with pulling a farm implement through soil that is used to generate a spatially variable map that represents the spatial variability of the physical characteristics of the soil. An instrumented hitch pin configured to measure a load force is provided that measures the load force generated by a farm implement when the farm implement is connected with a tractor and pulled through or across soil. Each time a load force is measured, a global positioning system identifies the location of the measurement. This data is stored and analyzed to generate a spatially variable map of the soil. This map is representative of the physical characteristics of the soil, which are inferred from the magnitude of the load force.
NASA Astrophysics Data System (ADS)
Li, Lianfa; Wu, Anna H.; Cheng, Iona; Chen, Jiu-Chiuan; Wu, Jun
2017-10-01
Monitoring of fine particulate matter with diameter <2.5 μm (PM2.5) started from 1999 in the US and even later in many other countries. The lack of historical PM2.5 data limits epidemiological studies of long-term exposure of PM2.5 and health outcomes such as cancer. In this study, we aimed to design a flexible approach to reliably estimate historical PM2.5 concentrations by incorporating spatial effect and the measurements of existing co-pollutants such as particulate matter with diameter <10 μm (PM10) and meteorological variables. Monitoring data of PM10, PM2.5, and meteorological variables covering the entire state of California were obtained from 1999 through 2013. We developed a spatiotemporal model that quantified non-linear associations between PM2.5 concentrations and the following predictor variables: spatiotemporal factors (PM10 and meteorological variables), spatial factors (land-use patterns, traffic, elevation, distance to shorelines, and spatial autocorrelation), and season. Our model accounted for regional-(county) scale spatial autocorrelation, using spatial weight matrix, and local-scale spatiotemporal variability, using local covariates in additive non-linear model. The spatiotemporal model was evaluated, using leaving-one-site-month-out cross validation. Our final daily model had an R2 of 0.81, with PM10, meteorological variables, and spatial autocorrelation, explaining 55%, 10%, and 10% of the variance in PM2.5 concentrations, respectively. The model had a cross-validation R2 of 0.83 for monthly PM2.5 concentrations (N = 8170) and 0.79 for daily PM2.5 concentrations (N = 51,421) with few extreme values in prediction. Further, the incorporation of spatial effects reduced bias in predictions. Our approach achieved a cross validation R2 of 0.61 for the daily model when PM10 was replaced by total suspended particulate. Our model can robustly estimate historical PM2.5 concentrations in California when PM2.5 measurements were not available.
Marked point process for modelling seismic activity (case study in Sumatra and Java)
NASA Astrophysics Data System (ADS)
Pratiwi, Hasih; Sulistya Rini, Lia; Wayan Mangku, I.
2018-05-01
Earthquake is a natural phenomenon that is random, irregular in space and time. Until now the forecast of earthquake occurrence at a location is still difficult to be estimated so that the development of earthquake forecast methodology is still carried out both from seismology aspect and stochastic aspect. To explain the random nature phenomena, both in space and time, a point process approach can be used. There are two types of point processes: temporal point process and spatial point process. The temporal point process relates to events observed over time as a sequence of time, whereas the spatial point process describes the location of objects in two or three dimensional spaces. The points on the point process can be labelled with additional information called marks. A marked point process can be considered as a pair (x, m) where x is the point of location and m is the mark attached to the point of that location. This study aims to model marked point process indexed by time on earthquake data in Sumatra Island and Java Island. This model can be used to analyse seismic activity through its intensity function by considering the history process up to time before t. Based on data obtained from U.S. Geological Survey from 1973 to 2017 with magnitude threshold 5, we obtained maximum likelihood estimate for parameters of the intensity function. The estimation of model parameters shows that the seismic activity in Sumatra Island is greater than Java Island.
Liu, Kui; Guo, Jun; Cai, Chunxiao; Zhang, Junxiang; Gao, Jiangrui
2016-11-15
Multipartite entanglement is used for quantum information applications, such as building multipartite quantum communications. Generally, generation of multipartite entanglement is based on a complex beam-splitter network. Here, based on the spatial freedom of light, we experimentally demonstrated spatial quadripartite continuous variable entanglement among first-order Hermite-Gaussian modes using a single type II optical parametric oscillator operating below threshold with an HG0245° pump beam. The entanglement can be scalable for larger numbers of spatial modes by changing the spatial profile of the pump beam. In addition, spatial multipartite entanglement will be useful for future spatial multichannel quantum information applications.
Temporal and spatial variability in North Carolina piedmont stream temperature
J.L. Boggs; G. Sun; S.G. McNulty; W. Swartley; Treasure E.; W. Summer
2009-01-01
Understanding temporal and spatial patterns of in-stream temperature can provide useful information to managing future impacts of climate change on these systems. This study will compare temporal patterns and spatial variability of headwater in-stream temperature in six catchments in the piedmont of North Carolina in two different geological regions, Carolina slate...
Li, Yan; Wagner, Tyler; Jiao, Yan; Lorantas, Robert M.; Murphy, Cheryl
2018-01-01
Understanding the spatial and temporal variability in life-history traits among populations is essential for the management of recreational fisheries. However, valuable freshwater recreational fish species often suffer from a lack of catch information. In this study, we demonstrated the use of an approach to estimate the spatial and temporal variability in growth and mortality in the absence of catch data and apply the method to riverine smallmouth bass (Micropterus dolomieu) populations in Pennsylvania, USA. Our approach included a growth analysis and a length-based analysis that estimates mortality. Using a hierarchical Bayesian approach, we examined spatial variability in growth and mortality by assuming parameters vary spatially but remain constant over time and temporal variability by assuming parameters vary spatially and temporally. The estimated growth and mortality of smallmouth bass showed substantial variability over time and across rivers. We explored the relationships of the estimated growth and mortality with spring water temperature and spring flow. Growth rate was likely to be positively correlated with these two factors, while young mortality was likely to be positively correlated with spring flow. The spatially and temporally varying growth and mortality suggest that smallmouth bass populations across rivers may respond differently to management plans and disturbance such as environmental contamination and land-use change. The analytical approach can be extended to other freshwater recreational species that also lack of catch data. The approach could also be useful in developing population assessments with erroneous catch data or be used as a model sensitivity scenario to verify traditional models even when catch data are available.
Remote sensing using MIMO systems
Bikhazi, Nicolas; Young, William F; Nguyen, Hung D
2015-04-28
A technique for sensing a moving object within a physical environment using a MIMO communication link includes generating a channel matrix based upon channel state information of the MIMO communication link. The physical environment operates as a communication medium through which communication signals of the MIMO communication link propagate between a transmitter and a receiver. A spatial information variable is generated for the MIMO communication link based on the channel matrix. The spatial information variable includes spatial information about the moving object within the physical environment. A signature for the moving object is generated based on values of the spatial information variable accumulated over time. The moving object is identified based upon the signature.
Assessing the Dynamic Effects of Climate on Individual Tree Growth Across Time and Space
NASA Astrophysics Data System (ADS)
Itter, M.; Finley, A. O.; D'Amato, A. W.; Foster, J. R.; Bradford, J. B.
2015-12-01
The relationship between climate variability and an ecosystem process, such as forest growth, is frequently not fixed over time, but changes due to complex interactions between unobserved ecological factors and the process of interest. Climate data and forecasts are frequently spatially and temporally misaligned with ecological observations making inference regarding the effects of climate on ecosystem processes particularly challenging. Here we develop a Bayesian dynamic hierarchical model for annual tree growth increment that allows the effects of climate to evolve over time, applies climate data at a spatial-temporal scale consistent with observations, and controls for individual-level variability commonly encountered in ecological datasets. The model is applied to individual tree data from northern Minnesota using a modified Thornthwaite-type water balance model to transform PRISM temperature and precipitation estimates to physiologically relevant values of actual and potential evapotranspiration (AET, PET), and climatic water deficit. Model results indicate that mean tree growth is most sensitive to AET during the growing season and PET and minimum temperature in the spring prior to growth. The effects of these variables on tree growth, however, are not stationary with significant effects observed in only a subset of years during the 111-year study period. Importantly, significant effects of climate do not result from anomalous climate observations, but follow from large growth deviations unexplained by tree age and size, and time since forest disturbance. Results differ markedly from alternative models that assume the effects of climate are stationary over time or apply climate estimates at the individual scale. Forecasts of future tree growth as a function of climate follow directly from the dynamic hierarchical model allowing for assessment of forest change. Current work is focused on extending the model framework to include regional climate and ecosystem effects for application to a larger tree growth dataset spanning a latitudinal gradient within the US from Maine to Florida.
The effect of short-range spatial variability on soil sampling uncertainty.
Van der Perk, Marcel; de Zorzi, Paolo; Barbizzi, Sabrina; Belli, Maria; Fajgelj, Ales; Sansone, Umberto; Jeran, Zvonka; Jaćimović, Radojko
2008-11-01
This paper aims to quantify the soil sampling uncertainty arising from the short-range spatial variability of elemental concentrations in the topsoils of agricultural, semi-natural, and contaminated environments. For the agricultural site, the relative standard sampling uncertainty ranges between 1% and 5.5%. For the semi-natural area, the sampling uncertainties are 2-4 times larger than in the agricultural area. The contaminated site exhibited significant short-range spatial variability in elemental composition, which resulted in sampling uncertainties of 20-30%.
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
Effect of land use on the spatial variability of organic matter and nutrient status in an Oxisol
NASA Astrophysics Data System (ADS)
Paz-Ferreiro, Jorge; Alves, Marlene Cristina; Vidal Vázquez, Eva
2013-04-01
Heterogeneity is now considered as an inherent soil property. Spatial variability of soil attributes in natural landscapes results mainly from soil formation factors. In cultivated soils much heterogeneity can additionally occur as a result of land use, agricultural systems and management practices. Organic matter content (OMC) and nutrients associated to soil exchange complex are key attribute in the maintenance of a high quality soil. Neglecting spatial heterogeneity in soil OMC and nutrient status at the field scale might result in reduced yield and in environmental damage. We analyzed the impact of land use on the pattern of spatial variability of OMC and soil macronutrients at the stand scale. The study was conducted in São Paulo state, Brazil. Land uses were pasture, mango orchard and corn field. Soil samples were taken at 0-10 cm and 10-20 cm depth in 84 points, within 100 m x 100 m plots. Texture, pH, OMC, cation exchange capacity (CEC), exchangeable cations (Ca, Mg, K, H, Al) and resin extractable phosphorus were analyzed.. Statistical variability was found to be higher in parameters defining the soil nutrient status (resin extractable P, K, Ca and Mg) than in general soil properties (OMC, CEC, base saturation and pH). Geostatistical analysis showed contrasting patterns of spatial dependence for the different soil uses, sampling depths and studied properties. Most of the studied data sets collected at two different depths exhibited spatial dependence at the sampled scale and their semivariograms were modeled by a nugget effect plus a structure. The pattern of soil spatial variability was found to be different between the three study soil uses and at the two sampling depths, as far as model type, nugget effect or ranges of spatial dependence were concerned. Both statistical and geostatistical results pointed out the importance of OMC as a driver responsible for the spatial variability of soil nutrient status.
Van der Laan, Carina; Verweij, Pita A; Quiñones, Marcela J; Faaij, André Pc
2014-12-01
Land use and land cover change occurring in tropical forest landscapes contributes substantially to carbon emissions. Better insights into the spatial variation of aboveground biomass is therefore needed. By means of multiple statistical tests, including geographically weighted regression, we analysed the effects of eight variables on the regional spatial variation of aboveground biomass. North and East Kalimantan were selected as the case study region; the third largest carbon emitting Indonesian provinces. Strong positive relationships were found between aboveground biomass and the tested variables; altitude, slope, land allocation zoning, soil type, and distance to the nearest fire, road, river and city. Furthermore, the results suggest that the regional spatial variation of aboveground biomass can be largely attributed to altitude, distance to nearest fire and land allocation zoning. Our study showed that in this landscape, aboveground biomass could not be explained by one single variable; the variables were interrelated, with altitude as the dominant variable. Spatial analyses should therefore integrate a variety of biophysical and anthropogenic variables to provide a better understanding of spatial variation in aboveground biomass. Efforts to minimise carbon emissions should incorporate the identified factors, by 1) the maintenance of lands with high AGB or carbon stocks, namely in the identified zones at the higher altitudes; and 2) regeneration or sustainable utilisation of lands with low AGB or carbon stocks, dependent on the regeneration capacity of the vegetation. Low aboveground biomass densities can be found in the lowlands in burned areas, and in non-forest zones and production forests.
Spatial distribution of Cd and Cu in soils in Shenyang Zhangshi Irrigation Area (SZIA), China*
Sun, Li-na; Yang, Xiao-bo; Wang, Wen-qing; Ma, Li; Chen, Su
2008-01-01
Heavy metal contamination of soils, derived from sewage irrigation, mining and inappropriate utilization of various agrochemicals and pesticides, and so on, has been of wide concern in the last several decades. The Shenyang Zhangshi Irrigation Area (SZIA) in China is a representative area of heavy metal contamination of soils resulting from sewage irrigation for about 30 years. This study investigated the spatial distribution and temporal variation of soil cadmium (Cd) and copper (Cu) contamination in the SZIA. The soil samples were collected from the SZIA in 1990 and 2004; Cd and Cu in soils was analyzed and then the spatial distribution and temporal variation of Cd and Cu in soils were modeled using Kriging methods. The results show that long-term sewage irrigation had caused serious Cd and Cu contamination in soils. The mean and the maximum of soil Cd are markedly higher than the levels in second grade standard soil (LSGSS) in China, and the maximum of soil Cu is close to the LSGSS in China in 2004 and is more than the LSGSS in China in 1990. The contamination magnitude of soil Cd and the soil extent of Cd contamination had evidently increased since sewage irrigation ceased in 1992. The contamination magnitude of soil Cu and the soil extent of Cu contamination had evidently increased in topsoil, but obviously decresed in subsoil. The soil contamination of Cd and Cu was mainly related to Cd and Cu reactivation of contaminated sediments in Shenyang Xi River and the import of Cd and Cu during irrigation. The eluviation of Cd and Cu in contaminated topsoil with rainfall and irrigation water was another factor of temporal-spatial variability of Cd and Cu contamination in soils. PMID:18357631
Morales-Soto, Nydia; Dunham, Sage J B; Baig, Nameera F; Ellis, Joseph F; Madukoma, Chinedu S; Bohn, Paul W; Sweedler, Jonathan V; Shrout, Joshua D
2018-03-27
There is a general lack of understanding about how communities of bacteria respond to exogenous toxins such as antibiotics. Most of our understanding of community-level stress responses comes from the study of stationary biofilm communities. Although several community behaviors and production of specific biomolecules affecting biofilm development and associated behavior have been described for Pseudomonas aeruginosa and other bacteria, we have little appreciation for the production and dispersal of secreted metabolites within the 2D and 3D spaces they occupy as they colonize, spread, and grow on surfaces. Here we specifically studied the phenotypic responses and spatial variability of alkyl quinolones, including the Pseudomonas quinolone signal (PQS) and members of the alkyl hydroxyquinoline (AQNO) subclass, in P. aeruginosa plate-assay swarming communities. We found that PQS production was not a universal signaling response to antibiotics as tobramycin elicited an alkyl quinolone response while carbenicillin did not. We also found that PQS and AQNO profiles in response to tobramycin were markedly distinct and influenced these swarms on different spatial scales. The distribution of alkyl quinolones varied by several orders of magnitude within the same swarm. At some tobramycin exposures, P. aeruginosa swarms produced alkyl quinolones in the range of 150 µM PQS and 400 µM AQNO that accumulated as aggregates. Our collective findings show that the distribution of alkyl quinolones can vary by several orders of magnitude within the same swarming community. More notably, our results suggest that multiple intercellular signals acting on different spatial scales can be triggered by one common cue. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Farrington, Stephen P.
Systems, methods, and software for measuring the spatially variable relative dielectric permittivity of materials along a linear or otherwise configured sensor element, and more specifically the spatial variability of soil moisture in one dimension as inferred from the dielectric profile of the soil matrix surrounding a linear sensor element. Various methods provided herein combine advances in the processing of time domain reflectometry data with innovations in physical sensing apparatuses. These advancements enable high temporal (and thus spatial) resolution of electrical reflectance continuously along an insulated waveguide that is permanently emplaced in contact with adjacent soils. The spatially resolved reflectance ismore » directly related to impedance changes along the waveguide that are dominated by electrical permittivity contrast due to variations in soil moisture. Various methods described herein are thus able to monitor soil moisture in profile with high spatial resolution.« less
NASA Astrophysics Data System (ADS)
Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo
2017-03-01
The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the total flow variability in the response of the urban drainage systems to heavy rainfall events.
NASA Astrophysics Data System (ADS)
Estrada, Rafael; Harvey, Michel; Gosselin, Michel; Starr, Michel; Galbraith, Peter S.; Straneo, Fiammetta
2012-08-01
Zooplankton communities were examined for the first time in three different hydrographic regions of the Hudson Bay system (HBS) in early August to early September from 2003 to 2006. Sampling was conducted at 50 stations distributed along different transects located in Hudson Bay (HB), Hudson Strait (HS), and Foxe Basin (FB). Variations in zooplankton biomass, abundance, taxonomic composition, and diversity in relation to environmental variables were studied using multivariate techniques. During all sampling years, the total zooplankton biomass was on average four times lower in HB than in HS and FB. Clustering samples by their relative species compositions revealed no interannual variation in zooplankton community but showed a marked interregional variability between the three regions. Water column stratification explained the greatest proportion (25%) of this spatial variability. According to redundancy analysis (RDA), the zooplankton taxa that contribute most to the separation of the three regions are Microcalanus spp., Oithona similis, Oncaea borealis, Aeginopsis laurentii, Sagitta elegans, Fritillaria sp., and larvae of cnidaria, chaetognatha, and pteropoda in HB; hyperiid amphipods in FB; and Pseudocalanus spp. CI-CV, Calanus glacialis CI-CVI, Calanus finmarchicus CI-CVI, Calanus hyperboreus CV-CVI, Acartia longiremis CI-CV, Metridia longa N3-N6 CI-CIII CVIf, Eukrohnia hamata, larvae of echinodermata, mollusca, cirripedia, appendicularia, and polychaeta in the northwestern and southeastern HS transects. For the HB transect, the RDA analyzed allowed us to distinguish three regions (HB west, central, and east) with different environmental gradients and zooplankton assemblages, in particular higher concentration of Pseudocalanus spp. nauplii and CI-CVI, as well as benthic macrozooplankton and meroplankton larvae in western HB. In HS, Calanoid species (mainly C. finmarchicus and C. glacialis) were mostly observed at the north shore stations associated with the weakly stratified Arctic-North Atlantic waters coming from southwestern Davis Strait (inflow). In general, the RDA models tested among the HBS regions were very consistent with its general surface circulation pattern for summer conditions in terms of environmental variables and distinct zooplankton assemblages. Overall, zooplankton biomass and diversity indices (H‧, J‧, and S) were lower in the most stratified environment (i.e., HB) than in the deeper (FB) and more dynamic (HS) regions. The results of this work clearly show that the spatial differentiation and structure of the zooplankton communities are strongly influenced by the hydrodynamic conditions in the HBS that, trough their actions on temperature, salinity, stratification, mixing conditions and depth strata, lead to the spatial differentiation of these communities.
NASA Astrophysics Data System (ADS)
Feeley, T. C.; Wilson, L. F.; Underwood, S. J.
2008-11-01
Variations in spatial abundances, compositions, and textures of undercooled magmatic inclusions were determined in a glaciated Pleistocene lava dome (Mt. Helen; ~ 0.6 km 3) at the Lassen volcanic center (LVC), southernmost Cascades. Spatial variations were determined by point-counting at 86 locations separated by ~ 100 m on the dome. Major and trace element compositions of host rocks and inclusions at 12 locations along the flow length of the dome were obtained. Important results include the following. (1) Inclusion abundances range from 3-19 vol.%, with the highest values generally located along the little eroded northwestern margin and flow front of the dome. (2) Host rock compositions are markedly uniform across the dome (65.4 +/- 0.4 wt.% SiO 2) indicating that the degree of inclusion disaggregation was uniform, despite large spatial variations in inclusion abundances. (3) Inclusion sizes range from a maximum of ~ 1 m across to mm-sized crystal clots of phenocrysts plus adhering Ca-rich plagioclase microphenocrysts. (4) Inclusions have variable macroscopic textures indicating that partial undercooling both prior to and following entrapment in cooler dacitic host magma were important processes. (5) Inclusions are variably fractionated magmas with large variations in Ni (79-11 ppm) and Cr (87-7 ppm) contents that are lower than presumed mantle-derived melts. Furthermore, large ranges in incompatible trace elements indicate that inclusion compositions also reflect deep processes involving either melting of variable mantle source rocks or assimilation-fractional crystallization. (6) Inclusions are variably mixed magmas (56-61 wt.% SiO 2) that contain up to 50% host dacitic magma. (7) Correlations between Ni and Cr contents in hosts and inclusions from individual outcrops indicate that the effect of inclusion disaggregation and magma mingling on host dacitic magma was local (e.g., < 50 m). These features are interpreted to reflect protracted recharge of diverse composition mafic magmas into the base of a shallow magma reservoir containing a lower layer of compositionally evolving hybrid mafic magma and an upper layer of rhyodacitic magma. Complex interactions among magmas in the upper and lower layers resulted in formation of mafic inclusions by both pre- and post-entrapment undercooling mechanisms, followed by buoyant rise and accumulation near the roof of the reservoir. The main stage of inclusion disaggregation probably occurred in the conduit during eruptive ascent and largely ceased upon surface eruption. We infer that endogenous growth concentrated inclusions along the margins and top of the dome as more inclusion-poor dacite was progressively tapped from deeper regions of the reservoir.
The Variability of Neural Responses to Naturalistic Videos Change with Age and Sex
Petroni, Agustin; Langer, Nicolas; Milham, Michael P.
2018-01-01
Abstract Neural development is generally marked by an increase in the efficiency and diversity of neural processes. In a large sample (n = 114) of human children and adults with ages ranging from 5 to 44 yr, we investigated the neural responses to naturalistic video stimuli. Videos from both real-life classroom settings and Hollywood feature films were used to probe different aspects of attention and engagement. For all stimuli, older ages were marked by more variable neural responses. Variability was assessed by the intersubject correlation of evoked electroencephalographic responses. Young males also had less-variable responses than young females. These results were replicated in an independent cohort (n = 303). When interpreted in the context of neural maturation, we conclude that neural function becomes more variable with maturity, at least during the passive viewing of real-world stimuli. PMID:29379880
Using optimal transport theory to estimate transition probabilities in metapopulation dynamics
Nichols, Jonathan M.; Spendelow, Jeffrey A.; Nichols, James D.
2017-01-01
This work considers the estimation of transition probabilities associated with populations moving among multiple spatial locations based on numbers of individuals at each location at two points in time. The problem is generally underdetermined as there exists an extremely large number of ways in which individuals can move from one set of locations to another. A unique solution therefore requires a constraint. The theory of optimal transport provides such a constraint in the form of a cost function, to be minimized in expectation over the space of possible transition matrices. We demonstrate the optimal transport approach on marked bird data and compare to the probabilities obtained via maximum likelihood estimation based on marked individuals. It is shown that by choosing the squared Euclidean distance as the cost, the estimated transition probabilities compare favorably to those obtained via maximum likelihood with marked individuals. Other implications of this cost are discussed, including the ability to accurately interpolate the population's spatial distribution at unobserved points in time and the more general relationship between the cost and minimum transport energy.
Svenning, J.-C.; Engelbrecht, B.M.J.; Kinner, D.A.; Kursar, T.A.; Stallard, R.F.; Wright, S.J.
2006-01-01
We used regression models and information-theoretic model selection to assess the relative importance of environment, local dispersal and historical contingency as controls of the distributions of 26 common plant species in tropical forest on Barro Colorado Island (BCI), Panama. We censused eighty-eight 0.09-ha plots scattered across the landscape. Environmental control, local dispersal and historical contingency were represented by environmental variables (soil moisture, slope, soil type, distance to shore, old-forest presence), a spatial autoregressive parameter (??), and four spatial trend variables, respectively. We built regression models, representing all combinations of the three hypotheses, for each species. The probability that the best model included the environmental variables, spatial trend variables and ?? averaged 33%, 64% and 50% across the study species, respectively. The environmental variables, spatial trend variables, ??, and a simple intercept model received the strongest support for 4, 15, 5 and 2 species, respectively. Comparing the model results to information on species traits showed that species with strong spatial trends produced few and heavy diaspores, while species with strong soil moisture relationships were particularly drought-sensitive. In conclusion, history and local dispersal appeared to be the dominant controls of the distributions of common plant species on BCI. Copyright ?? 2006 Cambridge University Press.
Soil variability in engineering applications
NASA Astrophysics Data System (ADS)
Vessia, Giovanna
2014-05-01
Natural geomaterials, as soils and rocks, show spatial variability and heterogeneity of physical and mechanical properties. They can be measured by in field and laboratory testing. The heterogeneity concerns different values of litho-technical parameters pertaining similar lithological units placed close to each other. On the contrary, the variability is inherent to the formation and evolution processes experienced by each geological units (homogeneous geomaterials on average) and captured as a spatial structure of fluctuation of physical property values about their mean trend, e.g. the unit weight, the hydraulic permeability, the friction angle, the cohesion, among others. The preceding spatial variations shall be managed by engineering models to accomplish reliable designing of structures and infrastructures. Materon (1962) introduced the Geostatistics as the most comprehensive tool to manage spatial correlation of parameter measures used in a wide range of earth science applications. In the field of the engineering geology, Vanmarcke (1977) developed the first pioneering attempts to describe and manage the inherent variability in geomaterials although Terzaghi (1943) already highlighted that spatial fluctuations of physical and mechanical parameters used in geotechnical designing cannot be neglected. A few years later, Mandelbrot (1983) and Turcotte (1986) interpreted the internal arrangement of geomaterial according to Fractal Theory. In the same years, Vanmarcke (1983) proposed the Random Field Theory providing mathematical tools to deal with inherent variability of each geological units or stratigraphic succession that can be resembled as one material. In this approach, measurement fluctuations of physical parameters are interpreted through the spatial variability structure consisting in the correlation function and the scale of fluctuation. Fenton and Griffiths (1992) combined random field simulation with the finite element method to produce the Random Finite Element Method (RFEM). This method has been used to investigate the random behavior of soils in the context of a variety of classical geotechnical problems. Afterward, some following studies collected the worldwide variability values of many technical parameters of soils (Phoon and Kulhawy 1999a) and their spatial correlation functions (Phoon and Kulhawy 1999b). In Italy, Cherubini et al. (2007) calculated the spatial variability structure of sandy and clayey soils from the standard cone penetration test readings. The large extent of the worldwide measured spatial variability of soils and rocks heavily affects the reliability of geotechnical designing as well as other uncertainties introduced by testing devices and engineering models. So far, several methods have been provided to deal with the preceding sources of uncertainties in engineering designing models (e.g. First Order Reliability Method, Second Order Reliability Method, Response Surface Method, High Dimensional Model Representation, etc.). Nowadays, the efforts in this field have been focusing on (1) measuring spatial variability of different rocks and soils and (2) developing numerical models that take into account the spatial variability as additional physical variable. References Cherubini C., Vessia G. and Pula W. 2007. Statistical soil characterization of Italian sites for reliability analyses. Proc. 2nd Int. Workshop. on Characterization and Engineering Properties of Natural Soils, 3-4: 2681-2706. Griffiths D.V. and Fenton G.A. 1993. Seepage beneath water retaining structures founded on spatially random soil, Géotechnique, 43(6): 577-587. Mandelbrot B.B. 1983. The Fractal Geometry of Nature. San Francisco: W H Freeman. Matheron G. 1962. Traité de Géostatistique appliquée. Tome 1, Editions Technip, Paris, 334 p. Phoon K.K. and Kulhawy F.H. 1999a. Characterization of geotechnical variability. Can Geotech J, 36(4): 612-624. Phoon K.K. and Kulhawy F.H. 1999b. Evaluation of geotechnical property variability. Can Geotech J, 36(4): 625-639. Terzaghi K. 1943. Theoretical Soil Mechanics. New York: John Wiley and Sons. Turcotte D.L. 1986. Fractals and fragmentation. J Geophys Res, 91: 1921-1926. Vanmarcke E.H. 1977. Probabilistic modeling of soil profiles. J Geotech Eng Div, ASCE, 103: 1227-1246. Vanmarcke E.H. 1983. Random fields: analysis and synthesis. MIT Press, Cambridge.
Spatial heterogeneity of within-stream methane concentrations
Crawford, John T.; Loken, Luke C.; West, William E.; Crary, Benjamin; Spawn, Seth A.; Gubbins, Nicholas; Jones, Stuart E.; Striegl, Robert G.; Stanley, Emily H.
2017-01-01
Streams, rivers, and other freshwater features may be significant sources of CH4 to the atmosphere. However, high spatial and temporal variabilities hinder our ability to understand the underlying processes of CH4 production and delivery to streams and also challenge the use of scaling approaches across large areas. We studied a stream having high geomorphic variability to assess the underlying scale of CH4 spatial variability and to examine whether the physical structure of a stream can explain the variation in surface CH4. A combination of high-resolution CH4 mapping, a survey of groundwater CH4 concentrations, quantitative analysis of methanogen DNA, and sediment CH4 production potentials illustrates the spatial and geomorphic controls on CH4 emissions to the atmosphere. We observed significant spatial clustering with high CH4 concentrations in organic-rich stream reaches and lake transitions. These sites were also enriched in the methane-producing mcrA gene and had highest CH4 production rates in the laboratory. In contrast, mineral-rich reaches had significantly lower concentrations and had lesser abundances of mcrA. Strong relationships between CH4and the physical structure of this aquatic system, along with high spatial variability, suggest that future investigations will benefit from viewing streams as landscapes, as opposed to ecosystems simply embedded in larger terrestrial mosaics. In light of such high spatial variability, we recommend that future workers evaluate stream networks first by using similar spatial tools in order to build effective sampling programs.
Parallel structure among environmental gradients and three trophic levels in a subarctic estuary
Speckman, Suzann G.; Piatt, John F.; Minte-Vera, C. V.; Parrish, Julia K.
2005-01-01
We assessed spatial and temporal variability in the physical environment of a subarctic estuary, and examined concurrent patterns of chlorophyll α abundance (fluorescence), and zooplankton and forage fish community structure. Surveys were conducted in lower Cook Inlet, Alaska, during late July and early August from 1997 through 1999. Principle components analysis (PCA) revealed that spatial heterogeneity in the physical oceanographic environment of lower Cook Inlet could be modeled as three marine-estuarine gradients characterized by temperature, salinity, bottom depth, and turbidity. The gradients persisted from 1997 through 1999, and PCA explained 68% to 92% of the variance in physical oceanography for each gradient-year combination. Correlations between chlorophyll α abundance and distribution and the PCA axes were weak. Chlorophyll was reduced by turbidity, and low levels occurred in areas with high levels of suspended sediments. Detrended correspondence analysis (DCA) was used to order the sample sites based on species composition and to order the zooplankton and forage fish taxa based on similarities among sample sites for each gradient-year. Correlations between the structure of the physical environment (PCA axis 1) and zooplankton community structure (DCA axis 1) were strong (r = 0.43-0.86) in all years for the three marine-estuarine gradients, suggesting that zooplankton community composition was structured by the physical environment. The physical environment (PCA) and forage fish community structure (DCA) were weakly correlated in all years along Gradient 2, defined by halocline intensity and surface temperature and salinity, even though these physical variables were more important for defining zooplankton habitats. However, the physical environment (PCA) and forage fish community structure (DCA) were strongly correlated along the primary marine-estuarine gradient (#1) in 1997 (r = 0.87) and 1998 (r = 0.82). The correlation was poor (r = 0.32) in 1999, when fish community structure changed markedly in lower Cook Inlet. Capelin (Mallotus villosus), walleye pollock (Theragra chalcogramma), and arrowtooth flounder (Atheresthes stomias) were caught farther north than in previous years. Waters were significantly colder and more saline in 1999, a La Nina year, than in other years of the study. Interannual fluctuations in environmental conditions in lower Cook Inlet did not have substantial effects on zooplankton community structure, although abundance of individual taxa varied significantly. The abundance and distribution of chlorophyll α, zooplankton and forage fish were affected much more by spatial variability in physical oceanography than by interannual variability. Our examination of physical-biological linkages in lower Cook Inlet supports the concept of "bottom-up control," i.e., that variability in the physical environment structures higher trophic-level communities by influencing their distribution and abundance across space.
Parallel structure among environmental gradients and three trophic levels in a subarctic estuary
NASA Astrophysics Data System (ADS)
Speckman, Suzann G.; Piatt, John F.; Minte-Vera, Carolina V.; Parrish, Julia K.
2005-07-01
We assessed spatial and temporal variability in the physical environment of a subarctic estuary, and examined concurrent patterns of chlorophyll α abundance (fluorescence), and zooplankton and forage fish community structure. Surveys were conducted in lower Cook Inlet, Alaska, during late July and early August from 1997 through 1999. Principle components analysis (PCA) revealed that spatial heterogeneity in the physical oceanographic environment of lower Cook Inlet could be modeled as three marine-estuarine gradients characterized by temperature, salinity, bottom depth, and turbidity. The gradients persisted from 1997 through 1999, and PCA explained 68% to 92% of the variance in physical oceanography for each gradient-year combination. Correlations between chlorophyll α abundance and distribution and the PCA axes were weak. Chlorophyll was reduced by turbidity, and low levels occurred in areas with high levels of suspended sediments. Detrended correspondence analysis (DCA) was used to order the sample sites based on species composition and to order the zooplankton and forage fish taxa based on similarities among sample sites for each gradient-year. Correlations between the structure of the physical environment (PCA axis 1) and zooplankton community structure (DCA axis 1) were strong ( r = 0.43-0.86) in all years for the three marine-estuarine gradients, suggesting that zooplankton community composition was structured by the physical environment. The physical environment (PCA) and forage fish community structure (DCA) were weakly correlated in all years along Gradient 2, defined by halocline intensity and surface temperature and salinity, even though these physical variables were more important for defining zooplankton habitats. However, the physical environment (PCA) and forage fish community structure (DCA) were strongly correlated along the primary marine-estuarine gradient (#1) in 1997 ( r = 0.87) and 1998 ( r = 0.82). The correlation was poor ( r = 0.32) in 1999, when fish community structure changed markedly in lower Cook Inlet. Capelin ( Mallotus villosus), walleye pollock ( Theragra chalcogramma), and arrowtooth flounder ( Atheresthes stomias) were caught farther north than in previous years. Waters were significantly colder and more saline in 1999, a La Niña year, than in other years of the study. Interannual fluctuations in environmental conditions in lower Cook Inlet did not have substantial effects on zooplankton community structure, although abundance of individual taxa varied significantly. The abundance and distribution of chlorophyll α, zooplankton and forage fish were affected much more by spatial variability in physical oceanography than by interannual variability. Our examination of physical-biological linkages in lower Cook Inlet supports the concept of “bottom-up control,” i.e., that variability in the physical environment structures higher trophic-level communities by influencing their distribution and abundance across space.
Quantifying Landscape Spatial Pattern: What Is the State of the Art?
Eric J. Gustafson
1998-01-01
Landscape ecology is based on the premise that there are strong links between ecological pattern and ecological function and process. Ecological systems are spatially heterogeneous, exhibiting consid-erable complexity and variability in time and space. This variability is typically represented by categorical maps or by a collection of samples taken at specific spatial...
Nolen, Matthew S.; Magoulick, Daniel D.; DiStefano, Robert J.; Imhoff, Emily M.; Wagner, Brian K.
2014-01-01
We found that a range of environmental variables were important in predicting crayfish distribution and abundance at multiple spatial scales and their importance was species-, response variable- and scale dependent. We would encourage others to examine the influence of spatial scale on species distribution and abundance patterns.
ERIC Educational Resources Information Center
Rakitin, Brian C.
2005-01-01
Five experiments examined the relations between timing and attention using a choice time production task in which the latency of a spatial choice response is matched to a target interval (3 or 5 s). Experiments 1 and 2 indicated that spatial stimulus-response incompatibility increased nonscalar timing variability without affecting timing accuracy…
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.
