Temporal scale dependent interactions between multiple environmental disturbances in microcosm ecosystems.

PubMed

Garnier, Aurélie; Pennekamp, Frank; Lemoine, Mélissa; Petchey, Owen L

2017-12-01

Global environmental change has negative impacts on ecological systems, impacting the stable provision of functions, goods, and services. Whereas effects of individual environmental changes (e.g. temperature change or change in resource availability) are reasonably well understood, we lack information about if and how multiple changes interact. We examined interactions among four types of environmental disturbance (temperature, nutrient ratio, carbon enrichment, and light) in a fully factorial design using a microbial aquatic ecosystem and observed responses of dissolved oxygen saturation at three temporal scales (resistance, resilience, and return time). We tested whether multiple disturbances combine in a dominant, additive, or interactive fashion, and compared the predictability of dissolved oxygen across scales. Carbon enrichment and shading reduced oxygen concentration in the short term (i.e. resistance); although no other effects or interactions were statistically significant, resistance decreased as the number of disturbances increased. In the medium term, only enrichment accelerated recovery, but none of the other effects (including interactions) were significant. In the long term, enrichment and shading lengthened return times, and we found significant two-way synergistic interactions between disturbances. The best performing model (dominant, additive, or interactive) depended on the temporal scale of response. In the short term (i.e. for resistance), the dominance model predicted resistance of dissolved oxygen best, due to a large effect of carbon enrichment, whereas none of the models could predict the medium term (i.e. resilience). The long-term response was best predicted by models including interactions among disturbances. Our results indicate the importance of accounting for the temporal scale of responses when researching the effects of environmental disturbances on ecosystems. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Multiscale spatial and temporal estimation of the b-value

NASA Astrophysics Data System (ADS)

García-Hernández, R.; D'Auria, L.; Barrancos, J.; Padilla, G.

2017-12-01

The estimation of the spatial and temporal variations of the Gutenberg-Richter b-value is of great importance in different seismological applications. One of the problems affecting its estimation is the heterogeneous distribution of the seismicity which makes its estimate strongly dependent upon the selected spatial and/or temporal scale. This is especially important in volcanoes where dense clusters of earthquakes often overlap the background seismicity. Proposed solutions for estimating temporal variations of the b-value include considering equally spaced time intervals or variable intervals having an equal number of earthquakes. Similar approaches have been proposed to image the spatial variations of this parameter as well.We propose a novel multiscale approach, based on the method of Ogata and Katsura (1993), allowing a consistent estimation of the b-value regardless of the considered spatial and/or temporal scales. Our method, named MUST-B (MUltiscale Spatial and Temporal characterization of the B-value), basically consists in computing estimates of the b-value at multiple temporal and spatial scales, extracting for a give spatio-temporal point a statistical estimator of the value, as well as and indication of the characteristic spatio-temporal scale. This approach includes also a consistent estimation of the completeness magnitude (Mc) and of the uncertainties over both b and Mc.We applied this method to example datasets for volcanic (Tenerife, El Hierro) and tectonic areas (Central Italy) as well as an example application at global scale.

Selective attention to temporal features on nested time scales.

PubMed

Henry, Molly J; Herrmann, Björn; Obleser, Jonas

2015-02-01

Meaningful auditory stimuli such as speech and music often vary simultaneously along multiple time scales. Thus, listeners must selectively attend to, and selectively ignore, separate but intertwined temporal features. The current study aimed to identify and characterize the neural network specifically involved in this feature-selective attention to time. We used a novel paradigm where listeners judged either the duration or modulation rate of auditory stimuli, and in which the stimulation, working memory demands, response requirements, and task difficulty were held constant. A first analysis identified all brain regions where individual brain activation patterns were correlated with individual behavioral performance patterns, which thus supported temporal judgments generically. A second analysis then isolated those brain regions that specifically regulated selective attention to temporal features: Neural responses in a bilateral fronto-parietal network including insular cortex and basal ganglia decreased with degree of change of the attended temporal feature. Critically, response patterns in these regions were inverted when the task required selectively ignoring this feature. The results demonstrate how the neural analysis of complex acoustic stimuli with multiple temporal features depends on a fronto-parietal network that simultaneously regulates the selective gain for attended and ignored temporal features. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Wild salmon response to natural disturbance processes

Treesearch

Russ Thurow; John M. Buffington

2016-01-01

Dynamic landscapes are shaped by a variety of natural processes and disturbances operating across multiple temporal and spatial scales. Persistence of species in these dynamic environments is also a matter of scale: how do species dispersal and reproductive rates merge with the scales of disturbance?

Towards a More Biologically-meaningful Climate Characterization: Variability in Space and Time at Multiple Scales

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.

Allometric and temporal scaling of movement characteristics in Galapagos tortoises

USGS Publications Warehouse

Bastille-Rousseau, Guillaume; Yackulic, Charles B.; Frair, Jacqueline L.; Cabrera, Freddy; Blake, Stephen

2016-01-01

Understanding how individual movement scales with body size is of fundamental importance in predicting ecological relationships for diverse species. One-dimensional movement metrics scale consistently with body size yet vary over different temporal scales. Knowing how temporal scale influences the relationship between animal body size and movement would better inform hypotheses about the efficiency of foraging behaviour, the ontogeny of energy budgets, and numerous life-history trade-offs.We investigated how the temporal scaling of allometric patterns in movement varies over the course of a year, specifically during periods of motivated (directional and fast movement) and unmotivated (stationary and tortuous movement) behaviour. We focused on a recently diverged group of species that displays wide variation in movement behaviour – giant Galapagos tortoises (Chelonoidis spp.) – to test how movement metrics estimated on a monthly basis scaled with body size.We used state-space modelling to estimate seven different movement metrics of Galapagos tortoises. We used log-log regression of the power law to evaluate allometric scaling for these movement metrics and contrasted relationships by species and sex.Allometric scaling of movement was more apparent during motivated periods of movement. During this period, allometry was revealed at multiple temporal intervals (hourly, daily and monthly), with values observed at daily and monthly intervals corresponding most closely to the expected one-fourth scaling coefficient, albeit with wide credible intervals. We further detected differences in the magnitude of scaling among taxa uncoupled from observed differences in the temporal structuring of their movement rates.Our results indicate that the definition of temporal scales is fundamental to the detection of allometry of movement and should be given more attention in movement studies. Our approach not only provides new conceptual insights into temporal attributes in one-dimensional scaling of movement, but also generates valuable insights into the movement ecology of iconic yet poorly understood Galapagos giant tortoises.

Allometric and temporal scaling of movement characteristics in Galapagos tortoises.

PubMed

Bastille-Rousseau, Guillaume; Yackulic, Charles B; Frair, Jacqueline L; Cabrera, Freddy; Blake, Stephen

2016-09-01

Understanding how individual movement scales with body size is of fundamental importance in predicting ecological relationships for diverse species. One-dimensional movement metrics scale consistently with body size yet vary over different temporal scales. Knowing how temporal scale influences the relationship between animal body size and movement would better inform hypotheses about the efficiency of foraging behaviour, the ontogeny of energy budgets, and numerous life-history trade-offs. We investigated how the temporal scaling of allometric patterns in movement varies over the course of a year, specifically during periods of motivated (directional and fast movement) and unmotivated (stationary and tortuous movement) behaviour. We focused on a recently diverged group of species that displays wide variation in movement behaviour - giant Galapagos tortoises (Chelonoidis spp.) - to test how movement metrics estimated on a monthly basis scaled with body size. We used state-space modelling to estimate seven different movement metrics of Galapagos tortoises. We used log-log regression of the power law to evaluate allometric scaling for these movement metrics and contrasted relationships by species and sex. Allometric scaling of movement was more apparent during motivated periods of movement. During this period, allometry was revealed at multiple temporal intervals (hourly, daily and monthly), with values observed at daily and monthly intervals corresponding most closely to the expected one-fourth scaling coefficient, albeit with wide credible intervals. We further detected differences in the magnitude of scaling among taxa uncoupled from observed differences in the temporal structuring of their movement rates. Our results indicate that the definition of temporal scales is fundamental to the detection of allometry of movement and should be given more attention in movement studies. Our approach not only provides new conceptual insights into temporal attributes in one-dimensional scaling of movement, but also generates valuable insights into the movement ecology of iconic yet poorly understood Galapagos giant tortoises. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

Mushroom biomass and diversity are driven by different spatio-temporal scales along Mediterranean elevation gradients

NASA Astrophysics Data System (ADS)

Alday, Josu G.; Martínez de Aragón, Juan; de-Miguel, Sergio; Bonet, José Antonio

2017-04-01

Mushrooms are important non-wood-forest-products in many Mediterranean ecosystems, being highly vulnerable to climate change. However, the ecological scales of variation of mushroom productivity and diversity, and climate dependence has been usually overlooked due to a lack of available data. We determined the spatio-temporal variability of epigeous sporocarps and the climatic factors driving their fruiting to plan future sustainable management of wild mushrooms production. We collected fruiting bodies in Pinus sylvestris stands along an elevation gradient for 8 consecutive years. Overall, sporocarp biomass was mainly dependent on inter-annual variations, whereas richness was more spatial-scale dependent. Elevation was not significant, but there were clear elevational differences in biomass and richness patterns between ectomycorrhizal and saprotrophic guilds. The main driver of variation was late-summer-early-autumn precipitation. Thus, different scale processes (inter-annual vs. spatial-scale) drive sporocarp biomass and diversity patterns; temporal effects for biomass and ectomycorrhizal fungi vs. spatial scale for diversity and saprotrophic fungi. The significant role of precipitation across fungal guilds and spatio-temporal scales indicates that it is a limiting resource controlling sporocarp production and diversity in Mediterranean regions. The high spatial and temporal variability of mushrooms emphasize the need for long-term datasets of multiple spatial points to effectively characterize fungal fruiting patterns.

Spatial and Temporal Dynamics of Pacific Oyster Hemolymph Microbiota across Multiple Scales

PubMed Central

Lokmer, Ana; Goedknegt, M. Anouk; Thieltges, David W.; Fiorentino, Dario; Kuenzel, Sven; Baines, John F.; Wegner, K. Mathias

2016-01-01

Unveiling the factors and processes that shape the dynamics of host associated microbial communities (microbiota) under natural conditions is an important part of understanding and predicting an organism's response to a changing environment. The microbiota is shaped by host (i.e., genetic) factors as well as by the biotic and abiotic environment. Studying natural variation of microbial community composition in multiple host genetic backgrounds across spatial as well as temporal scales represents a means to untangle this complex interplay. Here, we combined a spatially-stratified with a longitudinal sampling scheme within differentiated host genetic backgrounds by reciprocally transplanting Pacific oysters between two sites in the Wadden Sea (Sylt and Texel). To further differentiate contingent site from host genetic effects, we repeatedly sampled the same individuals over a summer season to examine structure, diversity and dynamics of individual hemolymph microbiota following experimental removal of resident microbiota by antibiotic treatment. While a large proportion of microbiome variation could be attributed to immediate environmental conditions, we observed persistent effects of antibiotic treatment and translocation suggesting that hemolymph microbial community dynamics is subject to within-microbiome interactions and host population specific factors. In addition, the analysis of spatial variation revealed that the within-site microenvironmental heterogeneity resulted in high small-scale variability, as opposed to large-scale (between-site) stability. Similarly, considerable within-individual temporal variability was in contrast with the overall temporal stability at the site level. Overall, our longitudinal, spatially-stratified sampling design revealed that variation in hemolymph microbiota is strongly influenced by site and immediate environmental conditions, whereas internal microbiome dynamics and oyster-related factors add to their long-term stability. The combination of small and large scale resolution of spatial and temporal observations therefore represents a crucial but underused tool to study host-associated microbiome dynamics. PMID:27630625

Geovisualization of Local and Regional Migration Using Web-mined Demographics

NASA Astrophysics Data System (ADS)

Schuermann, R. T.; Chow, T. E.

2014-11-01

The intent of this research was to augment and facilitate analyses, which gauges the feasibility of web-mined demographics to study spatio-temporal dynamics of migration. As a case study, we explored the spatio-temporal dynamics of Vietnamese Americans (VA) in Texas through geovisualization of mined demographic microdata from the World Wide Web. Based on string matching across all demographic attributes, including full name, address, date of birth, age and phone number, multiple records of the same entity (i.e. person) over time were resolved and reconciled into a database. Migration trajectories were geovisualized through animated sprites by connecting the different addresses associated with the same person and segmenting the trajectory into small fragments. Intra-metropolitan migration patterns appeared at the local scale within many metropolitan areas. At the scale of metropolitan area, varying degrees of immigration and emigration manifest different types of migration clusters. This paper presents a methodology incorporating GIS methods and cartographic design to produce geovisualization animation, enabling the cognitive identification of migration patterns at multiple scales. Identification of spatio-temporal patterns often stimulates further research to better understand the phenomenon and enhance subsequent modeling.