NASA Astrophysics Data System (ADS)
Comas, Carles; del Castillo, Jorge; Voltas, Jordi; Ferrio, Juan Pedro
2013-04-01
The stable isotope composition of xylem water reflects has been used to assess inter-specific differences in uptake patterns, revealing synergistic and competition processes in the use of water resources (see e.g. Dawson et al. 1993). However, there is a lack of detailed studies on spatial and temporal variability of inter- and intra-specific competition within forest stands. In this context, the aim of this work was to compare the isotope composition of xylem water (δ18O , δ2H) in two common Mediterranean tree species, Quercus ilex L. and Pinus halepensis Mill, in order to understand their water uptake patterns throughout the growing season. In addition, we analyze the spatial variability of xylem water, to get insight into inter-specific strategies employed to cope with drought and the interaction between the individuals. Our first hypothesis was that both species used different strategies to cope with drought by uptaking water at different depths; and our second hypothesis was that individual trees would behave in different manner according to the distance to their neighbours as well as to whether the neighbour is from one species or the other. The study was performed in a mixed stand where both species are nearly co-dominant, adding up to a total of 33 oaks and 77 pines (plot area= 893 m2). We sampled sun-exposed branches of each tree six times over the growing season, and extracted the xylem water with a cryogenic trap. The isotopic composition of the water was determined using a Picarro Water Analizer L2130-i. Tree mapping for spatial analysis was done using a high resolution GPS technology (Trimble GeoExplorer 6000). For the spatial analysis, we used the pair-correlation function to study intra-specific tree configuration and the bivariate pair correlation function to analyse the inter-specific spatial configurations (Stoyan et al 1995). Moreover, the isotopic composition of xylem water was assumed to be a mark associated to each tree and analysed as a marked point pattern. Preliminary results showed significant differences between species, but only during drought periods, confirming our first hypothesis. For example, in late-summer and early-autumn, the values for Q. Ilex (δ18O= -4.9 ±0.3 permille, δ2H=-53.5±1.2 permille) were significantly lower than for P. halepensis (δ18O= -1.1±0.2 permille, δ2H = -27.8±0.8 permille), pointing to the use of deeper soil layers by Q. ilex. On the other hand, point process analyses showed intra-specific interactions, whereas inter-specific interactions were not detected. Acknowledgements: This work was funded by MC-ERG-246725 (FP7, EU) and AGL 2012-40039-C02-02 (MINECO, Spain). JdC and JPF are supported by FPI fellowship (MCINN) and Ramón y Cajal programme (RYC-2008-02050, MINECO), respectively. References Dawson TE et al. 1993. In: Ehleringer JR, Hall AE, Farquhar GD (eds) Stable isotopes and plant carbon-water relations. Academic Press, Inc. IPCC. 2007 Climate Change 2007: The Physical Science Basis. Cambridge UP. Stoyan D et al. 1995. Stochastic Geometry and its Applications. Wiley&Sons.
Fukaya, Keiichi; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi
2014-11-01
Explanations for why population dynamics vary across the range of a species reflect two contrasting hypotheses: (i) temporal variability of populations is larger in the centre of the range compared to the margins because overcompensatory density dependence destabilizes population dynamics and (ii) population variability is larger near the margins, where populations are more susceptible to environmental fluctuations. In both of these hypotheses, positions within the range are assumed to affect population variability. In contrast, the fact that population variability is often related to mean population size implies that the spatial structure of the population size within the range of a species may also be a useful predictor of the spatial variation in temporal variability of population size over the range of the species. To explore how population temporal variability varies spatially and the underlying processes responsible for the spatial variation, we focused on the intertidal barnacle Chthamalus dalli and examined differences in its population dynamics along the tidal levels it inhabits. Changes in coverage of barnacle populations were monitored for 10.5 years at 25 plots spanning the elevational range of this species. Data were analysed by fitting a population dynamics model to estimate the effects of density-dependent and density-independent processes on population growth. We also examined the temporal mean-variance relationship of population size with parameters estimated from the population dynamics model. We found that the relative variability of populations tended to increase from the centre of the elevational range towards the margins because of an increase in the magnitude of stochastic fluctuations of growth rates. Thus, our results supported hypothesis (2). We also found that spatial variations in temporal population variability were well characterized by Taylor's power law, the relative population variability being inversely related to the mean population size. Results suggest that understanding the population dynamics of a species over its range may be facilitated by taking the spatial structure of population size into account as well as by considering changes in population processes as a function of position within the range of the species. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.
Spread of plague among black-tailed prairie dogs is associated with colony spatial characteristics
Johnson, T.L.; Cully, J.F.; Collinge, S.K.; Ray, C.; Frey, C.M.; Sandercock, B.K.
2011-01-01
Sylvatic plague (Yersinia pestis) is an exotic pathogen that is highly virulent in black-tailed prairie dogs (Cynomys ludovicianus) and causes widespread colony losses and individual mortality rates >95%. We investigated colony spatial characteristics that may influence inter-colony transmission of plague at 3 prairie dog colony complexes in the Great Plains. The 4 spatial characteristics we considered include: colony size, Euclidean distance to nearest neighboring colony, colony proximity index, and distance to nearest drainage (dispersal) corridor. We used multi-state mark-recapture models to determine the relationship between these colony characteristics and probability of plague transmission among prairie dog colonies. Annual mapping of colonies and mark-recapture analyses of disease dynamics in natural colonies led to 4 main results: 1) plague outbreaks exhibited high spatial and temporal variation, 2) the site of initiation of epizootic plague may have substantially influenced the subsequent inter-colony spread of plague, 3) the long-term effect of plague on individual colonies differed among sites because of how individuals and colonies were distributed, and 4) colony spatial characteristics were related to the probability of infection at all sites although the relative importance and direction of relationships varied among sites. Our findings suggest that conventional prairie dog conservation management strategies, including promoting large, highly connected colonies, may need to be altered in the presence of plague. ?? 2011 The Wildlife Society.
Hogerwerf, Lenny; Holstege, Manon M C; Benincà, Elisa; Dijkstra, Frederika; van der Hoek, Wim
2017-07-26
Human psittacosis is a highly under diagnosed zoonotic disease, commonly linked to psittacine birds. Psittacosis in birds, also known as avian chlamydiosis, is endemic in poultry, but the risk for people living close to poultry farms is unknown. Therefore, our study aimed to explore the temporal and spatial patterns of human psittacosis infections and identify possible associations with poultry farming in the Netherlands. We analysed data on 700 human cases of psittacosis notified between 01-01-2000 and 01-09-2015. First, we studied the temporal behaviour of psittacosis notifications by applying wavelet analysis. Then, to identify possible spatial patterns, we applied spatial cluster analysis. Finally, we investigated the possible spatial association between psittacosis notifications and data on the Dutch poultry sector at municipality level using a multivariable model. We found a large spatial cluster that covered a highly poultry-dense area but additional clusters were found in areas that had a low poultry density. There were marked geographical differences in the awareness of psittacosis and the amount and the type of laboratory diagnostics used for psittacosis, making it difficult to draw conclusions about the correlation between the large cluster and poultry density. The multivariable model showed that the presence of chicken processing plants and slaughter duck farms in a municipality was associated with a higher rate of human psittacosis notifications. The significance of the associations was influenced by the inclusion or exclusion of farm density in the model. Our temporal and spatial analyses showed weak associations between poultry-related variables and psittacosis notifications. Because of the low number of psittacosis notifications available for analysis, the power of our analysis was relative low. Because of the exploratory nature of this research, the associations found cannot be interpreted as evidence for airborne transmission of psittacosis from poultry to the general population. Further research is needed to determine the prevalence of C. psittaci in Dutch poultry. Also, efforts to promote PCR-based testing for C. psittaci and genotyping for source tracing are important to reduce the diagnostic deficit, and to provide better estimates of the human psittacosis burden, and the possible role of poultry.
ERIC Educational Resources Information Center
Smith, Linda C., Ed.; Gluck, Myke, Ed.
This document assembles conference papers which focus on how electronic technologies are creating new ways of meeting user needs for spatial and cartographic information. Contents include: (1) "Mapping Technology in Transition" (Mark Monmonier); (2) "Cataloging Planetospatial Data in Digital Form: Old Wine, New Bottles--New Wine,…
ERIC Educational Resources Information Center
Tremblay, Sebastien; Saint-Aubin, Jean
2009-01-01
In the present study, the authors offer a window onto the mechanisms that drive the Hebb repetition effect through the analysis of eye movement and recall performance. In a spatial serial recall task in which sequences of dots are to be remembered in order, when one particular series is repeated every 4 trials, memory performance markedly improves…
NASA Astrophysics Data System (ADS)
Brustolin, Marco C.; Thomas, Micheli C.; Mafra, Luiz L.; Lana, Paulo da Cunha
2014-08-01
Foraging macrofauna, such as the sand dollar Encope emarginata, can modify sediment properties and affect spatial distribution patterns of microphytobenthos and meiobenthos at different spatial scales. We adopted a spatial hierarchical approach composed of five spatial levels (km, 100 s m, 10 s m, 1 s m and cm) to describe variation patterns of microphytobenthos, meiobenthos and sediment variables in shallow subtidal regions in the subtropical Paranaguá Bay (Southern Brazil) with live E. emarginata (LE), dead E. emarginata (only skeletons - (DE), and no E. emarginata (WE). The overall structure of microphytobenthos and meiofauna was always less variable at WE and much of variation at the scale of 100 s m was related to variability within LE and DE, due to foraging activities or to the presence of shell hashes. Likewise, increased variability in chlorophyll-a and phaeopigment contents was observed among locations within LE, although textural parameters of sediment varied mainly at smaller scales. Variations within LE were related to changes on the amount and quality of food as a function of sediment heterogeneity induced by the foraging behavior of sand dollars. We provide strong evidence that top-down effects related to the occurrence of E. emarginata act in synergy with bottom-up structuring related to hydrodynamic processes in determining overall benthic spatial variability. Conversely, species richness is mainly influenced by environmental heterogeneity at small spatial scales (centimeters to meters), which creates a mosaic of microhabitats.
NASA Astrophysics Data System (ADS)
Szymanowski, Mariusz; Kryza, Maciej
2017-02-01
Our study examines the role of auxiliary variables in the process of spatial modelling and mapping of climatological elements, with air temperature in Poland used as an example. The multivariable algorithms are the most frequently applied for spatialization of air temperature, and their results in many studies are proved to be better in comparison to those obtained by various one-dimensional techniques. In most of the previous studies, two main strategies were used to perform multidimensional spatial interpolation of air temperature. First, it was accepted that all variables significantly correlated with air temperature should be incorporated into the model. Second, it was assumed that the more spatial variation of air temperature was deterministically explained, the better was the quality of spatial interpolation. The main goal of the paper was to examine both above-mentioned assumptions. The analysis was performed using data from 250 meteorological stations and for 69 air temperature cases aggregated on different levels: from daily means to 10-year annual mean. Two cases were considered for detailed analysis. The set of potential auxiliary variables covered 11 environmental predictors of air temperature. Another purpose of the study was to compare the results of interpolation given by various multivariable methods using the same set of explanatory variables. Two regression models: multiple linear (MLR) and geographically weighted (GWR) method, as well as their extensions to the regression-kriging form, MLRK and GWRK, respectively, were examined. Stepwise regression was used to select variables for the individual models and the cross-validation method was used to validate the results with a special attention paid to statistically significant improvement of the model using the mean absolute error (MAE) criterion. The main results of this study led to rejection of both assumptions considered. Usually, including more than two or three of the most significantly correlated auxiliary variables does not improve the quality of the spatial model. The effects of introduction of certain variables into the model were not climatologically justified and were seen on maps as unexpected and undesired artefacts. The results confirm, in accordance with previous studies, that in the case of air temperature distribution, the spatial process is non-stationary; thus, the local GWR model performs better than the global MLR if they are specified using the same set of auxiliary variables. If only GWR residuals are autocorrelated, the geographically weighted regression-kriging (GWRK) model seems to be optimal for air temperature spatial interpolation.
Spatial correlation of probabilistic earthquake ground motion and loss
Wesson, R.L.; Perkins, D.M.
2001-01-01
Spatial correlation of annual earthquake ground motions and losses can be used to estimate the variance of annual losses to a portfolio of properties exposed to earthquakes A direct method is described for the calculations of the spatial correlation of earthquake ground motions and losses. Calculations for the direct method can be carried out using either numerical quadrature or a discrete, matrix-based approach. Numerical results for this method are compared with those calculated from a simple Monte Carlo simulation. Spatial correlation of ground motion and loss is induced by the systematic attenuation of ground motion with distance from the source, by common site conditions, and by the finite length of fault ruptures. Spatial correlation is also strongly dependent on the partitioning of the variability, given an event, into interevent and intraevent components. Intraevent variability reduces the spatial correlation of losses. Interevent variability increases spatial correlation of losses. The higher the spatial correlation, the larger the variance in losses to a port-folio, and the more likely extreme values become. This result underscores the importance of accurately determining the relative magnitudes of intraevent and interevent variability in ground-motion studies, because of the strong impact in estimating earthquake losses to a portfolio. The direct method offers an alternative to simulation for calculating the variance of losses to a portfolio, which may reduce the amount of calculation required.
Radinger, Johannes; Wolter, Christian; Kail, Jochem
2015-01-01
Habitat suitability and the distinct mobility of species depict fundamental keys for explaining and understanding the distribution of river fishes. In recent years, comprehensive data on river hydromorphology has been mapped at spatial scales down to 100 m, potentially serving high resolution species-habitat models, e.g., for fish. However, the relative importance of specific hydromorphological and in-stream habitat variables and their spatial scales of influence is poorly understood. Applying boosted regression trees, we developed species-habitat models for 13 fish species in a sand-bed lowland river based on river morphological and in-stream habitat data. First, we calculated mean values for the predictor variables in five distance classes (from the sampling site up to 4000 m up- and downstream) to identify the spatial scale that best predicts the presence of fish species. Second, we compared the suitability of measured variables and assessment scores related to natural reference conditions. Third, we identified variables which best explained the presence of fish species. The mean model quality (AUC = 0.78, area under the receiver operating characteristic curve) significantly increased when information on the habitat conditions up- and downstream of a sampling site (maximum AUC at 2500 m distance class, +0.049) and topological variables (e.g., stream order) were included (AUC = +0.014). Both measured and assessed variables were similarly well suited to predict species’ presence. Stream order variables and measured cross section features (e.g., width, depth, velocity) were best-suited predictors. In addition, measured channel-bed characteristics (e.g., substrate types) and assessed longitudinal channel features (e.g., naturalness of river planform) were also good predictors. These findings demonstrate (i) the applicability of high resolution river morphological and instream-habitat data (measured and assessed variables) to predict fish presence, (ii) the importance of considering habitat at spatial scales larger than the sampling site, and (iii) that the importance of (river morphological) habitat characteristics differs depending on the spatial scale. PMID:26569119
NASA Astrophysics Data System (ADS)
Oster, J. L.; Weisman, I. E.; Sharp, W. D.; Ibarra, D. E.
2017-12-01
The synthesis of hydrologically sensitive proxy records across western North America reveals spatial patterns of variability that persist, with some variation, over multiple temporal scales. For example, tree ring records from the last century highlight a distinct north-south dipole pattern in the response of regional precipitation anomalies to ENSO and the PDO, while a similar dipole pattern of wet and dry precipitation anomalies developed across the region in response to climate forcing at the Last Glacial Maximum (LGM). Hydrologically sensitive proxy records from the intervening transition zone can shed light on the stationarity and spatial scale of this pattern over time. Here we present records of δ18O and δ13C from a Lake Shasta Caverns stalagmite (LSC3) from Northern California that grew from 36 to 14 ka. This cave, located at 40.8°N, is situated within the transition zone and is well-positioned to enhance our understanding of regional precipitation patterns and moisture transport variability during the last glacial period and deglaciation. Six years of weekly rain isotope data indicate that varying atmospheric temperatures and moisture sources are primary controls on δ18O in Northern California precipitation. Increased δ18O and δ13C in LSC3 and slower stalagmite growth rates during MIS 2 suggest increased subtropical moisture but also dry conditions in Northern California. The δ13C record displays distinct millennial-scale oscillations during MIS 3, suggesting drier conditions also occurred during interstadials associated with Dansgaard-Oeschger cycles. The LSC3 δ18O record documents changes synchronous with δ18O in the Fort Stanton stalagmite in New Mexico, though sometimes in phase (e.g. during Heinrich Stadial 1; HS1) and sometimes anti-phased (e.g. during the Bölling-Alleröd). Likewise, the LSC3 δ13C record suggests a transition from wet to drier conditions during HS1 in marked contrast to many more southerly records that indicate wetter conditions later in HS1. These comparisons show that changes in Northern California climate were both in and out of phase with hydroclimate variations occurring to the south and southeast. Thus, the LSC3 record refines our understanding of spatial patterns of hydroclimatic change in western North America.
NASA Astrophysics Data System (ADS)
Zhao, Yongcun; Xu, Xianghua; Darilek, Jeremy Landon; Huang, Biao; Sun, Weixia; Shi, Xuezheng
2009-05-01
Topsoil samples (0-20 cm) ( n = 237) were collected from Rugao County, China. Geostatistical variogram analysis, sequential Gaussian simulation (SGS), and principal component (PC) analysis were applied to assess spatial variability of soil nutrients, identify the possible areas of nutrient deficiency, and explore spatial scale of variability of soil nutrients in the county. High variability of soil nutrient such as soil organic matter (SOM), total nitrogen (TN), available P, K, Fe, Mn, Cu, Zn, and B concentrations were observed. Soil nutrient properties displayed significant differences in their spatial structures, with available Cu having strong spatial dependence, SOM and available P having weak spatial dependence, and other nutrient properties having moderate spatial dependence. The soil nutrient deficiency, defined here as measured nutrient concentrations which do not meet the advisory threshold values specific to the county for dominant crops, namely rice, wheat, and rape seeds, was observed in available K and Zn, and the deficient areas covered 38 and 11%, respectively. The first three PCs of the nine soil nutrient properties explained 62.40% of the total variance. TN and SOM with higher loadings on PC1 are closely related to soil texture derived from different parent materials. The PC2 combined intermediate response variables such as available Zn and P that are likely to be controlled by land use and soil pH. Available B has the highest loading on PC3 and its variability of concentrations may be primarily ascribed to localized anthropogenic influence. The amelioration of soil physical properties (i.e. soil texture) and soil pH may improve the availability of soil nutrients and the sustainability of the agricultural system of Rugao County.
Failure criterion for materials with spatially correlated mechanical properties
NASA Astrophysics Data System (ADS)
Faillettaz, J.; Or, D.
2015-03-01
The role of spatially correlated mechanical elements in the failure behavior of heterogeneous materials represented by fiber bundle models (FBMs) was evaluated systematically for different load redistribution rules. Increasing the range of spatial correlation for FBMs with local load sharing is marked by a transition from ductilelike failure characteristics into brittlelike failure. The study identified a global failure criterion based on macroscopic properties (external load and cumulative damage) that is independent of spatial correlation or load redistribution rules. This general metric could be applied to assess the mechanical stability of complex and heterogeneous systems and thus provide an important component for early warning of a class of geophysical ruptures.
Conflict resolved: On the role of spatial attention in reading and color naming tasks.
Robidoux, Serje; Besner, Derek
2015-12-01
The debate about whether or not visual word recognition requires spatial attention has been marked by a conflict: the results from different tasks yield different conclusions. Experiments in which the primary task is reading based show no evidence that unattended words are processed, whereas when the primary task is color identification, supposedly unattended words do affect processing. However, the color stimuli used to date does not appear to demand as much spatial attention as explicit word reading tasks. We first identify a color stimulus that requires as much spatial attention to identify as does a word. We then demonstrate that when spatial attention is appropriately captured, distractor words in unattended locations do not affect color identification. We conclude that there is no word identification without spatial attention.
Surface laser marking optimization using an experimental design approach
NASA Astrophysics Data System (ADS)
Brihmat-Hamadi, F.; Amara, E. H.; Lavisse, L.; Jouvard, J. M.; Cicala, E.; Kellou, H.
2017-04-01
Laser surface marking is performed on a titanium substrate using a pulsed frequency doubled Nd:YAG laser ( λ= 532 nm, τ pulse=5 ns) to process the substrate surface under normal atmospheric conditions. The aim of the work is to investigate, following experimental and statistical approaches, the correlation between the process parameters and the response variables (output), using a Design of Experiment method (DOE): Taguchi methodology and a response surface methodology (RSM). A design is first created using MINTAB program, and then the laser marking process is performed according to the planned design. The response variables; surface roughness and surface reflectance were measured for each sample, and incorporated into the design matrix. The results are then analyzed and the RSM model is developed and verified for predicting the process output for the given set of process parameters values. The analysis shows that the laser beam scanning speed is the most influential operating factor followed by the laser pumping intensity during marking, while the other factors show complex influences on the objective functions.
Temporal and spatial characteristics of annual and seasonal rainfall in Malawi
NASA Astrophysics Data System (ADS)
Ngongondo, Cosmo; Xu, Chong-Yu; Gottschalk, Lars; Tallaksen, Lena M.; Alemaw, Berhanu
2010-05-01
An understanding of the temporal and spatial characteristics of rainfall is central to water resources planning and management. However, such information is often limited in many developing countries like Malawi. In an effort to bridge the information gap, this study examined the temporal and spatial charecteristics of rainfall in Malawi. Rainfall readings from 42 stations across Malawi from 1960 to 2006 were analysed at monthly, annual and seasonal scales. The Malawian rainfall season lasts from November to April. The data were firstly subjected to quality checks through the cumulative deviations test and the Standard Normal Homogeinity Test (SNHT). Monthly distribution in a typical year, called heterogeneity, was investigated using the Precipitation Concentration Index (PCI). Further, normalized precipitation anomaly series of annual rainfall series (AR) and the PCI (APCI) were used to test for interannual rainfall variability. Spatial variability was characterised by fitting the Spatial Correlation function (SCF). The nonparametric Mann-Kendall statistic was used to investigate the temporal trends of the various rainfall variables. The results showed that 40 of the stations passed both data quality tests. For the two stations that failed, the data were adjusted using nearby stations. Annual and seasonal rainfall were found to be characterised by high spatial variation. The country mean annual rainfall was 1095 mm with mean interannual variability of 26%. The highland areas to the north and southeast of the country exhibited the highest rainfall and lowest interannual variability. Lowest rainfall coupled with high interannual variability was found in the Lower Shire basin, in the southern part of Malawi. This simillarity is the pattern of annual and seasonal rainfall should be expected because all stations had over 90% of their observed annual rainfall in the six month period between November and April. Monthly rainfall was found to be highly variable both temporally and spatially. None of the stations have stable monthly rainfall regimes (mean PCI of less than 10). Stations with the highest mean rainfall were found to have a lower interannual variability. The rainfall stations showed low spatial correlations for annual, monthly as well as seasonal timescales indicating that the data may not be suitable for spatial interpolation. However, some structure (i.e. lower correlation with distance) could be observed when aggregating the data at 50 mile intervals. The annual and seasonal rainfall series were dominated by negative trends. The spatial distribution of the trends can be described as heterogeneous, although most of the stations in the southern region have negative trends. At the monthly timescale, 37 of the stations show a negative trend with four of the stations, all in the south, showing significant negative trends. On the other hand, only 5 stations show positive trends with only one significant trend in the south. Keywords: Malawi, rainfall trends, spatial variation
NASA Astrophysics Data System (ADS)
Vanwalleghem, T.; Román, A.; Giraldez, J. V.
2016-12-01
There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of a geostatistical versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.
Spatial variation in attributable risks.
Congdon, Peter
2015-01-01
The attributable risk (AR) measures the contribution of a particular risk factor to a disease, and allows estimation of disease rates specific to that risk. While previous studies consider variability in ARs over demographic categories, this paper considers the extent of spatial variability in ARs estimated from multilevel data with confounders both at individual and geographic levels. A case study considers the AR for diabetes in relation to elevated BMI, and area rates for diabetes attributable to excess weight. Contextual adjustment includes known area variables, and unobserved spatially clustered influences, while spatial heterogeneity (effect modification) is considered in terms of varying effects of elevated BMI by neighbourhood deprivation category. The application is to patient register data in London, with clear evidence of spatial variation in ARs, and in small area diabetes rates attributable to excess weight. Copyright © 2015 Elsevier Ltd. All rights reserved.
Comparison of spatial variability in visible and near-infrared spectral images
Chavez, P.S.
1992-01-01
The visible and near-infrared bands of the Landsat Thematic Mapper (TM) and the Satellite Pour l'Observation de la Terre (SPOT) were analyzed to determine which band contained more spatial variability. It is important for applications that require spatial information, such as those dealing with mapping linear features and automatic image-to-image correlation, to know which spectral band image should be used. Statistical and visual analyses were used in the project. The amount of variance in an 11 by 11 pixel spatial filter and in the first difference at the six spacings of 1, 5, 11, 23, 47, and 95 pixels was computed for the visible and near-infrared bands. The results indicate that the near-infrared band has more spatial variability than the visible band, especially in images covering densely vegetated areas. -Author
Melisa L. Holman; David L. Peterson
2006-01-01
We compared annual basal area increment (BAI) at different spatial scales among all size classes and species at diverse locations in the wet western and dry northeastern Olympic Mountains. Weak growth correlations at small spatial scales (average R = 0.084-0.406) suggest that trees are responding to local growth conditions. However, significant...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sinistore, Julie C.; Reinemann, D. J.; Izaurralde, Roberto C.
Spatial variability in yields and greenhouse gas emissions from soils has been identified as a key source of variability in life cycle assessments (LCAs) of agricultural products such as cellulosic ethanol. This study aims to conduct an LCA of cellulosic ethanol production from switchgrass in a way that captures this spatial variability and tests results for sensitivity to using spatially averaged results. The Environment Policy Integrated Climate (EPIC) model was used to calculate switchgrass yields, greenhouse gas (GHG) emissions, and nitrogen and phosphorus emissions from crop production in southern Wisconsin and Michigan at the watershed scale. These data were combinedmore » with cellulosic ethanol production data via ammonia fiber expansion and dilute acid pretreatment methods and region-specific electricity production data into an LCA model of eight ethanol production scenarios. Standard deviations from the spatial mean yields and soil emissions were used to test the sensitivity of net energy ratio, global warming potential intensity, and eutrophication and acidification potential metrics to spatial variability. Substantial variation in the eutrophication potential was also observed when nitrogen and phosphorus emissions from soils were varied. This work illustrates the need for spatially explicit agricultural production data in the LCA of biofuels and other agricultural products.« less
Sheridan, Susan Rich
2005-01-01
A model of human language requires a theory of meaningful marks. Humans are the only species who use marks to think. A theory of marks identifies children's scribbles as significant behavior, while hypothesizing the importance of rotational systems to hominid brain evolution. By recognizing the importance of children's scribbles and drawings in developmental terms as well as in evolutionary terms, a marks-based rather than a predominantly speech-based theory of the human brain, language, and consciousness emerges. Combined research in anthropology, primatology, art history, neurology, child development (including research with deaf and blind children), gender studies and literacy suggests the importance of notational systems to human language, revealing the importance of mother/child interactions around marks and sounds to the development of an expressive, communicative, symbolic human brain. An understanding of human language is enriched by identifying marks carved on bone 1.9 million years ago as observational lunar calendar-keeping, pushing proto-literacy back dramatically. Neurologically, children recapitulate the meaningful marks of early hominins when they scribble and draw, reminding us that literacy belongs to humankind's earliest history. Even more than speech, such meaningful marks played - and continue to play - decisive roles in human brain evolution. The hominid brain required a model for integrative, transformative neural transfer. The research strongly suggests that humankind's multiple literacies (art, literature, scientific writing, mathematics and music) depended upon dyadic exchanges between hominid mothers and children, and that this exchange and sharing of visuo-spatial information drove the elaboration of human speech in terms of syntax, grammar and vocabulary. The human brain was spatial before it was linguistic. The child scribbles and draws before it speaks or writes. Children babble and scribble within the first two years of life. Hands and mouths are proximal on the sensory-motor cortex. Gestures accompany speech. Illiterate brains mis-pronounce nonsense sounds. Literate brains do not. Written language (work of the hands) enhances spoken language (work of the mouth). Until brain scans map the neurological links between human gesture, speech and marks in the context of mother/caregiver/child interactions, and research with literate and illiterate brains document even more precisely the long-term differences between these brains, the evolutionary pressure of marks on especially flexible maternal and infant brain tissue that occurred 1.9 million years, radically changing primate brain capabilities, requires an integrated theory of marks and mind.
Optimization techniques for integrating spatial data
Herzfeld, U.C.; Merriam, D.F.
1995-01-01
Two optimization techniques ta predict a spatial variable from any number of related spatial variables are presented. The applicability of the two different methods for petroleum-resource assessment is tested in a mature oil province of the Midcontinent (USA). The information on petroleum productivity, usually not directly accessible, is related indirectly to geological, geophysical, petrographical, and other observable data. This paper presents two approaches based on construction of a multivariate spatial model from the available data to determine a relationship for prediction. In the first approach, the variables are combined into a spatial model by an algebraic map-comparison/integration technique. Optimal weights for the map comparison function are determined by the Nelder-Mead downhill simplex algorithm in multidimensions. Geologic knowledge is necessary to provide a first guess of weights to start the automatization, because the solution is not unique. In the second approach, active set optimization for linear prediction of the target under positivity constraints is applied. Here, the procedure seems to select one variable from each data type (structure, isopachous, and petrophysical) eliminating data redundancy. Automating the determination of optimum combinations of different variables by applying optimization techniques is a valuable extension of the algebraic map-comparison/integration approach to analyzing spatial data. Because of the capability of handling multivariate data sets and partial retention of geographical information, the approaches can be useful in mineral-resource exploration. ?? 1995 International Association for Mathematical Geology.
Territory surveillance and prey management: Wolves keep track of space and time.
Schlägel, Ulrike E; Merrill, Evelyn H; Lewis, Mark A
2017-10-01
Identifying behavioral mechanisms that underlie observed movement patterns is difficult when animals employ sophisticated cognitive-based strategies. Such strategies may arise when timing of return visits is important, for instance to allow for resource renewal or territorial patrolling. We fitted spatially explicit random-walk models to GPS movement data of six wolves ( Canis lupus ; Linnaeus, 1758) from Alberta, Canada to investigate the importance of the following: (1) territorial surveillance likely related to renewal of scent marks along territorial edges, to reduce intraspecific risk among packs, and (2) delay in return to recently hunted areas, which may be related to anti-predator responses of prey under varying prey densities. The movement models incorporated the spatiotemporal variable "time since last visit," which acts as a wolf's memory index of its travel history and is integrated into the movement decision along with its position in relation to territory boundaries and information on local prey densities. We used a model selection framework to test hypotheses about the combined importance of these variables in wolf movement strategies. Time-dependent movement for territory surveillance was supported by all wolf movement tracks. Wolves generally avoided territory edges, but this avoidance was reduced as time since last visit increased. Time-dependent prey management was weak except in one wolf. This wolf selected locations with longer time since last visit and lower prey density, which led to a longer delay in revisiting high prey density sites. Our study shows that we can use spatially explicit random walks to identify behavioral strategies that merge environmental information and explicit spatiotemporal information on past movements (i.e., "when" and "where") to make movement decisions. The approach allows us to better understand cognition-based movement in relation to dynamic environments and resources.
NASA Astrophysics Data System (ADS)
Ackerer, Julien; Chabaux, François; Lucas, Yann; Pierret, Marie Claire; Viville, Daniel; Fritz, Bertrand; Clement, Alain; Beaulieu, Emilie; Negrel, Philippe
2017-04-01
Regular analysis of the major element concentrations in waters from springs emerging on the Strengbach catchment is made for more than 20 years (OHGE, Observatoire Hydro-Géochimique de l'Environnement). These data confirm the spatial variability of geochemical characteristics of the Strengbach springs linked, at least partly, to the lithological variability of the substratum (Pierret et al., 2014). The data also indicate that at the first order, the geochemical fluxes exported from each spring are mainly linked to the spring discharges, without significant variations of the relationships linking these two parameters between 1990 and 2010. There is also no observation of significant variations for the dissolved silica and for most of the cationic concentrations with time. Only a significant decrease of the Ca concentrations is observed for the Strengbach springs from 1990 to 2010. Numerical simulations, performed with the KIRMAT hydro-geochemical code, show that such a decrease can be considered as the response in the "bedrock" of the water-rock interactions to the variations of the soil solution chemical compositions recorded over the last 20 years, marked by a significant increase of pH and decrease of Ca concentrations. In particular, the modeling results show that the Ca concentration decrease is controlled by the couple apatite/clays, and that significant modifications of the apatite dissolution rate and clay compositions occurred between 1990 and 2010. This study shows that the temporal evolution of the Strengbach spring chemistry cannot be explained by the only variations of the clay mineral compositions, i.e. a modification of the chemical composition of the precipitated clays or a modification of the ionic exchange capacity of the clay minerals, but that it is definitely the interrelations between the apatite and the clay minerals that are involved.
Preliminary results of spatial modeling of selected forest health variables in Georgia
Brock Stewart; Chris J. Cieszewski
2009-01-01
Variables relating to forest health monitoring, such as mortality, are difficult to predict and model. We present here the results of fitting various spatial regression models to these variables. We interpolate plot-level values compiled from the Forest Inventory and Analysis National Information Management System (FIA-NIMS) data that are related to forest health....
Dynamics of Hippocampal Protein Expression During Long-term Spatial Memory Formation*
Borovok, Natalia; Nesher, Elimelech; Levin, Yishai; Reichenstein, Michal; Pinhasov, Albert
2016-01-01
Spatial memory depends on the hippocampus, which is particularly vulnerable to aging. This vulnerability has implications for the impairment of navigation capacities in older people, who may show a marked drop in performance of spatial tasks with advancing age. Contemporary understanding of long-term memory formation relies on molecular mechanisms underlying long-term synaptic plasticity. With memory acquisition, activity-dependent changes occurring in synapses initiate multiple signal transduction pathways enhancing protein turnover. This enhancement facilitates de novo synthesis of plasticity related proteins, crucial factors for establishing persistent long-term synaptic plasticity and forming memory engrams. Extensive studies have been performed to elucidate molecular mechanisms of memory traces formation; however, the identity of plasticity related proteins is still evasive. In this study, we investigated protein turnover in mouse hippocampus during long-term spatial memory formation using the reference memory version of radial arm maze (RAM) paradigm. We identified 1592 proteins, which exhibited a complex picture of expression changes during spatial memory formation. Variable linear decomposition reduced significantly data dimensionality and enriched three principal factors responsible for variance of memory-related protein levels at (1) the initial phase of memory acquisition (165 proteins), (2) during the steep learning improvement (148 proteins), and (3) the final phase of the learning curve (123 proteins). Gene ontology and signaling pathways analysis revealed a clear correlation between memory improvement and learning phase-curbed expression profiles of proteins belonging to specific functional categories. We found differential enrichment of (1) neurotrophic factors signaling pathways, proteins regulating synaptic transmission, and actin microfilament during the first day of the learning curve; (2) transcription and translation machinery, protein trafficking, enhancement of metabolic activity, and Wnt signaling pathway during the steep phase of memory formation; and (3) cytoskeleton organization proteins. Taken together, this study clearly demonstrates dynamic assembly and disassembly of protein-protein interaction networks depending on the stage of memory formation engrams. PMID:26598641
Variability of Arctic Sea Ice as Determined from Satellite Observations
NASA Technical Reports Server (NTRS)
Parkinson, Claire L.
1999-01-01
The compiled, quality-controlled satellite multichannel passive-microwave record of polar sea ice now spans over 18 years, from November 1978 through December 1996, and is revealing considerable information about the Arctic sea ice cover and its variability. The information includes data on ice concentrations (percent areal coverages of ice), ice extents, ice melt, ice velocities, the seasonal cycle of the ice, the interannual variability of the ice, the frequency of ice coverage, and the length of the sea ice season. The data reveal marked regional and interannual variabilities, as well as some statistically significant trends. For the north polar ice cover as a whole, maximum ice extents varied over a range of 14,700,000 - 15,900,000 sq km, while individual regions experienced much greater percent variations, for instance, with the Greenland Sea having a range of 740,000 - 1,110,000 sq km in its yearly maximum ice coverage. In spite of the large variations from year to year and region to region, overall the Arctic ice extents showed a statistically significant, 2.80% / decade negative trend over the 18.2-year period. Ice season lengths, which vary from only a few weeks near the ice margins to the full year in the large region of perennial ice coverage, also experienced interannual variability, along with spatially coherent overall trends. Linear least squares trends show the sea ice season to have lengthened in much of the Bering Sea, Baffin Bay, the Davis Strait, and the Labrador Sea, but to have shortened over a much larger area, including the Sea of Okhotsk, the Greenland Sea, the Barents Sea, and the southeastern Arctic.
Added-values of high spatiotemporal remote sensing data in crop yield estimation
NASA Astrophysics Data System (ADS)
Gao, F.; Anderson, M. C.
2017-12-01
Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing derived parameters have been used for estimating crop yield by using either empirical or crop growth models. The uses of remote sensing vegetation index (VI) in crop yield modeling have been typically evaluated at regional and country scales using coarse spatial resolution (a few hundred to kilo-meters) data or assessed over a small region at field level using moderate resolution spatial resolution data (10-100m). Both data sources have shown great potential in capturing spatial and temporal variability in crop yield. However, the added value of data with both high spatial and temporal resolution data has not been evaluated due to the lack of such data source with routine, global coverage. In recent years, more moderate resolution data have become freely available and data fusion approaches that combine data acquired from different spatial and temporal resolutions have been developed. These make the monitoring crop condition and estimating crop yield at field scale become possible. Here we investigate the added value of the high spatial and temporal VI for describing variability of crop yield. The explanatory ability of crop yield based on high spatial and temporal resolution remote sensing data was evaluated in a rain-fed agricultural area in the U.S. Corn Belt. Results show that the fused Landsat-MODIS (high spatial and temporal) VI explains yield variability better than single data source (Landsat or MODIS alone), with EVI2 performing slightly better than NDVI. The maximum VI describes yield variability better than cumulative VI. Even though VI is effective in explaining yield variability within season, the inter-annual variability is more complex and need additional information (e.g. weather, water use and management). Our findings augment the importance of high spatiotemporal remote sensing data and supports new moderate resolution satellite missions for agricultural applications.
Satellite Analysis of Ocean Biogeochemistry and Mesoscale Variability in the Sargasso Sea
NASA Technical Reports Server (NTRS)
Siegel, D. A.; Micheals, A. F.; Nelson, N. B.
1997-01-01
The objective of this study was to analyze the impact of spatial variability on the time-series of biogeochemical measurements made at the U.S. JGOFS Bermuda Atlantic Time-series Study (BATS) site. Originally the study was planned to use SeaWiFS as well as AVHRR high-resolution data. Despite the SeaWiFS delays we were able to make progress on the following fronts: (1) Operational acquisition, processing, and archive of HRPT data from a ground station located in Bermuda; (2) Validation of AVHRR SST data using BATS time-series and spatial validation cruise CTD data; (3) Use of AVHRR sea surface temperature imagery and ancillary data to assess the impact of mesoscale spatial variability on P(CO2) and carbon flux in the Sargasso Sea; (4) Spatial and temporal extent of tropical cyclone induced surface modifications; and (5) Assessment of eddy variability using TOPEX/Poseidon data.
McHugh, Stuart
1976-01-01
The material in this report is concerned with the effects of a vertically oriented rectangular dislocation loop on the tilts observed at the free surface of an elastic half-space. Part I examines the effect of a spatially variable static strike-slip distribution across the slip surface. The tilt components as a function of distance parallel, or perpendicular, to the strike of the slip surface are displayed for different slip-versus-distance profiles. Part II examines the effect of spatially and temporally variable slip distributions across the dislocation loop on the quasi-static tilts at the free surface of an elastic half space. The model discussed in part II may be used to generate theoretical tilt versus time curves produced by creep events.
Accounting for and predicting the influence of spatial autocorrelation in water quality modeling
NASA Astrophysics Data System (ADS)
Miralha, L.; Kim, D.
2017-12-01
Although many studies have attempted to investigate the spatial trends of water quality, more attention is yet to be paid to the consequences of considering and ignoring the spatial autocorrelation (SAC) that exists in water quality parameters. Several studies have mentioned the importance of accounting for SAC in water quality modeling, as well as the differences in outcomes between models that account for and ignore SAC. However, the capacity to predict the magnitude of such differences is still ambiguous. In this study, we hypothesized that SAC inherently possessed by a response variable (i.e., water quality parameter) influences the outcomes of spatial modeling. We evaluated whether the level of inherent SAC is associated with changes in R-Squared, Akaike Information Criterion (AIC), and residual SAC (rSAC), after accounting for SAC during modeling procedure. The main objective was to analyze if water quality parameters with higher Moran's I values (inherent SAC measure) undergo a greater increase in R² and a greater reduction in both AIC and rSAC. We compared a non-spatial model (OLS) to two spatial regression approaches (spatial lag and error models). Predictor variables were the principal components of topographic (elevation and slope), land cover, and hydrological soil group variables. We acquired these data from federal online sources (e.g. USGS). Ten watersheds were selected, each in a different state of the USA. Results revealed that water quality parameters with higher inherent SAC showed substantial increase in R² and decrease in rSAC after performing spatial regressions. However, AIC values did not show significant changes. Overall, the higher the level of inherent SAC in water quality variables, the greater improvement of model performance. This indicates a linear and direct relationship between the spatial model outcomes (R² and rSAC) and the degree of SAC in each water quality variable. Therefore, our study suggests that the inherent level of SAC in response variables can predict improvements in models even before performing spatial regression approaches. We also recognize the constraints of this research and suggest that further studies focus on better ways of defining spatial neighborhoods, considering the differences among stations set in tributaries near to each other and in upstream areas.
Pearse, Aaron T.; Brandt, David; Krapu, Gary
2016-01-01
Numerous wind energy projects have been constructed in the central and southern Great Plains, USA, the main wintering area for midcontinental Sandhill Cranes (Grus canadensis). In an initial assessment of the potential risks of wind towers to cranes, we estimated spatial overlap, investigated potential avoidance behavior, and determined the habitat associations of cranes. We used data from cranes marked with platform transmitting terminals (PTTs) with and without global positioning system (GPS) capabilities. We estimated the wintering distributions of PTT-marked cranes prior to the construction of wind towers, which we compared with current tower locations. Based on this analysis, we found 7% spatial overlap between the distributions of cranes and towers. When we looked at individually marked cranes, we found that 52% would have occurred within 10 km of a tower at some point during winter. Using data from cranes marked after tower construction, we found a potential indication of avoidance behavior, whereby GPS-marked cranes generally used areas slightly more distant from existing wind towers than would be expected by chance. Results from a habitat selection model suggested that distances between crane locations and towers may have been driven more by habitat selection than by avoidance, as most wind towers were constructed in locations not often selected by wintering cranes. Our findings of modest regional overlap and that few towers have been placed in preferred crane habitat suggest that the current distribution of wind towers may be of low risk to the continued persistence of wintering midcontinental Sandhill Cranes in the central and southern Great Plains.
NASA Astrophysics Data System (ADS)
Belik, Anton; Vasenev, Ivan; Jablonskikh, Lidia; Bozhko, Svetlana
2017-04-01
The crop yield is the most important indicator of the efficiency of agricultural production. It is the function that depends on a large number of groups of independent variables, such as the weather, soil fertility and overall culture agriculture. A huge number of combinations of these factors contribute to the formation of high spatial variety of crop yields within small areas, includes the slope agrolandscapes in Kursk region. Spatial variety of yield leads to a significant reduction in the efficiency of agriculture. In this connection, evaluation and analysis of the factors, which limits the yield of field crops is a very urgent proble in agroecology. The research was conducted in the period of 2003-2004 on a representative field. The typical and leached chernozems with the varying thickness and of erosion degree are dominated in soil cover. At the time of field research studied areas were busy by barley. The reseached soils have an average and increased fertility level. Chernozem typical full-face, and the leached contain an average of 4.5-6% humus, close to neutral pH, favorable values of physico-chemical parameters, medium and high content of nutrients. The eroded chernozems differs agrogenic marked declining in fertility parameters. The diversity of meso- and micro-relief in the fields and soil cover influence to significant spatial variety of fertility. For example the content of nutrients in the soil variation can be up to 5-fold level. High spatial heterogeneity of soils fertility ifluence to barley yield variety. During research on the productivity of the field varied in the range of 20-43 c/ha, and 7-44 c/ha (2004). Analysis of the factors, which limited the yield of barley, showed that the first priorities occupy unregulated characterises: slope angle and the classification of soils (subtype and race of chernozem and the difference in the degree of erosion), which determines the development of erosion processes and redistribution available to plants form of moisture. As a rule, the maximum yield of barley is marked on most flat areas covered with chernozem leached and typical with the full profile. The contain of nutrients usually takes 3-4 levels of limitation. The significance of a particular element is determined by the characteristics of the particular agro-ecological homogeneous area. Most, however, the value in the 2003 - 2004's. plants were available forms of phosphorus and potassium Thus, in terms of slope agricultural landscapes of the Kursk region, there is increased spatial varety of fertility and barley yields. This priority among the limiting factors are soils and agro-ecological conditions. Significant influence of agrochemical parameters are shown within the homogeneous agroecological regions. In this regard system of precision agriculture has a great prospects for acquiring practical, and must to imply the adaptation of existing agricultural technologies to change the conditions of cultivation of field crops within fields.
Spatial and seasonal variability of dissolved organic matter in the Cariaco Basin
NASA Astrophysics Data System (ADS)
Lorenzoni, Laura; Taylor, Gordon T.; Benitez-Nelson, Claudia; Hansell, Dennis A.; Montes, Enrique; Masserini, Robert; Fanning, Kent; Varela, Ramón; Astor, Yrene; GuzmáN, Laurencia; Muller-Karger, Frank E.
2013-06-01
organic carbon (DOC), nitrogen (DON), and phosphorus (DOP) were measured monthly at the CARIACO Time Series station (10°30'N, 64°40'W) in the southeastern Caribbean Sea between 2005 and 2012. Marked seasonal variability in DOC concentrations was observed, with lower values (~66 µM) in the upper water column (<75 m) during the upwelling season (December-April) due to the injection of cool, DOC-impoverished Subtropical Underwater from the Caribbean Sea. During the rainy season (May-November) waters were stratified and upper layer DOC concentrations increased to ~71 µM. Interannual variability in surface (1 m) concentrations of DOC was also observed in response to the variable strength in upwelling and stratification that the Cariaco Basin experienced. DON and DOP showed no such seasonality. At depths >350 m, DOC concentrations were 56 ± 4.7 µM, roughly 10 µM higher than those in the Caribbean Sea over the same depth range. DON and DOP showed similar vertical profiles to that of DOC, with higher concentrations (6.8 ± 1.2 µM N and 0.15 ±0.09 µM P) in the upper water column and invariant, lower concentrations at depth (4.8 ± 1.6 µM N and 0.10 ± 0.08 µM P). Wind-driven advection of surface DOC out of the Cariaco Basin was estimated to support a net export ~15 Gmol C yr-1 into the Caribbean Sea; this rate is comparable to the flux of settling particulate organic carbon to depths >275 m within the basin.
NASA Astrophysics Data System (ADS)
Tisseyre, Bruno
2015-04-01
For more than 15 years, research projects are conducted in the precision viticulture (PV) area around the world. These research projects have provided new insights into the within-field variability in viticulture. Indeed, access to high spatial resolution data (remote sensing, embedded sensors, etc.) changes the knowledge we have of the fields in viticulture. In particular, the field which was until now considered as a homogeneous management unit, presents actually a high spatial variability in terms of yield, vigour an quality. This knowledge will lead (and is already causing) changes on how to manage the vineyard and the quality of the harvest at the within field scale. From the experimental results obtained in various countries of the world, the goal of the presentation is to provide figures on: - the spatial variability of the main parameters (yield, vigor, quality), and how this variability is organized spatially, - the temporal stability of the observed spatial variability and the potential link with environmental parameters like soil, topography, soil water availability, etc. - information sources available at a high spatial resolution conventionally used in precision agriculture likely to highlight this spatial variability (multi-spectral images, soil electrical conductivity, etc.) and the limitations that these information sources are likely to present in viticulture. Several strategies are currently being developed to take into account the within field variability in viticulture. They are based on the development of specific equipments, sensors, actuators and site specific strategies with the aim of adapting the vineyard operations at the within-field level. These strategies will be presented briefly in two ways : - Site specific operations (fertilization, pruning, thinning, irrigation, etc.) in order to counteract the effects of the environment and to obtain a final product with a controlled and consistent wine quality, - Differential harvesting with the objective to take advantage of the observed spatial variability to produce different quality of wines. These later approach tends to produce very different quality wines which will be blended to control the final quality and/or marketed differently. These applications show that the environment and its spatial variability can be valued with the goal of controlling the final quality of the wine produced. Technologies to characterize the spatial variability of vine fields are currently in rapid evolution. They will significantly impact production methods and management strategies of the vineyard. In its last part, the presentation will summarize the technologies likely to impact the knowledge and the vineyard management either at the field level, at the vineyard level or at the regional level. A brief overview of the needs in terms of information processing will be also performed. A reflection on the difficulties that might limit the adoption of precision viticulture technologies (PV) will be done. Indeed, although very informative, PV entails high costs of information acquisition and data processing. Cost is one of the major obstacles to the dissemination of these tools and services to the majority of wine producers. In this context, the pooling of investments is a choke point to make the VP accessible to the highest number of growers. Thus, to be adopted, the VP will necessarily satisfy the operational requirements at the field level, but also throughout the whole production area (at the regional level). This working scale raises new scientific questions to be addressed.
NASA Astrophysics Data System (ADS)
Crawford, Ben; Grimmond, Sue; Kent, Christoph; Gabey, Andrew; Ward, Helen; Sun, Ting; Morrison, William
2017-04-01
Remotely sensed data from satellites have potential to enable high-resolution, automated calculation of urban surface energy balance terms and inform decisions about urban adaptations to environmental change. However, aerodynamic resistance methods to estimate sensible heat flux (QH) in cities using satellite-derived observations of surface temperature are difficult in part due to spatial and temporal variability of the thermal aerodynamic resistance term (rah). In this work, we extend an empirical function to estimate rah using observational data from several cities with a broad range of surface vegetation land cover properties. We then use this function to calculate spatially and temporally variable rah in London based on high-resolution (100 m) land cover datasets and in situ meteorological observations. In order to calculate high-resolution QH based on satellite-observed land surface temperatures, we also develop and employ novel methods to i) apply source area-weighted averaging of surface and meteorological variables across the study spatial domain, ii) calculate spatially variable, high-resolution meteorological variables (wind speed, friction velocity, and Obukhov length), iii) incorporate spatially interpolated urban air temperatures from a distributed sensor network, and iv) apply a modified Monte Carlo approach to assess uncertainties with our results, methods, and input variables. Modeled QH using the aerodynamic resistance method is then compared to in situ observations in central London from a unique network of scintillometers and eddy-covariance measurements.
Szabo, J.K.; Fedriani, E.M.; Segovia-Gonzalez, M. M.; Astheimer, L.B.; Hooper, M.J.
2010-01-01
This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. ?? 2010 World Scientific Publishing Company.
Atomic Force Microscope (AFM) measurements and analysis on Sagem 05R0025 secondary substrate
DOE Office of Scientific and Technical Information (OSTI.GOV)
Soufli, R; Baker, S L; Robinson, J C
2006-02-22
The summary of Atomic Force Microscope (AFM) on Sagem 05R0025 secondary substrate: (1) 2 x 2 {micro}m{sup 2} and 10 x 10 {micro}m{sup 2} AFM measurements and analysis on Sagem 05R0025 secondary substrate at LLNL indicate rather uniform and extremely isotropic finish across the surface, with high-spatial frequency roughness {sigma} in the range 5.1-5.5 {angstrom} rms; (2) the marked absence of pronounced long-range polishing marks in any direction, combined with increased roughness in the very high spatial frequencies, are consistent with ion-beam polishing treatment on the surface. These observations are consistent with all earlier mirrors they measured from the samemore » vendor; and (3) all data were obtained with a Digital Instruments Dimension 5000{trademark} atomic force microscope.« less
Wu, Zhixu; Zhang, Yunlin; Zhou, Yongqiang; Liu, Mingliang; Shi, Kun; Yu, Zuoming
2015-08-12
Water transparency is a useful indicator of water quality or productivity and is widely used to detect long-term changes in the water quality and eutrophication of lake ecosystems. Based on short-term spatial observations in the spring, summer, and winter and on long-term site-specific observation from 1988 to 2013, the spatial, seasonal, long-term variations, and the factors affecting transparency are presented for Xin'anjiang Reservoir (China). Spatially, transparency was high in the open water but low in the bays and the inflowing river mouths, reflecting the effect of river runoff. The seasonal effects were distinct, with lower values in the summer than in the winter, most likely due to river runoff and phytoplankton biomass increases. The transparency decreased significantly with a linear slope of 0.079 m/year, indicating a 2.05 m decrease and a marked decrease in water quality. A marked increase occurred in chlorophyll a (Chla) concentration, and a significant correlation was found between the transparency and Chla concentration, indicating that phytoplankton biomass can partially explain the long-term trend of transparency in Xin'anjiang Reservoir. The river input and phytoplankton biomass increase were associated with soil erosion and nutrient loss in the catchment. Our study will support future management of water quality in Xin'anjiang Reservoir.
Field-scale apparent soil electrical conductivity
USDA-ARS?s Scientific Manuscript database
Soils are notoriously spatially heterogeneous and many soil properties (e.g., salinity, water content, trace element concentration, etc.) are temporally variable, making soil a complex media. Spatial variability of soil properties has a profound influence on agricultural and environmental processes ...
NASA Astrophysics Data System (ADS)
Danesh-Yazdi, Mohammad; Botter, Gianluca; Foufoula-Georgiou, Efi
2017-05-01
Lack of hydro-bio-chemical data at subcatchment scales necessitates adopting an aggregated system approach for estimating water and solute transport properties, such as residence and travel time distributions, at the catchment scale. In this work, we show that within-catchment spatial heterogeneity, as expressed in spatially variable discharge-storage relationships, can be appropriately encapsulated within a lumped time-varying stochastic Lagrangian formulation of transport. This time (variability) for space (heterogeneity) substitution yields mean travel times (MTTs) that are not significantly biased to the aggregation of spatial heterogeneity. Despite the significant variability of MTT at small spatial scales, there exists a characteristic scale above which the MTT is not impacted by the aggregation of spatial heterogeneity. Extensive simulations of randomly generated river networks reveal that the ratio between the characteristic scale and the mean incremental area is on average independent of river network topology and the spatial arrangement of incremental areas.
Finley, Andrew O.; Banerjee, Sudipto; Cook, Bruce D.; Bradford, John B.
2013-01-01
In this paper we detail a multivariate spatial regression model that couples LiDAR, hyperspectral and forest inventory data to predict forest outcome variables at a high spatial resolution. The proposed model is used to analyze forest inventory data collected on the US Forest Service Penobscot Experimental Forest (PEF), ME, USA. In addition to helping meet the regression model's assumptions, results from the PEF analysis suggest that the addition of multivariate spatial random effects improves model fit and predictive ability, compared with two commonly applied modeling approaches. This improvement results from explicitly modeling the covariation among forest outcome variables and spatial dependence among observations through the random effects. Direct application of such multivariate models to even moderately large datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. We apply a spatial dimension reduction technique to help overcome this computational hurdle without sacrificing richness in modeling.
Prediction of hourly PM2.5 using a space-time support vector regression model
NASA Astrophysics Data System (ADS)
Yang, Wentao; Deng, Min; Xu, Feng; Wang, Hang
2018-05-01
Real-time air quality prediction has been an active field of research in atmospheric environmental science. The existing methods of machine learning are widely used to predict pollutant concentrations because of their enhanced ability to handle complex non-linear relationships. However, because pollutant concentration data, as typical geospatial data, also exhibit spatial heterogeneity and spatial dependence, they may violate the assumptions of independent and identically distributed random variables in most of the machine learning methods. As a result, a space-time support vector regression model is proposed to predict hourly PM2.5 concentrations. First, to address spatial heterogeneity, spatial clustering is executed to divide the study area into several homogeneous or quasi-homogeneous subareas. To handle spatial dependence, a Gauss vector weight function is then developed to determine spatial autocorrelation variables as part of the input features. Finally, a local support vector regression model with spatial autocorrelation variables is established for each subarea. Experimental data on PM2.5 concentrations in Beijing are used to verify whether the results of the proposed model are superior to those of other methods.
NASA Astrophysics Data System (ADS)
Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar
2014-08-01
As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good, time-stable estimate of mean soil water content, as no improvement was obtained with the 5 × 5 m mesh grid (30 probes). Finally, the results of temporal aggregation showed that decreasing the monitoring frequency down to 8 h during wetting-up periods and to 1 day during drying-down ones did not result in a loss of information on daily soil water content variations.
The need for spatially explicit quantification of benefits in invasive-species management.
Januchowski-Hartley, Stephanie R; Adams, Vanessa M; Hermoso, Virgilio
2018-04-01
Worldwide, invasive species are a leading driver of environmental change across terrestrial, marine, and freshwater environments and cost billions of dollars annually in ecological damages and economic losses. Resources limit invasive-species control, and planning processes are needed to identify cost-effective solutions. Thus, studies are increasingly considering spatially variable natural and socioeconomic assets (e.g., species persistence, recreational fishing) when planning the allocation of actions for invasive-species management. There is a need to improve understanding of how such assets are considered in invasive-species management. We reviewed over 1600 studies focused on management of invasive species, including flora and fauna. Eighty-four of these studies were included in our final analysis because they focused on the prioritization of actions for invasive species management. Forty-five percent (n = 38) of these studies were based on spatial optimization methods, and 35% (n = 13) accounted for spatially variable assets. Across all 84 optimization studies considered, 27% (n = 23) explicitly accounted for spatially variable assets. Based on our findings, we further explored the potential costs and benefits to invasive species management when spatially variable assets are explicitly considered or not. To include spatially variable assets in decision-making processes that guide invasive-species management there is a need to quantify environmental responses to invasive species and to enhance understanding of potential impacts of invasive species on different natural or socioeconomic assets. We suggest these gaps could be filled by systematic reviews, quantifying invasive species impacts on native species at different periods, and broadening sources and enhancing sharing of knowledge. © 2017 Society for Conservation Biology.
Analysis of shifts in the spatial distribution of vegetation due to climate change
NASA Astrophysics Data System (ADS)
del Jesus, Manuel; Díez-Sierra, Javier; Rinaldo, Andrea; Rodríguez-Iturbe, Ignacio
2017-04-01
Climate change will modify the statistical regime of most climatological variables, inducing changes on average values and in the natural variability of environmental variables. These environmental variables may be used to explain the spatial distribution of functional types of vegetation in arid and semiarid watersheds through the use of plant optimization theories. Therefore, plant optimization theories may be used to approximate the response of the spatial distribution of vegetation to a changing climate. Predicting changes in these spatial distributions is important to understand how climate change may affect vegetated ecosystems, but it is also important for hydrological engineering applications where climate change effects on water availability are assessed. In this work, Maximum Entropy Production (MEP) is used as the plant optimization theory that describes the spatial distribution of functional types of vegetation. Current climatological conditions are obtained from direct observations from meteorological stations. Climate change effects are evaluated for different temporal horizons and different climate change scenarios using numerical model outputs from the CMIP5. Rainfall estimates are downscaled by means of a stochastic point process used to model rainfall. The study is carried out for the Rio Salado watershed, located within the Sevilleta LTER site, in New Mexico (USA). Results show the expected changes in the spatial distribution of vegetation and allow to evaluate the expected variability of the changes. The updated spatial distributions allow to evaluate the vegetated ecosystem health and its updated resilience. These results can then be used to inform the hydrological modeling part of climate change assessments analyzing water availability in arid and semiarid watersheds.
Spatial scaling of net primary productivity using subpixel landcover information
NASA Astrophysics Data System (ADS)
Chen, X. F.; Chen, Jing M.; Ju, Wei M.; Ren, L. L.
2008-10-01
Gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of carbon budget components at local, regional and global scales. These biases result from overlooking subpixel variability of land surface characteristics. Vegetation heterogeneity is an important factor introducing biases in regional ecological modeling, especially when the modeling is made on large grids. This study suggests a simple algorithm that uses subpixel information on the spatial variability of land cover type to correct net primary productivity (NPP) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. The algorithm operates in such a way that NPP obtained from calculations made at coarse spatial resolutions are multiplied by simple functions that attempt to reproduce the effects of subpixel variability of land cover type on NPP. Its application to a carbon-hydrology coupled model(BEPS-TerrainLab model) estimates made at a 1-km resolution over a watershed (named Baohe River Basin) located in the southwestern part of Qinling Mountains, Shaanxi Province, China, improved estimates of average NPP as well as its spatial variability.
Robin M. Reich; C. Aguirre-Bravo; M.S. Williams
2006-01-01
A statistical strategy for spatial estimation and modeling of natural and environmental resource variables and indicators is presented. This strategy is part of an inventory and monitoring pilot study that is being carried out in the Mexican states of Jalisco and Colima. Fine spatial resolution estimates of key variables and indicators are outputs that will allow the...
Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method
2010-01-25
2010 / Accepted: 19 January 2010 / Published: 25 January 2010 Abstract: Spatial and temporal soil moisture dynamics are critically needed to...scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial... dynamics is essential in the hydrological and meteorological modeling, improves our understanding of land surface–atmosphere interactions. Spatial and
Veiga, Puri; Torres, Ana Catarina; Aneiros, Fernando; Sousa-Pinto, Isabel; Troncoso, Jesús S; Rubal, Marcos
2016-09-01
Spatial variability of environmental factors and macrobenthos, using species and functional groups, was examined over the same scales (100s of cm to >100 km) in intertidal sediments of two transitional water systems. The objectives were to test if functional groups were a good species surrogate and explore the relationship between environmental variables and macrobenthos. Environmental variables, diversity and the multivariate assemblage structure showed the highest variability at the scale of 10s of km. However, abundance was more variable at 10s of m. Consistent patterns were achieved using species and functional groups therefore, these may be a good species surrogate. Total carbon, salinity and silt/clay were the strongest correlated with macrobenthic assemblages. Results are valuable for design and interpretation of future monitoring programs including detection of anthropogenic disturbances in transitional systems and propose improvements in environmental variable sampling to refine the assessment of their relationship with biological data across spatial scales. Copyright © 2016 Elsevier Ltd. All rights reserved.
Allen, David T; Cardoso-Saldaña, Felipe J; Kimura, Yosuke
2017-10-17
A gridded inventory for emissions of methane, ethane, propane, and butanes from oil and gas sources in the Barnett Shale production region has been developed. This inventory extends previous spatially resolved inventories of emissions by characterizing the overall variability in emission magnitudes and the composition of emissions at an hourly time resolution. The inventory is divided into continuous and intermittent emission sources. Sources are defined as continuous if hourly averaged emissions are greater than zero in every hour; otherwise, they are classified as intermittent. In the Barnett Shale, intermittent sources accounted for 14-30% of the mean emissions for methane and 10-34% for ethane, leading to spatial and temporal variability in the location of hourly emissions. The combined variability due to intermittent sources and variability in emission factors can lead to wide confidence intervals in the magnitude and composition of time and location-specific emission inventories; therefore, including temporal and spatial variability in emission inventories is important when reconciling inventories and observations. Comparisons of individual aircraft measurement flights conducted in the Barnett Shale region versus the estimated emission rates for each flight from the emission inventory indicate agreement within the expected variability of the emission inventory for all flights for methane and for all but one flight for ethane.
Quantifying and mapping spatial variability in simulated forest plots
Gavin R. Corral; Harold E. Burkhart
2016-01-01
We used computer simulations to test the efficacy of multivariate statistical methods to detect, quantify, and map spatial variability of forest stands. Simulated stands were developed of regularly-spaced plantations of loblolly pine (Pinus taeda L.). We assumed no affects of competition or mortality, but random variability was added to individual tree characteristics...
Spatial variability in forest growthclimate relationships in the Olympic Mountains, Washington.
Jill M. Nakawatase; David L. Peterson
2006-01-01
For many Pacific Northwest forests, little is known about the spatial and temporal variability in tree growth - climate relationships, yet it is this information that is needed to predict how forests will respond to future climatic change. We studied the effects of climatic variability on forest growth at 74 plots in the western and northeastern Olympic Mountains....
NASA Astrophysics Data System (ADS)
Eshonkulov, Ravshan; Poyda, Arne; Ingwersen, Joachim; Streck, Thilo
2017-04-01
Assessing the spatial variability of soil physical properties is crucial for agricultural land management. We determined the spatial variability within two agricultural fields in the regions of Kraichgau and Swabian Jura in Southwest Germany. We determined soil physical properties and recorded the temporal development of soil mineral nitrogen (N) and water content as well as that of plant variables (phenology, biomass, leaf area index (LAI), N content, green vegetation fraction (GVF). The work was conducted during the vegetation periods of 2015 and 2016 in winter wheat, and winter rapeseed in Kraichgau and winter barley and silage maize on Swabian Jura. Measurements were taken in three-weekly intervals. On each field, we identified three plots with reduced plant development using high-resolution (RapidEye) satellite images ("cold spots"). Measurements taken on these cold spots were compared to those from five established (long-term) reference plots representing the average field variability. The software EXPERT-N was used to simulate the soil crop system at both cold spots and reference plots. Sensitivity analyses were conducted to identify the most important parameters for the determination of spatial variability in crop growth dynamics.
NASA Astrophysics Data System (ADS)
Provo, Judy; Lamar, Carlton; Newby, Timothy
2002-01-01
A cross section was used to enhance three-dimensional knowledge of anatomy of the canine head. All veterinary students in two successive classes (n = 124) dissected the head; experimental groups also identified structures on a cross section of the head. A test assessing spatial knowledge of the head generated 10 dependent variables from two administrations. The test had content validity and statistically significant interrater and test-retest reliability. A live-dog examination generated one additional dependent variable. Analysis of covariance controlling for performance on course examinations and quizzes revealed no treatment effect. Including spatial skill as a third covariate revealed a statistically significant effect of spatial skill on three dependent variables. Men initially had greater spatial skill than women, but spatial skills were equal after 8 months. A qualitative analysis showed the positive impact of this experience on participants. Suggestions for improvement and future research are discussed.
Effects of Verb Familiarity on Finiteness Marking in Children with Specific Language Impairment
ERIC Educational Resources Information Center
Abel, Alyson D.; Rice, Mabel L.; Bontempo, Daniel E.
2015-01-01
Purpose: Children with specific language impairment (SLI) have known deficits in the verb lexicon and finiteness marking. This study investigated a potential relationship between these 2 variables in children with SLI and 2 control groups considering predictions from 2 different theoretical perspectives, morphosyntactic versus morphophonological.…
NASA Astrophysics Data System (ADS)
Smith, Tony E.; Lee, Ka Lok
2012-01-01
There is a common belief that the presence of residual spatial autocorrelation in ordinary least squares (OLS) regression leads to inflated significance levels in beta coefficients and, in particular, inflated levels relative to the more efficient spatial error model (SEM). However, our simulations show that this is not always the case. Hence, the purpose of this paper is to examine this question from a geometric viewpoint. The key idea is to characterize the OLS test statistic in terms of angle cosines and examine the geometric implications of this characterization. Our first result is to show that if the explanatory variables in the regression exhibit no spatial autocorrelation, then the distribution of test statistics for individual beta coefficients in OLS is independent of any spatial autocorrelation in the error term. Hence, inferences about betas exhibit all the optimality properties of the classic uncorrelated error case. However, a second more important series of results show that if spatial autocorrelation is present in both the dependent and explanatory variables, then the conventional wisdom is correct. In particular, even when an explanatory variable is statistically independent of the dependent variable, such joint spatial dependencies tend to produce "spurious correlation" that results in over-rejection of the null hypothesis. The underlying geometric nature of this problem is clarified by illustrative examples. The paper concludes with a brief discussion of some possible remedies for this problem.
NASA Astrophysics Data System (ADS)
Pawson, S.; Nielsen, J.; Ott, L. E.; Darmenov, A.; Putman, W.
2015-12-01
Model-data fusion approaches, such as global inverse modeling for surface flux estimation, have traditionally been performed at spatial resolutions of several tens to a few hundreds of kilometers. Use of such coarse scales presents a fundamental limitation in reconciling the modeled field with both the atmospheric observations and the distribution of surface emissions and uptake. Emissions typically occur on small scales, including point sources (e.g. power plants, forest fires) or with inhomegeneous structure. Biological uptake can have spatial variations related to complex, diverse vegetation, etc. Atmospheric observations of CO2 are either surface based, providing information at a single point, or space based with a finite-sized footprint. For instance, GOSAT and OCO-2 have footprint sizes of around 10km and proposed active sensors (such as ASCENDS) will likely have even finer footprints. One important aspect of reconciling models to measurements is the representativeness of the observation for the model field, and this depends on the generally unknown spatio-temporal variations of the CO2 field around the measurement location and time. This work presents an assessment of the global spatio-temporal variations of the CO2 field using the "7km GEOS-5 Nature Run" (7km-G5NR), which includes CO2 emissions and uptake mapped to the finest possible resolution. Results are shown for surface CO2 concentrations, total-column CO2, and separate upper and lower tropospheric columns. Spatial variability is shown to be largest in regions with strong point sources and at night in regions with complex terrain, especially where biological processes dominate the local CO2 fluxes, where the day-night differences are also most marked. The spatio-temporal variations are strongest for surface concentrations and for lower tropospheric CO2. While these results are largely anticipated, these high resolution simulations provide quantitative estimates of the global nature of spatio-temporal CO2 variability. Implications for characterizing representativeness of passive CO2 observations will be discussed. Differences between daytime and nighttime structures will be considered in light of active CO2 sensors. Finally, some possible limitations of the model will be highlighted, using some global 3-km simulations.
NASA Astrophysics Data System (ADS)
Pechlivanidis, Ilias; McIntyre, Neil; Wheater, Howard
2017-04-01
Rainfall, one of the main inputs in hydrological modeling, is a highly heterogeneous process over a wide range of scales in space, and hence the ignorance of the spatial rainfall information could affect the simulated streamflow. Calibration of hydrological model parameters is rarely a straightforward task due to parameter equifinality and parameters' 'nature' to compensate for other uncertainties, i.e. structural and forcing input. In here, we analyse the significance of spatial variability of rainfall on streamflow as a function of catchment scale and type, and antecedent conditions using the continuous time, semi-distributed PDM hydrological model at the Upper Lee catchment, UK. The impact of catchment scale and type is assessed using 11 nested catchments ranging in scale from 25 to 1040 km2, and further assessed by artificially changing the catchment characteristics and translating these to model parameters with uncertainty using model regionalisation. Synthetic rainfall events are introduced to directly relate the change in simulated streamflow to the spatial variability of rainfall. Overall, we conclude that the antecedent catchment wetness and catchment type play an important role in controlling the significance of the spatial distribution of rainfall on streamflow. Results show a relationship between hydrograph characteristics (streamflow peak and volume) and the degree of spatial variability of rainfall for the impermeable catchments under dry antecedent conditions, although this decreases at larger scales; however this sensitivity is significantly undermined under wet antecedent conditions. Although there is indication that the impact of spatial rainfall on streamflow varies as a function of catchment scale, the variability of antecedent conditions between the synthetic catchments seems to mask this significance. Finally, hydrograph responses to different spatial patterns in rainfall depend on assumptions used for model parameter estimation and also the spatial variation in parameters indicating the need of an uncertainty framework in such investigation.
Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.
Li, Mingming; Zhang, Xingchang; Zhen, Qing; Han, Fengpeng
2013-01-01
Soil organic carbon (SOC) reflects soil quality and plays a critical role in soil protection, food safety, and global climate changes. This study involved grid sampling at different depths (6 layers) between 0 and 100 cm in a catchment. A total of 1282 soil samples were collected from 215 plots over 8.27 km(2). A combination of conventional analytical methods and geostatistical methods were used to analyze the data for spatial variability and soil carbon content patterns. The mean SOC content in the 1282 samples from the study field was 3.08 g · kg(-1). The SOC content of each layer decreased with increasing soil depth by a power function relationship. The SOC content of each layer was moderately variable and followed a lognormal distribution. The semi-variograms of the SOC contents of the six different layers were fit with the following models: exponential, spherical, exponential, Gaussian, exponential, and exponential, respectively. A moderate spatial dependence was observed in the 0-10 and 10-20 cm layers, which resulted from stochastic and structural factors. The spatial distribution of SOC content in the four layers between 20 and 100 cm exhibit were mainly restricted by structural factors. Correlations within each layer were observed between 234 and 562 m. A classical Kriging interpolation was used to directly visualize the spatial distribution of SOC in the catchment. The variability in spatial distribution was related to topography, land use type, and human activity. Finally, the vertical distribution of SOC decreased. Our results suggest that the ordinary Kriging interpolation can directly reveal the spatial distribution of SOC and the sample distance about this study is sufficient for interpolation or plotting. More research is needed, however, to clarify the spatial variability on the bigger scale and better understand the factors controlling spatial variability of soil carbon in the Loess Plateau region.
Soil nutrient-landscape relationships in a lowland tropical rainforest in Panama
Barthold, F.K.; Stallard, R.F.; Elsenbeer, H.