Temporal change in fragmentation of continental US forests

Treesearch

James D. Wickham; Kurt H. Riitters; Timothy G. Wade; Collin Homer

2008-01-01

Changes in forest ecosystem function and condition arise from changes in forest fragmentation. Previous studies estimated forest fragmentation for the continental United States (US). In this study, new temporal land-cover data from the National Land Cover Database (NLCD) were used to estimate changes in forest fragmentation at multiple scales for the continental US....

Spatial and temporal ecology of eastern spadefoot toads on a Florida landscape

Treesearch

Cathryn H. Greenberg; George W. Tanner

2005-01-01

Effective amphibian conservation must consider population and landscape processes, but information at multiple scales is rare. We explore spatial and temporal patterns of breeding and recruitment by eastern spadefoot toads (Scaphiopus holbrookii), using nine years of data from continuous monitoring with drift fences and pitfall traps at eight...

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Space and time scales in human-landscape systems.

PubMed

Kondolf, G Mathias; Podolak, Kristen

2014-01-01

Exploring spatial and temporal scales provides a way to understand human alteration of landscape processes and human responses to these processes. We address three topics relevant to human-landscape systems: (1) scales of human impacts on geomorphic processes, (2) spatial and temporal scales in river restoration, and (3) time scales of natural disasters and behavioral and institutional responses. Studies showing dramatic recent change in sediment yields from uplands to the ocean via rivers illustrate the increasingly vast spatial extent and quick rate of human landscape change in the last two millennia, but especially in the second half of the twentieth century. Recent river restoration efforts are typically small in spatial and temporal scale compared to the historical human changes to ecosystem processes, but the cumulative effectiveness of multiple small restoration projects in achieving large ecosystem goals has yet to be demonstrated. The mismatch between infrequent natural disasters and individual risk perception, media coverage, and institutional response to natural disasters results in un-preparedness and unsustainable land use and building practices.

Transboundary fisheries science: Meeting the challenges of inland fisheries management in the 21st century

USGS Publications Warehouse

Midway, Stephen R.; Wagner, Tyler; Zydlewski, Joseph D.; Irwin, Brian J.; Paukert, Craig P.

2016-01-01

Managing inland fisheries in the 21st century presents several obstacles, including the need to view fisheries from multiple spatial and temporal scales, which usually involves populations and resources spanning sociopolitical boundaries. Though collaboration is not new to fisheries science, inland aquatic systems have historically been managed at local scales and present different challenges than in marine or large freshwater systems like the Laurentian Great Lakes. Therefore, we outline a flexible strategy that highlights organization, cooperation, analytics, and implementation as building blocks toward effectively addressing transboundary fisheries issues. Additionally, we discuss the use of Bayesian hierarchical models (within the analytical stage), due to their flexibility in dealing with the variability present in data from multiple scales. With growing recognition of both ecological drivers that span spatial and temporal scales and the subsequent need for collaboration to effectively manage heterogeneous resources, we expect implementation of transboundary approaches to become increasingly critical for effective inland fisheries management.

HIS Design: Big Data that Supports Hydrologic Modeling from Continental to Hillslope Scales

NASA Astrophysics Data System (ADS)

Rasmussen, T. C.; Deemy, J. B.; Younger, S. E.; Kirk, S. E.; Brockman, L. E.

2016-12-01

Analogous to Google Maps, hydrologic data, information, and knowledge resolve differently depending upon the spatial and temporal scales of interest. We show how a multi-scale hydrologic information system (HIS) can be designed and populated for a broad range of spatial (e.g., hillslope, local, regional, continental) and temporal (e.g., current, recent, historic, geologic) scales. Surface and subsurface hydrologic and transport processes are assumed to be scale-dependent, requiring unique governing equations and parameters at each scale. This robust and flexible framework is designed to meet the inventory, monitoring, and management needs of multiple federal agencies (i.e., Forest Service, National Park Service, Fish and Wildlife Service, National Wildlife Reserves). Multi-scale HIS examples are provided using Geographic Information Systems (GIS) for the Southeastern US.

Confronting weather and climate models with observational data from soil moisture networks over the United States

PubMed Central

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal D.; Balsamo, Gianpaolo; Lawrence, David M.

2018-01-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison. PMID:29645013

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

NASA Technical Reports Server (NTRS)

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean;

Confronting weather and climate models with observational data from soil moisture networks over the United States.

PubMed

Dirmeyer, Paul A; Wu, Jiexia; Norton, Holly E; Dorigo, Wouter A; Quiring, Steven M; Ford, Trenton W; Santanello, Joseph A; Bosilovich, Michael G; Ek, Michael B; Koster, Randal D; Balsamo, Gianpaolo; Lawrence, David M

2016-04-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

Fully coupled approach to modeling shallow water flow, sediment transport, and bed evolution in rivers

NASA Astrophysics Data System (ADS)

Li, Shuangcai; Duffy, Christopher J.

2011-03-01

Our ability to predict complex environmental fluid flow and transport hinges on accurate and efficient simulations of multiple physical phenomenon operating simultaneously over a wide range of spatial and temporal scales, including overbank floods, coastal storm surge events, drying and wetting bed conditions, and simultaneous bed form evolution. This research implements a fully coupled strategy for solving shallow water hydrodynamics, sediment transport, and morphological bed evolution in rivers and floodplains (PIHM_Hydro) and applies the model to field and laboratory experiments that cover a wide range of spatial and temporal scales. The model uses a standard upwind finite volume method and Roe's approximate Riemann solver for unstructured grids. A multidimensional linear reconstruction and slope limiter are implemented, achieving second-order spatial accuracy. Model efficiency and stability are treated using an explicit-implicit method for temporal discretization with operator splitting. Laboratory-and field-scale experiments were compiled where coupled processes across a range of scales were observed and where higher-order spatial and temporal accuracy might be needed for accurate and efficient solutions. These experiments demonstrate the ability of the fully coupled strategy in capturing dynamics of field-scale flood waves and small-scale drying-wetting processes.

On temporal stochastic modeling of precipitation, nesting models across scales

NASA Astrophysics Data System (ADS)

Paschalis, Athanasios; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2014-01-01

We analyze the performance of composite stochastic models of temporal precipitation which can satisfactorily reproduce precipitation properties across a wide range of temporal scales. The rationale is that a combination of stochastic precipitation models which are most appropriate for specific limited temporal scales leads to better overall performance across a wider range of scales than single models alone. We investigate different model combinations. For the coarse (daily) scale these are models based on Alternating renewal processes, Markov chains, and Poisson cluster models, which are then combined with a microcanonical Multiplicative Random Cascade model to disaggregate precipitation to finer (minute) scales. The composite models were tested on data at four sites in different climates. The results show that model combinations improve the performance in key statistics such as probability distributions of precipitation depth, autocorrelation structure, intermittency, reproduction of extremes, compared to single models. At the same time they remain reasonably parsimonious. No model combination was found to outperform the others at all sites and for all statistics, however we provide insight on the capabilities of specific model combinations. The results for the four different climates are similar, which suggests a degree of generality and wider applicability of the approach.

Perspectives on why digital ecologies matter: combining population genetics and ecologically informed agent-based models with GIS for managing dipteran livestock pests.

PubMed

Peck, Steven L

2014-10-01

It is becoming clear that handling the inherent complexity found in ecological systems is an essential task for finding ways to control insect pests of tropical livestock such as tsetse flies, and old and new world screwworms. In particular, challenging multivalent management programs, such as Area Wide Integrated Pest Management (AW-IPM), face daunting problems of complexity at multiple spatial scales, ranging from landscape level processes to those of smaller scales such as the parasite loads of individual animals. Daunting temporal challenges also await resolution, such as matching management time frames to those found on ecological and even evolutionary temporal scales. How does one deal with representing processes with models that involve multiple spatial and temporal scales? Agent-based models (ABM), combined with geographic information systems (GIS), may allow for understanding, predicting and managing pest control efforts in livestock pests. This paper argues that by incorporating digital ecologies in our management efforts clearer and more informed decisions can be made. I also point out the power of these models in making better predictions in order to anticipate the range of outcomes possible or likely. Copyright © 2014 International Atomic Energy Agency 2014. Published by Elsevier B.V. All rights reserved.

An operational ensemble prediction system for catchment rainfall over eastern Africa spanning multiple temporal and spatial scales

NASA Astrophysics Data System (ADS)

Riddle, E. E.; Hopson, T. M.; Gebremichael, M.; Boehnert, J.; Broman, D.; Sampson, K. M.; Rostkier-Edelstein, D.; Collins, D. C.; Harshadeep, N. R.; Burke, E.; Havens, K.

2017-12-01

While it is not yet certain how precipitation patterns will change over Africa in the future, it is clear that effectively managing the available water resources is going to be crucial in order to mitigate the effects of water shortages and floods that are likely to occur in a changing climate. One component of effective water management is the availability of state-of-the-art and easy to use rainfall forecasts across multiple spatial and temporal scales. We present a web-based system for displaying and disseminating ensemble forecast and observed precipitation data over central and eastern Africa. The system provides multi-model rainfall forecasts integrated to relevant hydrological catchments for timescales ranging from one day to three months. A zoom-in features is available to access high resolution forecasts for small-scale catchments. Time series plots and data downloads with forecasts, recent rainfall observations and climatological data are available by clicking on individual catchments. The forecasts are calibrated using a quantile regression technique and an optimal multi-model forecast is provided at each timescale. The forecast skill at the various spatial and temporal scales will discussed, as will current applications of this tool for managing water resources in Sudan and optimizing hydropower operations in Ethiopia and Tanzania.

Temporal Context in Speech Processing and Attentional Stream Selection: A Behavioral and Neural perspective

PubMed Central

Zion Golumbic, Elana M.; Poeppel, David; Schroeder, Charles E.

2012-01-01

The human capacity for processing speech is remarkable, especially given that information in speech unfolds over multiple time scales concurrently. Similarly notable is our ability to filter out of extraneous sounds and focus our attention on one conversation, epitomized by the ‘Cocktail Party’ effect. Yet, the neural mechanisms underlying on-line speech decoding and attentional stream selection are not well understood. We review findings from behavioral and neurophysiological investigations that underscore the importance of the temporal structure of speech for achieving these perceptual feats. We discuss the hypothesis that entrainment of ambient neuronal oscillations to speech’s temporal structure, across multiple time-scales, serves to facilitate its decoding and underlies the selection of an attended speech stream over other competing input. In this regard, speech decoding and attentional stream selection are examples of ‘active sensing’, emphasizing an interaction between proactive and predictive top-down modulation of neuronal dynamics and bottom-up sensory input. PMID:22285024

Large-scale assessment of benthic communities across multiple marine protected areas using an autonomous underwater vehicle.

PubMed

Ferrari, Renata; Marzinelli, Ezequiel M; Ayroza, Camila Rezende; Jordan, Alan; Figueira, Will F; Byrne, Maria; Malcolm, Hamish A; Williams, Stefan B; Steinberg, Peter D

2018-01-01

Marine protected areas (MPAs) are designed to reduce threats to biodiversity and ecosystem functioning from anthropogenic activities. Assessment of MPAs effectiveness requires synchronous sampling of protected and non-protected areas at multiple spatial and temporal scales. We used an autonomous underwater vehicle to map benthic communities in replicate 'no-take' and 'general-use' (fishing allowed) zones within three MPAs along 7o of latitude. We recorded 92 taxa and 38 morpho-groups across three large MPAs. We found that important habitat-forming biota (e.g. massive sponges) were more prevalent and abundant in no-take zones, while short ephemeral algae were more abundant in general-use zones, suggesting potential short-term effects of zoning (5-10 years). Yet, short-term effects of zoning were not detected at the community level (community structure or composition), while community structure varied significantly among MPAs. We conclude that by allowing rapid, simultaneous assessments at multiple spatial scales, autonomous underwater vehicles are useful to document changes in marine communities and identify adequate scales to manage them. This study advanced knowledge of marine benthic communities and their conservation in three ways. First, we quantified benthic biodiversity and abundance, generating the first baseline of these benthic communities against which the effectiveness of three large MPAs can be assessed. Second, we identified the taxonomic resolution necessary to assess both short and long-term effects of MPAs, concluding that coarse taxonomic resolution is sufficient given that analyses of community structure at different taxonomic levels were generally consistent. Yet, observed differences were taxa-specific and may have not been evident using our broader taxonomic classifications, a classification of mid to high taxonomic resolution may be necessary to determine zoning effects on key taxa. Third, we provide an example of statistical analyses and sampling design that once temporal sampling is incorporated will be useful to detect changes of marine benthic communities across multiple spatial and temporal scales.

Large-scale assessment of benthic communities across multiple marine protected areas using an autonomous underwater vehicle

PubMed Central

Ayroza, Camila Rezende; Jordan, Alan; Figueira, Will F.; Byrne, Maria; Malcolm, Hamish A.; Williams, Stefan B.; Steinberg, Peter D.