2008-01-01
Soils play a crucial role in biogeochemical cycles as spatially distributed sources and sinks of nutrients. Any spatial patterns depend on soil forming processes, our understanding of which is still limited, especially in regards to tropical rainforests. The objective of our study was to investigate the effects of landscape properties, with an emphasis on the geometry of the land surface, on the spatial heterogeneity of soil chemical properties, and to test the suitability of soil-landscape modeling as an appropriate technique to predict the spatial variability of exchangeable K and Mg in a humid tropical forest in Panama. We used a design-based, stratified sampling scheme to collect soil samples at 108 sites on Barro Colorado Island, Panama. Stratifying variables are lithology, vegetation and topography. Topographic variables were generated from high-resolution digital elevation models with a grid size of 5 m. We took samples from five depths down to 1 m, and analyzed for total and exchangeable K and Mg. We used simple explorative data analysis techniques to elucidate the importance of lithology for soil total and exchangeable K and Mg. Classification and Regression Trees (CART) were adopted to investigate importance of topography, lithology and vegetation for the spatial distribution of exchangeable K and Mg and with the intention to develop models that regionalize the point observations using digital terrain data as explanatory variables. Our results suggest that topography and vegetation do not control the spatial distribution of the selected soil chemical properties at a landscape scale and lithology is important to some degree. Exchangeable K is distributed equally across the study area indicating that other than landscape processes, e.g. biogeochemical processes, are responsible for its spatial distribution. Lithology contributes to the spatial variation of exchangeable Mg but controlling variables could not be detected. The spatial variation of soil total K and Mg is mainly influenced by lithology. ?? 2007 Elsevier B.V. All rights reserved.
Bermejo, Ricardo; de la Fuente, Gina; Ramírez-Romero, Eduardo; Vergara, Juan J; Hernández, Ignacio
2016-04-15
The Cystoseira ericaefolia group is conformed by three species: C. tamariscifolia, C. mediterranea and C. amentacea. These species are among the most important habitat forming species of the upper sublittoral rocky shores of the Mediterranean Sea and adjacent Atlantic coast. This species group is sensitive to human pressures and therefore is currently suffering important losses. This study aimed to assess the influence of anthropogenic pressures, oceanographic conditions and local spatial variability in assemblages dominated by C. ericaefolia in the Alboran Sea. The results showed the absence of significant effects of anthropogenic pressures or its interactions with environmental conditions in the Cystoseira assemblages. This fact was attributed to the high spatial variability, which is most probably masking the impact of anthropogenic pressures. The results also showed that most of the variability occurred on at local levels. A relevant spatial variability was observed at regional level, suggesting a key role of oceanographic features in these assemblages. Copyright © 2016 Elsevier Ltd. All rights reserved.
Controls on the variability of net infiltration to desert sandstone
Heilweil, Victor M.; McKinney, Tim S.; Zhdanov, Michael S.; Watt, Dennis E.
2007-01-01
As populations grow in arid climates and desert bedrock aquifers are increasingly targeted for future development, understanding and quantifying the spatial variability of net infiltration becomes critically important for accurately inventorying water resources and mapping contamination vulnerability. This paper presents a conceptual model of net infiltration to desert sandstone and then develops an empirical equation for its spatial quantification at the watershed scale using linear least squares inversion methods for evaluating controlling parameters (independent variables) based on estimated net infiltration rates (dependent variables). Net infiltration rates used for this regression analysis were calculated from environmental tracers in boreholes and more than 3000 linear meters of vadose zone excavations in an upland basin in southwestern Utah underlain by Navajo sandstone. Soil coarseness, distance to upgradient outcrop, and topographic slope were shown to be the primary physical parameters controlling the spatial variability of net infiltration. Although the method should be transferable to other desert sandstone settings for determining the relative spatial distribution of net infiltration, further study is needed to evaluate the effects of other potential parameters such as slope aspect, outcrop parameters, and climate on absolute net infiltration rates.
Representativeness of regional and global mass-balance measurement networks (Invited)
NASA Astrophysics Data System (ADS)
Cogley, J. G.; Moholdt, G.; Gardner, A. S.
2013-12-01
We showed in a recent publication that regional estimates of glacier mass budgets, obtained by interpolation from in-situ measurements, were markedly more negative than corresponding estimates by satellite gravimetry (GRACE) and satellite altimetry (ICESat) during 2003-2009. Examining the ICESat data in more detail, we found that in-situ records tend to be located in areas where glaciers are thinning more rapidly than as observed in their regional surroundings. Because neither GRACE nor ICESat can provide information for times before 2002-2003, and may not operate without interruption in the future, we explore possible explanations of and remedies for the identified bias in the in-situ network. Sparse spatial sampling, coupled with previously undetected spatial variability of mass balance at scales between the 10-km in-situ scale and the 350-km gravimetric scale, appears to be the leading explanation. Satisfactory remedies are not obvious. Selecting glaciers for in-situ measurement that are more representative will yield only incremental improvements. There appears to be no alternative to mass-balance modelling as a versatile tool for estimation of regional mass balance. However the meteorological data for forcing the surface components of glacier models have coarser resolution than is desirable and are themselves uncertain, especially in the remote regions where much of the glacier ice is found. Measurements of frontal (dynamic) mass changes are still difficult, and modelling of these changes remains underdeveloped in spite of recent advances. Thus research on a broad scale is called for in order to meet the challenge of producing more accurate hindcasts and projections of glacier mass budgets with fine spatial and temporal resolution.
Qiu, Maolin; Ramani, Ramachandran; Swetye, Michael; Constable, Robert Todd
2009-01-01
Pulsed arterial spin labeling magnetic resonance imaging (MRI) was performed to investigate the local coupling between resting regional cerebral blood flow (rCBF) and BOLD (blood oxygen level dependent) signal changes in 22 normal human subjects during the administration of 0.25 MAC (minimum alveolar concentration) sevoflurane. Two states were compared with subjects at rest: anesthesia and no-anesthesia. Regions of both significantly increased and decreased resting-state rCBF were observed. Increases were limited primarily to subcortical structures and insula, whereas, decreases were observed primarily in neocortical regions. No significant change was found in global CBF (gCBF). By simultaneously measuring rCBF and BOLD, region-specific anesthetic effects on the coupling between rCBF and BOLD were identified. Multiple comparisons of the agent-induced rCBF and BOLD changes demonstrated significant (P < 0.05) spatial variability in rCBF–BOLD coupling. The slope of the linear regression line for AC, where rCBF was increased by sevoflurane, was markedly smaller than the slope for those ROIs where rCBF was decreased by sevoflurane, indicating a bigger change in BOLD per unit change in rCBF in regions where rCBF was increased by sevoflurane. These results suggest that it would be inaccurate to use a global quantitative model to describe coupling across all brain regions and in all anesthesia conditions. The observed spatial nonuniformity of rCBF and BOLD signal changes suggests that any interpretation of BOLD fMRI data in the presence of an anesthetic requires consideration of these insights. PMID:17948882
Downscaling Global Emissions and Its Implications Derived from Climate Model Experiments
Abe, Manabu; Kinoshita, Tsuguki; Hasegawa, Tomoko; Kawase, Hiroaki; Kushida, Kazuhide; Masui, Toshihiko; Oka, Kazutaka; Shiogama, Hideo; Takahashi, Kiyoshi; Tatebe, Hiroaki; Yoshikawa, Minoru
2017-01-01
In climate change research, future scenarios of greenhouse gas and air pollutant emissions generated by integrated assessment models (IAMs) are used in climate models (CMs) and earth system models to analyze future interactions and feedback between human activities and climate. However, the spatial resolutions of IAMs and CMs differ. IAMs usually disaggregate the world into 10–30 aggregated regions, whereas CMs require a grid-based spatial resolution. Therefore, downscaling emissions data from IAMs into a finer scale is necessary to input the emissions into CMs. In this study, we examined whether differences in downscaling methods significantly affect climate variables such as temperature and precipitation. We tested two downscaling methods using the same regionally aggregated sulfur emissions scenario obtained from the Asian-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model. The downscaled emissions were fed into the Model for Interdisciplinary Research on Climate (MIROC). One of the methods assumed a strong convergence of national emissions intensity (e.g., emissions per gross domestic product), while the other was based on inertia (i.e., the base-year remained unchanged). The emissions intensities in the downscaled spatial emissions generated from the two methods markedly differed, whereas the emissions densities (emissions per area) were similar. We investigated whether the climate change projections of temperature and precipitation would significantly differ between the two methods by applying a field significance test, and found little evidence of a significant difference between the two methods. Moreover, there was no clear evidence of a difference between the climate simulations based on these two downscaling methods. PMID:28076446
Quantum interference between transverse spatial waveguide modes.
Mohanty, Aseema; Zhang, Mian; Dutt, Avik; Ramelow, Sven; Nussenzveig, Paulo; Lipson, Michal
2017-01-20
Integrated quantum optics has the potential to markedly reduce the footprint and resource requirements of quantum information processing systems, but its practical implementation demands broader utilization of the available degrees of freedom within the optical field. To date, integrated photonic quantum systems have primarily relied on path encoding. However, in the classical regime, the transverse spatial modes of a multi-mode waveguide have been easily manipulated using the waveguide geometry to densely encode information. Here, we demonstrate quantum interference between the transverse spatial modes within a single multi-mode waveguide using quantum circuit-building blocks. This work shows that spatial modes can be controlled to an unprecedented level and have the potential to enable practical and robust quantum information processing.
[Evaluation of the lifetime of nail markings during polio vaccinations in Chad].
Quoc Cuong, Huong; Schlumberger, Martin; Garba Tchang, Salomon; Ould Cheikh, Dah; Savès, Marianne; Mallah, Barah; Demtilo Attilo, Jacques; Ngangro Mosurel, Ndeikoundam; Gamatié, Youssouf
2010-01-01
SID (Supplemental Immunization Days) is a special strategy intended to accelerate eradication of poliomyelitis in countries where it is still endemic (India, Afghanistan, and Pakistan in Asia, and Nigeria in Africa). This strategy is also applied in Nigeria's neighbours (Cameroon, Chad, Niger and Benin). Since the poliomyelitis virus was imported from Nigeria in 2001, Chad has reported cases of poliomyelitis every year. After 30 SIDs in Chad and the inaccurate or false attribution of side-effects to polio vaccines, some groups persistently refuse polio vaccination. To ascertain the true coverage of SID, the Ministry of Health and several partners (WHO, UNICEF and Rotary) conduct external coverage evaluations, to identify the under-vaccinated areas where population may be refusing immunization. The nails of the children receiving vaccinations are marked with indelible ink and those markings are the best indicator of the area's actual SID coverage. When coverage investigators arrive and propose vaccination to all children not immunized during SID, mothers who wish to refuse vaccination may claim that the children's markings disappeared after a few days, due to bathing. WHO experts have found that markings applied to their own nails with the WHO-recommended markers persist a few weeks, but others suggested that the markings may disappear much faster among children living in a traditional tropical environment. Until now, the lifetime of these markings has not been tested among children in Africa. To determine the lifetime of the fingernail markings after SID and factors that influence this lifetime in children young than 5 years old in Chad. This prospective cohort study of 200 children (aged 0 to 59 months) took place from March to May 2009 in Milezi, a health zone north of Ndjamena, the capital of Chad, in central Africa. These children received nail markings on their left little finger with an indelible marker pen provided by WHO. The finger was monitored for 35 days, visually and by photographs, to determine the factors associated with the lifetime of the markings. Kaplan-Meier and log-rank methods were applied to estimate their survival curve and the variables significant for their lifetime; the Cox proportional hazard model was used to determine multivariable-adjusted hazard ratios. Of the 184 children surveyed through the end of the study, the markings disappeared after 35 days of follow-up for 35% of them. The average lifetime of markings on these children was 28 days (SD: 4.95) and was associated, according to the Cox model, with 3 variables: the quality of the marking (RR = 0.335, 95% CI: 0.182-0.617, p < 0.001), playing with soil or mud (RR = 0.38, 95% CI: 0.208-0.697, p = 0.002), and living in different blocks, after stratification for the variable of application of chemical products on the nail. The latter could not be included in the Cox model because it made the markings disappear instantly. WHO experts were right in stating that the lifetime of the markings was sufficient to estimate coverage accurately when external evaluation takes place one or two weeks after SID. The only action found to make markings disappear rapidly was the application of chemical products. Mothers who tell SID attendance evaluation teams that the marking disappeared with bathing are expressing a tacit refusal of vaccination. These evaluations, which take place well before the disappearance of markings, help to determine the precise coverage of SID.
Harvester-based sensing system for cotton fiber-quality mapping
USDA-ARS?s Scientific Manuscript database
Precision agriculture in cotton production attempts to maximize profitability by exploiting information on field spatial variability to optimize the fiber yield and quality. For precision agriculture to be economically viable, collection of spatial variability data within a field must be automated a...
DOT National Transportation Integrated Search
2015-12-01
We develop an econometric framework for incorporating spatial dependence in integrated model systems of latent variables and multidimensional mixed data outcomes. The framework combines Bhats Generalized Heterogeneous Data Model (GHDM) with a spat...
Sea snakes rarely venture far from home
Lukoschek, Vimoksalehi; Shine, Richard
2012-01-01
The extent to which populations are connected by dispersal influences all aspects of their biology and informs the spatial scale of optimal conservation strategies. Obtaining direct estimates of dispersal is challenging, particularly in marine systems, with studies typically relying on indirect approaches to evaluate connectivity. To overcome this challenge, we combine information from an eight-year mark-recapture study with high-resolution genetic data to demonstrate extremely low dispersal and restricted gene flow at small spatial scales for a large, potentially mobile marine vertebrate, the turtleheaded sea snake (Emydocephalus annulatus). Our mark-recapture study indicated that adjacent bays in New Caledonia (<1.15 km apart) contain virtually separate sea snake populations. Sea snakes could easily swim between bays but rarely do so. Of 817 recaptures of marked snakes, only two snakes had moved between bays. We genotyped 136 snakes for 11 polymorphic microsatellite loci and found statistically significant genetic divergence between the two bays (FST= 0.008, P < 0.01). Bayesian clustering analyses detected low mixed ancestry within bays and genetic relatedness coefficients were higher, on average, within than between bays. Our results indicate that turtleheaded sea snakes rarely venture far from home, which has strong implications for their ecology, evolution, and conservation. PMID:22833788
Sea snakes rarely venture far from home.
Lukoschek, Vimoksalehi; Shine, Richard
2012-06-01
The extent to which populations are connected by dispersal influences all aspects of their biology and informs the spatial scale of optimal conservation strategies. Obtaining direct estimates of dispersal is challenging, particularly in marine systems, with studies typically relying on indirect approaches to evaluate connectivity. To overcome this challenge, we combine information from an eight-year mark-recapture study with high-resolution genetic data to demonstrate extremely low dispersal and restricted gene flow at small spatial scales for a large, potentially mobile marine vertebrate, the turtleheaded sea snake (Emydocephalus annulatus). Our mark-recapture study indicated that adjacent bays in New Caledonia (<1.15 km apart) contain virtually separate sea snake populations. Sea snakes could easily swim between bays but rarely do so. Of 817 recaptures of marked snakes, only two snakes had moved between bays. We genotyped 136 snakes for 11 polymorphic microsatellite loci and found statistically significant genetic divergence between the two bays (F(ST)= 0.008, P < 0.01). Bayesian clustering analyses detected low mixed ancestry within bays and genetic relatedness coefficients were higher, on average, within than between bays. Our results indicate that turtleheaded sea snakes rarely venture far from home, which has strong implications for their ecology, evolution, and conservation.
Craig, Marlies H; Sharp, Brian L; Mabaso, Musawenkosi LH; Kleinschmidt, Immo
2007-01-01
Background Several malaria risk maps have been developed in recent years, many from the prevalence of infection data collated by the MARA (Mapping Malaria Risk in Africa) project, and using various environmental data sets as predictors. Variable selection is a major obstacle due to analytical problems caused by over-fitting, confounding and non-independence in the data. Testing and comparing every combination of explanatory variables in a Bayesian spatial framework remains unfeasible for most researchers. The aim of this study was to develop a malaria risk map using a systematic and practicable variable selection process for spatial analysis and mapping of historical malaria risk in Botswana. Results Of 50 potential explanatory variables from eight environmental data themes, 42 were significantly associated with malaria prevalence in univariate logistic regression and were ranked by the Akaike Information Criterion. Those correlated with higher-ranking relatives of the same environmental theme, were temporarily excluded. The remaining 14 candidates were ranked by selection frequency after running automated step-wise selection procedures on 1000 bootstrap samples drawn from the data. A non-spatial multiple-variable model was developed through step-wise inclusion in order of selection frequency. Previously excluded variables were then re-evaluated for inclusion, using further step-wise bootstrap procedures, resulting in the exclusion of another variable. Finally a Bayesian geo-statistical model using Markov Chain Monte Carlo simulation was fitted to the data, resulting in a final model of three predictor variables, namely summer rainfall, mean annual temperature and altitude. Each was independently and significantly associated with malaria prevalence after allowing for spatial correlation. This model was used to predict malaria prevalence at unobserved locations, producing a smooth risk map for the whole country. Conclusion We have produced a highly plausible and parsimonious model of historical malaria risk for Botswana from point-referenced data from a 1961/2 prevalence survey of malaria infection in 1–14 year old children. After starting with a list of 50 potential variables we ended with three highly plausible predictors, by applying a systematic and repeatable staged variable selection procedure that included a spatial analysis, which has application for other environmentally determined infectious diseases. All this was accomplished using general-purpose statistical software. PMID:17892584
ERIC Educational Resources Information Center
Kopcha, Theodore J.; Otumfuor, Beryl A.; Wang, Lu
2015-01-01
This study examines the effects of spatial ability, gender differences, and pictorial training on fourth grade students' ability to recall landmark locations from memory. Ninety-six students used Google Earth over a 3-week period to locate landmarks (3-D) and mark their location on a 2-D topographical map. Analysis of covariance on posttest scores…
NASA Technical Reports Server (NTRS)
Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.
2014-01-01
Moderate Resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging Spectroradiomater (MISR) provide regular aerosol observations with global coverage. It is essential to examine the coherency between space- and ground-measured aerosol parameters in representing aerosol spatial and temporal variability, especially in the climate forcing and model validation context. In this paper, we introduce Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition analysis as an effective way to compare correlated aerosol spatial and temporal patterns between satellite measurements and AERONET data. This technique not only successfully extracts the variability of major aerosol regimes but also allows the simultaneous examination of the aerosol variability both spatially and temporally. More importantly, it well accommodates the sparsely distributed AERONET data, for which other spectral decomposition methods, such as Principal Component Analysis, do not yield satisfactory results. The comparison shows overall good agreement between MODIS/MISR and AERONET AOD variability. The correlations between the first three modes of MCA results for both MODIS/AERONET and MISR/ AERONET are above 0.8 for the full data set and above 0.75 for the AOD anomaly data. The correlations between MODIS and MISR modes are also quite high (greater than 0.9). We also examine the extent of spatial agreement between satellite and AERONET AOD data at the selected stations. Some sites with disagreements in the MCA results, such as Kanpur, also have low spatial coherency. This should be associated partly with high AOD spatial variability and partly with uncertainties in satellite retrievals due to the seasonally varying aerosol types and surface properties.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Huang, Maoyi; Liang, Xu; Leung, Lai R.
2008-12-05
Subsurface flow is an important hydrologic process and a key component of the water budget, especially in humid regions. In this study, a new subsurface flow formulation is developed that incorporates spatial variability of both topography and recharge. It is shown through theoretical derivation and case studies that the power law and exponential subsurface flow parameterizations and the parameterization proposed by Woods et al.[1997] are all special cases of the new formulation. The subsurface flows calculated using the new formulation compare well with values derived from observations at the Tulpehocken Creek and Walnut Creek watersheds. Sensitivity studies show that whenmore » the spatial variability of topography or recharge, or both is increased, the subsurface flows increase at the two aforementioned sites and the Maimai hillslope. This is likely due to enhancement of interactions between the groundwater table and the land surface that reduce the flow path. An important conclusion of this study is that the spatial variability of recharge alone, and/or in combination with the spatial variability of topography can substantially alter the behaviors of subsurface flows. This suggests that in macroscale hydrologic models or land surface models, subgrid variations of recharge and topography can make significant contributions to the grid mean subsurface flow and must be accounted for in regions with large surface heterogeneity. This is particularly true for regions with humid climate and relatively shallow groundwater table where the combined impacts of spatial variability of recharge and topography are shown to be more important. For regions with arid climate and relatively deep groundwater table, simpler formulations, especially the power law, for subsurface flow can work well, and the impacts of subgrid variations of recharge and topography may be ignored.« less
A Linkage of Recent Arctic Summer Sea Ice and Snowfall Variability of Japan
NASA Astrophysics Data System (ADS)
Iwamoto, K.; Honda, M.; Ukita, J.
2014-12-01
In spite of its mid-latitude location, Japan has a markedly high amount of snowfall, which owes much to the presence of cold air-break from Siberia and thus depends on the strength of the Siberian high and the Aleutian low. With this background this study examines the relationship between interannual variability and spatial patterns of snowfall in Japan with large-scale atmospheric and sea ice variations. The lag regression map of the winter snowfall in Japan on the time series of the Arctic SIE from the preceding summer shows a seesaw pattern in the snowfall, suggesting an Arctic teleconnection to regional weather. From the EOF analyses conducted on the snowfall distribution in Japan, we identify two modes with physical significance. The NH SIC and SLP regressed on PC1 show a sea ice reduction in the Barents and Kara Seas and anomalous strength of the Siberia high as discussed in Honda et al. (2009) and other studies, which support the above notion that the snowfall variability of Japan is influenced by Arctic sea ice conditions. Another mode is related to the AO/NAO and the hemispheric scale double sea-ice seesaw centered over the sub-Arctic region: one between the Labrador and Nordic Seas in the Atlantic and the other between the Okhotsk and Bering Seas from the Pacific as discussed in Ukita et al. (2007). Together, observations point to a significant role of the sea-ice in determining mid-latitude regional climate and weather patterns.
Mushet, David M.; Euliss, Ned H.; Chen, Yongjiu; Stockwell, Craig A.
2013-01-01
In contrast to most local amphibian populations, northeastern populations of the Northern Leopard Frog (Lithobates pipiens) have displayed uncharacteristically high levels of genetic diversity that have been attributed to large, stable populations. However, this widely distributed species also occurs in areas known for great climatic fluctuations that should be reflected in corresponding fluctuations in population sizes and reduced genetic diversity. To test our hypothesis that Northern Leopard Frog genetic diversity would be reduced in areas subjected to significant climate variability, we examined the genetic diversity of L. pipiens collected from 12 sites within the Prairie Pothole Region of North Dakota. Despite the region's fluctuating climate that includes periods of recurring drought and deluge, we found unexpectedly high levels of genetic diversity approaching that of northeastern populations. Further, genetic structure at a landscape scale was strikingly homogeneous; genetic differentiation estimates (Dest) averaged 0.10 (SD = 0.036) across the six microsatellite loci we studied, and two Bayesian assignment tests (STRUCTURE and BAPS) failed to reveal the development of significant population structure across the 68 km breadth of our study area. These results suggest that L. pipiens in the Prairie Pothole Region consists of a large, panmictic population capable of maintaining high genetic diversity in the face of marked climate variability.
NASA Astrophysics Data System (ADS)
Wang, Qiufeng; Tian, Jing; Yu, Guirui
2014-05-01
Patterns in the spatial distribution of organisms provide important information about mechanisms that regulate the diversity and complexity of soil ecosystems. Therefore, information on spatial distribution of microbial community composition and functional diversity is urgently necessary. The spatial variability on a 26×36 m plot and vertical distribution (0-10 cm and 10-20 cm) of soil microbial community composition and functional diversity were studied in a natural broad-leaved Korean pine (Pinus koraiensis) mixed forest soil in Changbai Mountain. The phospholipid fatty acid (PLFA) pattern was used to characterize the soil microbial community composition and was compared with the community substrate utilization pattern using Biolog. Bacterial biomass dominated and showed higher variability than fungal biomass at all scales examined. The microbial biomass decreased with soil depths increased and showed less variability in lower 10-20 cm soil layer. The Shannon-Weaver index value for microbial functional diversity showed higher variability in upper 0-10 cm than lower 10-20 cm soil layer. Carbohydrates, carboxylic acids, polymers and amino acids are the main carbon sources possessing higher utilization efficiency or utilization intensity. At the same time, the four carbon source types contributed to the differentiation of soil microbial communities. This study suggests the higher diversity and complexity for this mix forest ecosystem. To determine the driving factors that affect this spatial variability of microorganism is the next step for our study.
Minor, M A; Ermilov, S G; Philippov, D A; Prokin, A A
2016-11-01
We investigated communities of oribatid mites in five peat bogs in the north-west of the East European plain. We aimed to determine the extent to which geographic factors (latitude, separation distance), local environment (Sphagnum moss species, ground water level, biogeochemistry) and local habitat complexity (diversity of vascular plants and bryophytes in the surrounding plant community) influence diversity and community composition of Oribatida. There was a significant north-to-south increase in Oribatida abundance. In the variance partitioning, spatial factors explained 33.1 % of variability in abundance across samples; none of the environmental factors were significant. Across all bogs, Oribatida species richness and community composition were similar in Sphagnum rubellum and Sphagnum magellanicum, but significantly different and less diverse in Sphagnum cuspidatum. Sphagnum microhabitat explained 52.2 % of variability in Oribatida species richness, whereas spatial variables explained only 8.7 %. There was no distance decay in community similarity between bogs with increased geographical distance. The environmental variables explained 34.9 % of the variance in community structure, with vascular plants diversity, bryophytes diversity, and ground water level all contributing significantly; spatial variables explained 15.1 % of the total variance. Overall, only 50 % of the Oribatida community variance was explained by the spatial structure and environmental variables. We discuss relative importance of spatial and local environmental factors, and make general inferences about the formation of fauna in Sphagnum bogs.
Lequy, Emeline; Saby, Nicolas P A; Ilyin, Ilia; Bourin, Aude; Sauvage, Stéphane; Leblond, Sébastien
2017-07-15
Air pollution in trace elements (TE) remains a concern for public health in Europe. For this reasons, networks of air pollution concentrations or exposure are deployed, including a moss bio-monitoring programme in Europe. Spatial determinants of TE concentrations in mosses remain unclear. In this study, the French dataset of TE in mosses is analyzed by spatial autoregressive model to account for spatial structure of the data and several variables proven or suspected to affect TE concentrations in mosses. Such variables include source (atmospheric deposition and soil concentrations), protocol (sampling month, collector, and moss species), and environment (forest type and canopy density, distance to the coast or the highway, and elevation). Modeled atmospheric deposition was only available for Cd and Pb and was one of the main explanatory variables of the concentrations in mosses. Predicted soil content was also an important explanatory variable except for Cr, Ni, and Zn. However, the moss species was the main factor for all the studied TE. The other environmental variables affected differently the TE. In particular, the forest type and canopy density were important in most cases. These results stress the need for further research on the effect of the moss species on the capture and retention of TE, as well as for accounting for several variables and the spatial structure of the data in statistical analyses. Copyright © 2017 Elsevier B.V. All rights reserved.
Spatial and temporal variability in rates of landsliding in seismically active mountain ranges
NASA Astrophysics Data System (ADS)
Parker, R.; Petley, D.; Rosser, N.; Densmore, A.; Gunasekera, R.; Brain, M.
2012-04-01
Where earthquake and precipitation driven disasters occur in steep, mountainous regions, landslides often account for a large proportion of the associated damage and losses. This research addresses spatial and temporal variability in rates of landslide occurrence in seismically active mountain ranges as a step towards developing better regional scale prediction of losses in such events. In the first part of this paper we attempt to explain reductively the variability in spatial rates of landslide occurrence, using data from five major earthquakes. This is achieved by fitting a regression-based conditional probability model to spatial probabilities of landslide occurrence, using as predictor variables proxies for spatial patterns of seismic ground motion and modelled hillslope stability. A combined model for all earthquakes performs well in hindcasting spatial probabilities of landslide occurrence as a function of readily-attainable spatial variables. We present validation of the model and demonstrate the extent to which it may be applied globally to derive landslide probabilities for future earthquakes. In part two we examine the temporal behaviour of rates of landslide occurrence. This is achieved through numerical modelling to simulate the behaviour of a hypothetical landscape. The model landscape is composed of hillslopes that continually weaken, fail and reset in response to temporally-discrete forcing events that represent earthquakes. Hillslopes with different geometries require different amounts of weakening to fail, such that they fail and reset at different temporal rates. Our results suggest that probabilities of landslide occurrence are not temporally constant, but rather vary with time, irrespective of changes in forcing event magnitudes or environmental conditions. Various parameters influencing the magnitude and temporal patterns of this variability are identified, highlighting areas where future research is needed. This model has important implications for landslide hazard and risk analysis in mountain areas as existing techniques usually assume that susceptibility to failure does not change with time.
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.
Drivers of metacommunity structure diverge for common and rare Amazonian tree species.
Bispo, Polyanna da Conceição; Balzter, Heiko; Malhi, Yadvinder; Slik, J W Ferry; Dos Santos, João Roberto; Rennó, Camilo Daleles; Espírito-Santo, Fernando D; Aragão, Luiz E O C; Ximenes, Arimatéa C; Bispo, Pitágoras da Conceição
2017-01-01
We analysed the flora of 46 forest inventory plots (25 m x 100 m) in old growth forests from the Amazonian region to identify the role of environmental (topographic) and spatial variables (obtained using PCNM, Principal Coordinates of Neighbourhood Matrix analysis) for common and rare species. For the analyses, we used multiple partial regression to partition the specific effects of the topographic and spatial variables on the univariate data (standardised richness, total abundance and total biomass) and partial RDA (Redundancy Analysis) to partition these effects on composition (multivariate data) based on incidence, abundance and biomass. The different attributes (richness, abundance, biomass and composition based on incidence, abundance and biomass) used to study this metacommunity responded differently to environmental and spatial processes. Considering standardised richness, total abundance (univariate) and composition based on biomass, the results for common species differed from those obtained for all species. On the other hand, for total biomass (univariate) and for compositions based on incidence and abundance, there was a correspondence between the data obtained for the total community and for common species. Our data also show that in general, environmental and/or spatial components are important to explain the variability in tree communities for total and common species. However, with the exception of the total abundance, the environmental and spatial variables measured were insufficient to explain the attributes of the communities of rare species. These results indicate that predicting the attributes of rare tree species communities based on environmental and spatial variables is a substantial challenge. As the spatial component was relevant for several community attributes, our results demonstrate the importance of using a metacommunities approach when attempting to understand the main ecological processes underlying the diversity of tropical forest communities.
Mukerjee, Shaibal; Smith, Luther A; Johnson, Mary M; Neas, Lucas M; Stallings, Casson A
2009-08-01
Passive ambient air sampling for nitrogen dioxide (NO(2)) and volatile organic compounds (VOCs) was conducted at 25 school and two compliance sites in Detroit and Dearborn, Michigan, USA during the summer of 2005. Geographic Information System (GIS) data were calculated at each of 116 schools. The 25 selected schools were monitored to assess and model intra-urban gradients of air pollutants to evaluate impact of traffic and urban emissions on pollutant levels. Schools were chosen to be statistically representative of urban land use variables such as distance to major roadways, traffic intensity around the schools, distance to nearest point sources, population density, and distance to nearest border crossing. Two approaches were used to investigate spatial variability. First, Kruskal-Wallis analyses and pairwise comparisons on data from the schools examined coarse spatial differences based on city section and distance from heavily trafficked roads. Secondly, spatial variation on a finer scale and as a response to multiple factors was evaluated through land use regression (LUR) models via multiple linear regression. For weeklong exposures, VOCs did not exhibit spatial variability by city section or distance from major roads; NO(2) was significantly elevated in a section dominated by traffic and industrial influence versus a residential section. Somewhat in contrast to coarse spatial analyses, LUR results revealed spatial gradients in NO(2) and selected VOCs across the area. The process used to select spatially representative sites for air sampling and the results of coarse and fine spatial variability of air pollutants provide insights that may guide future air quality studies in assessing intra-urban gradients.
On the uncertainties associated with using gridded rainfall data as a proxy for observed
NASA Astrophysics Data System (ADS)
Tozer, C. R.; Kiem, A. S.; Verdon-Kidd, D. C.
2012-05-01
Gridded rainfall datasets are used in many hydrological and climatological studies, in Australia and elsewhere, including for hydroclimatic forecasting, climate attribution studies and climate model performance assessments. The attraction of the spatial coverage provided by gridded data is clear, particularly in Australia where the spatial and temporal resolution of the rainfall gauge network is sparse. However, the question that must be asked is whether it is suitable to use gridded data as a proxy for observed point data, given that gridded data is inherently "smoothed" and may not necessarily capture the temporal and spatial variability of Australian rainfall which leads to hydroclimatic extremes (i.e. droughts, floods). This study investigates this question through a statistical analysis of three monthly gridded Australian rainfall datasets - the Bureau of Meteorology (BOM) dataset, the Australian Water Availability Project (AWAP) and the SILO dataset. The results of the monthly, seasonal and annual comparisons show that not only are the three gridded datasets different relative to each other, there are also marked differences between the gridded rainfall data and the rainfall observed at gauges within the corresponding grids - particularly for extremely wet or extremely dry conditions. Also important is that the differences observed appear to be non-systematic. To demonstrate the hydrological implications of using gridded data as a proxy for gauged data, a rainfall-runoff model is applied to one catchment in South Australia initially using gauged data as the source of rainfall input and then gridded rainfall data. The results indicate a markedly different runoff response associated with each of the different sources of rainfall data. It should be noted that this study does not seek to identify which gridded dataset is the "best" for Australia, as each gridded data source has its pros and cons, as does gauged data. Rather, the intention is to quantify differences between various gridded data sources and how they compare with gauged data so that these differences can be considered and accounted for in studies that utilise these gridded datasets. Ultimately, if key decisions are going to be based on the outputs of models that use gridded data, an estimate (or at least an understanding) of the uncertainties relating to the assumptions made in the development of gridded data and how that gridded data compares with reality should be made.
Phytoplankton plasticity drives large variability in carbon fixation efficiency
NASA Astrophysics Data System (ADS)
Ayata, Sakina-Dorothée.; Lévy, Marina; Aumont, Olivier; Resplandy, Laure; Tagliabue, Alessandro; Sciandra, Antoine; Bernard, Olivier
2014-12-01
Phytoplankton C:N stoichiometry is highly flexible due to physiological plasticity, which could lead to high variations in carbon fixation efficiency (carbon consumption relative to nitrogen). However, the magnitude, as well as the spatial and temporal scales of variability, remains poorly constrained. We used a high-resolution biogeochemical model resolving various scales from small to high, spatially and temporally, in order to quantify and better understand this variability. We find that phytoplankton C:N ratio is highly variable at all spatial and temporal scales (5-12 molC/molN), from mesoscale to regional scale, and is mainly driven by nitrogen supply. Carbon fixation efficiency varies accordingly at all scales (±30%), with higher values under oligotrophic conditions and lower values under eutrophic conditions. Hence, phytoplankton plasticity may act as a buffer by attenuating carbon sequestration variability. Our results have implications for in situ estimations of C:N ratios and for future predictions under high CO2 world.
Defining Chlorophyll-a Reference Conditions in European Lakes
Alves, Maria Helena; Argillier, Christine; van den Berg, Marcel; Buzzi, Fabio; Hoehn, Eberhard; de Hoyos, Caridad; Karottki, Ivan; Laplace-Treyture, Christophe; Solheim, Anne Lyche; Ortiz-Casas, José; Ott, Ingmar; Phillips, Geoff; Pilke, Ansa; Pádua, João; Remec-Rekar, Spela; Riedmüller, Ursula; Schaumburg, Jochen; Serrano, Maria Luisa; Soszka, Hanna; Tierney, Deirdre; Urbanič, Gorazd; Wolfram, Georg
2010-01-01
The concept of “reference conditions” describes the benchmark against which current conditions are compared when assessing the status of water bodies. In this paper we focus on the establishment of reference conditions for European lakes according to a phytoplankton biomass indicator—the concentration of chlorophyll-a. A mostly spatial approach (selection of existing lakes with no or minor human impact) was used to set the reference conditions for chlorophyll-a values, supplemented by historical data, paleolimnological investigations and modelling. The work resulted in definition of reference conditions and the boundary between “high” and “good” status for 15 main lake types and five ecoregions of Europe: Alpine, Atlantic, Central/Baltic, Mediterranean, and Northern. Additionally, empirical models were developed for estimating site-specific reference chlorophyll-a concentrations from a set of potential predictor variables. The results were recently formulated into the EU legislation, marking the first attempt in international water policy to move from chemical quality standards to ecological quality targets. PMID:20401659
Phenological sensitivity to climate across taxa and trophic levels.
Thackeray, Stephen J; Henrys, Peter A; Hemming, Deborah; Bell, James R; Botham, Marc S; Burthe, Sarah; Helaouet, Pierre; Johns, David G; Jones, Ian D; Leech, David I; Mackay, Eleanor B; Massimino, Dario; Atkinson, Sian; Bacon, Philip J; Brereton, Tom M; Carvalho, Laurence; Clutton-Brock, Tim H; Duck, Callan; Edwards, Martin; Elliott, J Malcolm; Hall, Stephen J G; Harrington, Richard; Pearce-Higgins, James W; Høye, Toke T; Kruuk, Loeske E B; Pemberton, Josephine M; Sparks, Tim H; Thompson, Paul M; White, Ian; Winfield, Ian J; Wanless, Sarah
2016-07-14
Differences in phenological responses to climate change among species can desynchronise ecological interactions and thereby threaten ecosystem function. To assess these threats, we must quantify the relative impact of climate change on species at different trophic levels. Here, we apply a Climate Sensitivity Profile approach to 10,003 terrestrial and aquatic phenological data sets, spatially matched to temperature and precipitation data, to quantify variation in climate sensitivity. The direction, magnitude and timing of climate sensitivity varied markedly among organisms within taxonomic and trophic groups. Despite this variability, we detected systematic variation in the direction and magnitude of phenological climate sensitivity. Secondary consumers showed consistently lower climate sensitivity than other groups. We used mid-century climate change projections to estimate that the timing of phenological events could change more for primary consumers than for species in other trophic levels (6.2 versus 2.5-2.9 days earlier on average), with substantial taxonomic variation (1.1-14.8 days earlier on average).