2018-01-01

Marine protected areas (MPAs) are designed to reduce threats to biodiversity and ecosystem functioning from anthropogenic activities. Assessment of MPAs effectiveness requires synchronous sampling of protected and non-protected areas at multiple spatial and temporal scales. We used an autonomous underwater vehicle to map benthic communities in replicate ‘no-take’ and ‘general-use’ (fishing allowed) zones within three MPAs along 7o of latitude. We recorded 92 taxa and 38 morpho-groups across three large MPAs. We found that important habitat-forming biota (e.g. massive sponges) were more prevalent and abundant in no-take zones, while short ephemeral algae were more abundant in general-use zones, suggesting potential short-term effects of zoning (5–10 years). Yet, short-term effects of zoning were not detected at the community level (community structure or composition), while community structure varied significantly among MPAs. We conclude that by allowing rapid, simultaneous assessments at multiple spatial scales, autonomous underwater vehicles are useful to document changes in marine communities and identify adequate scales to manage them. This study advanced knowledge of marine benthic communities and their conservation in three ways. First, we quantified benthic biodiversity and abundance, generating the first baseline of these benthic communities against which the effectiveness of three large MPAs can be assessed. Second, we identified the taxonomic resolution necessary to assess both short and long-term effects of MPAs, concluding that coarse taxonomic resolution is sufficient given that analyses of community structure at different taxonomic levels were generally consistent. Yet, observed differences were taxa-specific and may have not been evident using our broader taxonomic classifications, a classification of mid to high taxonomic resolution may be necessary to determine zoning effects on key taxa. Third, we provide an example of statistical analyses and sampling design that once temporal sampling is incorporated will be useful to detect changes of marine benthic communities across multiple spatial and temporal scales. PMID:29547656

Changes in channel morphology over human time scales [Chapter 32

Treesearch

John M. Buffington

2012-01-01

Rivers are exposed to changing environmental conditions over multiple spatial and temporal scales, with the imposed environmental conditions and response potential of the river modulated to varying degrees by human activity and our exploitation of natural resources. Watershed features that control river morphology include topography (valley slope and channel...

The role of temporal structure in the investigation of sensory memory, auditory scene analysis, and speech perception: a healthy-aging perspective.

PubMed

Rimmele, Johanna Maria; Sussman, Elyse; Poeppel, David

2015-02-01

Listening situations with multiple talkers or background noise are common in everyday communication and are particularly demanding for older adults. Here we review current research on auditory perception in aging individuals in order to gain insights into the challenges of listening under noisy conditions. Informationally rich temporal structure in auditory signals--over a range of time scales from milliseconds to seconds--renders temporal processing central to perception in the auditory domain. We discuss the role of temporal structure in auditory processing, in particular from a perspective relevant for hearing in background noise, and focusing on sensory memory, auditory scene analysis, and speech perception. Interestingly, these auditory processes, usually studied in an independent manner, show considerable overlap of processing time scales, even though each has its own 'privileged' temporal regimes. By integrating perspectives on temporal structure processing in these three areas of investigation, we aim to highlight similarities typically not recognized. Copyright © 2014 Elsevier B.V. All rights reserved.

The role of temporal structure in the investigation of sensory memory, auditory scene analysis, and speech perception: A healthy-aging perspective

PubMed Central

Rimmele, Johanna Maria; Sussman, Elyse; Poeppel, David

2014-01-01

Listening situations with multiple talkers or background noise are common in everyday communication and are particularly demanding for older adults. Here we review current research on auditory perception in aging individuals in order to gain insights into the challenges of listening under noisy conditions. Informationally rich temporal structure in auditory signals - over a range of time scales from milliseconds to seconds - renders temporal processing central to perception in the auditory domain. We discuss the role of temporal structure in auditory processing, in particular from a perspective relevant for hearing in background noise, and focusing on sensory memory, auditory scene analysis, and speech perception. Interestingly, these auditory processes, usually studied in an independent manner, show considerable overlap of processing time scales, even though each has its own ‚privileged‘ temporal regimes. By integrating perspectives on temporal structure processing in these three areas of investigation, we aim to highlight similarities typically not recognized. PMID:24956028

Circumpolar spatio-temporal patterns and contributing climatic factors of wildfire activity in the Arctic tundra from 2001-2015

NASA Astrophysics Data System (ADS)

Masrur, Arif; Petrov, Andrey N.; DeGroote, John

2018-01-01

Recent years have seen an increased frequency of wildfire events in different parts of Arctic tundra ecosystems. Contemporary studies have largely attributed these wildfire events to the Arctic’s rapidly changing climate and increased atmospheric disturbances (i.e. thunderstorms). However, existing research has primarily examined the wildfire-climate dynamics of individual large wildfire events. No studies have investigated wildfire activity, including climatic drivers, for the entire tundra biome across multiple years, i.e. at the planetary scale. To address this limitation, this paper provides a planetary/circumpolar scale analyses of space-time patterns of tundra wildfire occurrence and climatic association in the Arctic over a 15 year period (2001-2015). In doing so, we have leveraged and analyzed NASA Terra’s MODIS active fire and MERRA climate reanalysis products at multiple temporal scales (decadal, seasonal and monthly). Our exploratory spatial data analysis found that tundra wildfire occurrence was spatially clustered and fire intensity was spatially autocorrelated across the Arctic regions. Most of the wildfire events occurred in the peak summer months (June-August). Our multi-temporal (decadal, seasonal and monthly) scale analyses provide further support to the link between climate variability and wildfire activity. Specifically, we found that warm and dry conditions in the late spring to mid-summer influenced tundra wildfire occurrence, spatio-temporal distribution, and fire intensity. Additionally, reduced average surface precipitation and soil moisture levels in the winter-spring period were associated with increased fire intensity in the following summer. These findings enrich contemporary knowledge on tundra wildfire’s spatial and seasonal patterns, and shed new light on tundra wildfire-climate relationships in the circumpolar context. Furthermore, this first pan-Arctic analysis provides a strong incentive and direction for future studies which integrate multiple datasets (i.e. climate, fuels, topography, and ignition sources) to accurately estimate carbon emission from tundra burning and its global climate feedbacks in coming decades.

Environmental stochasticity controls soil erosion variability

PubMed Central

Kim, Jongho; Ivanov, Valeriy Y.; Fatichi, Simone

2016-01-01

Understanding soil erosion by water is essential for a range of research areas but the predictive skill of prognostic models has been repeatedly questioned because of scale limitations of empirical data and the high variability of soil loss across space and time scales. Improved understanding of the underlying processes and their interactions are needed to infer scaling properties of soil loss and better inform predictive methods. This study uses data from multiple environments to highlight temporal-scale dependency of soil loss: erosion variability decreases at larger scales but the reduction rate varies with environment. The reduction of variability of the geomorphic response is attributed to a ‘compensation effect’: temporal alternation of events that exhibit either source-limited or transport-limited regimes. The rate of reduction is related to environment stochasticity and a novel index is derived to reflect the level of variability of intra- and inter-event hydrometeorologic conditions. A higher stochasticity index implies a larger reduction of soil loss variability (enhanced predictability at the aggregated temporal scales) with respect to the mean hydrologic forcing, offering a promising indicator for estimating the degree of uncertainty of erosion assessments. PMID:26925542

Taking the pulse of a continent: Expanding site-based research infrastructure for regional- to continental-scale ecology

USDA-ARS?s Scientific Manuscript database

Many of the most dramatic and surprising effects of global change on ecological systems will occur across large spatial extents, from regions to continents. Multiple ecosystem types will be impacted across a range of interacting spatial and temporal scales. The ability of ecologists to understand an...

MONITORING COASTAL RESOURCES AT MULTIPLE SPATIAL AND TEMPORAL SCALES: LESSONS FROM EMAP 2001 EMAP SYMPOSIUM, APRIL 24-27, PENSACOLA BEACH, FL

EPA Science Inventory

In 1990, EMAP's Coastal Monitoring Program conducted its first regional sampling program in the Virginian Province. This first effort focused only at large spatial scales (regional) with some stratification to examine estuarine types. In the ensuing decade, EMAP-Coastal has condu...

Irresistible ants: exposure to novel toxic prey increases consumption over multiple temporal scales.

PubMed

Herr, Mark W; Robbins, Travis R; Centi, Alan; Thawley, Christopher J; Langkilde, Tracy

2016-07-01

As species become increasingly exposed to novel challenges, it is critical to understand how evolutionary (i.e., generational) and plastic (i.e., within lifetime) responses work together to determine a species' fate or predict its distribution. The introduction of non-native species imposes novel pressures on the native species that they encounter. Understanding how native species exposed to toxic or distasteful invaders change their feeding behavior can provide insight into their ability to cope with these novel threats as well as broader questions about the evolution of this behavior. We demonstrated that native eastern fence lizards do not avoid consuming invasive fire ants following repeated exposure to this toxic prey. Rather fence lizards increased their consumption of these ants following exposure on three different temporal scales. Lizards ate more fire ants when they were exposed to this toxic prey over successive days. Lizards consumed more fire ants if they had been exposed to fire ants as juveniles 6 months earlier. Finally, lizards from populations exposed to fire ants over multiple generations consumed more fire ants than those from fire ant-free areas. These results suggest that the potentially lethal consumption of fire ants may carry benefits resulting in selection for this behavior, and learning that persists long after initial exposure. Future research on the response of native predators to venomous prey over multiple temporal scales will be valuable in determining the long-term effects of invasion by these novel threats.

Spatio-temporal error growth in the multi-scale Lorenz'96 model

NASA Astrophysics Data System (ADS)

Herrera, S.; Fernández, J.; Rodríguez, M. A.; Gutiérrez, J. M.

2010-07-01

The influence of multiple spatio-temporal scales on the error growth and predictability of atmospheric flows is analyzed throughout the paper. To this aim, we consider the two-scale Lorenz'96 model and study the interplay of the slow and fast variables on the error growth dynamics. It is shown that when the coupling between slow and fast variables is weak the slow variables dominate the evolution of fluctuations whereas in the case of strong coupling the fast variables impose a non-trivial complex error growth pattern on the slow variables with two different regimes, before and after saturation of fast variables. This complex behavior is analyzed using the recently introduced Mean-Variance Logarithmic (MVL) diagram.

Novel patch modelling method for efficient simulation and prediction uncertainty analysis of multi-scale groundwater flow and transport processes

NASA Astrophysics Data System (ADS)

Sreekanth, J.; Moore, Catherine

2018-04-01

The application of global sensitivity and uncertainty analysis techniques to groundwater models of deep sedimentary basins are typically challenged by large computational burdens combined with associated numerical stability issues. The highly parameterized approaches required for exploring the predictive uncertainty associated with the heterogeneous hydraulic characteristics of multiple aquifers and aquitards in these sedimentary basins exacerbate these issues. A novel Patch Modelling Methodology is proposed for improving the computational feasibility of stochastic modelling analysis of large-scale and complex groundwater models. The method incorporates a nested groundwater modelling framework that enables efficient simulation of groundwater flow and transport across multiple spatial and temporal scales. The method also allows different processes to be simulated within different model scales. Existing nested model methodologies are extended by employing 'joining predictions' for extrapolating prediction-salient information from one model scale to the next. This establishes a feedback mechanism supporting the transfer of information from child models to parent models as well as parent models to child models in a computationally efficient manner. This feedback mechanism is simple and flexible and ensures that while the salient small scale features influencing larger scale prediction are transferred back to the larger scale, this does not require the live coupling of models. This method allows the modelling of multiple groundwater flow and transport processes using separate groundwater models that are built for the appropriate spatial and temporal scales, within a stochastic framework, while also removing the computational burden associated with live model coupling. The utility of the method is demonstrated by application to an actual large scale aquifer injection scheme in Australia.

Multisensor data fusion across time and space

NASA Astrophysics Data System (ADS)

Villeneuve, Pierre V.; Beaven, Scott G.; Reed, Robert A.

2014-06-01

Field measurement campaigns typically deploy numerous sensors having different sampling characteristics for spatial, temporal, and spectral domains. Data analysis and exploitation is made more difficult and time consuming as the sample data grids between sensors do not align. This report summarizes our recent effort to demonstrate feasibility of a processing chain capable of "fusing" image data from multiple independent and asynchronous sensors into a form amenable to analysis and exploitation using commercially-available tools. Two important technical issues were addressed in this work: 1) Image spatial registration onto a common pixel grid, 2) Image temporal interpolation onto a common time base. The first step leverages existing image matching and registration algorithms. The second step relies upon a new and innovative use of optical flow algorithms to perform accurate temporal upsampling of slower frame rate imagery. Optical flow field vectors were first derived from high-frame rate, high-resolution imagery, and then finally used as a basis for temporal upsampling of the slower frame rate sensor's imagery. Optical flow field values are computed using a multi-scale image pyramid, thus allowing for more extreme object motion. This involves preprocessing imagery to varying resolution scales and initializing new vector flow estimates using that from the previous coarser-resolution image. Overall performance of this processing chain is demonstrated using sample data involving complex too motion observed by multiple sensors mounted to the same base. Multiple sensors were included, including a high-speed visible camera, up to a coarser resolution LWIR camera.