Proximate causes of natal dispersal in female yellow-bellied marmots, Marmota flaviventris.
Armitage, Kenneth B; Van Vuren, Dirk H; Ozgul, Arpat; Oli, Madan K
2011-01-01
We investigated factors influencing natal dispersal in 231 female yearling yellow-bellied marmots (Marmota flaviventris) using comprehensive analysis of 10 years (1983-1993) of radiotelemetry and 37 years (1963-1999) of capture-mark-recapture data. Only individuals whose dispersal status was verified, primarily by radiotelemetry, were considered. Univariate analyses revealed that six of the 24 variables we studied significantly influenced dispersal: dispersal was less likely when the mother was present, amicable behavior with the mother and play behavior were more frequent, and spatial overlap was greater with the mother, with matriline females, and with other yearling females. Using both univariate and multivariate analyses, we tested several hypotheses proposed as proximate causes of dispersal. We rejected inbreeding avoidance, population density, body size, social intolerance, and kin competition as factors influencing dispersal. Instead, our results indicate that kin cooperation, expressed via cohesive behaviors and with a focus on the mother, influenced dispersal by promoting philopatry. Kin cooperation may be an underappreciated factor influencing dispersal in both social and nonsocial species.
The Dallas-Fort Worth Airport Earthquake Sequence: Seismicity Beyond Injection Period
NASA Astrophysics Data System (ADS)
Ogwari, Paul O.; DeShon, Heather R.; Hornbach, Matthew J.
2018-01-01
The 2008 Dallas-Fort Worth Airport earthquakes mark the beginning of seismicity rate changes linked to oil and gas operations in the central United States. We assess the spatial and temporal evolution of the sequence through December 2015 using template-based waveform correlation and relative location methods. We locate 400 earthquakes spanning 2008-2015 along a basement fault mapped as the Airport fault. The sequence exhibits temporally variable b values, and small-magnitude (m < 3.4) earthquakes spread northeast along strike over time. Pore pressure diffusion models indicate that the high-volume brine injection well located within 1 km of the 2008 earthquakes, although only operating from September 2008 to August 2009, contributes most significantly to long-term pressure perturbations, and hence stress changes, along the fault; a second long-operating, low-volume injector located 10 km north causes insufficient pressure changes. High-volume injection for a short time period near a critically stressed fault can induce long-lasting seismicity.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garten Jr, Charles T; Kang, S.; Brice, Deanne Jane
2007-01-01
The purpose of this research was to test the hypothesis that variability in 11 soil properties, related to soil texture and soil C and N, would increase from small (1 m) to large (1 km) spatial scales in a temperate, mixed-hardwood forest ecosystem in east Tennessee, USA. The results were somewhat surprising and indicated that a fundamental assumption in geospatial analysis, namely that variability increases with increasing spatial scale, did not apply for at least five of the 11 soil properties measured over a 0.5-km2 area. Composite mineral soil samples (15 cm deep) were collected at 1, 5, 10, 50,more » 250, and 500 m distances from a center point along transects in a north, south, east, and westerly direction. A null hypothesis of equal variance at different spatial scales was rejected (P{le}0.05) for mineral soil C concentration, silt content, and the C-to-N ratios in particulate organic matter (POM), mineral-associated organic matter (MOM), and whole surface soil. Results from different tests of spatial variation, based on coefficients of variation or a Mantel test, led to similar conclusions about measurement variability and geographic distance for eight of the 11 variables examined. Measurements of mineral soil C and N concentrations, C concentrations in MOM, extractable soil NH{sub 4}-N, and clay contents were just as variable at smaller scales (1-10 m) as they were at larger scales (50-500 m). On the other hand, measurement variation in mineral soil C-to-N ratios, MOM C-to-N ratios, and the fraction of soil C in POM clearly increased from smaller to larger spatial scales. With the exception of extractable soil NH4-N, measured soil properties in the forest ecosystem could be estimated (with 95% confidence) to within 15% of their true mean with a relatively modest number of sampling points (n{le}25). For some variables, scaling up variation from smaller to larger spatial domains within the ecosystem could be relatively easy because small-scale variation may be indicative of variation at larger scales.« less
Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P. A.; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel
2014-01-01
Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes
Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel
2014-01-01
Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes
Impacts of rainfall spatial variability on hydrogeological response
NASA Astrophysics Data System (ADS)
Sapriza-Azuri, Gonzalo; Jódar, Jorge; Navarro, Vicente; Slooten, Luit Jan; Carrera, Jesús; Gupta, Hoshin V.
2015-02-01
There is currently no general consensus on how the spatial variability of rainfall impacts and propagates through complex hydrogeological systems. Most studies to date have focused on the effects of rainfall spatial variability (RSV) on river discharge, while paying little attention to other important aspects of system response. Here, we study the impacts of RSV on several responses of a hydrological model of an overexploited system. To this end, we drive a spatially distributed hydrogeological model for the semiarid Upper Guadiana basin in central Spain with stochastic daily rainfall fields defined at three different spatial resolutions (fine → 2.5 km × 2.5 km, medium → 50 km × 50 km, large → lumped). This enables us to investigate how (i) RSV at different spatial resolutions, and (ii) rainfall uncertainty, are propagated through the hydrogeological model of the system. Our results demonstrate that RSV has a significant impact on the modeled response of the system, by specifically affecting groundwater recharge and runoff generation, and thereby propagating through to various other related hydrological responses (river discharge, river-aquifer exchange, groundwater levels). These results call into question the validity of management decisions made using hydrological models calibrated or forced with spatially lumped rainfall.
NASA Astrophysics Data System (ADS)
Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz
2017-04-01
This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.
High spatial variability of carbon dioxide and methane emission in three tropical reservoirs
NASA Astrophysics Data System (ADS)
Reinaldo Paranaiba, José; Barros, Nathan O.; Mendonça, Raquel F.; Linkhorst, Annika; Isidorova, Anastasija; Roland, Fabio; Sobek, Sebastian
2017-04-01
In the tropics, many new large hydropower dams are being built, in order to produce renewable energy for economic growth. Most inland waters, such as rivers, lakes and reservoirs, emit greenhouse gases to the atmosphere, and especially tropical reservoirs have been pointed out as strong sources of methane. However, present estimates of greenhouse gas emission from reservoirs are limited by the amount of available data. In particular, the spatial variability of greenhouse gas emission from reservoirs is insufficiently understood. In order to test the hypothesis that the diffusive emission of carbon dioxide (CO2) and methane (CH4) from tropical reservoirs is characterized by strong spatial variability and incorrectly represented by measurements at one site only, we studied three reservoirs situated in different tropical climates, during the dry period. We conducted spatially resolved measurements of surface water concentrations of dissolved carbon dioxide and methane using an on-line equilibration system, as well as of the gas exchange velocity using floating chambers. We found pronounced spatial variability of diffusive CO2 and CH4 emission in all three reservoirs. River inflow areas were more likely to have high concentrations of particularly CH4, but also CO2, than other areas in the reservoirs. Close to the dam, CH4 concentrations were comparatively low in each reservoir. The variability of CH4 concentration was linked to geographical position, which we ascribe to hot spots of methanogenesis at sites of high sediment deposition, such as river inflow areas. The variability of CO2 concentration seemed instead rather to be linked to in-situ metabolism. Also the gas exchange velocity varied pronouncedly in each reservoir, but without any detectable systematic patterns, calling for further studies. We conclude that accurate upscaling of reservoir greenhouse gas emissions requires accounting for within-reservoir spatial variability, and that the anthropogenic increase of sediment flux from catchments to downstream reservoirs may be linked to increased reservoir CH4 emission.
Ho, Hung Chak; Knudby, Anders; Walker, Blake Byron; Henderson, Sarah B
2017-01-01
Climate change has increased the frequency and intensity of extremely hot weather. The health risks associated with extemely hot weather are not uniform across affected areas owing to variability in heat exposure and social vulnerability, but these differences are challenging to map with precision. We developed a spatially and temporally stratified case-crossover approach for delineation of areas with higher and lower risks of mortality on extremely hot days and applied this approach in greater Vancouver, Canada. Records of all deaths with an extremely hot day as a case day or a control day were extracted from an administrative vital statistics database spanning the years of 1998-2014. Three heat exposure and 11 social vulnerability variables were assigned at the residential location of each decedent. Conditional logistic regression was used to estimate the odds ratio for a 1°C increase in daily mean temperature at a fixed site with an interaction term for decedents living above and below different values of the spatial variables. The heat exposure and social vulnerability variables with the strongest spatially stratified results were the apparent temperature and the labor nonparticipation rate, respectively. Areas at higher risk had values ≥ 34.4°C for the maximum apparent temperature and ≥ 60% of the population neither employed nor looking for work. These variables were combined in a composite index to quantify their interaction and to enhance visualization of high-risk areas. Our methods provide a data-driven framework for spatial delineation of the temperature--mortality relationship by heat exposure and social vulnerability. The results can be used to map and target the most vulnerable areas for public health intervention. Citation: Ho HC, Knudby A, Walker BB, Henderson SB. 2017. Delineation of spatial variability in the temperature-mortality relationship on extremely hot days in greater Vancouver, Canada. Environ Health Perspect 125:66-75; http://dx.doi.org/10.1289/EHP224.
Ho, Hung Chak; Knudby, Anders; Walker, Blake Byron; Henderson, Sarah B.
2016-01-01
Background: Climate change has increased the frequency and intensity of extremely hot weather. The health risks associated with extemely hot weather are not uniform across affected areas owing to variability in heat exposure and social vulnerability, but these differences are challenging to map with precision. Objectives: We developed a spatially and temporally stratified case-crossover approach for delineation of areas with higher and lower risks of mortality on extremely hot days and applied this approach in greater Vancouver, Canada. Methods: Records of all deaths with an extremely hot day as a case day or a control day were extracted from an administrative vital statistics database spanning the years of 1998–2014. Three heat exposure and 11 social vulnerability variables were assigned at the residential location of each decedent. Conditional logistic regression was used to estimate the odds ratio for a 1°C increase in daily mean temperature at a fixed site with an interaction term for decedents living above and below different values of the spatial variables. Results: The heat exposure and social vulnerability variables with the strongest spatially stratified results were the apparent temperature and the labor nonparticipation rate, respectively. Areas at higher risk had values ≥ 34.4°C for the maximum apparent temperature and ≥ 60% of the population neither employed nor looking for work. These variables were combined in a composite index to quantify their interaction and to enhance visualization of high-risk areas. Conclusions: Our methods provide a data-driven framework for spatial delineation of the temperature-–mortality relationship by heat exposure and social vulnerability. The results can be used to map and target the most vulnerable areas for public health intervention. Citation: Ho HC, Knudby A, Walker BB, Henderson SB. 2017. Delineation of spatial variability in the temperature–mortality relationship on extremely hot days in greater Vancouver, Canada. Environ Health Perspect 125:66–75; http://dx.doi.org/10.1289/EHP224 PMID:27346526
Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying
2016-01-01
Background Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. Methods The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008–2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. Results The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse “V” shape and “V” shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. Conclusion We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across provinces. Future research should explore the risk factors that cause spatial correlated structure or high variation of HFMD incidence which can be explained by temperature. When analyzing association between HFMD incidence and climatic variables, spatial heterogeneity among provinces should be evaluated. Moreover, the extra-Poisson multilevel model was capable of modeling the association between overdispersion of HFMD incidence and climatic variables. PMID:26808311
Liao, Jiaqiang; Yu, Shicheng; Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying
2016-01-01
Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008-2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse "V" shape and "V" shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across provinces. Future research should explore the risk factors that cause spatial correlated structure or high variation of HFMD incidence which can be explained by temperature. When analyzing association between HFMD incidence and climatic variables, spatial heterogeneity among provinces should be evaluated. Moreover, the extra-Poisson multilevel model was capable of modeling the association between overdispersion of HFMD incidence and climatic variables.
Groundwater Variability Across Temporal and Spatial Scales in the Central and Northeastern U.S.
NASA Technical Reports Server (NTRS)
Li, Bailing; Rodell, Matthew; Famiglietti, James S.
2015-01-01
Depth-to-water measurements from 181 monitoring wells in unconfined or semi-confined aquifers in nine regions of the central and northeastern U.S. were analyzed. Groundwater storage exhibited strong seasonal variations in all regions, with peaks in spring and lows in autumn, and its interannual variability was nearly unbounded, such that the impacts of droughts, floods, and excessive pumping could persist for many years. We found that the spatial variability of groundwater storage anomalies (deviations from the long term mean) increases as a power function of extent scale (square root of area). That relationship, which is linear on a log-log graph, is common to other hydrological variables but had never before been shown with groundwater data. We describe how the derived power function can be used to determine the number of wells needed to estimate regional mean groundwater storage anomalies with a desired level of accuracy, or to assess uncertainty in regional mean estimates from a set number of observations. We found that the spatial variability of groundwater storage anomalies within a region often increases with the absolute value of the regional mean anomaly, the opposite of the relationship between soil moisture spatial variability and mean. Recharge (drainage from the lowest model soil layer) simulated by the Variable Infiltration Capacity (VIC) model was compatible with observed monthly groundwater storage anomalies and month-to-month changes in groundwater storage.
SimAlba: A Spatial Microsimulation Approach to the Analysis of Health Inequalities
Campbell, Malcolm; Ballas, Dimitris
2016-01-01
This paper presents applied geographical research based on a spatial microsimulation model, SimAlba, aimed at estimating geographically sensitive health variables in Scotland. SimAlba has been developed in order to answer a variety of “what-if” policy questions pertaining to health policy in Scotland. Using the SimAlba model, it is possible to simulate the distributions of previously unknown variables at the small area level such as smoking, alcohol consumption, mental well-being, and obesity. The SimAlba microdataset has been created by combining Scottish Health Survey and Census data using a deterministic reweighting spatial microsimulation algorithm developed for this purpose. The paper presents SimAlba outputs for Scotland’s largest city, Glasgow, and examines the spatial distribution of the simulated variables for small geographical areas in Glasgow as well as the effects on individuals of different policy scenario outcomes. In simulating previously unknown spatial data, a wealth of new perspectives can be examined and explored. This paper explores a small set of those potential avenues of research and shows the power of spatial microsimulation modeling in an urban context. PMID:27818989
Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.
Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J
2010-12-01
Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies conservation planning. Journal compilation © 2010 Society for Conservation Biology. No claim to original US government works.
Bayesian spatio-temporal discard model in a demersal trawl fishery
NASA Astrophysics Data System (ADS)
Grazia Pennino, M.; Muñoz, Facundo; Conesa, David; López-Quílez, Antonio; Bellido, José M.
2014-07-01
Spatial management of discards has recently been proposed as a useful tool for the protection of juveniles, by reducing discard rates and can be used as a buffer against management errors and recruitment failure. In this study Bayesian hierarchical spatial models have been used to analyze about 440 trawl fishing operations of two different metiers, sampled between 2009 and 2012, in order to improve our understanding of factors that influence the quantity of discards and to identify their spatio-temporal distribution in the study area. Our analysis showed that the relative importance of each variable was different for each metier, with a few similarities. In particular, the random vessel effect and seasonal variability were identified as main driving variables for both metiers. Predictive maps of the abundance of discards and maps of the posterior mean of the spatial component show several hot spots with high discard concentration for each metier. We argue how the seasonal/spatial effects, and the knowledge about the factors influential to discarding, could potentially be exploited as potential mitigation measures for future fisheries management strategies. However, misidentification of hotspots and uncertain predictions can culminate in inappropriate mitigation practices which can sometimes be irreversible. The proposed Bayesian spatial method overcomes these issues, since it offers a unified approach which allows the incorporation of spatial random-effect terms, spatial correlation of the variables and the uncertainty of the parameters in the modeling process, resulting in a better quantification of the uncertainty and accurate predictions.
Pressey, Robert L.; Weeks, Rebecca; Andréfouët, Serge; Moloney, James
2016-01-01
Spatial data characteristics have the potential to influence various aspects of prioritising biodiversity areas for systematic conservation planning. There has been some exploration of the combined effects of size of planning units and level of classification of physical environments on the pattern and extent of priority areas. However, these data characteristics have yet to be explicitly investigated in terms of their interaction with different socioeconomic cost data during the spatial prioritisation process. We quantify the individual and interacting effects of three factors—planning-unit size, thematic resolution of reef classes, and spatial variability of socioeconomic costs—on spatial priorities for marine conservation, in typical marine planning exercises that use reef classification maps as a proxy for biodiversity. We assess these factors by creating 20 unique prioritisation scenarios involving combinations of different levels of each factor. Because output data from these scenarios are analogous to ecological data, we applied ecological statistics to determine spatial similarities between reserve designs. All three factors influenced prioritisations to different extents, with cost variability having the largest influence, followed by planning-unit size and thematic resolution of reef classes. The effect of thematic resolution on spatial design depended on the variability of cost data used. In terms of incidental representation of conservation objectives derived from finer-resolution data, scenarios prioritised with uniform cost outperformed those prioritised with variable cost. Following our analyses, we make recommendations to help maximise the spatial and cost efficiency and potential effectiveness of future marine conservation plans in similar planning scenarios. We recommend that planners: employ the smallest planning-unit size practical; invest in data at the highest possible resolution; and, when planning across regional extents with the intention of incidentally representing fine-resolution features, prioritise the whole region with uniform costs rather than using coarse-resolution data on variable costs. PMID:27829042
Cheok, Jessica; Pressey, Robert L; Weeks, Rebecca; Andréfouët, Serge; Moloney, James
2016-01-01
Spatial data characteristics have the potential to influence various aspects of prioritising biodiversity areas for systematic conservation planning. There has been some exploration of the combined effects of size of planning units and level of classification of physical environments on the pattern and extent of priority areas. However, these data characteristics have yet to be explicitly investigated in terms of their interaction with different socioeconomic cost data during the spatial prioritisation process. We quantify the individual and interacting effects of three factors-planning-unit size, thematic resolution of reef classes, and spatial variability of socioeconomic costs-on spatial priorities for marine conservation, in typical marine planning exercises that use reef classification maps as a proxy for biodiversity. We assess these factors by creating 20 unique prioritisation scenarios involving combinations of different levels of each factor. Because output data from these scenarios are analogous to ecological data, we applied ecological statistics to determine spatial similarities between reserve designs. All three factors influenced prioritisations to different extents, with cost variability having the largest influence, followed by planning-unit size and thematic resolution of reef classes. The effect of thematic resolution on spatial design depended on the variability of cost data used. In terms of incidental representation of conservation objectives derived from finer-resolution data, scenarios prioritised with uniform cost outperformed those prioritised with variable cost. Following our analyses, we make recommendations to help maximise the spatial and cost efficiency and potential effectiveness of future marine conservation plans in similar planning scenarios. We recommend that planners: employ the smallest planning-unit size practical; invest in data at the highest possible resolution; and, when planning across regional extents with the intention of incidentally representing fine-resolution features, prioritise the whole region with uniform costs rather than using coarse-resolution data on variable costs.
NASA Astrophysics Data System (ADS)
Noth, Elizabeth M.; Hammond, S. Katharine; Biging, Gregory S.; Tager, Ira B.
2011-05-01
BackgroundPolycyclic aromatic hydrocarbons (PAHs) are generated as a byproduct of combustion, and are associated with respiratory symptoms and increased risk of asthma attacks. ObjectivesTo assign daily, outdoor exposures to participants in the Fresno Asthmatic Children's Environment Study (FACES) using land use regression models for the sum of 4-, 5- and 6-ring PAHs (PAH456). MethodsPAH data were collected daily at the EPA Supersite in Fresno, CA from 10/2000 through 2/2007. From 2/2002 to 2/2003, intensive air pollution sampling was conducted at 83 homes of participants in the FACES study. These measurement data were combined with meteorological data, source data, and other spatial variables to form a land use regression model to assign daily exposure at all FACES homes for all years of the study (2001-2008). ResultsThe model for daily, outdoor residential PAH456 concentrations accounted for 80% of the between-home variability and 18% of the within-home variability. Both temporal and spatial variables were significant in the model. Traffic characteristics and home heating fuel were the main spatial explanatory variables. ConclusionsBecause spatial and temporal distributions of PAHs vary on an intra-urban scale, the location of the child's home within the urban setting plays an important role in the level of exposure that each child has to PAHs.
Spatial modeling of households' knowledge about arsenic pollution in Bangladesh.
Sarker, M Mizanur Rahman
2012-04-01
Arsenic in drinking water is an important public health issue in Bangladesh, which is affected by households' knowledge about arsenic threats from their drinking water. In this study, spatial statistical models were used to investigate the determinants and spatial dependence of households' knowledge about arsenic risk. The binary join matrix/binary contiguity matrix and inverse distance spatial weight matrix techniques are used to capture spatial dependence in the data. This analysis extends the spatial model by allowing spatial dependence to vary across divisions and regions. A positive spatial correlation was found in households' knowledge across neighboring districts at district, divisional and regional levels, but the strength of this spatial correlation varies considerably by spatial weight. Literacy rate, daily wage rate of agricultural labor, arsenic status, and percentage of red mark tube well usage in districts were found to contribute positively and significantly to households' knowledge. These findings have policy implications both at regional and national levels in mitigating the present arsenic crisis and to ensure arsenic-free water in Bangladesh. Copyright © 2012 Elsevier Ltd. All rights reserved.
Kimball T. Harper; John D. Shane; John R. Jones
1985-01-01
Quaking aspen, or trembling aspen (Populus tremuloides), was named and described by Michaux in 1803. It exhibits marked phenotypic variability throughout its transcontinental range. Numerous authors, especially the early ones, tried to give order to the variability by subdividing it taxonomically. Quahng aspen has been subdivided by various...
Gebler, J.B.
2004-01-01
The related topics of spatial variability of aquatic invertebrate community metrics, implications of spatial patterns of metric values to distributions of aquatic invertebrate communities, and ramifications of natural variability to the detection of human perturbations were investigated. Four metrics commonly used for stream assessment were computed for 9 stream reaches within a fairly homogeneous, minimally impaired stream segment of the San Pedro River, Arizona. Metric variability was assessed for differing sampling scenarios using simple permutation procedures. Spatial patterns of metric values suggest that aquatic invertebrate communities are patchily distributed on subsegment and segment scales, which causes metric variability. Wide ranges of metric values resulted in wide ranges of metric coefficients of variation (CVs) and minimum detectable differences (MDDs), and both CVs and MDDs often increased as sample size (number of reaches) increased, suggesting that any particular set of sampling reaches could yield misleading estimates of population parameters and effects that can be detected. Mean metric variabilities were substantial, with the result that only fairly large differences in metrics would be declared significant at ?? = 0.05 and ?? = 0.20. The number of reaches required to obtain MDDs of 10% and 20% varied with significance level and power, and differed for different metrics, but were generally large, ranging into tens and hundreds of reaches. Study results suggest that metric values from one or a small number of stream reach(es) may not be adequate to represent a stream segment, depending on effect sizes of interest, and that larger sample sizes are necessary to obtain reasonable estimates of metrics and sample statistics. For bioassessment to progress, spatial variability may need to be investigated in many systems and should be considered when designing studies and interpreting data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Keser, Saniye; Duzgun, Sebnem; Department of Geodetic and Geographic Information Technologies, Middle East Technical University, 06800 Ankara
Highlights: Black-Right-Pointing-Pointer Spatial autocorrelation exists in municipal solid waste generation rates for different provinces in Turkey. Black-Right-Pointing-Pointer Traditional non-spatial regression models may not provide sufficient information for better solid waste management. Black-Right-Pointing-Pointer Unemployment rate is a global variable that significantly impacts the waste generation rates in Turkey. Black-Right-Pointing-Pointer Significances of global parameters may diminish at local scale for some provinces. Black-Right-Pointing-Pointer GWR model can be used to create clusters of cities for solid waste management. - Abstract: In studies focusing on the factors that impact solid waste generation habits and rates, the potential spatial dependency in solid waste generation datamore » is not considered in relating the waste generation rates to its determinants. In this study, spatial dependency is taken into account in determination of the significant socio-economic and climatic factors that may be of importance for the municipal solid waste (MSW) generation rates in different provinces of Turkey. Simultaneous spatial autoregression (SAR) and geographically weighted regression (GWR) models are used for the spatial data analyses. Similar to ordinary least squares regression (OLSR), regression coefficients are global in SAR model. In other words, the effect of a given independent variable on a dependent variable is valid for the whole country. Unlike OLSR or SAR, GWR reveals the local impact of a given factor (or independent variable) on the waste generation rates of different provinces. Results show that provinces within closer neighborhoods have similar MSW generation rates. On the other hand, this spatial autocorrelation is not very high for the exploratory variables considered in the study. OLSR and SAR models have similar regression coefficients. GWR is useful to indicate the local determinants of MSW generation rates. GWR model can be utilized to plan waste management activities at local scale including waste minimization, collection, treatment, and disposal. At global scale, the MSW generation rates in Turkey are significantly related to unemployment rate and asphalt-paved roads ratio. Yet, significances of these variables may diminish at local scale for some provinces. At local scale, different factors may be important in affecting MSW generation rates.« less
Horak, Jakub
2013-01-01
The interaction of arthropods with the environment and the management of their populations is a focus of the ecological agenda. Spatial autocorrelation and under-sampling may generate bias and, when they are ignored, it is hard to determine if results can in any way be trusted. Arthropod communities were studied during two seasons and using two methods: window and panel traps, in an area of ancient temperate lowland woodland of Zebracka (Czech Republic). The composition of arthropod communities was studied focusing on four site level variables (canopy openness, diameter in the breast height and height of tree, and water distance) and finally analysed using two approaches: with and without effects of spatial autocorrelation. I found that the proportion of variance explained by space cannot be ignored (≈20% in both years). Potential bias in analyses of the response of arthropods to site level variables without including spatial co-variables is well illustrated by redundancy analyses. Inclusion of space led to more accurate results, as water distance and tree diameter were significant, showing approximately the same ratio of explained variance and direction in both seasons. Results without spatial co-variables were much more disordered and were difficult to explain. This study showed that neglecting the effects of spatial autocorrelation could lead to wrong conclusions in site level studies and, furthermore, that inclusion of space may lead to more accurate and unambiguous outcomes. Rarefactions showed that lower sampling intensity, when appropriately designed, can produce sufficient results without exploitation of the environment.
Variability in human body size
NASA Technical Reports Server (NTRS)
Annis, J. F.
1978-01-01
The range of variability found among homogeneous groups is described and illustrated. Those trends that show significantly marked differences between sexes and among a number of racial/ethnic groups are also presented. Causes of human-body size variability discussed include genetic endowment, aging, nutrition, protective garments, and occupation. The information is presented to aid design engineers of space flight hardware and equipment.
NASA Astrophysics Data System (ADS)
Steinschneider, S.; Ho, M.; Cook, E. R.; Lall, U.
2017-12-01
This work explores how extreme cold-season precipitation dynamics along the west coast of the United States have varied in the past under natural climate variability through an analysis of the moisture anomalies recorded by tree-ring chronologies across the coast and interior of the western U.S. Winters with high total precipitation amounts in the coastal regions are marked by a small number of extreme storms that exhibit distinct spatial patterns of precipitation across the coast and further inland. Building from this observation, this work develops a novel application of dendroclimatic evidence to explore the following questions: a) how is extreme precipitation variability expressed in a network of tree-ring chronologies; b) can this information provide insight on the space-time variability of storm tracks that cause these extreme events; and c) how can the joint variability of extreme precipitation and storm tracks be modeled to develop consistent, multi-centennial reconstructions of both? We use gridded, tree-ring based reconstructions of the summer Palmer Drought Severity Index (PDSI) extending back 500 years within the western U.S. to build and test a novel statistical framework for reconstructing the space-time variability of coastal extreme precipitation and the associated wintertime storm tracks. Within this framework, we (1) identify joint modes of variability of extreme precipitation fields and tree-ring based PDSI reconstructions; (2) relate these modes to previously identified, unique storm track patterns associated with atmospheric rivers (ARs), which are the dominant type of storm that is responsible for extreme precipitation in the region; and (3) determine latitudinal variations of landfalling ARs across the west coast and their relationship to the these joint modes. To our knowledge, this work is the first attempt to leverage information on storm track patterns stored in a network of paleoclimate proxies to improve reconstruction fidelity.
NASA Astrophysics Data System (ADS)
Steinschneider, S.; Ho, M.; Cook, E. R.; Lall, U.
2016-12-01
This work explores how extreme cold-season precipitation dynamics along the west coast of the United States have varied in the past under natural climate variability through an analysis of the moisture anomalies recorded by tree-ring chronologies across the coast and interior of the western U.S. Winters with high total precipitation amounts in the coastal regions are marked by a small number of extreme storms that exhibit distinct spatial patterns of precipitation across the coast and further inland. Building from this observation, this work develops a novel application of dendroclimatic evidence to explore the following questions: a) how is extreme precipitation variability expressed in a network of tree-ring chronologies; b) can this information provide insight on the space-time variability of storm tracks that cause these extreme events; and c) how can the joint variability of extreme precipitation and storm tracks be modeled to develop consistent, multi-centennial reconstructions of both? We use gridded, tree-ring based reconstructions of the summer Palmer Drought Severity Index (PDSI) extending back 500 years within the western U.S. to build and test a novel statistical framework for reconstructing the space-time variability of coastal extreme precipitation and the associated wintertime storm tracks. Within this framework, we (1) identify joint modes of variability of extreme precipitation fields and tree-ring based PDSI reconstructions; (2) relate these modes to previously identified, unique storm track patterns associated with atmospheric rivers (ARs), which are the dominant type of storm that is responsible for extreme precipitation in the region; and (3) determine latitudinal variations of landfalling ARs across the west coast and their relationship to the these joint modes. To our knowledge, this work is the first attempt to leverage information on storm track patterns stored in a network of paleoclimate proxies to improve reconstruction fidelity.
NASA Astrophysics Data System (ADS)
Liu, Meixian; Xu, Xianli; Sun, Alex
2015-07-01
Climate extremes can cause devastating damage to human society and ecosystems. Recent studies have drawn many conclusions about trends in climate extremes, but few have focused on quantitative analysis of their spatial variability and underlying mechanisms. By using the techniques of overlapping moving windows, the Mann-Kendall trend test, correlation, and stepwise regression, this study examined the spatial-temporal variation of precipitation extremes and investigated the potential key factors influencing this variation in southwestern (SW) China, a globally important biodiversity hot spot and climate-sensitive region. Results showed that the changing trends of precipitation extremes were not spatially uniform, but the spatial variability of these precipitation extremes decreased from 1959 to 2012. Further analysis found that atmospheric circulations rather than local factors (land cover, topographic conditions, etc.) were the main cause of such precipitation extremes. This study suggests that droughts or floods may become more homogenously widespread throughout SW China. Hence, region-wide assessments and coordination are needed to help mitigate the economic and ecological impacts.
Wu, Zhixu; Zhang, Yunlin; Zhou, Yongqiang; Liu, Mingliang; Shi, Kun; Yu, Zuoming
2015-01-01
Water transparency is a useful indicator of water quality or productivity and is widely used to detect long-term changes in the water quality and eutrophication of lake ecosystems. Based on short-term spatial observations in the spring, summer, and winter and on long-term site-specific observation from 1988 to 2013, the spatial, seasonal, long-term variations, and the factors affecting transparency are presented for Xin’anjiang Reservoir (China). Spatially, transparency was high in the open water but low in the bays and the inflowing river mouths, reflecting the effect of river runoff. The seasonal effects were distinct, with lower values in the summer than in the winter, most likely due to river runoff and phytoplankton biomass increases. The transparency decreased significantly with a linear slope of 0.079 m/year, indicating a 2.05 m decrease and a marked decrease in water quality. A marked increase occurred in chlorophyll a (Chla) concentration, and a significant correlation was found between the transparency and Chla concentration, indicating that phytoplankton biomass can partially explain the long-term trend of transparency in Xin’anjiang Reservoir. The river input and phytoplankton biomass increase were associated with soil erosion and nutrient loss in the catchment. Our study will support future management of water quality in Xin’anjiang Reservoir. PMID:26274970
NASA Astrophysics Data System (ADS)
Tanaka, Yukinobu; Ogata, Takeshi; Imagawa, Seiji
2015-09-01
We developed a decoupled direct tracking control system for multilayer optical disk that uses a separate guide layer. Data marks are recorded on a recording layer immediately above the guide layer by using two spatially separated spots with different wavelengths. Accurate data mark recording requires that the relative positions of the corresponding spots on the recording layer and guide layer are maintained. However, a disk tilt can shift their relative positions and cause previously recorded data marks to be overwritten. Additionally, a two-input/two-output control system is susceptible to mutual interference phenomenon between the two outputs, which can destabilize tracking control. A tracking control system based on use of data marks previously recorded as a virtual track has been developed that prevents spot shifting and mutual interference even if the disk tilt reaches 0.7°, thereby preventing overwriting.
Botbol, Joseph Moses; Evenden, Gerald Ian
1989-01-01
Tables, graphs, and maps are used to portray the frequency characteristics and spatial distribution of manganese oxide-rich phase geochemical data, to characterize the northern Pacific in terms of publicly available nodule geochemical data, and to develop data portrayal methods that will facilitate data analysis. Source data are a subset of the Scripps Institute of Oceanography's Sediment Data Bank. The study area is bounded by 0° N., 40° N., 120° E., and 100° W. and is arbitrarily subdivided into 14-20°x20° geographic subregions. Frequency distributions of trace metals characterized in the original raw data are graphed as ogives, and salient parameters are tabulated. All variables are transformed to enrichment values relative to median concentration within their host subregions. Scatter plots of all pairs of original variables and their enrichment transforms are provided as an aid to the interpretation of correlations between variables. Gridded spatial distributions of all variables are portrayed as gray-scale maps. The use of tables and graphs to portray frequency statistics and gray-scale maps to portray spatial distributions is an effective way to prepare for and facilitate multivariate data analysis.
Multiscale drivers of spatially variable grass production and loss in the Chihuahuan Desert
USDA-ARS?s Scientific Manuscript database
Historic regime shifts from grass- to shrub-dominated states have been widespread in the Chihuahuan Desert and other arid and semiarid regions globally. These patterns of grass production and shifts to shrub dominance are spatially variable, and show a weak correlation with precipitation, suggesting...
Variability of Soil Temperature: A Spatial and Temporal Analysis.
ERIC Educational Resources Information Center
Walsh, Stephen J.; And Others
1991-01-01
Discusses an analysis of the relationship of soil temperatures at 3 depths to various climatic variables along a 200-kilometer transect in west-central Oklahoma. Reports that temperature readings increased from east to west. Concludes that temperature variations were explained by a combination of spatial, temporal, and biophysical factors. (SG)
The spatial and temporal variability of terrestrial water storage and snowpack in the Pacific Northwest (PNW) was analyzed for water years 2001–2010 using measurements from the Gravity Recovery and Climate Experiment (GRACE) instrument. GRACE provides remotely-sensed measurements...
Spatial and Temporal Monitoring of Dissolved Oxygen in NJ Coastal Waters using AUVs (Presentation)
The coastal ocean is a highly variable system with processes that have significant implications on the hydrographic and oxygen characteristics of the water column. The spatial and temporal variability of these fields can cause dramatic changes to water quality and in turn the h...
Probabilistic and spatially variable niches inferred from demography
Jeffrey M. Diez; Itamar Giladi; Robert Warren; H. Ronald Pulliam
2014-01-01
Summary 1. Mismatches between species distributions and habitat suitability are predicted by niche theory and have important implications for forecasting how species may respond to environmental changes. Quantifying these mismatches is challenging, however, due to the high dimensionality of species niches and the large spatial and temporal variability in population...
Variability of hazardous air pollutants in an urban area
NASA Astrophysics Data System (ADS)
Spicer, Chester W.; Buxton, Bruce E.; Holdren, Michael W.; Smith, Deborah L.; Kelly, Thomas J.; Rust, Steven W.; Pate, Alan D.; Sverdrup, George M.; Chuang, Jane C.