Multi-scale Drivers of Variations in Atmospheric Evaporative Demand Based on Observations and Physically-based Modeling

NASA Astrophysics Data System (ADS)

Peng, L.; Sheffield, J.; Li, D.

2015-12-01

Evapotranspiration (ET) is a key link between the availability of water resources and climate change and climate variability. Variability of ET has important environmental and socioeconomic implications for managing hydrological hazards, food and energy production. Although there have been many observational and modeling studies of ET, how ET has varied and the drivers of the variations at different temporal scales remain elusive. Much of the uncertainty comes from the atmospheric evaporative demand (AED), which is the combined effect of radiative and aerodynamic controls. The inconsistencies among modeled AED estimates and the limited observational data may originate from multiple sources including the limited time span and uncertainties in the data. To fully investigate and untangle the intertwined drivers of AED, we present a spectrum analysis to identify key controls of AED across multiple temporal scales. We use long-term records of observed pan evaporation for 1961-2006 from 317 weather stations across China and physically-based model estimates of potential evapotranspiration (PET). The model estimates are based on surface meteorology and radiation derived from reanalysis, satellite retrievals and station data. Our analyses show that temperature plays a dominant role in regulating variability of AED at the inter-annual scale. At the monthly and seasonal scales, the primary control of AED shifts from radiation in humid regions to humidity in dry regions. Unlike many studies focusing on the spatial pattern of ET drivers based on a traditional supply and demand framework, this study underlines the importance of temporal scales when discussing controls of ET variations.

The spatial and temporal domains of modern ecology.

PubMed

Estes, Lyndon; Elsen, Paul R; Treuer, Timothy; Ahmed, Labeeb; Caylor, Kelly; Chang, Jason; Choi, Jonathan J; Ellis, Erle C

2018-05-01

To understand ecological phenomena, it is necessary to observe their behaviour across multiple spatial and temporal scales. Since this need was first highlighted in the 1980s, technology has opened previously inaccessible scales to observation. To help to determine whether there have been corresponding changes in the scales observed by modern ecologists, we analysed the resolution, extent, interval and duration of observations (excluding experiments) in 348 studies that have been published between 2004 and 2014. We found that observational scales were generally narrow, because ecologists still primarily use conventional field techniques. In the spatial domain, most observations had resolutions ≤1 m 2 and extents ≤10,000 ha. In the temporal domain, most observations were either unreplicated or infrequently repeated (>1 month interval) and ≤1 year in duration. Compared with studies conducted before 2004, observational durations and resolutions appear largely unchanged, but intervals have become finer and extents larger. We also found a large gulf between the scales at which phenomena are actually observed and the scales those observations ostensibly represent, raising concerns about observational comprehensiveness. Furthermore, most studies did not clearly report scale, suggesting that it remains a minor concern. Ecologists can better understand the scales represented by observations by incorporating autocorrelation measures, while journals can promote attentiveness to scale by implementing scale-reporting standards.

Bioregional monitoring design and occupancy estimation for two Sierra Nevadan amphibian taxa

EPA Science Inventory

Land-management agencies need quantitative, statistically rigorous monitoring data, often at large spatial and temporal scales, to support resource-management decisions. Monitoring designs typically must accommodate multiple ecological, logistical, political, and economic objec...

A functional model for characterizing long-distance movement behaviour

USGS Publications Warehouse

Buderman, Frances E.; Hooten, Mevin B.; Ivan, Jacob S.; Shenk, Tanya M.

2016-01-01

Advancements in wildlife telemetry techniques have made it possible to collect large data sets of highly accurate animal locations at a fine temporal resolution. These data sets have prompted the development of a number of statistical methodologies for modelling animal movement.Telemetry data sets are often collected for purposes other than fine-scale movement analysis. These data sets may differ substantially from those that are collected with technologies suitable for fine-scale movement modelling and may consist of locations that are irregular in time, are temporally coarse or have large measurement error. These data sets are time-consuming and costly to collect but may still provide valuable information about movement behaviour.We developed a Bayesian movement model that accounts for error from multiple data sources as well as movement behaviour at different temporal scales. The Bayesian framework allows us to calculate derived quantities that describe temporally varying movement behaviour, such as residence time, speed and persistence in direction. The model is flexible, easy to implement and computationally efficient.We apply this model to data from Colorado Canada lynx (Lynx canadensis) and use derived quantities to identify changes in movement behaviour.

Assessing risks to multiple resources affected by wildfire and forest management using an integrated probabilistic framework

Treesearch

Steven P. Norman; Danny C. Lee; Sandra Jacobson; Christine Damiani

2010-01-01

The tradeoffs that surround forest management are inherently complex, often involving multiple temporal and spatial scales. For example, conflicts may result when fuel treatments are designed to mediate long-term fuel hazards, but activities could impair sensitive aquatic habitat or degrade wildlife habitat in the short term. This complexity makes it hard for managers...

A Multi-Stage Method for Connecting Participatory Sensing and Noise Simulations

PubMed Central

Hu, Mingyuan; Che, Weitao; Zhang, Qiuju; Luo, Qingli; Lin, Hui

2015-01-01

Most simulation-based noise maps are important for official noise assessment but lack local noise characteristics. The main reasons for this lack of information are that official noise simulations only provide information about expected noise levels, which is limited by the use of large-scale monitoring of noise sources, and are updated infrequently. With the emergence of smart cities and ubiquitous sensing, the possible improvements enabled by sensing technologies provide the possibility to resolve this problem. This study proposed an integrated methodology to propel participatory sensing from its current random and distributed sampling origins to professional noise simulation. The aims of this study were to effectively organize the participatory noise data, to dynamically refine the granularity of the noise features on road segments (e.g., different portions of a road segment), and then to provide a reasonable spatio-temporal data foundation to support noise simulations, which can be of help to researchers in understanding how participatory sensing can play a role in smart cities. This study first discusses the potential limitations of the current participatory sensing and simulation-based official noise maps. Next, we explain how participatory noise data can contribute to a simulation-based noise map by providing (1) spatial matching of the participatory noise data to the virtual partitions at a more microscopic level of road networks; (2) multi-temporal scale noise estimations at the spatial level of virtual partitions; and (3) dynamic aggregation of virtual partitions by comparing the noise values at the relevant temporal scale to form a dynamic segmentation of each road segment to support multiple spatio-temporal noise simulations. In this case study, we demonstrate how this method could play a significant role in a simulation-based noise map. Together, these results demonstrate the potential benefits of participatory noise data as dynamic input sources for noise simulations on multiple spatio-temporal scales. PMID:25621604

A multi-stage method for connecting participatory sensing and noise simulations.

PubMed

Hu, Mingyuan; Che, Weitao; Zhang, Qiuju; Luo, Qingli; Lin, Hui

2015-01-22

Most simulation-based noise maps are important for official noise assessment but lack local noise characteristics. The main reasons for this lack of information are that official noise simulations only provide information about expected noise levels, which is limited by the use of large-scale monitoring of noise sources, and are updated infrequently. With the emergence of smart cities and ubiquitous sensing, the possible improvements enabled by sensing technologies provide the possibility to resolve this problem. This study proposed an integrated methodology to propel participatory sensing from its current random and distributed sampling origins to professional noise simulation. The aims of this study were to effectively organize the participatory noise data, to dynamically refine the granularity of the noise features on road segments (e.g., different portions of a road segment), and then to provide a reasonable spatio-temporal data foundation to support noise simulations, which can be of help to researchers in understanding how participatory sensing can play a role in smart cities. This study first discusses the potential limitations of the current participatory sensing and simulation-based official noise maps. Next, we explain how participatory noise data can contribute to a simulation-based noise map by providing (1) spatial matching of the participatory noise data to the virtual partitions at a more microscopic level of road networks; (2) multi-temporal scale noise estimations at the spatial level of virtual partitions; and (3) dynamic aggregation of virtual partitions by comparing the noise values at the relevant temporal scale to form a dynamic segmentation of each road segment to support multiple spatio-temporal noise simulations. In this case study, we demonstrate how this method could play a significant role in a simulation-based noise map. Together, these results demonstrate the potential benefits of participatory noise data as dynamic input sources for noise simulations on multiple spatio-temporal scales.

Integrated Modeling for Environmental Assessment of Ecosystem Services

EPA Science Inventory

The U.S. Environmental Protection Agency uses environmental models to inform rulemaking and policy decisions at multiple spatial and temporal scales. In this study, several sophisticated modeling technologies are seamlessly integrated to facilitate a baseline assessment of the re...

A Hierarchical Analysis of Tree Growth and Environmental Drivers Across Eastern US Temperate Forests

NASA Astrophysics Data System (ADS)

Mantooth, J.; Dietze, M.

2014-12-01

Improving predictions of how forests in the eastern United States will respond to future global change requires a better understanding of the drivers of variability in tree growth rates. Current inventory data lack the temporal resolution to characterize interannual variability, while existing growth records lack the extent required to assess spatial scales of variability. Therefore, we established a network of forest inventory plots across ten sites across the eastern US, and measured growth in adult trees using increment cores. Sites were chosen to maximize climate space explored, while within sites, plots were spread across primary environmental gradients to explore landscape-level variability in growth. Using the annual growth record available from tree cores, we explored the responses of trees to multiple environmental covariates over multiple spatial and temporal scales. We hypothesized that within and across sites growth rates vary among species, and that intraspecific growth rates increase with temperature along a species' range. We also hypothesized that trees show synchrony in growth responses to landscape-scale climatic changes. Initial analyses of growth increments indicate that across sites, trees with intermediate shade tolerance, e.g. Red Oak (Quercus rubra), tend to have the highest growth rates. At the site level, there is evidence for synchrony in response to large-scale climatic events (e.g. prolonged drought and above average temperatures). However, growth responses to climate at the landscape scale have yet to be detected. Our current analysis utilizes hierarchical Bayesian state-space modeling to focus on growth responses of adult trees to environmental covariates at multiple spatial and temporal scales. This predictive model of tree growth currently incorporates observed effects at the individual, plot, site, and landscape scale. Current analysis using this model shows a potential slowing of growth in the past decade for two sites in the northeastern US (Harvard Forest and Bartlett Experimental Forest), however more work is required to determine the robustness of this trend. Finally, these observations are being incorporated into ecosystem models using the Brown Dog informatics tools and the Predictive Ecosystem Analyzer (PEcAn) data assimilation workflow.

Change detection using vegetation indices and multiplatform satellite imagery at multiple temporal and spatial scales

USGS Publications Warehouse

Glenn, Edward P.; Nagler, Pamela L.; Huete, Alfredo R.; Weng, Qihao

2014-01-01

This chapter describes emerging methods for using satellite imagery across temporal and spatial scales using a case study approach to illustrate some of the opportunities now available for combining observations across scales. It explores the use of multiplatform sensor systems to characterize ecological change, as exemplified by efforts to scale the effects of a biocontrol insect (the leaf beetle Diorhabda carinulata) on the phenology and water use of Tamarix shrubs (Tamarix ramosissima and related species and hybrids) targeted for removal on western U.S. rivers, from the level of individual leaves to the regional level of measurement. Finally, the chapter summarizes the lessons learned and emphasize the need for ground data to calibrate and validate remote sensing data and the types of errors inherent in scaling point data over wide areas, illustrated with research on evapotranspiration (ET) of Tamarix using a wide range of ground measurement and remote sensing methods.

Coordinated learning of grid cell and place cell spatial and temporal properties: multiple scales, attention and oscillations.

PubMed

Grossberg, Stephen; Pilly, Praveen K

2014-02-05

A neural model proposes how entorhinal grid cells and hippocampal place cells may develop as spatial categories in a hierarchy of self-organizing maps (SOMs). The model responds to realistic rat navigational trajectories by learning both grid cells with hexagonal grid firing fields of multiple spatial scales, and place cells with one or more firing fields, that match neurophysiological data about their development in juvenile rats. Both grid and place cells can develop by detecting, learning and remembering the most frequent and energetic co-occurrences of their inputs. The model's parsimonious properties include: similar ring attractor mechanisms process linear and angular path integration inputs that drive map learning; the same SOM mechanisms can learn grid cell and place cell receptive fields; and the learning of the dorsoventral organization of multiple spatial scale modules through medial entorhinal cortex to hippocampus (HC) may use mechanisms homologous to those for temporal learning through lateral entorhinal cortex to HC ('neural relativity'). The model clarifies how top-down HC-to-entorhinal attentional mechanisms may stabilize map learning, simulates how hippocampal inactivation may disrupt grid cells, and explains data about theta, beta and gamma oscillations. The article also compares the three main types of grid cell models in the light of recent data.

Evaluating the status of individuals and populations: Advantages of multiple approaches and time scales: Chapter 6

USGS Publications Warehouse

Monson, Daniel H.; Bowen, Lizabeth

2015-01-01

Overall, a variety of indices used to measure population status throughout the sea otter’s range have provided insights for understanding the mechanisms driving the trajectory of various sea otter populations, which a single index could not, and we suggest using multiple methods to measure a population’s status at multiple spatial and temporal scales. The work described here also illustrates the usefulness of long-term data sets and/or approaches that can be used to assess population status retrospectively, providing information otherwise not available. While not all systems will be as amenable to using all the approaches presented here, we expect innovative researchers could adapt analogous multi-scale methods to a broad range of habitats and species including apex predators occupying the top trophic levels, which are often of conservation concern.

A Multi-Scale Distribution Model for Non-Equilibrium Populations Suggests Resource Limitation in an Endangered Rodent

PubMed Central

Bean, William T.; Stafford, Robert; Butterfield, H. Scott; Brashares, Justin S.

2014-01-01

Species distributions are known to be limited by biotic and abiotic factors at multiple temporal and spatial scales. Species distribution models, however, frequently assume a population at equilibrium in both time and space. Studies of habitat selection have repeatedly shown the difficulty of estimating resource selection if the scale or extent of analysis is incorrect. Here, we present a multi-step approach to estimate the realized and potential distribution of the endangered giant kangaroo rat. First, we estimate the potential distribution by modeling suitability at a range-wide scale using static bioclimatic variables. We then examine annual changes in extent at a population-level. We define “available” habitat based on the total suitable potential distribution at the range-wide scale. Then, within the available habitat, model changes in population extent driven by multiple measures of resource availability. By modeling distributions for a population with robust estimates of population extent through time, and ecologically relevant predictor variables, we improved the predictive ability of SDMs, as well as revealed an unanticipated relationship between population extent and precipitation at multiple scales. At a range-wide scale, the best model indicated the giant kangaroo rat was limited to areas that received little to no precipitation in the summer months. In contrast, the best model for shorter time scales showed a positive relation with resource abundance, driven by precipitation, in the current and previous year. These results suggest that the distribution of the giant kangaroo rat was limited to the wettest parts of the drier areas within the study region. This multi-step approach reinforces the differing relationship species may have with environmental variables at different scales, provides a novel method for defining “available” habitat in habitat selection studies, and suggests a way to create distribution models at spatial and temporal scales relevant to theoretical and applied ecologists. PMID:25237807

Temporal variations in patterns of Escherichia coli strain diversity and antimicrobial resistance in the migrant Egyptian vulture

PubMed Central

Maherchandani, Sunil; Shringi, B. N.; Kashyap, Sudhir Kumar

2018-01-01

ABSTRACT Aims: Multiple antimicrobial resistance in Escherichia coli of wild vertebrates is a global concern with scarce assessments on the subject from developing countries that have high human-wild species interactions. We studied the ecology of E. coli in a wintering population of Egyptian Vultures in India to understand temporal changes in both E. coli strains and patterns of antimicrobial resistance. Methods and Results: We ribotyped E. coli strains and assessed antimicrobial resistance from wintering vultures at a highly synanthropic carcass dump in north-west India. Both E. coli occurence (90.32%) and resistance to multiple antimicrobials (71.43%) were very high. Clear temporal patterns were apparent. Diversity of strains changed and homogenized at the end of the Vultures’ wintering period, while the resistance pattern showed significantly difference inter-annually, as well as between arrival and departing individuals within a wintering cycle. Significance of study: The carcass dump environment altered both E. coli strains and multiple antimicrobial resistance in migratory Egyptian Vultures within a season. Long-distance migratory species could therefore disseminate resistant E. coli strains across broad geographical scales rendering regional mitigation strategies to control multiple antimicrobial resistance in bacteria ineffective. PMID:29755700

Time-Frequency Analysis of Beach Bacteria Variations and its Implication for Recreational Water Quality Modeling

EPA Science Inventory

This paper explores the potential of time-frequency wavelet analysis in resolving beach bacteria concentration and possible explanatory variables across multiple time scales with temporal information still preserved. The wavelet scalograms of E. coli concentrations and the explan...

Multi-scale monitoring for improved nutrient management

USDA-ARS?s Scientific Manuscript database

In many watersheds, monitoring at the outlet of small watersheds has not been able to demonstrate that conservation efforts have had any impact on stream water quality. Reasons are multiple including legacy issues, time for the conservation practices to have any benefit, temporal variability of weat...

Body size distributions signal a regime shift in a lake ecosystem

EPA Science Inventory

Communities of organisms, from mammals to microorganisms, have discontinuous distributions of body size. This pattern of size structuring is a conservative trait of community organization and is a product of processes that occur at multiple spatial and temporal scales. In this st...

Testing for shared biogeographic history in the lower Central American freshwater fish assemblage using comparative phylogeography: concerted, independent, or multiple evolutionary responses?

PubMed Central

Bagley, Justin C; Johnson, Jerald B

2014-01-01

A central goal of comparative phylogeography is determining whether codistributed species experienced (1) concerted evolutionary responses to past geological and climatic events, indicated by congruent spatial and temporal patterns (“concerted-response hypothesis”); (2) independent responses, indicated by spatial incongruence (“independent-response hypothesis”); or (3) multiple responses (“multiple-response hypothesis”), indicated by spatial congruence but temporal incongruence (“pseudocongruence”) or spatial and temporal incongruence (“pseudoincongruence”). We tested these competing hypotheses using DNA sequence data from three livebearing fish species codistributed in the Nicaraguan depression of Central America (Alfaro cultratus, Poecilia gillii, and Xenophallus umbratilis) that we predicted might display congruent responses due to co-occurrence in identical freshwater drainages. Spatial analyses recovered different subdivisions of genetic structure for each species, despite shared finer-scale breaks in northwestern Costa Rica (also supported by phylogenetic results). Isolation-with-migration models estimated incongruent timelines of among-region divergences, with A. cultratus and Xenophallus populations diverging over Miocene–mid-Pleistocene while P. gillii populations diverged over mid-late Pleistocene. Approximate Bayesian computation also lent substantial support to multiple discrete divergences over a model of simultaneous divergence across shared spatial breaks (e.g., Bayes factor [B10] = 4.303 for Ψ [no. of divergences] > 1 vs. Ψ = 1). Thus, the data support phylogeographic pseudoincongruence consistent with the multiple-response hypothesis. Model comparisons also indicated incongruence in historical demography, for example, support for intraspecific late Pleistocene population growth was unique to P. gillii, despite evidence for finer-scale population expansions in the other taxa. Empirical tests for phylogeographic congruence indicate that multiple evolutionary responses to historical events have shaped the population structure of freshwater species codistributed within the complex landscapes in/around the Nicaraguan depression. Recent community assembly through different routes (i.e., different past distributions or colonization routes), and intrinsic ecological differences among species, has likely contributed to the unique phylogeographical patterns displayed by these Neotropical fishes. PMID:24967085

Spatio-Temporal Evolution and Scaling Properties of Human Settlements (Invited)

NASA Astrophysics Data System (ADS)

Small, C.; Milesi, C.; Elvidge, C.; Baugh, K.; Henebry, G. M.; Nghiem, S. V.

2013-12-01

Growth and evolution of cities and smaller settlements is usually studied in the context of population and other socioeconomic variables. While this is logical in the sense that settlements are groups of humans engaged in socioeconomic processes, our means of collecting information about spatio-temporal distributions of population and socioeconomic variables often lack the spatial and temporal resolution to represent the processes at scales which they are known to occur. Furthermore, metrics and definitions often vary with country and through time. However, remote sensing provides globally consistent, synoptic observations of several proxies for human settlement at spatial and temporal resolutions sufficient to represent the evolution of settlements over the past 40 years. We use several independent but complementary proxies for anthropogenic land cover to quantify spatio-temporal (ST) evolution and scaling properties of human settlements globally. In this study we begin by comparing land cover and night lights in 8 diverse settings - each spanning gradients of population density and degree of land surface modification. Stable anthropogenic night light is derived from multi-temporal composites of emitted luminance measured by the VIIRS and DMSP-OLS sensors. Land cover is represented as mixtures of sub-pixel fractions of rock, soil and impervious Substrates, Vegetation and Dark surfaces (shadow, water and absorptive materials) estimated from Landsat imagery with > 94% accuracy. Multi-season stability and variability of land cover fractions effectively distinguishes between spectrally similar land covers that corrupt thematic classifications based on single images. We find that temporal stability of impervious substrates combined with persistent shadow cast between buildings results in temporally stable aggregate reflectance across seasons at the 30 m scale of a Landsat pixel. Comparison of night light brightness with land cover composition, stability and variability yields several consistent relationships that persist across a variety of settlement types and physical environments. We use the multiple threshold method of Small et al (2011) to represent a continuum of settlement density by segmenting both night light brightness and multi-season land cover characteristics. Rank-size distributions of spatially contiguous segments quantify scaling and connectivity of land cover. Spatial and temporal evolution of rank-size distributions is consistent with power laws as suggested by Zipf's Law for city size based on population. However, unlike Zipf's Law, the observed distributions persist to global scales in which the larger agglomerations are much larger than individual cities. The scaling relations observed extend from the scale of cities and smaller settlements up to vast spatial networks of interconnected settlements.

Managing data from multiple disciplines, scales, and sites to support synthesis and modeling

USGS Publications Warehouse

Olson, R. J.; Briggs, J. M.; Porter, J.H.; Mah, Grant R.; Stafford, S.G.

1999-01-01

The synthesis and modeling of ecological processes at multiple spatial and temporal scales involves bringing together and sharing data from numerous sources. This article describes a data and information system model that facilitates assembling, managing, and sharing diverse data from multiple disciplines, scales, and sites to support integrated ecological studies. Cross-site scientific-domain working groups coordinate the development of data associated with their particular scientific working group, including decisions about data requirements, data to be compiled, data formats, derived data products, and schedules across the sites. The Web-based data and information system consists of nodes for each working group plus a central node that provides data access, project information, data query, and other functionality. The approach incorporates scientists and computer experts in the working groups and provides incentives for individuals to submit documented data to the data and information system.

Ecohydrological consequences of vegetation interactions within the critical zone in the tropical Andes: multi-scale assessment of vegetation change consequences

NASA Astrophysics Data System (ADS)

Villegas, J. C.; Salazar, J. F.; Arias, P. A.; León, J. D.

2017-12-01

Land cover transformation is currently one of the most important challenges in tropical South America. These transformations occur both because of climate-related ecological perturbations, as well as in response to ongoing socio-economic processes. A fundamental difference between those two drivers is the spatial and temporal scale at which they operate. However, when considered in a larger context, both drivers affect the ability of ecosystems to provide fundamental services to society. In this work, we use a multi-scale approach to identify key-mechanisms through which land cover transformation significantly affects ecological, hydrological and ecoclimatological dynamics, potentially leading to loss of societally-critical regulation services. We propose a suite of examples spanning multiple spatial and temporal scales that illustrate the effects of land cover trnasformations in ecological, hydrological, biogeochemical and climatic functions in tropical South America. These examples highlight important global-change-effects management challenges, as well as the need to consider the feedbacks and interactions between multi-scale processes.

Mercury and methylmercury stream concentrations in a Coastal Plain watershed: A multi-scale simulation analysis

USGS Publications Warehouse

Knightes, Christopher D.; Golden, Heather E.; Journey, Celeste A.; Davis, Gary M.; Conrads, Paul; Marvin-DiPasquale, Mark; Brigham, Mark E.; Bradley, Paul M.

2014-01-01

Mercury is a ubiquitous global environmental toxicant responsible for most US fish advisories. Processes governing mercury concentrations in rivers and streams are not well understood, particularly at multiple spatial scales. We investigate how insights gained from reach-scale mercury data and model simulations can be applied at broader watershed scales using a spatially and temporally explicit watershed hydrology and biogeochemical cycling model, VELMA. We simulate fate and transport using reach-scale (0.1 km2) study data and evaluate applications to multiple watershed scales. Reach-scale VELMA parameterization was applied to two nested sub-watersheds (28 km2 and 25 km2) and the encompassing watershed (79 km2). Results demonstrate that simulated flow and total mercury concentrations compare reasonably to observations at different scales, but simulated methylmercury concentrations are out-of-phase with observations. These findings suggest that intricacies of methylmercury biogeochemical cycling and transport are under-represented in VELMA and underscore the complexity of simulating mercury fate and transport.

From seconds to months: an overview of multi-scale dynamics of mobile telephone calls

NASA Astrophysics Data System (ADS)

Saramäki, Jari; Moro, Esteban

2015-06-01

Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected by telecom operators for billing purposes, have proven especially fruitful for understanding one-to-one communication patterns as well as the dynamics of social networks that are reflected in such patterns. We present an overview of empirical results on the multi-scale dynamics of social dynamics and networks inferred from mobile telephone calls. We begin with the shortest timescales and fastest dynamics, such as burstiness of call sequences between individuals, and "zoom out" towards longer temporal and larger structural scales, from temporal motifs formed by correlated calls between multiple individuals to long-term dynamics of social groups. We conclude this overview with a future outlook.

Simulating Mercury And Methyl Mercury Stream Concentrations At Multiple Scales in a Wetland Influenced Coastal Plain Watershed (McTier Creek, SC, USA)

EPA Science Inventory

Use of Mechanistic Models to?Improve Understanding: Differential, mass balance, process-based Spatial and temporal resolution Necessary simplifications of system complexity Combing field monitoring and modeling efforts Balance between capturing complexity and maintaining...