The variability of hazardous air pollutants (HAPs) is an important factor in determining human exposure to such chemicals, and in designing HAP measurement programs. This study has investigated the factors which contribute to HAP variability in an urban area. Six measurement sites separated by up to 12 km collected data with 3 h time resolution to examine spatial variability within neighborhoods and between neighborhoods. The measurements were made in Columbus, OH. The 3 h results also were used to study temporal variability, and duplicate samples collected at each site were used to determine the component of variability attributable to the measurement process. Hourly samples collected over 10 days at one site provided further insight into the temporal resolution needed to capture short-term peak concentrations. Measurements at the 6 spatial sites focused on 78 chemicals. Twenty-three of these species were found in at least 95% of the 3 h samples, and 39 chemicals were present at least 60% of the time. The relative standard deviations for most of these 39 frequently detected chemicals was 1.0 or lower. Variability was segmented into temporal, spatial, and measurement components. Temporal variation was the major contributor to HAP variability for 19 of the 39 frequently detected compounds, based on the 3 h data. Measurement imprecision contributed less than 25% for most of the volatile organic species, but 30% or more of the variability for carbonyl compounds, trace elements, and particle-bound extractable organic mass. Interestingly, the spatial component contributed less than 20% of the total variability for all the chemicals except sulfur. Based on the data with hourly resolution, peak to median ratios (hourly peak to 24 h median) averaged between 2 and 4 for most of the volatile organic compounds, but there were two species with peak to median ratios of about 10.
[Spatial differentiation and impact factors of Yutian Oasis's soil surface salt based on GWR model].
Yuan, Yu Yun; Wahap, Halik; Guan, Jing Yun; Lu, Long Hui; Zhang, Qin Qin
2016-10-01
In this paper, topsoil salinity data gathered from 24 sampling sites in the Yutian Oasis were used, nine different kinds of environmental variables closely related to soil salinity were selec-ted as influencing factors, then, the spatial distribution characteristics of topsoil salinity and spatial heterogeneity of influencing factors were analyzed by combining the spatial autocorrelation with traditional regression analysis and geographically weighted regression model. Results showed that the topsoil salinity in Yutian Oasis was not of random distribution but had strong spatial dependence, and the spatial autocorrelation index for topsoil salinity was 0.479. Groundwater salinity, groundwater depth, elevation and temperature were the main factors influencing topsoil salt accumulation in arid land oases and they were spatially heterogeneous. The nine selected environmental variables except soil pH had significant influences on topsoil salinity with spatial disparity. GWR model was superior to the OLS model on interpretation and estimation of spatial non-stationary data, also had a remarkable advantage in visualization of modeling parameters.
Using spatial mark-recapture for conservation monitoring of grizzly bear populations in Alberta.
Boulanger, John; Nielsen, Scott E; Stenhouse, Gordon B
2018-03-26
One of the challenges in conservation is determining patterns and responses in population density and distribution as it relates to habitat and changes in anthropogenic activities. We applied spatially explicit capture recapture (SECR) methods, combined with density surface modelling from five grizzly bear (Ursus arctos) management areas (BMAs) in Alberta, Canada, to assess SECR methods and to explore factors influencing bear distribution. Here we used models of grizzly bear habitat and mortality risk to test local density associations using density surface modelling. Results demonstrated BMA-specific factors influenced density, as well as the effects of habitat and topography on detections and movements of bears. Estimates from SECR were similar to those from closed population models and telemetry data, but with similar or higher levels of precision. Habitat was most associated with areas of higher bear density in the north, whereas mortality risk was most associated (negatively) with density of bears in the south. Comparisons of the distribution of mortality risk and habitat revealed differences by BMA that in turn influenced local abundance of bears. Combining SECR methods with density surface modelling increases the resolution of mark-recapture methods by directly inferring the effect of spatial factors on regulating local densities of animals.
Dynamics of Learning in Cultured Neuronal Networks with Antagonists of Glutamate Receptors
Li, Yanling; Zhou, Wei; Li, Xiangning; Zeng, Shaoqun; Luo, Qingming
2007-01-01
Cognitive dysfunction may result from abnormality of ionotropic glutamate receptors. Although various forms of synaptic plasticity in learning that rely on altering of glutamate receptors have been considered, the evidence is insufficient from an informatics view. Dynamics could reflect neuroinformatics encoding, including temporal pattern encoding, spatial pattern encoding, and energy distribution. Discovering informatics encoding is fundamental and crucial to understanding the working principle of the neural system. In this article, we analyzed the dynamic characteristics of response activities during learning training in cultured hippocampal networks under normal and abnormal conditions of ionotropic glutamate receptors, respectively. The rate, which is one of the temporal configurations, was decreased markedly by inhibition of α-amino-3-hydroxy-5-methylisoxazole-4-proprionic acid (AMPA) receptors. Moreover, the energy distribution in different characteristic frequencies was changed markedly by inhibition of AMPA receptors. Spatial configurations, including regularization, correlation, and synchrony, were changed significantly by inhibition of N-methyl-d-aspartate receptors. These results suggest that temporal pattern encoding and energy distribution of response activities in cultured hippocampal neuronal networks during learning training are modulated by AMPA receptors, whereas spatial pattern encoding of response activities is modulated by N-methyl-d-aspartate receptors. PMID:17766359
Regional patterns of total nitrogen concentrations in the National Rivers and Streams Assessment
Omernik, James M.; Paulsen, Steven G.; Griffith, Glenn E.; Weber, Marc H.
2016-01-01
Patterns of nitrogen (N) concentrations in streams sampled by the National Rivers and Streams Assessment (NRSA) were examined semiquantitatively to identify regional differences in stream N levels. The data were categorized and analyzed by watershed size classes to reveal patterns of the concentrations that are consistent with the spatial homogeneity in natural and anthropogenic characteristics associated with regional differences in N levels. Ecoregions and mapped information on human activities including agricultural practices were used to determine the resultant regions. Marked differences in N levels were found among the nine aggregations of ecoregions used to report the results of the NRSA. We identified distinct regional patterns of stream N concentrations within the reporting regions that are associated with the characteristics of specific Level III ecoregions, groups of Level III ecoregions, groups of Level IV ecoregions, certain geographic characteristics within ecoregions, and/or particular watershed size classes. We described each of these regions and illustrated their areal extent and median and range in N concentrations. Understanding the spatial variability of nutrient concentrations in flowing waters and the apparent contributions that human and nonhuman factors have on different sizes of streams and rivers is critical to the development of effective water quality assessment and management plans. This semi-quantitative analysis is also intended to identify areas within which more detailed quantitative work can be conducted to determine specific regional factors associated with variations in stream N concentrations.
Evidence of Water Quality Degradation in Lower Mekong Basin Revealed by Self-Organizing Map
Chea, Ratha; Grenouillet, Gaël; Lek, Sovan
2016-01-01
To reach a better understanding of the spatial variability of water quality in the Lower Mekong Basin (LMB), the Self-Organizing Map (SOM) was used to classify 117 monitoring sites and hotspots of pollution within the basin identified according to water quality indicators and US-EPA guidelines. Four different clusters were identified based on their similar physicochemical characteristics. The majority of sites in upper (Laos and Thailand) and middle part (Cambodia) of the basin were grouped in two clusters, considered as good quality water with high DO and low nutrient levels. The other two clusters were mostly composed of sites in Mekong delta (Vietnam) and few sites in upstream tributaries (i.e., northwestern Thailand, Tonle Sap Lake, and swamps close to Vientiane), known for moderate to poor quality of water and characterized by high nutrient and dissolved solid levels. Overall, we found that the water in the mainstream was less polluted than its tributaries; eutrophication and salinity could be key factors affecting water quality in LMB. Moreover, the seasonal variation of water quality seemed to be less marked than spatial variation occurring along the longitudinal gradient of Mekong River. Significant degradations were mainly associated with human disturbance and particularly apparent in sites distributed along the man-made canals in Vietnam delta where population growth and agricultural development are intensive. PMID:26731522
NASA Astrophysics Data System (ADS)
Cortesi, Nicola; Peña-Angulo, Dhais; Simolo, Claudia; Stepanek, Peter; Brunetti, Michele; Gonzalez-Hidalgo, José Carlos
2014-05-01
One of the key point in the develop of the MOTEDAS dataset (see Poster 1 MOTEDAS) in the framework of the HIDROCAES Project (Impactos Hidrológicos del Calentamiento Global en España, Spanish Ministery of Research CGL2011-27574-C02-01) is the reference series for which no generalized metadata exist. In this poster we present an analysis of spatial variability of monthly minimum and maximum temperatures in the conterminous land of Spain (Iberian Peninsula, IP), by using the Correlation Decay Distance function (CDD), with the aim of evaluating, at sub-regional level, the optimal threshold distance between neighbouring stations for producing the set of reference series used in the quality control (see MOTEDAS Poster 1) and the reconstruction (see MOREDAS Poster 3). The CDD analysis for Tmax and Tmin was performed calculating a correlation matrix at monthly scale between 1981-2010 among monthly mean values of maximum (Tmax) and minimum (Tmin) temperature series (with at least 90% of data), free of anomalous data and homogenized (see MOTEDAS Poster 1), obtained from AEMEt archives (National Spanish Meteorological Agency). Monthly anomalies (difference between data and mean 1981-2010) were used to prevent the dominant effect of annual cycle in the CDD annual estimation. For each station, and time scale, the common variance r2 (using the square of Pearson's correlation coefficient) was calculated between all neighbouring temperature series and the relation between r2 and distance was modelled according to the following equation (1): Log (r2ij) = b*°dij (1) being Log(rij2) the common variance between target (i) and neighbouring series (j), dij the distance between them and b the slope of the ordinary least-squares linear regression model applied taking into account only the surrounding stations within a starting radius of 50 km and with a minimum of 5 stations required. Finally, monthly, seasonal and annual CDD values were interpolated using the Ordinary Kriging with a spherical variogram over conterminous land of Spain, and converted on a regular 10 km2 grid (resolution similar to the mean distance between stations) to map the results. In the conterminous land of Spain the distance at which couples of stations have a common variance in temperature (both maximum Tmax, and minimum Tmin) above the selected threshold (50%, r Pearson ~0.70) on average does not exceed 400 km, with relevant spatial and temporal differences. The spatial distribution of the CDD shows a clear coastland-to-inland gradient at annual, seasonal and monthly scale, with highest spatial variability along the coastland areas and lower variability inland. The highest spatial variability coincide particularly with coastland areas surrounded by mountain chains and suggests that the orography is one of the most driving factor causing higher interstation variability. Moreover, there are some differences between the behaviour of Tmax and Tmin, being Tmin spatially more homogeneous than Tmax, but its lower CDD values indicate that night-time temperature is more variable than diurnal one. The results suggest that in general local factors affects the spatial variability of monthly Tmin more than Tmax and then higher network density would be necessary to capture the higher spatial variability highlighted for Tmin respect to Tmax. The results suggest that in general local factors affects the spatial variability of Tmin more than Tmax and then higher network density would be necessary to capture the higher spatial variability highlighted for minimum temperature respect to maximum temperature. A conservative distance for reference series could be evaluated in 200 km, that we propose for continental land of Spain and use in the development of MOTEDAS.
The impact of sedimentary anisotropy on solute mixing in stacked scour-pool structures
NASA Astrophysics Data System (ADS)
Bennett, Jeremy P.; Haslauer, Claus P.; Cirpka, Olaf A.
2017-04-01
The spatial variability of hydraulic conductivity is known to have a strong impact on solute spreading and mixing. In most investigations, its local anisotropy has been neglected. Recent studies have shown that spatially varying orientation in sedimentary anisotropy can lead to twisting flow enhancing transverse mixing, but most of these studies used geologically implausible geometries. We use an object-based approach to generate stacked scour-pool structures with either isotropic or anisotropic filling which are typically reported in glacial outwash deposits. We analyze how spatially variable isotropic conductivity and variation of internal anisotropy in these features impacts transverse plume deformation and both longitudinal and transverse spreading and mixing. In five test cases, either the scalar values of conductivity or the spatial orientation of its anisotropy is varied between the scour-pool structures. Based on 100 random configurations, we compare the variability of velocity components, stretching and folding metrics, advective travel-time distributions, one and two-particle statistics in advective-dispersive transport, and the flux-related dilution indices for steady state advective-dispersive transport among the five test cases. Variation in the orientation of internal anisotropy causes strong variability in the lateral velocity components, which leads to deformation in transverse directions and enhances transverse mixing, whereas it hardly affects the variability of the longitudinal velocity component and thus longitudinal spreading and mixing. The latter is controlled by the spatial variability in the scalar values of hydraulic conductivity. Our results demonstrate that sedimentary anisotropy is important for transverse mixing, whereas it may be neglected when considering longitudinal spreading and mixing.
NASA Astrophysics Data System (ADS)
Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L.
2014-12-01
The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units.
Glisson, Wesley J.; Conway, Courtney J.; Nadeau, Christopher P.; Borgmann, Kathi L.
2017-01-01
Understanding species–habitat relationships for endangered species is critical for their conservation. However, many studies have limited value for conservation because they fail to account for habitat associations at multiple spatial scales, anthropogenic variables, and imperfect detection. We addressed these three limitations by developing models for an endangered wetland bird, Yuma Ridgway's rail (Rallus obsoletus yumanensis), that examined how the spatial scale of environmental variables, inclusion of anthropogenic disturbance variables, and accounting for imperfect detection in validation data influenced model performance. These models identified associations between environmental variables and occupancy. We used bird survey and spatial environmental data at 2473 locations throughout the species' U.S. range to create and validate occupancy models and produce predictive maps of occupancy. We compared habitat-based models at three spatial scales (100, 224, and 500 m radii buffers) with and without anthropogenic disturbance variables using validation data adjusted for imperfect detection and an unadjusted validation dataset that ignored imperfect detection. The inclusion of anthropogenic disturbance variables improved the performance of habitat models at all three spatial scales, and the 224-m-scale model performed best. All models exhibited greater predictive ability when imperfect detection was incorporated into validation data. Yuma Ridgway's rail occupancy was negatively associated with ephemeral and slow-moving riverine features and high-intensity anthropogenic development, and positively associated with emergent vegetation, agriculture, and low-intensity development. Our modeling approach accounts for common limitations in modeling species–habitat relationships and creating predictive maps of occupancy probability and, therefore, provides a useful framework for other species.
Sparse modeling of spatial environmental variables associated with asthma
Chang, Timothy S.; Gangnon, Ronald E.; Page, C. David; Buckingham, William R.; Tandias, Aman; Cowan, Kelly J.; Tomasallo, Carrie D.; Arndt, Brian G.; Hanrahan, Lawrence P.; Guilbert, Theresa W.
2014-01-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin’s Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5–50 years over a three-year period. Each patient’s home address was geocoded to one of 3,456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin’s geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. PMID:25533437
Sparse modeling of spatial environmental variables associated with asthma.
Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W
2015-02-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.
ERIC Educational Resources Information Center
Massey, Alf
1983-01-01
The effects of penmanship, complexity and accuracy of prose, length of answers, and use of quotations on marks awarded by English literature examiners were studied. The sex of students and examiners, untidiness, and prose complexity and accuracy were unrelated to grades. The results suggested that examiners avoid crediting students for…
Better marking means cheaper pruning.
Kenneth R. Eversole
1953-01-01
Careful selection of trees to be pruned can make the difference between profit and loss on the pruning investment, especially in stands where no thinning is contemplated. Expert marking is required to make sure that the pruned trees will grow rapidly. The most important variable influencing the cost of clear wood produced by pruning is growth rate. For example, at 3...
ERIC Educational Resources Information Center
Sarnecka, Barbara W.; Kamenskaya, Valentina G.; Yamana, Yuko; Ogura, Tamiko; Yudovina, Yulia B.
2007-01-01
This study examined whether singular/plural marking in a language helps children learn the meanings of the words "one," "two," and "three." First, CHILDES data in English, Russian (which marks singular/plural), and Japanese (which does not) were compared for frequency, variability, and contexts of number-word use.…
NASA Astrophysics Data System (ADS)
Villate, Fernando; Iriarte, Arantza; Uriarte, Ibon; Sanchez, Iraide
2017-12-01
Seasonal and interannual variations of total mesozooplankton abundance and community variability were assessed for the period 1998-2005 at 3 salinity sites (35, 33 and 30) of the estuaries of Bilbao and Urdaibai (southeast Bay of Biscay). Spatial differences in mesozooplankton seasonality were recognized, both within and between estuaries, related to differences between sites in hydrodynamic features and anthropogenic nutrient enrichment that drive phytoplankton biomass seasonal cycles. The within estuary seasonal differences in mesozooplankton community were mainly shown through seaward time-advances in the seasonal peak from summer to spring along the salinity gradient, linked to differences in phytoplankton availability during the summer, in turn, related to nutrient availability. These differences were most marked in the estuary of Urdaibai, where zooplankton seasonal pattern at 35 salinity (high tidal flushing) resembled that of shelf waters, while at 35 of the estuary of Bilbao zooplankton showed an estuarine seasonal pattern due to the influence of the estuarine plume. Cirripede larvae contributed most to the mesozooplankton seasonal variability, except at the outer estuary of Bilbao, where cladocerans and fish eggs and larvae were the major contributors, and the inner estuary of Urdaibai, where gastropod larvae contributed most. Total mesozooplankton increased at 30 salinity of the estuary of Bilbao and 35 salinity of the estuary of Urdaibai. Interannual variability of mesozooplankton at the lowest salinity of the estuary of Bilbao was mainly accounted for by copepods due to the introduction of non-indigenous species during estuarine rehabilitation from intense pollution. However, bivalve larvae and gastropod larvae showed the highest contributions at 35 salinity of the estuary of Urdaibai. At the rest of sites, the opposite interannual trends of polychaete larvae and hydromedusae generally made the highest contribution.
Development of Spatiotemporal Bias-Correction Techniques for Downscaling GCM Predictions
NASA Astrophysics Data System (ADS)
Hwang, S.; Graham, W. D.; Geurink, J.; Adams, A.; Martinez, C. J.
2010-12-01
Accurately representing the spatial variability of precipitation is an important factor for predicting watershed response to climatic forcing, particularly in small, low-relief watersheds affected by convective storm systems. Although Global Circulation Models (GCMs) generally preserve spatial relationships between large-scale and local-scale mean precipitation trends, most GCM downscaling techniques focus on preserving only observed temporal variability on point by point basis, not spatial patterns of events. Downscaled GCM results (e.g., CMIP3 ensembles) have been widely used to predict hydrologic implications of climate variability and climate change in large snow-dominated river basins in the western United States (Diffenbaugh et al., 2008; Adam et al., 2009). However fewer applications to smaller rain-driven river basins in the southeastern US (where preserving spatial variability of rainfall patterns may be more important) have been reported. In this study a new method was developed to bias-correct GCMs to preserve both the long term temporal mean and variance of the precipitation data, and the spatial structure of daily precipitation fields. Forty-year retrospective simulations (1960-1999) from 16 GCMs were collected (IPCC, 2007; WCRP CMIP3 multi-model database: https://esg.llnl.gov:8443/), and the daily precipitation data at coarse resolution (i.e., 280km) were interpolated to 12km spatial resolution and bias corrected using gridded observations over the state of Florida (Maurer et al., 2002; Wood et al, 2002; Wood et al, 2004). In this method spatial random fields which preserved the observed spatial correlation structure of the historic gridded observations and the spatial mean corresponding to the coarse scale GCM daily rainfall were generated. The spatiotemporal variability of the spatio-temporally bias-corrected GCMs were evaluated against gridded observations, and compared to the original temporally bias-corrected and downscaled CMIP3 data for the central Florida. The hydrologic response of two southwest Florida watersheds to the gridded observation data, the original bias corrected CMIP3 data, and the new spatiotemporally corrected CMIP3 predictions was compared using an integrated surface-subsurface hydrologic model developed by Tampa Bay Water.
A global sensitivity analysis of crop virtual water content
NASA Astrophysics Data System (ADS)
Tamea, S.; Tuninetti, M.; D'Odorico, P.; Laio, F.; Ridolfi, L.
2015-12-01
The concepts of virtual water and water footprint are becoming widely used in the scientific literature and they are proving their usefulness in a number of multidisciplinary contexts. With such growing interest a measure of data reliability (and uncertainty) is becoming pressing but, as of today, assessments of data sensitivity to model parameters, performed at the global scale, are not known. This contribution aims at filling this gap. Starting point of this study is the evaluation of the green and blue virtual water content (VWC) of four staple crops (i.e. wheat, rice, maize, and soybean) at a global high resolution scale. In each grid cell, the crop VWC is given by the ratio between the total crop evapotranspiration over the growing season and the crop actual yield, where evapotranspiration is determined with a detailed daily soil water balance and actual yield is estimated using country-based data, adjusted to account for spatial variability. The model provides estimates of the VWC at a 5x5 arc minutes and it improves on previous works by using the newest available data and including multi-cropping practices in the evaluation. The model is then used as the basis for a sensitivity analysis, in order to evaluate the role of model parameters in affecting the VWC and to understand how uncertainties in input data propagate and impact the VWC accounting. In each cell, small changes are exerted to one parameter at a time, and a sensitivity index is determined as the ratio between the relative change of VWC and the relative change of the input parameter with respect to its reference value. At the global scale, VWC is found to be most sensitive to the planting date, with a positive (direct) or negative (inverse) sensitivity index depending on the typical season of crop planting date. VWC is also markedly dependent on the length of the growing period, with an increase in length always producing an increase of VWC, but with higher spatial variability for rice than for other crops. The sensitivity to the reference evapotranspiration is highly variable with the considered crop and ranges from positive values (for soybean), to negative values (for rice and maize) and near-zero values for wheat. This variability reflects the different yield response factors of crops, which expresses their tolerance to water stress.
Peters, N.E.; Buell, G.R.; Frick, E.A.
1997-01-01
Nutrient concentrations from the early 1970s through 1995 were evaluated at several sites along the Chattahoochee River and its tributaries near Atlanta, to determine general patterns and processes controlling nutrient concentrations in the river. A spatial analysis was conducted on data collected in 1994 and 1995 from an intensive nutrient study of the Chattahoochee River and its tributaries by the Georgia Department of Natural Resources, Environmental Protection Division. The 1994-1995 data show step increases in ammonium (NH4-N), nitrite plus nitrate (NO2 + NO3-N), and total-phosphorus (Tot-P) concentrations in the river. The step increases occur downstream of two wastewater treatment facilities (WWTFs) and Peachtree Creek, a small tributary inflow with degraded water quality draining a predominantly urban and industrial area. Median NO2 + NO3-N and Tot-P concentrations in the mainstem increase downstream of these inputs from 0.5 to 1 mg 1-1 and from 0.04 to 0.13 mg 1-1, respectively. NH4-N concentrations were typically low with 95% of the 2575 observations less than 0.2 mg 1-1 throughout the river system, except some high values (>1 mg 1-1) in some tributaries, particularly near the central part of Atlanta. High NH4-N concentrations are attributed to sewage discharge as they also are associated with high biological oxygen demand and faecal coliform bacteria concentrations. Nutrient concentrations vary temporally. An assessment of four sites, two mainstem and two tributaries, from 1970 to 1995 indicates a progressive increase and variability in NO2 + NO3-N concentrations during the period. The progressive increase in NO2 + NO3-N concentrations and their variability is similar to that reported for surface waters throughout the world and for which increased fertilizer usage has been attributed. Tot-P concentrations increase at mainstem sites through the middle to late 1980s and decrease markedly thereafter, due to improvements to WWTFs and a 1990 phosphate detergent ban. NH4-N concentrations, although less pronounced than Tot-P, display a similar decrease from the late 1980s to 1995 at the four sites. Tot-P concentration variability has increased at the tributary sites since 1993, although recent concentrations, on average, are the lowest since 1970 at each of the four sites.
A Method to Categorize 2-Dimensional Patterns Using Statistics of Spatial Organization.
López-Sauceda, Juan; Rueda-Contreras, Mara D
2017-01-01
We developed a measurement framework of spatial organization to categorize 2-dimensional patterns from 2 multiscalar biological architectures. We propose that underlying shapes of biological entities can be approached using the statistical concept of degrees of freedom, defining it through expansion of area variability in a pattern. To help scope this suggestion, we developed a mathematical argument recognizing the deep foundations of area variability in a polygonal pattern (spatial heterogeneity). This measure uses a parameter called eutacticity . Our measuring platform of spatial heterogeneity can assign particular ranges of distribution of spatial areas for 2 biological architectures: ecological patterns of Namibia fairy circles and epithelial sheets. The spatial organizations of our 2 analyzed biological architectures are demarcated by being in a particular position among spatial order and disorder. We suggest that this theoretical platform can give us some insights about the nature of shapes in biological systems to understand organizational constraints.
Li, Tao; Hao, Xinmei; Kang, Shaozhong
2016-01-01
There is a growing interest in precision viticulture with the development of global positioning system and geographical information system technologies. Limited information is available on spatial variation of bud behavior and its possible association with soil properties. The objective of this study was to investigate spatial variability of bud burst percentage and its association with soil properties based on 2-year experiments at a vineyard of arid northwest China. Geostatistical approach was used to describe the spatial variation in bud burst percentage within the vineyard. Partial least square regressions (PLSRs) of bud burst percentage with soil properties were used to evaluate the contribution of soil properties to overall spatial variability in bud burst percentage for the high, medium and low bud burst percentage groups. Within the vineyard, the coefficient of variation (CV) of bud burst percentage was 20% and 15% for 2012 and 2013 respectively. Bud burst percentage within the vineyard showed moderate spatial variability, and the overall spatial pattern of bud burst percentage was similar between the two years. Soil properties alone explained 31% and 37% of the total spatial variation respectively for the low group of 2012 and 2013, and 16% and 24% for the high group of 2012 and 2013 respectively. For the low group, the fraction of variations explained by soil properties was found similar between the two years, while there was substantial difference for the high group. The findings are expected to lay a good foundation for developing remedy measures in the areas with low bud burst percentage, thus in turn improving the overall grape yield and quality. PMID:27798692
Sampling design for spatially distributed hydrogeologic and environmental processes
Christakos, G.; Olea, R.A.
1992-01-01
A methodology for the design of sampling networks over space is proposed. The methodology is based on spatial random field representations of nonhomogeneous natural processes, and on optimal spatial estimation techniques. One of the most important results of random field theory for physical sciences is its rationalization of correlations in spatial variability of natural processes. This correlation is extremely important both for interpreting spatially distributed observations and for predictive performance. The extent of site sampling and the types of data to be collected will depend on the relationship of subsurface variability to predictive uncertainty. While hypothesis formulation and initial identification of spatial variability characteristics are based on scientific understanding (such as knowledge of the physics of the underlying phenomena, geological interpretations, intuition and experience), the support offered by field data is statistically modelled. This model is not limited by the geometric nature of sampling and covers a wide range in subsurface uncertainties. A factorization scheme of the sampling error variance is derived, which possesses certain atttactive properties allowing significant savings in computations. By means of this scheme, a practical sampling design procedure providing suitable indices of the sampling error variance is established. These indices can be used by way of multiobjective decision criteria to obtain the best sampling strategy. Neither the actual implementation of the in-situ sampling nor the solution of the large spatial estimation systems of equations are necessary. The required values of the accuracy parameters involved in the network design are derived using reference charts (readily available for various combinations of data configurations and spatial variability parameters) and certain simple yet accurate analytical formulas. Insight is gained by applying the proposed sampling procedure to realistic examples related to sampling problems in two dimensions. ?? 1992.
NASA Astrophysics Data System (ADS)
Fan, Linfeng; Lehmann, Peter; Or, Dani
2015-04-01
Naturally-occurring spatial variations in soil properties (e.g., soil depth, moisture, and texture) affect key hydrological processes and potentially the mechanical response of soil to hydromechanical loading (relative to the commonly-assumed uniform soil mantle). We quantified the effects of soil spatial variability on the triggering of rainfall-induced shallow landslides at the hillslope- and catchment-scales, using a physically-based landslide triggering model that considers interacting soil columns with mechanical strength thresholds (represented by the Fiber Bundle Model). The spatial variations in soil properties are represented as Gaussian random distributions and the level of variation is characterized by the coefficient of variation and correlation lengths of soil properties (i.e., soil depth, soil texture and initial water content in this study). The impacts of these spatial variations on landslide triggering characteristics were measured by comparing the times to triggering and landslide volumes for heterogeneous soil properties and homogeneous cases. Results at hillslope scale indicate that for spatial variations of an individual property (without cross correlation), the increasing of coefficient of variation introduces weak spots where mechanical damage is accelerated and leads to earlier onset of landslide triggering and smaller volumes. Increasing spatial correlation length of soil texture and initial water content also induces early landslide triggering and small released volumes due to the transition of failure mode from brittle to ductile failure. In contrast, increasing spatial correlation length of soil depth "reduces" local steepness and postpones landslide triggering. Cross-correlated soil properties generally promote landslide initiation, but depending on the internal structure of spatial distribution of each soil property, landslide triggering may be reduced. The effects of cross-correlation between initial water content and soil texture were investigated in detail at the catchment scale by incorporating correlations of both variables with topography. Results indicate that the internal structure of the spatial distribution of each soil property together with their interplays determine the overall performance of the coupled spatial variability. This study emphasizes the importance of both the randomness and spatial structure of soil properties on landslide triggering and characteristics.
Hardiness commitment, gender, and age differentiate university academic performance.
Sheard, Michael
2009-03-01
The increasing diversity of students, particularly in age, attending university has seen a concomitant interest in factors predicting academic success. This 2-year correlational study examined whether age, gender (demographic variables), and hardiness (cognitive/emotional variable) differentiate and predict university final degree grade point average (GPA) and final-year dissertation mark. Data are reported from a total of 134 university undergraduate students. Participants provided baseline data in questionnaires administered during the first week of their second year of undergraduate study and gave consent for their academic progress to be tracked. Final degree GPA and dissertation mark were the academic performance criteria. Mature-age students achieved higher final degree GPA compared to young undergraduates. Female students significantly outperformed their male counterparts in each measured academic assessment criteria. Female students also reported a significantly higher mean score on hardiness commitment compared to male students. commitment was the most significant positive correlate of academic achievement. Final degree GPA and dissertation mark were significantly predicted by commitment, and commitment and gender, respectively. The findings have implications for universities targeting academic support services to maximize student scholastic potential. Future research should incorporate hardiness, gender, and age with other variables known to predict academic success.
Some insight on censored cost estimators.
Zhao, H; Cheng, Y; Bang, H
2011-08-30
Censored survival data analysis has been studied for many years. Yet, the analysis of censored mark variables, such as medical cost, quality-adjusted lifetime, and repeated events, faces a unique challenge that makes standard survival analysis techniques invalid. Because of the 'informative' censorship imbedded in censored mark variables, the use of the Kaplan-Meier (Journal of the American Statistical Association 1958; 53:457-481) estimator, as an example, will produce biased estimates. Innovative estimators have been developed in the past decade in order to handle this issue. Even though consistent estimators have been proposed, the formulations and interpretations of some estimators are less intuitive to practitioners. On the other hand, more intuitive estimators have been proposed, but their mathematical properties have not been established. In this paper, we prove the analytic identity between some estimators (a statistically motivated estimator and an intuitive estimator) for censored cost data. Efron (1967) made similar investigation for censored survival data (between the Kaplan-Meier estimator and the redistribute-to-the-right algorithm). Therefore, we view our study as an extension of Efron's work to informatively censored data so that our findings could be applied to other marked variables. Copyright © 2011 John Wiley & Sons, Ltd.
Congdon, Peter
2012-01-01
Ecological studies of suicide and self-harm have established the importance of area variables (e.g., deprivation, social fragmentation) in explaining variations in suicide risk. However, there are likely to be unobserved influences on risk, typically spatially clustered, which can be modeled as random effects. Regression impacts may be biased if no account is taken of spatially structured influences on risk. Furthermore a default assumption of linear effects of area variables may also misstate or understate their impact. This paper considers variations in suicide outcomes for small areas across England, and investigates the impact on them of area socio-economic variables, while also investigating potential nonlinearity in their impact and allowing for spatially clustered unobserved factors. The outcomes are self-harm hospitalisations and suicide mortality over 6,781 Middle Level Super Output Areas. PMID:23271304
Congdon, Peter
2012-12-27
Ecological studies of suicide and self-harm have established the importance of area variables (e.g., deprivation, social fragmentation) in explaining variations in suicide risk. However, there are likely to be unobserved influences on risk, typically spatially clustered, which can be modeled as random effects. Regression impacts may be biased if no account is taken of spatially structured influences on risk. Furthermore a default assumption of linear effects of area variables may also misstate or understate their impact. This paper considers variations in suicide outcomes for small areas across England, and investigates the impact on them of area socio-economic variables, while also investigating potential nonlinearity in their impact and allowing for spatially clustered unobserved factors. The outcomes are self-harm hospitalisations and suicide mortality over 6,781 Middle Level Super Output Areas.
NASA Astrophysics Data System (ADS)
Korres, W.; Reichenau, T. G.; Schneider, K.
2013-08-01
Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.
Effect of Variable Spatial Scales on USLE-GIS Computations
NASA Astrophysics Data System (ADS)
Patil, R. J.; Sharma, S. K.
2017-12-01
Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.
NASA Astrophysics Data System (ADS)
Zhang, X.; Roman, M.; Kimmel, D.; McGilliard, C.; Boicourt, W.
2006-05-01
High-resolution, axial sampling surveys were conducted in Chesapeake Bay during April, July, and October from 1996 to 2000 using a towed sampling device equipped with sensors for depth, temperature, conductivity, oxygen, fluorescence, and an optical plankton counter (OPC). The results suggest that the axial distribution and variability of hydrographic and biological parameters in Chesapeake Bay were primarily influenced by the source and magnitude of freshwater input. Bay-wide spatial trends in the water column-averaged values of salinity were linear functions of distance from the main source of freshwater, the Susquehanna River, at the head of the bay. However, spatial trends in the water column-averaged values of temperature, dissolved oxygen, chlorophyll-a and zooplankton biomass were nonlinear along the axis of the bay. Autocorrelation analysis and the residuals of linear and quadratic regressions between each variable and latitude were used to quantify the patch sizes for each axial transect. The patch sizes of each variable depended on whether the data were detrended, and the detrending techniques applied. However, the patch size of each variable was generally larger using the original data compared to the detrended data. The patch sizes of salinity were larger than those for dissolved oxygen, chlorophyll-a and zooplankton biomass, suggesting that more localized processes influence the production and consumption of plankton. This high-resolution quantification of the zooplankton spatial variability and patch size can be used for more realistic assessments of the zooplankton forage base for larval fish species.
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
Accounting for substitution and spatial heterogeneity in a labelled choice experiment.
Lizin, S; Brouwer, R; Liekens, I; Broeckx, S
2016-10-01
Many environmental valuation studies using stated preferences techniques are single-site studies that ignore essential spatial aspects, including possible substitution effects. In this paper substitution effects are captured explicitly in the design of a labelled choice experiment and the inclusion of different distance variables in the choice model specification. We test the effect of spatial heterogeneity on welfare estimates and transfer errors for minor and major river restoration works, and the transferability of river specific utility functions, accounting for key variables such as site visitation, spatial clustering and income. River specific utility functions appear to be transferable, resulting in low transfer errors. However, ignoring spatial heterogeneity increases transfer errors. Copyright © 2016 Elsevier Ltd. All rights reserved.
Spatial analysis of agri-environmental policy uptake and expenditure in Scotland.
Yang, Anastasia L; Rounsevell, Mark D A; Wilson, Ronald M; Haggett, Claire
2014-01-15
Agri-environment is one of the most widely supported rural development policy measures in Scotland in terms of number of participants and expenditure. It comprises 69 management options and sub-options that are delivered primarily through the competitive 'Rural Priorities scheme'. Understanding the spatial determinants of uptake and expenditure would assist policy-makers in guiding future policy targeting efforts for the rural environment. This study is unique in examining the spatial dependency and determinants of Scotland's agri-environmental measures and categorised options uptake and payments at the parish level. Spatial econometrics is applied to test the influence of 40 explanatory variables on farming characteristics, land capability, designated sites, accessibility and population. Results identified spatial dependency for each of the dependent variables, which supported the use of spatially-explicit models. The goodness of fit of the spatial models was better than for the aspatial regression models. There was also notable improvement in the models for participation compared with the models for expenditure. Furthermore a range of expected explanatory variables were found to be significant and varied according to the dependent variable used. The majority of models for both payment and uptake showed a significant positive relationship with SSSI (Sites of Special Scientific Interest), which are designated sites prioritised in Scottish policy. These results indicate that environmental targeting efforts by the government for AEP uptake in designated sites can be effective. However habitats outside of SSSI, termed here the 'wider countryside' may not be sufficiently competitive to receive funding in the current policy system. Copyright © 2013 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.
2017-12-01
Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.
Post-Fire Spatial Patterns of Soil Nitrogen Mineralization and Microbial Abundance
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
NASA Astrophysics Data System (ADS)
Roy, M. L.; Roy, A. G.
2009-12-01
Flow velocity is a major feature of fluvial fish habitat. It affects swimming energy expenditures, resource distribution and efficiency of prey capture, thus exerting a major influence on fish distribution. Preferences of juvenile salmonids for ranges of flow velocity are well documented. Preference curves are usually generated by comparing velocities measured at the precise location of captured fish (nose velocity) with velocities measured at random locations where fish are absent. However, these preferences tend to be specific to sites and rivers and show important variability with time. Recent biotelemetry studies have revealed that juvenile salmonids are more mobile than previously assumed and use larger home ranges and multiple micro-habitats. Therefore, fish might select habitats based on the characteristics of a microhabitat, but also based on the properties of the surrounding area. Furthermore, mobile fish could present temporal variability in their habitat preferences. Recent advances in biotelemetry provide new ways to monitor fish locations and to obtain habitat preferences both at the individual and the population levels at high temporal and spatial resolutions for extended periods. In this study, we seek to identify the most relevant spatial scales defining habitat preferences of juvenile Atlantic salmon. We emphasize both the group and individual temporal variability in hydraulic habitat preferences. During a three month period, we monitored the location and movements of 61 juveniles marked with 23-mm passive integrated transponders (PIT) using a network of 186 antennas buried into the bed of a natural river reach in Saguenay, Canada. Each antenna was scanned every 33 seconds to detect and record the presence or absence of tagged fish. The reach was 70 m long and 9 m wide on average and presented a very clear morphological sequence consisting of two pools separated by a riffle. Mean flow velocity and turbulent flow properties were measured at 3500 velocity locations across the reach with ADVs on a regular grid at 10 cm above the bed at low flow. We examined fish preferences at the microhabitat scale (nose velocity), at the feeding habitat scale (1.5 X 1.5 m), at a scale of surrounding feeding habitats (2.5 X 2.5 m) and at a scale of morphological units (pools and riffles). Over the study period, the antenna grid generated 106208 detections. Fish monitoring revealed a variability of spatial behaviors among individuals, some fish showing strong attachment to a small number of adjacent micro-habitats whereas others used a large number of micro-habitats located far apart, in both pools and riffles. Juvenile salmon exhibited preferences for medium to high velocity micro-habitats. However, fish presented hydraulic habitat preferences occurring at the scale of flow patches (≈ 6 m2). Furthermore, juvenile Atlantic salmon also showed an active habitat selection dynamics, where temporal individual preference curves for several hours were similar to that of the entire group of fish for a short time period. These observations highlight the importance of patch scale habitat features which provide valuable information for fish management.
Kevin L. O' Hara; Lathrop P. Leonard; Christopher R. Keyes
2012-01-01
Variable-density thinning (VDT) is an emerging thinning method that attempts to enhance stand structural heterogeneity by deliberately thinning at different intensities throughout a stand. VDT may create stands with dense areas, open areas, and other areas that may be intermediate in density. Subsequent stand development forms a more varied structure than is...
NASA Astrophysics Data System (ADS)
Ruttenberg, Kathleen C.; Dyhrman, Sonya T.
2005-10-01
High-frequency temporal and spatial shifts in the various dissolved P pools (total, inorganic, and organic) are linked to upwelling/relaxation events and to phytoplankton bloom dynamics in the upwelling-dominated Oregon coastal system. The presence and regulation of alkaline phosphatase activity (APA) is apparent in the bulk phytoplankton population and in studies of cell-specific APA using Enzyme Labeled Fluorescence (ELF®). Spatial and temporal variability are also evident in phytoplankton community composition and in APA. The spatial pattern of dissolved phosphorus and APA variability can be explained by bottom-controlled patterns of upwelling, and flushing times of different regions within the study area. The presence of APA in eukaryotic taxa indicates that dissolved organic phosphorus (DOP) may contribute to phytoplankton P nutrition in this system, highlighting the need for a more complete understanding of P cycling and bioavailability in the coastal ocean.
Quantitative analysis of spatial variability of geotechnical parameters
NASA Astrophysics Data System (ADS)
Fang, Xing
2018-04-01
Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.
El Sebai, T; Lagacherie, B; Soulas, G; Martin-Laurent, F
2007-02-01
We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass.
USDA-ARS?s Scientific Manuscript database
Determination of indicator bacteria concentrations in irrigation water recently became mandatory for farmers. These concentrations are known to have large spatial variability in ponds and reservoirs. This variability is partially attributed to affinity of indicator bacteria to algae accumulations. W...
Passive samplers deployed at 25 sites for three week-long intervals were used to characterize spatial variability in the mass and composition of coarse particulate matter (PM10-2.5) in Cleveland, OH in summer 2008. The size and composition of individual particles deter...
The coastal ocean is a highly variable system with processes that have significant implications on the hydrographic and oxygen characteristics of the water column. The spatial and temporal variability of these fields can cause dramatic changes to water quality and in turn the h...
NASA Astrophysics Data System (ADS)
Piazzi, L.; Bonaviri, C.; Castelli, A.; Ceccherelli, G.; Costa, G.; Curini-Galletti, M.; Langeneck, J.; Manconi, R.; Montefalcone, M.; Pipitone, C.; Rosso, A.; Pinna, S.
2018-07-01
In the Mediterranean Sea, Cystoseira species are the most important canopy-forming algae in shallow rocky bottoms, hosting high biodiverse sessile and mobile communities. A large-scale study has been carried out to investigate the structure of the Cystoseira-dominated assemblages at different spatial scales and to test the hypotheses that alpha and beta diversity of the assemblages, the abundance and the structure of epiphytic macroalgae, epilithic macroalgae, sessile macroinvertebrates and mobile macroinvertebrates associated to Cystoseira beds changed among scales. A hierarchical sampling design in a total of five sites across the Mediterranean Sea (Croatia, Montenegro, Sardinia, Tuscany and Balearic Islands) was used. A total of 597 taxa associated to Cystoseira beds were identified with a mean number per sample ranging between 141.1 ± 6.6 (Tuscany) and 173.9 ± 8.5(Sardinia). A high variability at small (among samples) and large (among sites) scale was generally highlighted, but the studied assemblages showed different patterns of spatial variability. The relative importance of the different scales of spatial variability should be considered to optimize sampling designs and propose monitoring plans of this habitat.
Leong, Y J; Sanchez, N P; Wallace, H W; Karakurt Cevik, B; Hernandez, C S; Han, Y; Flynn, J H; Massoli, P; Floerchinger, C; Fortner, E C; Herndon, S; Bean, J K; Hildebrandt Ruiz, L; Jeon, W; Choi, Y; Lefer, B; Griffin, R J
2017-08-01
The sources of submicrometer particulate matter (PM 1 ) remain poorly characterized in the industrialized city of Houston, TX. A mobile sampling approach was used to characterize PM 1 composition and concentration across Houston based on high-time-resolution measurements of nonrefractory PM 1 and trace gases during the DISCOVER-AQ Texas 2013 campaign. Two pollution zones with marked differences in PM 1 levels, character, and dynamics were established based on cluster analysis of organic aerosol mass loadings sampled at 16 sites. The highest PM 1 mass concentrations (average 11.6 ± 5.7 µg/m 3 ) were observed to the northwest of Houston (zone 1), dominated by secondary organic aerosol (SOA) mass likely driven by nighttime biogenic organonitrate formation. Zone 2, an industrial/urban area south/east of Houston, exhibited lower concentrations of PM 1 (average 4.4 ± 3.3 µg/m 3 ), significant organic aerosol (OA) aging, and evidence of primary sulfate emissions. Diurnal patterns and backward-trajectory analyses enable the classification of airmass clusters characterized by distinct PM sources: biogenic SOA, photochemical aged SOA, and primary sulfate emissions from the Houston Ship Channel. Principal component analysis (PCA) indicates that secondary biogenic organonitrates primarily related with monoterpenes are predominant in zone 1 (accounting for 34% of the variability in the data set). The relevance of photochemical processes and industrial and traffic emission sources in zone 2 also is highlighted by PCA, which identifies three factors related with these processes/sources (~50% of the aerosol/trace gas concentration variability). PCA reveals a relatively minor contribution of isoprene to SOA formation in zone 1 and the absence of isoprene-derived aerosol in zone 2. The relevance of industrial amine emissions and the likely contribution of chloride-displaced sea salt aerosol to the observed variability in pollution levels in zone 2 also are captured by PCA. This article describes an urban-scale mobile study to characterize spatial variations in submicrometer particulate matter (PM 1 ) in greater Houston. The data set indicates substantial spatial variations in PM 1 sources/chemistry and elucidates the importance of photochemistry and nighttime oxidant chemistry in producing secondary PM 1 . These results emphasize the potential benefits of effective control strategies throughout the region, not only to reduce primary emissions of PM 1 from automobiles and industry but also to reduce the emissions of important secondary PM 1 precursors, including sulfur oxides, nitrogen oxides, ammonia, and volatile organic compounds. Such efforts also could aid in efforts to reduce mixing ratios of ozone.
Observations of the Winter Thermal Structure of Lake Superior
NASA Astrophysics Data System (ADS)
Titze, Daniel James
Moored thermistor strings that span the water column have been deployed at up to seven locations throughout Lake Superior from 2005 through present, producing a unique year-round record of the thermal structure of a large lake. This extensive temperature record reveals significant interannual and spatial variability in Lake Superior's winter heat content, thermocline depth, and phenology. Of particular mention is a stark contrast in thermal structure between the cold, icy winter of 2009 and the much warmer winter of 2012, during which especially strong and weak negative stratification was observed, respectively. Significant interannual and spatial variability was also observed in Lake Superior ice cover, as shown through data extracted from Ice Mapping System satellite imagery (NOAA/NESDIS 2004). When water column heat content was estimated from temperature data and analyzed in concert with lake ice-cover data, it was found that ice cover can inhibit heat flux between the lake and the atmosphere, and that spatial variability in ice cover can translate into spatial variability in end-of-winter heat content. Such variability in end-of-winter heat content is found to be preserved through the spring warming season, and is strongly correlated with variability in the timing of the onset of summer stratification, with regions that have warmer end-of-winter water columns stratifying earlier than regions with colder end-of-winter water-columns.
NASA Astrophysics Data System (ADS)
Koenig, W.
2016-12-01
The ecological impacts of modern global climate change are detectable in a wide variety of phenomena ranging from shifts in species ranges to changes in community composition and human disease dynamics. Thus far, however, little attention has been given to temporal changes in environmental spatial synchrony-the coincident change in abundance or value across the landscape-or environmental variability, despite the importance of these factors as drivers of population rescue and extinction and reproductive dynamics of both animal and plant populations. We quantified spatial synchrony of widespread North American wintering birds species using Audubon Christmas Bird Counts over the past 50 years and seed set variability (mast fruiting) among trees over the past century and found that both spatial synchrony of the birds and seed set variability have significantly increased over these time periods. The first of these results was mirrored by significant increases in spatial synchrony of mean maximum air temperature across North America, primarily during the summer, while the second is consistent with the hypothesis that climate change is resulting in greater seed set variability. These findings suggest the potential for temporal changes in envioronmental synchrony and variability to be affecting a wide range of ecological phenomena by influencing the probability of population rescue and extinction and by affecting ecosystem processes that rely on the resource pulses provided by mast fruiting plants.
Analysis of field-scale spatial correlations and variations of soil nutrients using geostatistics.
Liu, Ruimin; Xu, Fei; Yu, Wenwen; Shi, Jianhan; Zhang, Peipei; Shen, Zhenyao
2016-02-01
Spatial correlations and soil nutrient variations are important for soil nutrient management. They help to reduce the negative impacts of agricultural nonpoint source pollution. Based on the sampled available nitrogen (AN), available phosphorus (AP), and available potassium (AK), soil nutrient data from 2010, the spatial correlation, was analyzed, and the probabilities of the nutrient's abundance or deficiency were discussed. This paper presents a statistical approach to spatial analysis, the spatial correlation analysis (SCA), which was originally developed for describing heterogeneity in the presence of correlated variation and based on ordinary kriging (OK) results. Indicator kriging (IK) was used to assess the susceptibility of excess of soil nutrients based on crop needs. The kriged results showed there was a distinct spatial variability in the concentration of all three soil nutrients. High concentrations of these three soil nutrients were found near Anzhou. As the distance from the center of town increased, the concentration of the soil nutrients gradually decreased. Spatially, the relationship between AN and AP was negative, and the relationship between AP and AK was not clear. The IK results showed that there were few areas with a risk of AN and AP overabundance. However, almost the entire study region was at risk of AK overabundance. Based on the soil nutrient distribution results, it is clear that the spatial variability of the soil nutrients differed throughout the study region. This spatial soil nutrient variability might be caused by different fertilizer types and different fertilizing practices.
Wong, Man Sing; Ho, Hung Chak; Yang, Lin; Shi, Wenzhong; Yang, Jinxin; Chan, Ta-Chien
2017-07-24
Dust events have long been recognized to be associated with a higher mortality risk. However, no study has investigated how prolonged dust events affect the spatial variability of mortality across districts in a downwind city. In this study, we applied a spatial regression approach to estimate the district-level mortality during two extreme dust events in Hong Kong. We compared spatial and non-spatial models to evaluate the ability of each regression to estimate mortality. We also compared prolonged dust events with non-dust events to determine the influences of community factors on mortality across the city. The density of a built environment (estimated by the sky view factor) had positive association with excess mortality in each district, while socioeconomic deprivation contributed by lower income and lower education induced higher mortality impact in each territory planning unit during a prolonged dust event. Based on the model comparison, spatial error modelling with the 1st order of queen contiguity consistently outperformed other models. The high-risk areas with higher increase in mortality were located in an urban high-density environment with higher socioeconomic deprivation. Our model design shows the ability to predict spatial variability of mortality risk during an extreme weather event that is not able to be estimated based on traditional time-series analysis or ecological studies. Our spatial protocol can be used for public health surveillance, sustainable planning and disaster preparation when relevant data are available.
Lin, Yu-Pin; Chu, Hone-Jay; Wang, Cheng-Long; Yu, Hsiao-Hsuan; Wang, Yung-Chieh
2009-01-01
This study applies variogram analyses of normalized difference vegetation index (NDVI) images derived from SPOT HRV images obtained before and after the ChiChi earthquake in the Chenyulan watershed, Taiwan, as well as images after four large typhoons, to delineate the spatial patterns, spatial structures and spatial variability of landscapes caused by these large disturbances. The conditional Latin hypercube sampling approach was applied to select samples from multiple NDVI images. Kriging and sequential Gaussian simulation with sufficient samples were then used to generate maps of NDVI images. The variography of NDVI image results demonstrate that spatial patterns of disturbed landscapes were successfully delineated by variogram analysis in study areas. The high-magnitude Chi-Chi earthquake created spatial landscape variations in the study area. After the earthquake, the cumulative impacts of typhoons on landscape patterns depended on the magnitudes and paths of typhoons, but were not always evident in the spatiotemporal variability of landscapes in the study area. The statistics and spatial structures of multiple NDVI images were captured by 3,000 samples from 62,500 grids in the NDVI images. Kriging and sequential Gaussian simulation with the 3,000 samples effectively reproduced spatial patterns of NDVI images. However, the proposed approach, which integrates the conditional Latin hypercube sampling approach, variogram, kriging and sequential Gaussian simulation in remotely sensed images, efficiently monitors, samples and maps the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial variability and heterogeneity.
Quantifying measurement uncertainty and spatial variability in the context of model evaluation
NASA Astrophysics Data System (ADS)
Choukulkar, A.; Brewer, A.; Pichugina, Y. L.; Bonin, T.; Banta, R. M.; Sandberg, S.; Weickmann, A. M.; Djalalova, I.; McCaffrey, K.; Bianco, L.; Wilczak, J. M.; Newman, J. F.; Draxl, C.; Lundquist, J. K.; Wharton, S.; Olson, J.; Kenyon, J.; Marquis, M.
2017-12-01
In an effort to improve wind forecasts for the wind energy sector, the Department of Energy and the NOAA funded the second Wind Forecast Improvement Project (WFIP2). As part of the WFIP2 field campaign, a large suite of in-situ and remote sensing instrumentation was deployed to the Columbia River Gorge in Oregon and Washington from October 2015 - March 2017. The array of instrumentation deployed included 915-MHz wind profiling radars, sodars, wind- profiling lidars, and scanning lidars. The role of these instruments was to provide wind measurements at high spatial and temporal resolution for model evaluation and improvement of model physics. To properly determine model errors, the uncertainties in instrument-model comparisons need to be quantified accurately. These uncertainties arise from several factors such as measurement uncertainty, spatial variability, and interpolation of model output to instrument locations, to name a few. In this presentation, we will introduce a formalism to quantify measurement uncertainty and spatial variability. The accuracy of this formalism will be tested using existing datasets such as the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign. Finally, the uncertainties in wind measurement and the spatial variability estimates from the WFIP2 field campaign will be discussed to understand the challenges involved in model evaluation.
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.
One perspective on spatial variability in geologic mapping
Markewich, H.W.; Cooper, S.C.
1991-01-01
This paper discusses some of the differences between geologic mapping and soil mapping, and how the resultant maps are interpreted. The role of spatial variability in geologic mapping is addressed only indirectly because in geologic mapping there have been few attempts at quantification of spatial differences. This is largely because geologic maps deal with temporal as well as spatial variability and consider time, age, and origin, as well as composition and geometry. Both soil scientists and geologists use spatial variability to delineate mappable units; however, the classification systems from which these mappable units are defined differ greatly. Mappable soil units are derived from systematic, well-defined, highly structured sets of taxonomic criteria; whereas mappable geologic units are based on a more arbitrary heirarchy of categories that integrate many features without strict values or definitions. Soil taxonomy is a sorting tool used to reduce heterogeneity between soil units. Thus at the series level, soils in any one series are relatively homogeneous because their range of properties is small and well-defined. Soil maps show the distribution of soils on the land surface. Within a map area, soils, which are often less than 2 m thick, show a direct correlation to topography and to active surface processes as well as to parent material.
Spatial-temporal and cancer risk assessment of selected hazardous air pollutants in Seattle.
Wu, Chang-fu; Liu, L-J Sally; Cullen, Alison; Westberg, Hal; Williamson, John
2011-01-01
In the Seattle Air Toxics Monitoring Pilot Program, we measured 15 hazardous air pollutants (HAPs) at 6 sites for more than a year between 2000 and 2002. Spatial-temporal variations were evaluated with random-effects models and principal component analyses. The potential health risks were further estimated based on the monitored data, with the incorporation of the bootstrapping technique for the uncertainty analysis. It is found that the temporal variability was generally higher than the spatial variability for most air toxics. The highest temporal variability was observed for tetrachloroethylene (70% temporal vs. 34% spatial variability). Nevertheless, most air toxics still exhibited significant spatial variations, even after accounting for the temporal effects. These results suggest that it would require operating multiple air toxics monitoring sites over a significant period of time with proper monitoring frequency to better evaluate population exposure to HAPs. The median values of the estimated inhalation cancer risks ranged between 4.3 × 10⁻⁵ and 6.0 × 10⁻⁵, with the 5th and 95th percentile levels exceeding the 1 in a million level. VOCs as a whole contributed over 80% of the risk among the HAPs measured and arsenic contributed most substantially to the overall risk associated with metals. Copyright © 2010 Elsevier Ltd. All rights reserved.
Shryock, Daniel F.; Havrilla, Caroline A.; DeFalco, Lesley; Esque, Todd C.; Custer, Nathan; Wood, Troy E.
2015-01-01
Local adaptation influences plant species’ responses to climate change and their performance in ecological restoration. Fine-scale physiological or phenological adaptations that direct demographic processes may drive intraspecific variability when baseline environmental conditions change. Landscape genomics characterize adaptive differentiation by identifying environmental drivers of adaptive genetic variability and mapping the associated landscape patterns. We applied such an approach to Sphaeralcea ambigua, an important restoration plant in the arid southwestern United States, by analyzing variation at 153 amplified fragment length polymorphism loci in the context of environmental gradients separating 47 Mojave Desert populations. We identified 37 potentially adaptive loci through a combination of genome scan approaches. We then used a generalized dissimilarity model (GDM) to relate variability in potentially adaptive loci with spatial gradients in temperature, precipitation, and topography. We identified non-linear thresholds in loci frequencies driven by summer maximum temperature and water stress, along with continuous variation corresponding to temperature seasonality. Two GDM-based approaches for mapping predicted patterns of local adaptation are compared. Additionally, we assess uncertainty in spatial interpolations through a novel spatial bootstrapping approach. Our study presents robust, accessible methods for deriving spatially-explicit models of adaptive genetic variability in non-model species that will inform climate change modelling and ecological restoration.
NASA Astrophysics Data System (ADS)
Samuel, Putra A.; Widyaningsih, Yekti; Lestari, Dian
2016-02-01
The objective of this study is modeling the Unemployment Rate (UR) in West Java, Central Java, and East Java, with rate of disease, infant mortality rate, educational level, population size, proportion of married people, and GDRP as the explanatory variables. Spatial factors are also considered in the modeling since the closer the distance, the higher the correlation. This study uses the secondary data from BPS (Badan Pusat Statistik). The data will be analyzed using Moran I test, to obtain the information about spatial dependence, and using Spatial Autoregressive modeling to obtain the information, which variables are significant affecting UR and how great the influence of the spatial factors. The result is, variables proportion of married people, rate of disease, and population size are related significantly to UR. In all three regions, the Hotspot of unemployed will also be detected districts/cities using Spatial Scan Statistics Method. The results are 22 districts/cities as a regional group with the highest unemployed (Most likely cluster) in the study area; 2 districts/cities as a regional group with the highest unemployed in West Java; 1 district/city as a regional groups with the highest unemployed in Central Java; 15 districts/cities as a regional group with the highest unemployed in East Java.
Evaluation of potential water conservation using site-specific irrigation
USDA-ARS?s Scientific Manuscript database
With the advent of site-specific variable-rate irrigation (VRI) systems, irrigation can be spatially managed within sub-field-sized zones. Spatial irrigation management can optimize spatial water use efficiency and may conserve water. Spatial VRI systems are currently being managed by consultants ...
Peña-Perez, Luis Manuel; Pedraza-Ortega, Jesus Carlos; Ramos-Arreguin, Juan Manuel; Arriaga, Saul Tovar; Fernandez, Marco Antonio Aceves; Becerra, Luis Omar; Hurtado, Efren Gorrostieta; Vargas-Soto, Jose Emilio
2013-10-24
The present work presents an improved method to align the measurement scale mark in an immersion hydrometer calibration system of CENAM, the National Metrology Institute (NMI) of Mexico, The proposed method uses a vision system to align the scale mark of the hydrometer to the surface of the liquid where it is immersed by implementing image processing algorithms. This approach reduces the variability in the apparent mass determination during the hydrostatic weighing in the calibration process, therefore decreasing the relative uncertainty of calibration.
Peña-Perez, Luis Manuel; Pedraza-Ortega, Jesus Carlos; Ramos-Arreguin, Juan Manuel; Arriaga, Saul Tovar; Fernandez, Marco Antonio Aceves; Becerra, Luis Omar; Hurtado, Efren Gorrostieta; Vargas-Soto, Jose Emilio
2013-01-01
The present work presents an improved method to align the measurement scale mark in an immersion hydrometer calibration system of CENAM, the National Metrology Institute (NMI) of Mexico, The proposed method uses a vision system to align the scale mark of the hydrometer to the surface of the liquid where it is immersed by implementing image processing algorithms. This approach reduces the variability in the apparent mass determination during the hydrostatic weighing in the calibration process, therefore decreasing the relative uncertainty of calibration. PMID:24284770
NASA Astrophysics Data System (ADS)
Teodoro, A. C.; Amaral, A.
2017-10-01
Portugal is one of the most affected countries in Europe by forest fires. Every year in the summer, hundreds of hectares burn, destroying goods and forests at an alarming rate. The objective of this work was to analyze the forest areas burned in Portugal in 2016 (summer) using different satellite data with different spatial resolution (Sentinel-2A MSI and Landsat 8 OLI) in two affected areas. Data from spring from 2016 and 2017 were chosen (pre-fire event and post-fire event) in order to maximize the Normalized Difference Vegetation Index (NDVI) values. The QGIS software's plugin - Semi- Automatic Classification Plugin- which allowed to obtain NDVI values for the Landsat 8 OLI and Sentinel- 2A was used. The results showed that the NDVI decreased considerably in Arouca and Vila Nova de Cerveira after de fire event, meaning a marked drop in vegetation level. In Sintra municipality this change was not verified because non forest fire was registered in this area during the study period. The results from the Sentinel-2A and Landsat 8 OLI data analysis are in agreement, however the Sentinel-2A satellite gives results more accurate than Landsat-8 OLI since it has best spatial resolution. This study could help the experts to understand both the causes and consequences of spatial variability of post-fire effects. Other vegetation spectral indices related with fire and burnt areas could also be calculated in order to discriminate burnt areas. Added to the best spatial resolution of Sentinel-2A (10 m), the temporal resolution of Sentinel- 2A (10 days) was increased with the launch of the twin Sentinel-2B (very recently) and therefore the frequency of the combined constellation revisit will be 5 days. However, for historical studies, the Landsat program remains the best option.
NASA Astrophysics Data System (ADS)
Kammel, L.; Pasternack, G. B.; Wyrick, J. R.; Massa, D.; Bratovich, P.; Johnson, T.
2012-12-01
Currently accepted perception assumes Oncorhynchus mykiss prefer different ranges of similar physical habitat elements for spawning than Chinook salmon (Oncorhynchus tshawytscha), taking into account their difference in size. While there is increasing research interest regarding O. mykiss habitat use and migratory behavior, research conducted to date distinguishing the physical habitat conditions utilized for O. mykiss spawning has not provided quantified understanding of their spawning habitat preferences. The purpose of this study was to use electivity indices and other measures to assess the physical habitat characteristics preferred for O. mykiss spawning in terms of both 1-m scale microhabitat attributes, and landforms at different spatial scales from 0.1-100 times channel width. The testbed for this study was the 37.5-km regulated gravel-cobble Lower Yuba River (LYR). Using spatially distributed 2D hydrodynamic model results, substrate mapping, and a census of O. mykiss redds from two years of observation, micro- and meso-scale representations of physical habitat were tested for their ability to predict spawning habitat preference and avoidance. Overall there was strong stratification of O. mykiss redd occurrence for all representation types of physical habitat. A strong preference of hydraulic conditions was shown for mean water column velocities of 1.18-2.25 ft/s, and water depths of 1.25-2.76 ft. There was a marked preference for the two most upstream alluvial reaches of the LYR (out of 8 total reaches), accounting for 92% of all redds observed. The preferred morphological units (MUs) for O. mykiss spawning were more variable than for Chinook salmon and changed with increasing discharge, demonstrating that O. mykiss shift spawning to different MUs in order to utilize their preferred hydraulic conditions. The substrate range preferred for O. mykiss spawning was within 32-90 mm. Overall, O. mykiss spawning behavior was highly predictable and required a holistic blend of hydraulic and geomorphic representations to explain.
Numerical investigation of aggregated fuel spatial pattern impacts on fire behavior
Parsons, Russell A.; Linn, Rodman Ray; Pimont, Francois; ...
2017-06-18
Here, landscape heterogeneity shapes species distributions, interactions, and fluctuations. Historically, in dry forest ecosystems, low canopy cover and heterogeneous fuel patterns often moderated disturbances like fire. Over the last century, however, increases in canopy cover and more homogeneous patterns have contributed to altered fire regimes with higher fire severity. Fire management strategies emphasize increasing within-stand heterogeneity with aggregated fuel patterns to alter potential fire behavior. Yet, little is known about how such patterns may affect fire behavior, or how sensitive fire behavior changes from fuel patterns are to winds and canopy cover. Here, we used a physics-based fire behavior model,more » FIRETEC, to explore the impacts of spatially aggregated fuel patterns on the mean and variability of stand-level fire behavior, and to test sensitivity of these effects to wind and canopy cover. Qualitative and quantitative approaches suggest that spatial fuel patterns can significantly affect fire behavior. Based on our results we propose three hypotheses: (1) aggregated spatial fuel patterns primarily affect fire behavior by increasing variability; (2) this variability should increase with spatial scale of aggregation; and (3) fire behavior sensitivity to spatial pattern effects should be more pronounced under moderate wind and fuel conditions.« less
Numerical investigation of aggregated fuel spatial pattern impacts on fire behavior
DOE Office of Scientific and Technical Information (OSTI.GOV)
Parsons, Russell A.; Linn, Rodman Ray; Pimont, Francois
Here, landscape heterogeneity shapes species distributions, interactions, and fluctuations. Historically, in dry forest ecosystems, low canopy cover and heterogeneous fuel patterns often moderated disturbances like fire. Over the last century, however, increases in canopy cover and more homogeneous patterns have contributed to altered fire regimes with higher fire severity. Fire management strategies emphasize increasing within-stand heterogeneity with aggregated fuel patterns to alter potential fire behavior. Yet, little is known about how such patterns may affect fire behavior, or how sensitive fire behavior changes from fuel patterns are to winds and canopy cover. Here, we used a physics-based fire behavior model,more » FIRETEC, to explore the impacts of spatially aggregated fuel patterns on the mean and variability of stand-level fire behavior, and to test sensitivity of these effects to wind and canopy cover. Qualitative and quantitative approaches suggest that spatial fuel patterns can significantly affect fire behavior. Based on our results we propose three hypotheses: (1) aggregated spatial fuel patterns primarily affect fire behavior by increasing variability; (2) this variability should increase with spatial scale of aggregation; and (3) fire behavior sensitivity to spatial pattern effects should be more pronounced under moderate wind and fuel conditions.« less
Mai, Ji-shan; Zhao, Ting-ning; Zheng, Jiang-kun; Shi, Chang-qing
2015-12-01
Based on grid sampling and laboratory analysis, spatial variability of surface soil nutrients was analyzed with GS⁺ and other statistics methods on the landslide area of Fenghuang Mountain, Leigu Town, Beichuan County. The results showed that except for high variability of available phosphorus, other soil nutrients exhibited moderate variability. The ratios of nugget to sill of the soil available phosphorus and soil organic carbon were 27.9% and 28.8%, respectively, showing moderate spatial correlation, while the ratios of nugget to sill of the total nitrogen (20.0%), total phosphorus (24.3%), total potassium (11.1%), available nitrogen (11.2%), and available potassium (22.7%) suggested strong spatial correlation. The total phosphorus had the maximum range (1232.7 m), followed by available nitrogen (541.27 m), total nitrogen (468.35 m), total potassium (136.0 m), available potassium (128.7 m), available phosphorus (116.6 m), and soil organic carbon (93.5 m). Soil nutrients had no significant variation with the increase of altitude, but gradually increased from the landslide area, the transition area, to the little-impacted area. The total and available phosphorus contents of the landslide area decreased by 10.3% and 79.7% compared to that of the little-impacted area, respectively. The soil nutrient contents in the transition area accounted for 31.1%-87.2% of that of the little-impacted area, with the nant reason for the spatial variability of surface soil nutrients.
Olfactory eavesdropping by a competitively foraging stingless bee, Trigona spinipes.
Nieh, James C.; Barreto, Lillian S.; Contrera, Felipe A. L.; Imperatriz-Fonseca, Vera L.
2004-01-01
Signals that are perceived over long distances or leave extended spatial traces are subject to eavesdropping. Eavesdropping has therefore acted as a selective pressure in the evolution of diverse animal communication systems, perhaps even in the evolution of functionally referential communication. Early work suggested that some species of stingless bees (Hymenoptera, Apidae, Meliponini) may use interceptive olfactory eavesdropping to discover food sources being exploited by competitors, but it is not clear if any stingless bee can be attracted to the odour marks deposited by an interspecific competitor. We show that foragers of the aggressive meliponine bee, Trigona spinipes, can detect and orient towards odour marks deposited by a competitor, Melipona rufiventris, and then rapidly take over the food source, driving away or killing their competitors. When searching for food sources at new locations that they are not already exploiting, T. spinipes foragers strongly prefer M. rufiventris odour marks to odour marks deposited by their own nest-mates, whereas they prefer nest-mate odour marks over M. rufiventris odour marks at a location already occupied by T. spinipes nest-mates. Melipona rufiventris foragers flee from T. spinipes odour marks. This olfactory eavesdropping may have played a role in the evolution of potentially cryptic communication mechanisms such as shortened odour trails, point-source only odour marking and functionally referential communication concealed at the nest. PMID:15306311
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.
Hinckley, A; Bachand, A; Nuckols, J; Reif, J
2005-01-01
Background and Aims: Epidemiological studies of disinfection by-products (DBPs) and reproductive outcomes have been hampered by misclassification of exposure. In most epidemiological studies conducted to date, all persons living within the boundaries of a water distribution system have been assigned a common exposure value based on facility-wide averages of trihalomethane (THM) concentrations. Since THMs do not develop uniformly throughout a distribution system, assignment of facility-wide averages may be inappropriate. One approach to mitigate this potential for misclassification is to select communities for epidemiological investigations that are served by distribution systems with consistently low spatial variability of THMs. Methods and Results: A feasibility study was conducted to develop methods for community selection using the Information Collection Rule (ICR) database, assembled by the US Environmental Protection Agency. The ICR database contains quarterly DBP concentrations collected between 1997 and 1998 from the distribution systems of 198 public water facilities with minimum service populations of 100 000 persons. Facilities with low spatial variation of THMs were identified using two methods; 33 facilities were found with low spatial variability based on one or both methods. Because brominated THMs may be important predictors of risk for adverse reproductive outcomes, sites were categorised into three exposure profiles according to proportion of brominated THM species and average TTHM concentration. The correlation between THMs and haloacetic acids (HAAs) in these facilities was evaluated to see whether selection by total trihalomethanes (TTHMs) corresponds to low spatial variability for HAAs. TTHMs were only moderately correlated with HAAs (r = 0.623). Conclusions: Results provide a simple method for a priori selection of sites with low spatial variability from state or national public water facility datasets as a means to reduce exposure misclassification in epidemiological studies of DBPs. PMID:15961627
Changes In The Heating Degree-days In Norway Due Toglobal Warming
NASA Astrophysics Data System (ADS)
Skaugen, T. E.; Tveito, O. E.; Hanssen-Bauer, I.
A continuous spatial representation of temperature improves the possibility topro- duce maps of temperature-dependent variables. A temperature scenario for the period 2021-2050 is obtained for Norway from the Max-Planck-Institute? AOGCM, GSDIO ECHAM4/OPEC 3. This is done by an ?empirical downscaling method? which in- volves the use of empirical links between large-scale fields and local variables to de- duce estimates of the local variables. The analysis is obtained at forty-six sites in Norway. Spatial representation of the anomalies of temperature in the scenario period compared to the normal period (1961-1990) is obtained with the use of spatial interpo- lation in a GIS. The temperature scenario indicates that we will have a warmer climate in Norway in the future, especially during the winter season. The heating degree-days (HDD) is defined as the accumulated Celsius degrees be- tween the daily mean temperature and a threshold temperature. For Scandinavian countries, this threshold temperature is 17 Celsius degrees. The HDD is found to be a good estimate of accumulated cold. It is therefore a useful index for heating energy consumption within the heating season, and thus to power production planning. As a consequence of the increasing temperatures, the length of the heating season and the HDD within this season will decrease in Norway in the future. The calculations of the heating season and the HDD is estimated at grid level with the use of a GIS. The spatial representation of the heating season and the HDD can then easily be plotted. Local information of the variables being analysed can be withdrawn from the spatial grid in a GIS. The variable is prepared for further spatial analysis. It may also be used as an input to decision making systems.
NASA Astrophysics Data System (ADS)
Tolu, Julie; Rydberg, Johan; Meyer-Jacob, Carsten; Gerber, Lorenz; Bindler, Richard
2017-04-01
The composition of sediment organic matter (OM) exerts a strong control on biogeochemical processes in lakes, such as those involved in the fate of carbon, nutrients and trace metals. While between-lake spatial variability of OM quality is increasingly investigated, we explored in this study how the molecular composition of sediment OM varies spatially within a single lake and related this variability to physical parameters and elemental geochemistry. Surface sediment samples (0-10 cm) from 42 locations in Härsvatten - a small boreal forest lake with a complex basin morphometry - were analyzed for OM molecular composition using pyrolysis gas chromatography mass spectrometry for the contents of 23 major and trace elements and biogenic silica. We identified 162 organic compounds belonging to different biochemical classes of OM (e.g., carbohydrates, lignin and lipids). Close relationships were found between the spatial patterns of sediment OM molecular composition and elemental geochemistry. Differences in the source types of OM (i.e., terrestrial, aquatic plant and algal) were linked to the individual basin morphometries and chemical status of the lake. The variability in OM molecular composition was further driven by the degradation status of these different source pools, which appeared to be related to sedimentary physicochemical parameters (e.g., redox conditions) and to the molecular structure of the organic compounds. Given the high spatial variation in OM molecular composition within Härsvatten and its close relationship with elemental geochemistry, the potential for large spatial variability across lakes should be considered when studying biogeochemical processes involved in the cycling of carbon, nutrients and trace elements or when assessing lake budgets.