LAND-COVER CHARACTERIZATION AND CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDIV DATA

EPA Science Inventory

Land-cover (LC) composition and conversions are important factors that affect ecosystem condition and function. These data are frequently used as a primary data source to generate landscape-based metrics to assess landscape condition at multiple assessment scales. The use of sate...

Insights and challenges to Intergrating data from diverse ecological networks

USDA-ARS?s Scientific Manuscript database

Many of the most dramatic and surprising effects of global change occur across large spatial extents, from regions to continents, that impact multiple ecosystem types across a range of interacting spatial and temporal scales. The ability of ecologists and interdisciplinary scientists to understand a...

Ultrafast Microscopy of Energy and Charge Transport

NASA Astrophysics Data System (ADS)

Huang, Libai

The frontier in solar energy research now lies in learning how to integrate functional entities across multiple length scales to create optimal devices. Advancing the field requires transformative experimental tools that probe energy transfer processes from the nano to the meso lengthscales. To address this challenge, we aim to understand multi-scale energy transport across both multiple length and time scales, coupling simultaneous high spatial, structural, and temporal resolution. In my talk, I will focus on our recent progress on visualization of exciton and charge transport in solar energy harvesting materials from the nano to mesoscale employing ultrafast optical nanoscopy. With approaches that combine spatial and temporal resolutions, we have recently revealed a new singlet-mediated triplet transport mechanism in certain singlet fission materials. This work demonstrates a new triplet exciton transport mechanism leading to favorable long-range triplet exciton diffusion on the picosecond and nanosecond timescales for solar cell applications. We have also performed a direct measurement of carrier transport in space and in time by mapping carrier density with simultaneous ultrafast time resolution and 50 nm spatial precision in perovskite thin films using transient absorption microscopy. These results directly visualize long-range carrier transport of 220nm in 2 ns for solution-processed polycrystalline CH3NH3PbI3 thin films. The spatially and temporally resolved measurements reported here underscore the importance of the local morphology and establish an important first step towards discerning the underlying transport properties of perovskite materials.

THEORETICAL REVIEW The Hippocampus, Time, and Memory Across Scales

PubMed Central

Howard, Marc W.; Eichenbaum, Howard

2014-01-01

A wealth of experimental studies with animals have offered insights about how neural networks within the hippocampus support the temporal organization of memories. These studies have revealed the existence of “time cells” that encode moments in time, much as the well-known “place cells” map locations in space. Another line of work inspired by human behavioral studies suggests that episodic memories are mediated by a state of temporal context that changes gradually over long time scales, up to at least a few thousand seconds. In this view, the “mental time travel” hypothesized to support the experience of episodic memory corresponds to a “jump back in time” in which a previous state of temporal context is recovered. We suggest that these 2 sets of findings could be different facets of a representation of temporal history that maintains a record at the last few thousand seconds of experience. The ability to represent long time scales comes at the cost of discarding precise information about when a stimulus was experienced—this uncertainty becomes greater for events further in the past. We review recent computational work that describes a mechanism that could construct such a scale-invariant representation. Taken as a whole, this suggests the hippocampus plays its role in multiple aspects of cognition by representing events embedded in a general spatiotemporal context. The representation of internal time can be useful across nonhippocampal memory systems. PMID:23915126

Retinal and Optic Nerve Degeneration in Patients with Multiple Sclerosis Followed up for 5 Years.

PubMed

Garcia-Martin, Elena; Ara, Jose R; Martin, Jesus; Almarcegui, Carmen; Dolz, Isabel; Vilades, Elisa; Gil-Arribas, Laura; Fernandez, Francisco J; Polo, Vicente; Larrosa, Jose M; Pablo, Luis E; Satue, Maria

2017-05-01

To quantify retinal nerve fiber layer (RNFL) changes in patients with multiple sclerosis (MS) and healthy controls with a 5-year follow-up and to analyze correlations between disability progression and RNFL degeneration. Observational and longitudinal study. One hundred patients with relapsing-remitting MS and 50 healthy controls. All participants underwent a complete ophthalmic and electrophysiologic exploration and were re-evaluated annually for 5 years. Visual acuity (Snellen chart), color vision (Ishihara pseudoisochromatic plates), visual field examination, optical coherence tomography (OCT), scanning laser polarimetry (SLP), and visual evoked potentials. Expanded Disability Status Scale (EDSS) scores, disease duration, treatments, prior optic neuritis episodes, and quality of life (QOL; based on the 54-item Multiple Sclerosis Quality of Life Scale score). Optical coherence tomography (OCT) revealed changes in all RNFL thicknesses in both groups. In the MS group, changes were detected in average thickness and in the mean deviation using the GDx-VCC nerve fiber analyzer (Laser Diagnostic Technologies, San Diego, CA) and in the P100 latency of visual evoked potentials; no changes were detected in visual acuity, color vision, or visual fields. Optical coherence tomography showed greater differences in the inferior and temporal RNFL thicknesses in both groups. In MS patients only, OCT revealed a moderate correlation between the increase in EDSS and temporal and superior RNFL thinning. Temporal RNFL thinning based on OCT results was correlated moderately with decreased QOL. Multiple sclerosis patients exhibit a progressive axonal loss in the optic nerve fiber layer. Retinal nerve fiber layer thinning based on OCT results is a useful marker for assessing MS progression and correlates with increased disability and reduced QOL. Copyright © 2017 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Spatial-temporal consistency between gross primary productivity and solar-induced chlorophyll fluorescence of vegetation in China during 2007-2014.

PubMed

Ma, Jun; Xiao, Xiangming; Zhang, Yao; Doughty, Russell; Chen, Bangqian; Zhao, Bin

2018-10-15

Accurately estimating spatial-temporal patterns of gross primary production (GPP) is important for the global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatial-temporal dynamics of GPP. However, the accuracy assessment of GPP simulations from LUE models at both spatial and temporal scales remains a challenge. In this study, we simulated GPP of vegetation in China during 2007-2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images with 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPP VPM ) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPP VPM and SIF data over a single year (2010) and multiple years (2007-2014) in most areas of China. GPP VPM is also significantly positive correlated with GOME-2 SIF (R 2  > 0.43) spatially for seasonal scales. However, poor consistency was detected between GPP VPM and SIF data at yearly scale. GPP dynamic trends have high spatial-temporal variation in China during 2007-2014. Temperature, leaf area index (LAI), and precipitation are the most important factors influence GPP VPM in the regions of East Qinghai-Tibet Plateau, Loss Plateau, and Southwestern China, respectively. The results of this study indicate that GPP VPM is temporally and spatially in line with GOME-2 SIF data, and space-borne SIF data have great potential for evaluating LUE-based GPP models. Copyright © 2018 Elsevier B.V. All rights reserved.

Time-Accurate Local Time Stepping and High-Order Time CESE Methods for Multi-Dimensional Flows Using Unstructured Meshes

NASA Technical Reports Server (NTRS)

Chang, Chau-Lyan; Venkatachari, Balaji Shankar; Cheng, Gary

2013-01-01

With the wide availability of affordable multiple-core parallel supercomputers, next generation numerical simulations of flow physics are being focused on unsteady computations for problems involving multiple time scales and multiple physics. These simulations require higher solution accuracy than most algorithms and computational fluid dynamics codes currently available. This paper focuses on the developmental effort for high-fidelity multi-dimensional, unstructured-mesh flow solvers using the space-time conservation element, solution element (CESE) framework. Two approaches have been investigated in this research in order to provide high-accuracy, cross-cutting numerical simulations for a variety of flow regimes: 1) time-accurate local time stepping and 2) highorder CESE method. The first approach utilizes consistent numerical formulations in the space-time flux integration to preserve temporal conservation across the cells with different marching time steps. Such approach relieves the stringent time step constraint associated with the smallest time step in the computational domain while preserving temporal accuracy for all the cells. For flows involving multiple scales, both numerical accuracy and efficiency can be significantly enhanced. The second approach extends the current CESE solver to higher-order accuracy. Unlike other existing explicit high-order methods for unstructured meshes, the CESE framework maintains a CFL condition of one for arbitrarily high-order formulations while retaining the same compact stencil as its second-order counterpart. For large-scale unsteady computations, this feature substantially enhances numerical efficiency. Numerical formulations and validations using benchmark problems are discussed in this paper along with realistic examples.

Toward daily monitoring of vegetation conditions at field scale through fusing data from multiple sensors

USDA-ARS?s Scientific Manuscript database

Vegetation monitoring requires remote sensing data at fine spatial and temporal resolution. While imagery from coarse resolution sensors such as MODIS/VIIRS can provide daily observations, they lack spatial detail to capture surface features for crop and rangeland monitoring. The Landsat satellite s...

An Integrative Approach to Ecosystem Goods and Services – Putting the Pieces Together for the Tampa Bay Region

EPA Science Inventory

Ecosystem goods and services production, delivery, and use by humans involve multiple systems working together at various different spatial and temporal scales. Assessments of ecosystem goods and services and their benefits to current and or future human populations in any given ...

Interaction-Dominant Dynamics in Human Cognition: Beyond 1/f[superscript [alpha

ERIC Educational Resources Information Center

Ihlen, Espen A. F.; Vereijken, Beatrix

2010-01-01

It has been suggested that human behavior in general and cognitive performance in particular emerge from coordination between multiple temporal scales. In this article, we provide quantitative support for such a theory of interaction-dominant dynamics in human cognition by using wavelet-based multifractal analysis and accompanying multiplicative…

LAND USE AND LOTIC DIATOM ASSEMBLAGES: A MULTI-SPATIAL AND TEMPORAL ASSESSMENT

EPA Science Inventory

We assessed the effects of land-use at multiple spatial scales (e.g., catchment, stream network, and stream reach) on periphyton from 25 wadeable streams along a land-use gradient in the Willamette River Basin, Oregon, in a dry season. Additional water chemistry samples were col...

Nitrogen mineralization in riparian soils along a river continuum within a multi-landuse basin

EPA Science Inventory

Nitrogen dynamics in riparian systems are often addressed within one landuse type and are rarely studied on watershed scales involving multiple land uses. This study tested for both temporal trends and watershed-wide spatial patterns in N mineralization and identified site fact...

Spatial and Temporal Variability in Biogenic Gas Accumulation and Release in The Greater Everglades at Multiple Scales of Measurement

NASA Astrophysics Data System (ADS)

McClellan, M. D.; Cornett, C.; Schaffer, L.; Comas, X.

2017-12-01

Wetlands play a critical role in the carbon (C) cycle by producing and releasing significant amounts of greenhouse biogenic gasses (CO2, CH4) into the atmosphere. Wetlands in tropical and subtropical climates (such as the Florida Everglades) have become of great interest in the past two decades as they account for more than 20% of the global peatland C stock and are located in climates that favor year-round C emissions. Despite the increase in research involving C emission from these types of wetlands, the spatial and temporal variability involving C production, accumulation and release is still highly uncertain, and is the focus of this research at multiple scales of measurement (i.e. lab, field and landscape). Spatial variability in biogenic gas content, build up and release, at both the lab and field scales, was estimated using a series of ground penetrating radar (GPR) surveys constrained with gas traps fitted with time-lapse cameras. Variability in gas content was estimated at the sub-meter scale (lab scale) within two extracted monoliths from different wetland ecosystems at the Disney wilderness Preserve (DWP) and the Blue Cypress Preserve (BCP) using high frequency GPR (1.2 GHz) transects across the monoliths. At the field scale (> 10m) changes in biogenic gas content were estimated using 160 MHz GPR surveys collected within 4 different emergent wetlands at the DWP. Additionally, biogenic gas content from the extracted monoliths was used to developed a landscape comparison of C accumulation and emissions for each different wetland ecosystem. Changes in gas content over time were estimated at the lab scale at high temporal resolution (i.e. sub-hourly) in monoliths from the BCP and Water Conservation Area 1-A. An autonomous rail system was constructed to estimate biogenic gas content variability within the wetland soil matrix using a series of continuous, uninterrupted 1.2 GHz GPR transects along the samples. Measurements were again constrained with an array of gas traps fitted with time-lapse cameras. This research seeks to better understand the spatial and temporal variability of biogenic gas content within wetlands from the Greater Everglades Watershed. Such understanding may help to identify potential hotspots (both in space and time) and their implication for the flux estimates used as input in climate models.

Scale-Free Neural and Physiological Dynamics in Naturalistic Stimuli Processing

PubMed Central

Lin, Amy

2016-01-01

Abstract Neural activity recorded at multiple spatiotemporal scales is dominated by arrhythmic fluctuations without a characteristic temporal periodicity. Such activity often exhibits a 1/f-type power spectrum, in which power falls off with increasing frequency following a power-law function: P(f)∝1/fβ, which is indicative of scale-free dynamics. Two extensively studied forms of scale-free neural dynamics in the human brain are slow cortical potentials (SCPs)—the low-frequency (<5 Hz) component of brain field potentials—and the amplitude fluctuations of α oscillations, both of which have been shown to carry important functional roles. In addition, scale-free dynamics characterize normal human physiology such as heartbeat dynamics. However, the exact relationships among these scale-free neural and physiological dynamics remain unclear. We recorded simultaneous magnetoencephalography and electrocardiography in healthy subjects in the resting state and while performing a discrimination task on scale-free dynamical auditory stimuli that followed different scale-free statistics. We observed that long-range temporal correlation (captured by the power-law exponent β) in SCPs positively correlated with that of heartbeat dynamics across time within an individual and negatively correlated with that of α-amplitude fluctuations across individuals. In addition, across individuals, long-range temporal correlation of both SCP and α-oscillation amplitude predicted subjects’ discrimination performance in the auditory task, albeit through antagonistic relationships. These findings reveal interrelations among different scale-free neural and physiological dynamics and initial evidence for the involvement of scale-free neural dynamics in the processing of natural stimuli, which often exhibit scale-free dynamics. PMID:27822495

Use of multiple correspondence analysis (MCA) to identify interactive meteorological conditions affecting relative throughfall

NASA Astrophysics Data System (ADS)

Van Stan, John T.; Gay, Trent E.; Lewis, Elliott S.

2016-02-01

Forest canopies alter rainfall reaching the surface by redistributing it as throughfall. Throughfall supplies water and nutrients to a variety of ecohydrological components (soil microbial communities, stream water discharge/chemistry, and stormflow pathways) and is controlled by canopy structural interactions with meteorological conditions across temporal scales. This work introduces and applies multiple correspondence analyses (MCAs) to a range of meteorological thresholds (median intensity, median absolute deviation (MAD) of intensity, median wind-driven droplet inclination angle, and MAD of wind speed) for an example throughfall problem: identification of interacting storm conditions corresponding to temporal concentration in relative throughfall beyond the median observation (⩾73% of rain). MCA results from the example show that equalling or exceeding rain intensity thresholds (median and MAD) corresponded with temporal concentration of relative throughfall across all storms. Under these intensity conditions, two wind mechanisms produced significant correspondences: (1) high, steady wind-driven droplet inclination angles increased surface wetting; and (2) sporadic winds shook entrained droplets from surfaces. A discussion is provided showing that these example MCA findings agree well with previous work relying on more historically common methods (e.g., multiple regression and analytical models). Meteorological threshold correspondences to temporal concentration of relative throughfall at our site may be a function of heavy Tillandsia usneoides coverage. Applications of MCA within other forests may provide useful insights to how temporal throughfall dynamics are affected for drainage pathways dependent on different structures (leaves, twigs, branches, etc.).

Multiscale Modeling in the Clinic: Drug Design and Development

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

Clancy, Colleen E.; An, Gary; Cannon, William R.

A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multi-scale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multi-scale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions tomore » guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multi-scale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical techniques employed for multi-scale modeling approaches used in pharmacology and present several examples illustrating the current state-of-the-art regarding drug development for: Excitable Systems (Heart); Cancer (Metastasis and Differentiation); Cancer (Angiogenesis and Drug Targeting); Metabolic Disorders; and Inflammation and Sepsis. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multi-scale models.« less

Spatial and temporal aspects of chromatic adaptation and their functional significance for colour constancy.

PubMed

Werner, Annette

2014-11-01

Illumination in natural scenes changes at multiple temporal and spatial scales: slow changes in global illumination occur in the course of a day, and we encounter fast and localised illumination changes when visually exploring the non-uniform light field of three-dimensional scenes; in addition, very long-term chromatic variations may come from the environment, like for example seasonal changes. In this context, I consider the temporal and spatial properties of chromatic adaptation and discuss their functional significance for colour constancy in three-dimensional scenes. A process of fast spatial tuning in chromatic adaptation is proposed as a possible sensory mechanism for linking colour constancy to the spatial structure of a scene. The observed middlewavelength selectivity of this process is particularly suitable for adaptation to the mean chromaticity and the compensation of interreflections in natural scenes. Two types of sensory colour constancy are distinguished, based on the functional differences of their temporal and spatial scales: a slow type, operating at a global scale for the compensation of the ambient illumination; and a fast colour constancy, which is locally restricted and well suited to compensate region-specific variations in the light field of three dimensional scenes. Copyright © 2014 Elsevier B.V. All rights reserved.

Reach-scale channel sensitivity to multiple human activities and natural events: Lower Santa Clara River, California, USA

NASA Astrophysics Data System (ADS)

Downs, Peter W.; Dusterhoff, Scott R.; Sears, William A.

2013-05-01

Understanding the cumulative impact of natural and human influences on the sensitivity of channel morphodynamics, a relative measure between the drivers for change and the magnitude of channel response, requires an approach that accommodates spatial and temporal variability in the suite of primary stressors. Multiple historical data sources were assembled to provide a reach-scale analysis of the lower Santa Clara River (LSCR) in Ventura County, California, USA. Sediment supply is naturally high due to tectonic activity, earthquake-generated landslides, wildfires, and high magnitude flow events during El Niño years. Somewhat typically for the region, the catchment has been subject to four reasonably distinct land use and resource management combinations since European-American settlement. When combined with analysis of channel morphological response (quantifiable since ca. 1930), reach-scale and temporal differences in channel sensitivity become apparent. Downstream reaches have incised on average 2.4 m and become narrower by almost 50% with changes focused in a period of highly sensitive response after about 1950 followed by forced insensitivity caused by structural flood embankments and a significant grade control structure. In contrast, the middle reaches have been responsive but are morphologically resilient, and the upstream reaches show a mildly sensitive aggradational trend. Superimposing the natural and human drivers for change reveals that large scale stressors (related to ranching and irrigation) have been replaced over time by a suite of stressors operating at multiple spatial scales. Lower reaches have been sensitive primarily to 'local' scale impacts (urban growth, flood control, and aggregate mining) whereas, upstream, catchment-scale influences still prevail (including flow regulation and climate-driven sediment supply factors). These factors illustrate the complexity inherent to cumulative impact assessment in fluvial systems, provide evidence for a distinct Anthropocene fluvial response, and underpin the enormity of the challenge faced in trying to sustainably manage and restore rivers.

Exploring the limits to energy scaling and distant-target delivery of high-intensity midinfrared pulses

NASA Astrophysics Data System (ADS)

Panagiotopoulos, Paris; Kolesik, Miroslav; Moloney, Jerome V.

2016-09-01

We numerically investigate the scaling behavior of midinfrared filaments at extremely high input energies. It is shown that, given sufficient power, kilometer-scale, low-loss atmospheric filamentation is attainable by prechirping the pulse. Fully resolved four-dimensional (x y z t ) simulations show that, while in a spatially imperfect beam the modulation instability can lead to multiple hot-spot formation, the individual filaments are still stabilized by the recently proposed mechanism that relies on the temporal walk-off of short-wavelength radiation.

Temporal Changes in Forest Contexts at Multiple Extents: Three Decades of Fragmentation in the Gran Chaco (1979-2010), Central Argentina.

PubMed

Frate, Ludovico; Acosta, Alicia T R; Cabido, Marcelo; Hoyos, Laura; Carranza, Maria Laura

2015-01-01

The context in which a forest exists strongly influences its function and sustainability. Unveiling the multi-scale nature of forest fragmentation context is crucial to understand how human activities affect the spatial patterns of forests across a range of scales. However, this issue remains almost unexplored in subtropical ecosystems. In this study, we analyzed temporal changes (1979-2010) in forest contexts in the Argentinean dry Chaco at multiple extents. We classified forests over the last three decades based on forest context amount (Pf) and structural connectivity (Pff), which were measured using a moving window approach fixed at eight different extents (from local, ~ 6 ha, to regional, ~ 8300 ha). Specific multi-scale forest context profiles (for the years 1979 and 2010) were defined by projecting Pf vs. Pff mean values and were compared across spatial extents. The distributions of Pf across scales were described by scalograms and their shapes over time were compared. The amount of agricultural land and rangelands across the scales were also analyzed. The dry Chaco has undergone an intensive process of fragmentation, resulting in a shift from landscapes dominated by forests with gaps of rangelands to landscapes where small forest patches are embedded in agricultural lands. Multi-scale fragmentation analysis depicted landscapes in which local exploitation, which perforates forest cover, occurs alongside extensive forest clearings, reducing forests to small and isolated patches surrounded by agricultural lands. In addition, the temporal diminution of Pf's variability along with the increment of the mean slope of the Pf 's scalograms, indicate a simplification of the spatial pattern of forest over time. The observed changes have most likely been the result of the interplay between human activities and environmental constraints, which have shaped the spatial patterns of forests across scales. Based on our results, strategies for the conservation and sustainable management of the dry Chaco should take into account both the context of each habitat location and the scales over which a forest pattern might be preserved, altered or restored.

Temporal Changes in Forest Contexts at Multiple Extents: Three Decades of Fragmentation in the Gran Chaco (1979-2010), Central Argentina

PubMed Central

Frate, Ludovico; Acosta, Alicia T. R.; Cabido, Marcelo; Hoyos, Laura; Carranza, Maria Laura

2015-01-01

The context in which a forest exists strongly influences its function and sustainability. Unveiling the multi-scale nature of forest fragmentation context is crucial to understand how human activities affect the spatial patterns of forests across a range of scales. However, this issue remains almost unexplored in subtropical ecosystems. In this study, we analyzed temporal changes (1979–2010) in forest contexts in the Argentinean dry Chaco at multiple extents. We classified forests over the last three decades based on forest context amount (P f) and structural connectivity (P ff), which were measured using a moving window approach fixed at eight different extents (from local, ~ 6 ha, to regional, ~ 8300 ha). Specific multi-scale forest context profiles (for the years 1979 and 2010) were defined by projecting P f vs. P ff mean values and were compared across spatial extents. The distributions of P f across scales were described by scalograms and their shapes over time were compared. The amount of agricultural land and rangelands across the scales were also analyzed. The dry Chaco has undergone an intensive process of fragmentation, resulting in a shift from landscapes dominated by forests with gaps of rangelands to landscapes where small forest patches are embedded in agricultural lands. Multi-scale fragmentation analysis depicted landscapes in which local exploitation, which perforates forest cover, occurs alongside extensive forest clearings, reducing forests to small and isolated patches surrounded by agricultural lands. In addition, the temporal diminution of P f’s variability along with the increment of the mean slope of the P f ‘s scalograms, indicate a simplification of the spatial pattern of forest over time. The observed changes have most likely been the result of the interplay between human activities and environmental constraints, which have shaped the spatial patterns of forests across scales. Based on our results, strategies for the conservation and sustainable management of the dry Chaco should take into account both the context of each habitat location and the scales over which a forest pattern might be preserved, altered or restored. PMID:26630387

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

PubMed

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

2017-01-01

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

Scale-dependent intrinsic entropies of complex time series.

PubMed

Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E

2016-04-13

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).

Simultaneous nano-tracking of multiple motor proteins via spectral discrimination of quantum dots.

PubMed

Kakizuka, Taishi; Ikezaki, Keigo; Kaneshiro, Junichi; Fujita, Hideaki; Watanabe, Tomonobu M; Ichimura, Taro

2016-07-01

Simultaneous nanometric tracking of multiple motor proteins was achieved by combining multicolor fluorescent labeling of target proteins and imaging spectroscopy, revealing dynamic behaviors of multiple motor proteins at the sub-diffraction-limit scale. Using quantum dot probes of distinct colors, we experimentally verified the localization precision to be a few nanometers at temporal resolution of 30 ms or faster. One-dimensional processive movement of two heads of a single myosin molecule and multiple myosin molecules was successfully traced. Furthermore, the system was modified for two-dimensional measurement and applied to tracking of multiple myosin molecules. Our approach is useful for investigating cooperative movement of proteins in supramolecular nanomachinery.

Simultaneous nano-tracking of multiple motor proteins via spectral discrimination of quantum dots

PubMed Central

Kakizuka, Taishi; Ikezaki, Keigo; Kaneshiro, Junichi; Fujita, Hideaki; Watanabe, Tomonobu M.; Ichimura, Taro

2016-01-01

Simultaneous nanometric tracking of multiple motor proteins was achieved by combining multicolor fluorescent labeling of target proteins and imaging spectroscopy, revealing dynamic behaviors of multiple motor proteins at the sub-diffraction-limit scale. Using quantum dot probes of distinct colors, we experimentally verified the localization precision to be a few nanometers at temporal resolution of 30 ms or faster. One-dimensional processive movement of two heads of a single myosin molecule and multiple myosin molecules was successfully traced. Furthermore, the system was modified for two-dimensional measurement and applied to tracking of multiple myosin molecules. Our approach is useful for investigating cooperative movement of proteins in supramolecular nanomachinery. PMID:27446684

Short- and long-term rhythmic interventions: perspectives for language rehabilitation.