Qiu, Maolin; Ramani, Ramachandran; Swetye, Michael; Constable, Robert Todd
2008-12-01
Pulsed arterial spin labeling magnetic resonance imaging (MRI) was performed to investigate the local coupling between resting regional cerebral blood flow (rCBF) and BOLD (blood oxygen level dependent) signal changes in 22 normal human subjects during the administration of 0.25 MAC (minimum alveolar concentration) sevoflurane. Two states were compared with subjects at rest: anesthesia and no-anesthesia. Regions of both significantly increased and decreased resting-state rCBF were observed. Increases were limited primarily to subcortical structures and insula, whereas, decreases were observed primarily in neocortical regions. No significant change was found in global CBF (gCBF). By simultaneously measuring rCBF and BOLD, region-specific anesthetic effects on the coupling between rCBF and BOLD were identified. Multiple comparisons of the agent-induced rCBF and BOLD changes demonstrated significant (P < 0.05) spatial variability in rCBF-BOLD coupling. The slope of the linear regression line for AC, where rCBF was increased by sevoflurane, was markedly smaller than the slope for those ROIs where rCBF was decreased by sevoflurane, indicating a bigger change in BOLD per unit change in rCBF in regions where rCBF was increased by sevoflurane. These results suggest that it would be inaccurate to use a global quantitative model to describe coupling across all brain regions and in all anesthesia conditions. The observed spatial nonuniformity of rCBF and BOLD signal changes suggests that any interpretation of BOLD fMRI data in the presence of an anesthetic requires consideration of these insights. Copyright 2007 Wiley-Liss, Inc.
Modeling movement and fidelity of American black ducks
Zimpfer, N.L.; Conroy, M.J.
2006-01-01
Spatial relationships among stocks of breeding waterfowl can be an important component of harvest management. Prediction and optimal harvest management under adaptive harvest management (AHM) requires information on the spatial relationships among breeding populations (fidelity and inter-year exchange), as well as rates of movements from breeding to harvest regions. We used band-recovery data to develop a model to estimate probabilities of movement for American black ducks (Anas rubripes) among 3 Canadian breeding strata and 6 harvest regions (3 in Canada, and 3 in the United States) over the period 1965-1998. Model selection criteria suggested that models containing area-, year-, and age-specific recovery rates with area- and sex-specific movement rates were the best for modeling movement. Movement by males to southern harvest areas was variable depending on the originating area. Males from the western breeding area predominantly moved to the Mississippi Flyway or southern Atlantic Flyway (??ij = 0.353, SE = 0.0187 and ??ij = 0.473, SE = 0.037, respectively), whereas males that originated in the eastern and central breeding strata moved to the northern Atlantic flyway (??ij = 0.842, SE = 0.010 and ??ij = 0.578, SE = 0.0222, respectively). We used combined recoveries and recaptures in Program MARK to estimate fidelity to the 3 Canadian breeding strata. Information criteria identified a model containing sex- and age-specific fidelity for black ducks. Estimates of fidelity were 0.9695 (SE = 0.0249) and 0.9554 (SE = 0.0434) for adult males and females, respectively. Estimates of fidelity for juveniles were slightly lower at 0.9210 (SE = 0.0931) and 0.8870 (SE = 0.0475) for males and females, respectively. These models have application to the development of spatially stratified black duck harvest management models for use in AHM.
Distribution of heavy metals in agricultural soils near a petrochemical complex in Guangzhou, China.
Li, Junhui; Lu, Ying; Yin, Wei; Gan, Haihua; Zhang, Chao; Deng, Xianglian; Lian, Jin
2009-06-01
The aim of the study was to investigate influence of an industrialized environment on the accumulation of heavy metals in agricultural soils. Seventy soil samples collected from surface layers (0-20 cm) and horizons of five selected pedons in the vicinity area of petrochemical complex in Guangzhou, China were analyzed for Zn, Cu, Pb, Cd, Hg and As concentrations, the horizontal and vertical variation of these metals were studied and geographic information system (GIS)-based mapping techniques were applied to generate spatial distribution maps. The mean concentrations of these heavy metals in the topsoils did not exceed the maximum allowable concentrations in agricultural soil of China with the exception of Hg. Significant differences between land-use types showed that Cu, Pb, Cd, Hg and As concentrations in topsoils were strongly influenced by agricultural practices and soil management. Within a radius of 1,300 m there were no marked decreasing trends for these element concentrations (except for Zn) with the increase of distance from the complex boundary, which reflected little influence of petroleum air emission on soil heavy metal accumulation. Concentrations of Zn, Cu, Pb, Cd, Hg and As in the five pedons, particularly in cultivated vegetable field and orchard, decreased with soil depth, indicating these elements mainly originated from anthropogenic sources. GIS mapping was a useful tool for evaluating spatial variability of heavy metals in the affected soil. The spatial distribution maps allowed the identification of hot-spot areas with high metal concentration. Effective measures should be taken to avoid or minimize heavy metal further contamination of soils and to remediate the contaminated areas in order to prevent pollutants affecting human health through agricultural products.
Spatially explicit population estimates for black bears based on cluster sampling
Humm, J.; McCown, J. Walter; Scheick, B.K.; Clark, Joseph D.
2017-01-01
We estimated abundance and density of the 5 major black bear (Ursus americanus) subpopulations (i.e., Eglin, Apalachicola, Osceola, Ocala-St. Johns, Big Cypress) in Florida, USA with spatially explicit capture-mark-recapture (SCR) by extracting DNA from hair samples collected at barbed-wire hair sampling sites. We employed a clustered sampling configuration with sampling sites arranged in 3 × 3 clusters spaced 2 km apart within each cluster and cluster centers spaced 16 km apart (center to center). We surveyed all 5 subpopulations encompassing 38,960 km2 during 2014 and 2015. Several landscape variables, most associated with forest cover, helped refine density estimates for the 5 subpopulations we sampled. Detection probabilities were affected by site-specific behavioral responses coupled with individual capture heterogeneity associated with sex. Model-averaged bear population estimates ranged from 120 (95% CI = 59–276) bears or a mean 0.025 bears/km2 (95% CI = 0.011–0.44) for the Eglin subpopulation to 1,198 bears (95% CI = 949–1,537) or 0.127 bears/km2 (95% CI = 0.101–0.163) for the Ocala-St. Johns subpopulation. The total population estimate for our 5 study areas was 3,916 bears (95% CI = 2,914–5,451). The clustered sampling method coupled with information on land cover was efficient and allowed us to estimate abundance across extensive areas that would not have been possible otherwise. Clustered sampling combined with spatially explicit capture-recapture methods has the potential to provide rigorous population estimates for a wide array of species that are extensive and heterogeneous in their distribution.
NASA Astrophysics Data System (ADS)
Gao, Zhaofu; Zhu, Xiangkun; Sun, Jian; Luo, Zhaohua; Bao, Chuang; Tang, Chao; Ma, Jianxiong
2018-01-01
Analyses of sphalerite minerals from the characteristic brecciated Zn-Pb ores of the main ore body in the giant Dongshengmiao deposit have revealed variations in δ66Zn from 0.17 to 0.40‰ and in δ56Fe from -1.78 to -0.35‰. Further, the investigated pyrrhotite samples have iron that is isotopically similar to that of associated sphalerite minerals. The most distinctive pattern revealed by the zinc and iron isotope data is the lateral trend of increasing δ66Zn and δ56Fe values from southwest to northeast within the main ore body. The lead isotopic homogeneity of ore sulfides from the main ore body suggests that there is only one significant source for metal, thus precluding the mixing of multiple metal sources as the key factor controlling spatial variations of zinc and iron isotopes. The most likely control on spatial variations is Rayleigh fractionation during hydrothermal fluid flow, with lighter Zn and Fe isotopes preferentially incorporated into the earliest sulfides to precipitate from fluids. Precipitations of sphalerite and pyrrhotite have played vital roles in the Zn and Fe isotopic variations, respectively, of the ore-forming system. Accordingly, the larger isotopic variability for Fe than Zn within the same hydrothermal system perhaps resulted from a larger proportion of precipitation for pyrrhotite than for sphalerite. The lateral trend pattern revealed by the zinc and iron isotope data is consistent with the occurrence of a cystic-shaped breccia zone, which is characterized by marked elevation in Cu. The results further confirm that Zn and Fe isotopes can be used as a vectoring tool for mineral prospecting.
Rossiter, Wayne; Sukhdeo, Michael V K
2012-04-01
Several studies have suggested that the fitness of a parasite can be directly impacted by the quality of its host. In such cases, selective pressures could act to funnel parasites towards the highest-quality hosts in a population. The results of this study demonstrate that snail host quality is strongly correlated with spatial patterning in trematode infections and that habitat type is the underlying driver for both of these variables. Two trematodes (Himasthla quissetensis and Zoogonus rubellus) with very different life cycles assume the same spatial infection pattern in populations of the first intermediate host (Ilyanassa obsoleta) in coastal marsh habitats. Infected snails are disproportionately recovered from intertidal panne habitats, which offer more hospitable environs for snails than do adjacent habitats (intertidal creeks, coastal flats, and subtidal creeks), in terms of protection from turbulence and wave action, as well as the availability of food stuffs. Snails in intertidal panne habitats are of higher quality when assessed in terms of average size-specific mass, growth rate, and fecundity. In mark-recapture experiments, snails frequently dispersed into intertidal pannes but were never observed leaving them. In addition, field experiments demonstrate that snails confined to intertidal panne habitats are disproportionately infected by both trematode species, relative to conspecifics confined to adjacent habitats. Laboratory experiments show that infected snails suffer significant energetic losses and consume more than uninfected conspecifics, suggesting that infected snails in intertidal pannes may survive better than in adjacent habitats. We speculate that 1 possible mechanism for the observed patterns is that the life cycles of both trematode species allows them to contact the highest-quality snails in this marsh ecosystem.
NASA Astrophysics Data System (ADS)
Ives, Christopher
2015-04-01
Measuring social values for landscapes is an emerging field of research and is critical to the successful management of urban ecosystems. Green open space planning has traditionally relied on rigid standards and metrics without considering the physical requirements of green spaces that are valued for different reasons and by different people. Relating social landscape values to key environmental variables provides a much stronger evidence base for planning landscapes that are both socially desirable and environmentally sustainable. This study spatially quantified residents' values for green space in the Lower Hunter Valley of New South Wales, Australia by enabling participants to mark their values for specific open spaces on interactive paper maps. The survey instrument was designed to evaluate the effect of spatial scale by providing maps of residents' local area at both suburb and municipality scales. The importance of open space values differed depending on whether they were indicated via marker dots or reported on in a general aspatial sense. This suggests that certain open space functions were inadequately provided for in the local area (specifically, cultural significance and health/therapeutic value). Additionally, all value types recorded a greater abundance of marker dots at the finer (suburb) scale compared to the coarser (municipality) scale, but this pattern was more pronounced for some values than others (e.g. physical exercise value). Finally, significant relationships were observed between the abundance of value marker dots in parks and their environmental characteristics (e.g. percentage of vegetation). These results have interesting implications when considering the compatibility between different functions of green spaces and how planners can incorporate information about social values with more traditional approaches to green space planning.
Geostatistical mapping of effluent-affected sediment distribution on the Palos Verdes shelf
Murray, C.J.; Lee, H.J.; Hampton, M.A.
2002-01-01
Geostatistical techniques were used to study the spatial continuity of the thickness of effluent-affected sediment in the offshore Palos Verdes Margin area. The thickness data were measured directly from cores and indirectly from high-frequency subbottom profiles collected over the Palos Verdes Margin. Strong spatial continuity of the sediment thickness data was identified, with a maximum range of correlation in excess of 1.4 km. The spatial correlation showed a marked anisotropy, and was more than twice as continuous in the alongshore direction as in the cross-shelf direction. Sequential indicator simulation employing models fit to the thickness data variograms was used to map the distribution of the sediment, and to quantify the uncertainty in those estimates. A strong correlation between sediment thickness data and measurements of the mass of the contaminant p,p???-DDE per unit area was identified. A calibration based on the bivariate distribution of the thickness and p,p???-DDE data was applied using Markov-Bayes indicator simulation to extend the geostatistical study and map the contamination levels in the sediment. Integrating the map grids produced by the geostatistical study of the two variables indicated that 7.8 million m3 of effluent-affected sediment exist in the map area, containing approximately 61-72 Mg (metric tons) of p,p???-DDE. Most of the contaminated sediment (about 85% of the sediment and 89% of the p,p???-DDE) occurs in water depths < 100 m. The geostatistical study also indicated that the samples available for mapping are well distributed and the uncertainty of the estimates of the thickness and contamination level of the sediments is lowest in areas where the contaminated sediment is most prevalent. ?? 2002 Elsevier Science Ltd. All rights reserved.
Tao, Wen; Shi, Jianjian; Dorn, Gerald W.; Wei, Lei; Rubart, Michael
2012-01-01
Pathological left ventricular hypertrophy (LVH) is consistently associated with prolongation of the ventricular action potentials. A number of previous studies, employing various experimental models of hypertrophy, have revealed marked differences in the effects of hypertrophy on action potential duration (APD) between myocytes from endocardial and epicardial layers of the LV free wall. It is not known, however, whether pathological LVH is also accompanied by redistribution of APD among myocytes from the same layer in the LV free wall. In the experiments here, LV epicardial action potential remodeling was examined in a mouse model of decompensated LVH, produced by cardiac-restricted transgenic Gαq overexpression. Confocal linescanning-based optical recordings of propagated action potentials from individual in situ cardiomyocytes across the outer layer of the anterior LV epicardium demonstrated spatially non-uniform action potential prolongation in transgenic hearts, giving rise to alterations in spatial dispersion of epicardial repolarization. Local density and distribution of anti-Cx43 mmune reactivity in Gαq hearts were unchanged compared to wild-type hearts, suggesting preservation of intercellular coupling. Confocal microscopy also revealed heterogeneous disorganization of T-tubules in epicardial cardiomyocytes in situ. These data provide evidence of the existence of significant electrical and structural heterogeneity within the LV epicardial layer of hearts with transgenic Gαq overexpression-induced hypertrophy, and further support the notion that a small portion of electrically well connected LV tissue can maintain dispersion of action potential duration through heterogeneity in the activities of sarcolemmal ionic currents that control repolarization. It remains to be examined whether other experimental models of pathological LVH, including pressure overload LVH, similarly exhibit alterations in T-tubule organization and/or dispersion of repolarization within distinct layers of LV myocardium. PMID:22728217
NASA Astrophysics Data System (ADS)
Larson, T.
2010-12-01
Measuring air pollution concentrations from a moving platform is not a new idea. Historically, however, most information on the spatial variability of air pollutants have been derived from fixed site networks operating simultaneously over space. While this approach has obvious advantages from a regulatory perspective, with the increasing need to understand ever finer scales of spatial variability in urban pollution levels, the use of mobile monitoring to supplement fixed site networks has received increasing attention. Here we present examples of the use of this approach: 1) to assess existing fixed-site fine particle networks in Seattle, WA, including the establishment of new fixed-site monitoring locations; 2) to assess the effectiveness of a regulatory intervention, a wood stove burning ban, on the reduction of fine particle levels in the greater Puget Sound region; and 3) to assess spatial variability of both wood smoke and mobile source impacts in both Vancouver, B.C. and Tacoma, WA. Deducing spatial information from the inherently spatio-temporal measurements taken from a mobile platform is an area that deserves further attention. We discuss the use of “fuzzy” points to address the fine-scale spatio-temporal variability in the concentration of mobile source pollutants, specifically to deduce the broader distribution and sources of fine particle soot in the summer in Vancouver, B.C. We also discuss the use of principal component analysis to assess the spatial variability in multivariate, source-related features deduced from simultaneous measurements of light scattering, light absorption and particle-bound PAHs in Tacoma, WA. With increasing miniaturization and decreasing power requirements of air monitoring instruments, the number of simultaneous measurements that can easily be made from a mobile platform is rapidly increasing. Hopefully the methods used to design mobile monitoring experiments for differing purposes, and the methods used to interpret those measurements will keep pace.
NASA Astrophysics Data System (ADS)
Sheridan, Gary; nyman, petter; Duff, Tom; Baillie, Craig; Bovill, William; Lane, Patrick; Tolhurst, Kevin
2015-04-01
The prediction of fuel moisture content is important for estimating the rate of spread of wildfires, the ignition probability of firebrands, and for the efficient scheduling of prescribed fire. The moisture content of fine surface fuels varies spatially at large scales (10's to 100's km) due to variation in meteorological variables (eg. temperature, relative humidity, precipitation). At smaller scales (100's of metres) in steep topography spatial variability is attributed to topographic influences that include differences in radiation due to aspect and slope, differences in precipitation, temperature and relative humidity due to elevation, and differences in soil moisture due to hillslope drainage position. Variable forest structure and canopy shading adds further to the spatial variability in surface fuel moisture. In this study we aim to combine daily 5km resolution gridded weather data with 20m resolution DEM and vegetation structure data to predict the spatial variability of fine surface fuels in steep topography. Microclimate stations were established in south east Australia to monitor surface fine fuel moisture continuously (every 15 minutes) using newly developed instrumented litter packs, in addition to temperature and relative humidity measurements inside the litter pack, and measurement of precipitation and energy inputs above and below the forest canopy. Microclimate stations were established across a gradient of aspect (5 stations), drainage position (7 stations), elevation (15 stations), and canopy cover conditions (6 stations). The data from this extensive network of microclimate stations across a broad spectrum of topographic conditions is being analysed to enable the downscaling of gridded weather data to spatial scales that are relevant to the connectivity of wildfire fuels and to the scheduling and outcome of prescribed fires. The initial results from the first year of this study are presented here.
On the spatial decorrelation of stochastic solar resource variability at long timescales
Perez, Marc J. R.; Fthenakis, Vasilis M.
2015-05-16
Understanding the spatial and temporal characteristics of solar resource variability is important because it helps inform the discussion surrounding the merits of geographic dispersion and subsequent electrical interconnection of photovoltaics as part of a portfolio of future solutions for coping with this variability. The unpredictable resource variability arising from the stochastic nature of meteorological phenomena (from the passage of clouds to the movement of weather systems) is of most concern for achieving high PV penetration because unlike the passage of seasons or the shift from day to night, the uncertainty makes planning a challenge. A suitable proxy for unpredictable solarmore » resource variability at any given location is the series of variations in the clearness index from one time period to the next because the clearness index is largely independent of the predictable influence of solar geometry. At timescales shorter than one day, the correlation between these variations in clearness index at pairs of distinct geographic locations decreases with spatial extent and with timescale. As the aggregate variability across N decorrelated locations decreases as 1/√N, identifying the distance required to achieve this decorrelation is critical to quantifying the expected reduction in variability from geographic dispersion.« less
Global Variability and Changes in Ocean Total Alkalinity from Aquarius Satellite
NASA Astrophysics Data System (ADS)
Fine, R. A.; Willey, D. A.; Millero, F. J., Jr.
2016-02-01
To document effects of ocean acidification it is important to have an understanding of the processes and parameters that influence alkalinity. Alkalinity is a gauge on the ability of seawater to neutralize acids. We use Aquarius satellite data, which allow unprecedented global mapping of surface total alkalinity as it correlates strongly with salinity and to a lesser extent with temperature. Spatial variability in total alkalinity and salinity exceed temporal variability, the latter includes seasonal and differences compared to climatological data. The northern hemisphere has more spatial and monthly variability in total alkalinity and salinity, while less variability in Southern Ocean alkalinity is due to less salinity variability and upwelling of waters enriched in alkalinity. Satellite alkalinity data are providing a global baseline that can be used for comparing with future carbon data, and for evaluating spatial and temporal variability and past trends. For the first time it is shown that recent satellite derived total alkalinity in the subtropics have increased as compared with climatological data; this is reflective of large scale changes in the global water cycle. Total alkalinity increases imply increased dissolution of calcareous minerals and difficulty for calcifying organisms to make their shells.
Characterization of the spatial variability of channel morphology
Moody, J.A.; Troutman, B.M.
2002-01-01
The spatial variability of two fundamental morphological variables is investigated for rivers having a wide range of discharge (five orders of magnitude). The variables, water-surface width and average depth, were measured at 58 to 888 equally spaced cross-sections in channel links (river reaches between major tributaries). These measurements provide data to characterize the two-dimensional structure of a channel link which is the fundamental unit of a channel network. The morphological variables have nearly log-normal probability distributions. A general relation was determined which relates the means of the log-transformed variables to the logarithm of discharge similar to previously published downstream hydraulic geometry relations. The spatial variability of the variables is described by two properties: (1) the coefficient of variation which was nearly constant (0.13-0.42) over a wide range of discharge; and (2) the integral length scale in the downstream direction which was approximately equal to one to two mean channel widths. The joint probability distribution of the morphological variables in the downstream direction was modelled as a first-order, bivariate autoregressive process. This model accounted for up to 76 per cent of the total variance. The two-dimensional morphological variables can be scaled such that the channel width-depth process is independent of discharge. The scaling properties will be valuable to modellers of both basin and channel dynamics. Published in 2002 John Wiley and Sons, Ltd.
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.
ERIC Educational Resources Information Center
Taninmis, Gamze Elif
2016-01-01
The purpose of this study is to determine violin students' cognitive levels about articulation marks in Department of Music Education, Fine Arts Education, Gazi Faculty of Education, Gazi University (GUGEF), and to identify the variables on which the cognitive levels vary. It is a descriptive research considering the study purpose, method and…
NASA Astrophysics Data System (ADS)
McKay, N.
2017-12-01
As timescale increases from years to centuries, the spatial scale of covariability in the climate system is hypothesized to increase as well. Covarying spatial scales are larger for temperature than for hydroclimate, however, both aspects of the climate system show systematic changes on large-spatial scales on orbital to tectonic timescales. The extent to which this phenomenon is evident in temperature and hydroclimate at centennial timescales is largely unknown. Recent syntheses of multidecadal to century-scale variability in hydroclimate during the past 2k in the Arctic, North America, and Australasia show little spatial covariability in hydroclimate during the Common Era. To determine 1) the evidence for systematic relationships between the spatial scale of climate covariability as a function of timescale, and 2) whether century-scale hydroclimate variability deviates from the relationship between spatial covariability and timescale, we quantify this phenomenon during the Common Era by calculating the e-folding distance in large instrumental and paleoclimate datasets. We calculate this metric of spatial covariability, at different timescales (1, 10 and 100-yr), for a large network of temperature and precipitation observations from the Global Historical Climatology Network (n=2447), from v2.0.0 of the PAGES2k temperature database (n=692), and from moisture-sensitive paleoclimate records North America, the Arctic, and the Iso2k project (n = 328). Initial results support the hypothesis that the spatial scale of covariability is larger for temperature, than for precipitation or paleoclimate hydroclimate indicators. Spatially, e-folding distances for temperature are largest at low latitudes and over the ocean. Both instrumental and proxy temperature data show clear evidence for increasing spatial extent as a function of timescale, but this phenomenon is very weak in the hydroclimate data analyzed here. In the proxy hydroclimate data, which are predominantly indicators of effective moisture, e-folding distance increases from annual to decadal timescales, but does not continue to increase to centennial timescales. Future work includes examining additional instrumental and proxy datasets of moisture variability, and extending the analysis to millennial timescales of variability.
Guo, X; Fu, B; Ma, K; Chen, L
2000-08-01
Geostatistics combined with GIS was applied to analyze the spatial variability of soil nutrients in topsoil (0-20 cm) in Zunghua City of Hebei Province. GIS can integrate attribute data with geographical data of system variables, which makes the application of geostatistics technique for large spatial scale more convenient. Soil nutrient data in this study included available N (alkaline hydrolyzing nitrogen), total N, available K, available P and organic matter. The results showed that the semivariograms of soil nutrients were best described by spherical model, except for that of available K, which was best fitted by complex structure of exponential model and linear with sill model. The spatial variability of available K was mainly produced by structural factor, while that of available N, total N, available P and organic matter was primarily caused by random factor. However, their spatial heterogeneity degree was different: the degree of total N and organic matter was higher, and that of available P and available N was lower. The results also indicated that the spatial correlation of the five tested soil nutrients at this large scale was moderately dependent. The ranges of available N and available P were almost same, which were 5 km and 5.5 km, respectively. The range of total N was up to 18 km, and that of organic matter was 8.5 km. For available K, the spatial variability scale primarily expressed exponential model between 0-3.5 km, but linear with sill model between 3.5-25.5 km. In addition, five soil nutrients exhibited different isotropic ranges. Available N and available P were isotropic through the whole research range (0-28 km). The isotropic range of available K was 0-8 km, and that of total N and organic matter was 0-10 km.
Using a spatially explicit analysis model to evaluate spatial variation of corn yield
USDA-ARS?s Scientific Manuscript database
Spatial irrigation of agricultural crops using site-specific variable-rate irrigation (VRI) systems is beginning to have wide-spread acceptance. However, optimizing the management of these VRI systems to conserve natural resources and increase profitability requires an understanding of the spatial ...
Spatial uncertainty analysis: Propagation of interpolation errors in spatially distributed models
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.
Spatial Variability of Wet Troposphere Delays Over Inland Water Bodies
NASA Astrophysics Data System (ADS)
Mehran, Ali; Clark, Elizabeth A.; Lettenmaier, Dennis P.
2017-11-01
Satellite radar altimetry has enabled the study of water levels in large lakes and reservoirs at a global scale. The upcoming Surface Water and Ocean Topography (SWOT) satellite mission (scheduled launch 2020) will simultaneously measure water surface extent and elevation at an unprecedented accuracy and resolution. However, SWOT retrieval accuracy will be affected by a number of factors, including wet tropospheric delay—the delay in the signal's passage through the atmosphere due to atmospheric water content. In past applications, the wet tropospheric delay over large inland water bodies has been corrected using atmospheric moisture profiles based on atmospheric reanalysis data at relatively coarse (tens to hundreds of kilometers) spatial resolution. These products cannot resolve subgrid variations in wet tropospheric delays at the spatial resolutions (of 1 km and finer) that SWOT is intended to resolve. We calculate zenith wet tropospheric delays (ZWDs) and their spatial variability from Weather Research and Forecasting (WRF) numerical weather prediction model simulations at 2.33 km spatial resolution over the southwestern U.S., with attention in particular to Sam Rayburn, Ray Hubbard, and Elephant Butte Reservoirs which have width and length dimensions that are of order or larger than the WRF spatial resolution. We find that spatiotemporal variability of ZWD over the inland reservoirs depends on climatic conditions at the reservoir location, as well as distance from ocean, elevation, and surface area of the reservoir, but that the magnitude of subgrid variability (relative to analysis and reanalysis products) is generally less than 10 mm.
An underestimated role of precipitation frequency in regulating summer soil moisture
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, Chaoyang; Chen, Jing M.; Pumpanen, Jukka
2012-04-26
Soil moisture induced droughts are expected to become more frequent under future global climate change. Precipitation has been previously assumed to be mainly responsible for variability in summer soil moisture. However, little is known about the impacts of precipitation frequency on summer soil moisture, either interannually or spatially. To better understand the temporal and spatial drivers of summer drought, 415 site yr measurements observed at 75 flux sites world wide were used to analyze the temporal and spatial relationships between summer soil water content (SWC) and the precipitation frequencies at various temporal scales, i.e., from half-hourly, 3, 6, 12 andmore » 24 h measurements. Summer precipitation was found to be an indicator of interannual SWC variability with r of 0.49 (p < 0.001) for the overall dataset. However, interannual variability in summer SWC was also significantly correlated with the five precipitation frequencies and the sub-daily precipitation frequencies seemed to explain the interannual SWC variability better than the total of precipitation. Spatially, all these precipitation frequencies were better indicators of summer SWC than precipitation totals, but these better performances were only observed in non-forest ecosystems. Our results demonstrate that precipitation frequency may play an important role in regulating both interannual and spatial variations of summer SWC, which has probably been overlooked or underestimated. However, the spatial interpretation should carefully consider other factors, such as the plant functional types and soil characteristics of diverse ecoregions.« less
Malide, Daniela; Métais, Jean-Yves; Dunbar, Cynthia E.
2014-01-01
We developed and validated a fluorescent marking methodology for clonal tracking of hematopoietic stem and progenitor cells (HSPCs) with high spatial and temporal resolution to study in vivo hematopoiesis using the murine bone marrow transplant experimental model. Genetic combinatorial marking using lentiviral vectors encoding fluorescent proteins (FPs) enabled cell fate mapping through advanced microscopy imaging. Vectors encoding five different FPs: Cerulean, EGFP, Venus, tdTomato, and mCherry were used to concurrently transduce HSPCs, creating a diverse palette of color marked cells. Imaging using confocal/two-photon hybrid microscopy enables simultaneous high resolution assessment of uniquely marked cells and their progeny in conjunction with structural components of the tissues. Volumetric analyses over large areas reveal that spectrally coded HSPC-derived cells can be detected non-invasively in various intact tissues, including the bone marrow (BM), for extensive periods of time following transplantation. Live studies combining video-rate multiphoton and confocal time-lapse imaging in 4D demonstrate the possibility of dynamic cellular and clonal tracking in a quantitative manner. PMID:25145579
Kramer, V L; Carper, E R; Beesley, C; Reisen, W K
1995-05-01
Two mark-release-recapture studies were conducted along the Sacramento-San Joaquin River Delta in northern California to describe the population ecology and dispersal pattern of Aedes dorsalis (Meigen). Immature Ae. dorsalis were collected from saline tidal marshes, reared to adults, marked, and released. Recapture grids during the July and September studies were within 8.0 and 2.4 km of the release sites, and recapture rates were 0.1 and 1.2%, respectively. The longest recorded flight was 5.8 km, and mosquitoes were recaptured up to 15 d after release. In September, 84% of the marked mosquitoes were recaptured within 2.0 km of the release site, and the mean dispersal distance was 1.9 km. Marked mosquitoes flew predominantly downwind to the east. There was no evidence that Ae. dorsalis traversed the 1.6-km-wide river from Contra Costa to Solano County. Temporal and spatial recapture patterns indicated a possible short-range migration pattern from oviposition sites to upland host-seeking areas. Changes in the recapture rate with cohort age delineated a 7-d gonotrophic cycle during September.
NASA Astrophysics Data System (ADS)
Santamaria-Aguilar, S.; Arns, A.; Vafeidis, A. T.
2017-04-01
Both the temporal and spatial variability of storm surge water level (WL) curves are usually not taken into account in flood risk assessments as observational data are often scarce. In addition, sea-level rise (SLR) can further affect the variability of WLs. We analyze the temporal and spatial variability of the WL curve of 75 historical storm surge events that have been numerically simulated for St. Peter-Ording at the German North Sea coast, considering the effects induced by three SLR scenarios (RCP 4.5, RCP 8.5, and a RCP 8.5 high end scenario). We assess potential impacts of these scenarios on two parameters related to flooding: overflow volumes and fullness. Our results indicate that due to both the temporal and spatial variability of those events the resulting overflow volume can be two or even three times greater. We observe a steepening of the WL curve with an increase of the tidal range under the three SLR scenarios, although SLR induced effects are relatively higher for the RCP 4.5. The steepening of the WL curve with SLR produces a reduction of the fullness, but the changes in overflow volumes also depend on the magnitude of the storm surge event.
NASA Astrophysics Data System (ADS)
Garcia-Estringana, P.; Latron, J.; Molina, A. J.; Llorens, P.
2012-04-01
Rainfall partitioning fluxes (throughfall and stemflow) have a large degree of temporal and spatial variability and may consequently lead to significant changes in the volume and composition of water that reach the understory and the soil. The objective of this work is to study the effect of rainfall partitioning on the seasonal and spatial variability of the soil water content in a Mediterranean downy oak forest (Quercus pubescens), located in the Vallcebre research catchments (42° 12'N, 1° 49'E). The monitoring design, started on July 2011, consists of a set of 20 automatic rain recorders and 40 automatic soil moisture probes located below the canopy. One hundred hemispheric photographs of the canopy were used to place the instruments at representative locations (in terms of canopy cover) within the plot. Bulk rainfall, stemflow and meteorological conditions above the forest cover are also automatically recorded. Canopy cover, in leaf and leafless periods, as well as biometric characteristics of the plot, are also regularly measured. This work presents the first results describing throughfall and soil moisture spatial variability during both the leaf and leafless periods. The main drivers of throughfall variability, as canopy structure and meteorological conditions are also analysed.
Environmental characteristics drive variation in Amazonian understorey bird assemblages
Magnusson, William E.; Anderson, Marti J.; Schlegel, Martin; Pe’er, Guy; Henle, Klaus
2017-01-01
Tropical bird assemblages display patterns of high alpha and beta diversity and, as tropical birds exhibit strong habitat specificity, their spatial distributions are generally assumed to be driven primarily by environmental heterogeneity and interspecific interactions. However, spatial distributions of some Amazonian forest birds are also often restricted by large rivers and other large-scale topographic features, suggesting that dispersal limitation may also play a role in driving species’ turnover. In this study, we evaluated the effects of environmental characteristics, topographic and spatial variables on variation in local assemblage structure and diversity of birds in an old-growth forest in central Amazonia. Birds were mist-netted in 72 plots distributed systematically across a 10,000 ha reserve in each of three years. Alpha diversity remained stable through time, but species composition changed. Spatial variation in bird-assemblage structure was significantly related to environmental and topographic variables but not strongly related to spatial variables. At a broad scale, we found bird assemblages to be significantly distinct between two watersheds that are divided by a central ridgeline. We did not detect an effect of the ridgeline per se in driving these patterns, indicating that most birds are able to fly across it, and that differences in assemblage structure between watersheds may be due to unmeasured environmental variables or unique combinations of measured variables. Our study indicates that complex geography and landscape features can act together with environmental variables to drive changes in the diversity and composition of tropical bird assemblages at local scales, but highlights that we still know very little about what makes different parts of tropical forest suitable for different species. PMID:28225774
Remote-sensing based approach to forecast habitat quality under climate change scenarios.
Requena-Mullor, Juan M; López, Enrique; Castro, Antonio J; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier
2017-01-01
As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios.
Remote-sensing based approach to forecast habitat quality under climate change scenarios
Requena-Mullor, Juan M.; López, Enrique; Castro, Antonio J.; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier
2017-01-01
As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios. PMID:28257501
Aspect-related Vegetation Differences Amplify Soil Moisture Variability in Semiarid Landscapes
NASA Astrophysics Data System (ADS)
Yetemen, O.; Srivastava, A.; Kumari, N.; Saco, P. M.
2017-12-01
Soil moisture variability (SMV) in semiarid landscapes is affected by vegetation, soil texture, climate, aspect, and topography. The heterogeneity in vegetation cover that results from the effects of microclimate, terrain attributes (slope gradient, aspect, drainage area etc.), soil properties, and spatial variability in precipitation have been reported to act as the dominant factors modulating SMV in semiarid ecosystems. However, the role of hillslope aspect in SMV, though reported in many field studies, has not received the same degree of attention probably due to the lack of extensive large datasets. Numerical simulations can then be used to elucidate the contribution of aspect-driven vegetation patterns to this variability. In this work, we perform a sensitivity analysis to study on variables driving SMV using the CHILD landscape evolution model equipped with a spatially-distributed solar-radiation component that couples vegetation dynamics and surface hydrology. To explore how aspect-driven vegetation heterogeneity contributes to the SMV, CHILD was run using a range of parameters selected to reflect different scenarios (from uniform to heterogeneous vegetation cover). Throughout the simulations, the spatial distribution of soil moisture and vegetation cover are computed to estimate the corresponding coefficients of variation. Under the uniform spatial precipitation forcing and uniform soil properties, the factors affecting the spatial distribution of solar insolation are found to play a key role in the SMV through the emergence of aspect-driven vegetation patterns. Hence, factors such as catchment gradient, aspect, and latitude, define water stress and vegetation growth, and in turn affect the available soil moisture content. Interestingly, changes in soil properties (porosity, root depth, and pore-size distribution) over the domain are not as effective as the other factors. These findings show that the factors associated to aspect-related vegetation differences amplify the soil moisture variability of semi-arid landscapes.
Random vectors and spatial analysis by geostatistics for geotechnical applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Young, D.S.
1987-08-01
Geostatistics is extended to the spatial analysis of vector variables by defining the estimation variance and vector variogram in terms of the magnitude of difference vectors. Many random variables in geotechnology are in vectorial terms rather than scalars, and its structural analysis requires those sample variable interpolations to construct and characterize structural models. A better local estimator will result in greater quality of input models; geostatistics can provide such estimators; kriging estimators. The efficiency of geostatistics for vector variables is demonstrated in a case study of rock joint orientations in geological formations. The positive cross-validation encourages application of geostatistics tomore » spatial analysis of random vectors in geoscience as well as various geotechnical fields including optimum site characterization, rock mechanics for mining and civil structures, cavability analysis of block cavings, petroleum engineering, and hydrologic and hydraulic modelings.« less