PubMed

Schön, Daniele; Tillmann, Barbara

2015-03-01

This paper brings together different perspectives on the investigation and understanding of temporal processing and temporal expectations. We aim to bridge different temporal deficit hypotheses in dyslexia, dysphasia, or deafness in a larger framework, taking into account multiple nested temporal scales. We present data testing the hypothesis that temporal attention can be influenced by external rhythmic auditory stimulation (i.e., musical rhythm) and benefits subsequent language processing, including syntax processing and speech production. We also present data testing the hypothesis that phonological awareness can be influenced by several months of musical training and, more particularly, rhythmic training, which in turn improves reading skills. Together, our data support the hypothesis of a causal role of rhythm-based processing for language processing and acquisition. These results open new avenues for music-based remediation of language and hearing impairment. © 2015 New York Academy of Sciences.

An optimal merging technique for high-resolution precipitation products: OPTIMAL MERGING OF PRECIPITATION METHOD

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

Shrestha, Roshan; Houser, Paul R.; Anantharaj, Valentine G.

2011-04-01

Precipitation products are currently available from various sources at higher spatial and temporal resolution than any time in the past. Each of the precipitation products has its strengths and weaknesses in availability, accuracy, resolution, retrieval techniques and quality control. By merging the precipitation data obtained from multiple sources, one can improve its information content by minimizing these issues. However, precipitation data merging poses challenges of scale-mismatch, and accurate error and bias assessment. In this paper we present Optimal Merging of Precipitation (OMP), a new method to merge precipitation data from multiple sources that are of different spatial and temporal resolutionsmore » and accuracies. This method is a combination of scale conversion and merging weight optimization, involving performance-tracing based on Bayesian statistics and trend-analysis, which yields merging weights for each precipitation data source. The weights are optimized at multiple scales to facilitate multiscale merging and better precipitation downscaling. Precipitation data used in the experiment include products from the 12-km resolution North American Land Data Assimilation (NLDAS) system, the 8-km resolution CMORPH and the 4-km resolution National Stage-IV QPE. The test cases demonstrate that the OMP method is capable of identifying a better data source and allocating a higher priority for them in the merging procedure, dynamically over the region and time period. This method is also effective in filtering out poor quality data introduced into the merging process.« less

Combining Monitoring Data Spanning Multiple Temporal and Spatial Scales To Evaluate Water Quality Affecting Seagrass Habitat Extent in northwest Florida Estuaries

EPA Science Inventory

The ability to understand and manage ecological changes caused by anthropogenic stressors is often impeded by a lack of sufficient information to resolve pattern and change with sufficient resolution and extent. Increasingly, different types of environmental data are available t...

Hierarchical analysis of species distributions and abundance across environmental gradients

Treesearch

Jeffery Diez; Ronald H. Pulliam

2007-01-01

Abiotic and biotic processes operate at multiple spatial and temporal scales to shape many ecological processes, including species distributions and demography. Current debate about the relative roles of niche-based and stochastic processes in shaping species distributions and community composition reflects, in part, the challenge of understanding how these processes...

Using landscape disturbance and succession models to support forest management

Treesearch

Eric J. Gustafson; Brian R. Sturtevant; Anatoly S. Shvidenko; Robert M. Scheller

2010-01-01

Managers of forested landscapes must account for multiple, interacting ecological processes operating at broad spatial and temporal scales. These interactions can be of such complexity that predictions of future forest ecosystem states are beyond the analytical capability of the human mind. Landscape disturbance and succession models (LDSM) are predictive and...

Remote sensing for restoration planning: how the big picture can inform stakeholders

Treesearch

Susan Cordell; Erin J. Questad; Gregory P. Asner; Kealoha M. Kinney; Jarrod M. Thaxton; Amanda Uowolo; Sam Brooks; Mark W. Chynoweth

2016-01-01

The use of remote sensing in ecosystem management has transformed how land managers, practitioners, and policymakers evaluate ecosystem loss, gain, and change at multiple spatial and temporal scales. Less developed is the use of these spatial tools for planning, implementing, and evaluating ecosystem restoration projects and especially so in multifunctional...

An Integrated Modeling Framework for Performing Environmental Assessments: Application to Ecosystem Services in the Albemarle-Pamlico Basins (NC and VA,USA)

EPA Science Inventory

The U.S. Environmental Protection Agency uses environmental models to inform rulemaking and policy decisions at multiple spatial and temporal scales. As decision-making has moved towards integrated thinking and assessment (e.g. media, site, region, services), the increasing compl...

An event map of memory space in the hippocampus

PubMed Central

Deuker, Lorena; Bellmund, Jacob LS; Navarro Schröder, Tobias; Doeller, Christian F

2016-01-01

The hippocampus has long been implicated in both episodic and spatial memory, however these mnemonic functions have been traditionally investigated in separate research strands. Theoretical accounts and rodent data suggest a common mechanism for spatial and episodic memory in the hippocampus by providing an abstract and flexible representation of the external world. Here, we monitor the de novo formation of such a representation of space and time in humans using fMRI. After learning spatio-temporal trajectories in a large-scale virtual city, subject-specific neural similarity in the hippocampus scaled with the remembered proximity of events in space and time. Crucially, the structure of the entire spatio-temporal network was reflected in neural patterns. Our results provide evidence for a common coding mechanism underlying spatial and temporal aspects of episodic memory in the hippocampus and shed new light on its role in interleaving multiple episodes in a neural event map of memory space. DOI: http://dx.doi.org/10.7554/eLife.16534.001 PMID:27710766

A large-scale circuit mechanism for hierarchical dynamical processing in the primate cortex

PubMed Central

Chaudhuri, Rishidev; Knoblauch, Kenneth; Gariel, Marie-Alice; Kennedy, Henry; Wang, Xiao-Jing

2015-01-01

We developed a large-scale dynamical model of the macaque neocortex, which is based on recently acquired directed- and weighted-connectivity data from tract-tracing experiments, and which incorporates heterogeneity across areas. A hierarchy of timescales naturally emerges from this system: sensory areas show brief, transient responses to input (appropriate for sensory processing), whereas association areas integrate inputs over time and exhibit persistent activity (suitable for decision-making and working memory). The model displays multiple temporal hierarchies, as evidenced by contrasting responses to visual versus somatosensory stimulation. Moreover, slower prefrontal and temporal areas have a disproportionate impact on global brain dynamics. These findings establish a circuit mechanism for “temporal receptive windows” that are progressively enlarged along the cortical hierarchy, suggest an extension of time integration in decision-making from local to large circuits, and should prompt a re-evaluation of the analysis of functional connectivity (measured by fMRI or EEG/MEG) by taking into account inter-areal heterogeneity. PMID:26439530

Mercury and methylmercury stream concentrations in a Coastal Plain watershed: a multi-scale simulation analysis.

PubMed

Knightes, C D; Golden, H E; Journey, C A; Davis, G M; Conrads, P A; Marvin-DiPasquale, M; Brigham, M E; Bradley, P M

2014-04-01

Mercury is a ubiquitous global environmental toxicant responsible for most US fish advisories. Processes governing mercury concentrations in rivers and streams are not well understood, particularly at multiple spatial scales. We investigate how insights gained from reach-scale mercury data and model simulations can be applied at broader watershed scales using a spatially and temporally explicit watershed hydrology and biogeochemical cycling model, VELMA. We simulate fate and transport using reach-scale (0.1 km(2)) study data and evaluate applications to multiple watershed scales. Reach-scale VELMA parameterization was applied to two nested sub-watersheds (28 km(2) and 25 km(2)) and the encompassing watershed (79 km(2)). Results demonstrate that simulated flow and total mercury concentrations compare reasonably to observations at different scales, but simulated methylmercury concentrations are out-of-phase with observations. These findings suggest that intricacies of methylmercury biogeochemical cycling and transport are under-represented in VELMA and underscore the complexity of simulating mercury fate and transport. Published by Elsevier Ltd.

Spatial and Temporal Scales of Surface Water-Groundwater Interactions

NASA Astrophysics Data System (ADS)

Boano, F.

2016-12-01

The interfaces between surface water and groundwater (i.e., river and lake sediments) represent hotspots for nutrient transformation in watersheds. This intense biochemical activity stems from the peculiar physicochemical properties of these interface areas. Here, the exchange of water and nutrients between surface and subsurface environments creates an ecotone region that can support the presence of different microbial species responsible for nutrient transformation. Previous studies have elucidated that water exchange between rivers and aquifers is organized in a complex system of nested flow cells. Each cell entails a range of residence timescales spanning multiple order of magnitudes, providing opportunities for different biochemical reactions to occur. Physically-bases models represent useful tools to deal with the wide range of spatial and temporal scales that characterize surface-subsurface water exchange. This contribution will present insights about how hydrodynamic processes control scale organization for surface water - groundwater interactions. The specific focus will be the influence of exchange processes on microbial activity and nutrient transformation, discussing how groundwater flow at watershed scale controls flow conditions and hence constrain microbial reactions at much smaller scales.

Reasoning from non-stationarity

NASA Astrophysics Data System (ADS)

Struzik, Zbigniew R.; van Wijngaarden, Willem J.; Castelo, Robert

2002-11-01

Complex real-world (biological) systems often exhibit intrinsically non-stationary behaviour of their temporal characteristics. We discuss local measures of scaling which can capture and reveal changes in a system's behaviour. Such measures offer increased insight into a system's behaviour and are superior to global, spectral characteristics like the multifractal spectrum. They are, however, often inadequate for fully understanding and modelling the phenomenon. We illustrate an attempt to capture complex model characteristics by analysing (multiple order) correlations in a high dimensional space of parameters of the (biological) system being studied. Both temporal information, among others local scaling information, and external descriptors/parameters, possibly influencing the system's state, are used to span the search space investigated for the presence of a (sub-)optimal model. As an example, we use fetal heartbeat monitored during labour.

Recurrence plot analysis of nonstationary data: the understanding of curved patterns.

PubMed

Facchini, A; Kantz, H; Tiezzi, E

2005-08-01

Recurrence plots of the calls of the Nomascus concolor (Western black crested gibbon) and Hylobates lar (White-handed gibbon) show characteristic circular, curved, and hyperbolic patterns superimposed to the main temporal scale of the signal. It is shown that these patterns are related to particular nonstationarities in the signal. Some of them can be reproduced by artificial signals like frequency modulated sinusoids and sinusoids with time divergent frequency. These modulations are too faint to be resolved by conventional time-frequency analysis with similar precision. Therefore, recurrence plots act as a magnifying glass for the detection of multiple temporal scales in slightly modulated signals. The detected phenomena in these acoustic signals can be explained in the biomechanical context by taking in account the role of the muscles controlling the vocal folds.

Spontaneous alterations of regional brain activity in patients with adult generalized anxiety disorder

PubMed Central

Xia, Likun; Li, Shumei; Wang, Tianyue; Guo, Yaping; Meng, Lihong; Feng, Yunping; Cui, Yu; Wang, Fan; Ma, Jian; Jiang, Guihua

2017-01-01

Objective We aimed to examine how spontaneous brain activity might be related to the pathophysiology of generalized anxiety disorder (GAD). Patients and methods Using resting-state functional MRI, we examined spontaneous regional brain activity in 31 GAD patients (mean age, 36.87±9.16 years) and 36 healthy control participants (mean age, 39.53±8.83 years) matched for age, education, and sex from December 2014 to October 2015. We performed a two-sample t-test on the voxel-based analysis of the regional homogeneity (ReHo) maps. We used Pearson correlation analysis to compare scores from the Hamilton Anxiety Rating Scale, Hamilton Depression Rating Scale, State–Trait Anxiety Scale-Trait Scale, and mean ReHo values. Results We found abnormal spontaneous activity in multiple regions of brain in GAD patients, especially in the sensorimotor cortex and emotional regions. GAD patients showed decreased ReHo values in the right orbital middle frontal gyrus, left anterior cingulate cortex, right middle frontal gyrus, and bilateral supplementary motor areas, with increased ReHo values in the left middle temporal gyrus, left superior temporal gyrus, and right superior occipital gyrus. The ReHo value of the left middle temporal gyrus correlated positively with the Hamilton Anxiety Rating Scale scores. Conclusion These results suggest that altered local synchronization of spontaneous brain activity may be related to the pathophysiology of GAD. PMID:28790831

Enhancing the Temporal Complexity of Distributed Brain Networks with Patterned Cerebellar Stimulation

PubMed Central

Farzan, Faranak; Pascual-Leone, Alvaro; Schmahmann, Jeremy D.; Halko, Mark

2016-01-01

Growing evidence suggests that sensory, motor, cognitive and affective processes map onto specific, distributed neural networks. Cerebellar subregions are part of these networks, but how the cerebellum is involved in this wide range of brain functions remains poorly understood. It is postulated that the cerebellum contributes a basic role in brain functions, helping to shape the complexity of brain temporal dynamics. We therefore hypothesized that stimulating cerebellar nodes integrated in different networks should have the same impact on the temporal complexity of cortical signals. In healthy humans, we applied intermittent theta burst stimulation (iTBS) to the vermis lobule VII or right lateral cerebellar Crus I/II, subregions that prominently couple to the dorsal-attention/fronto-parietal and default-mode networks, respectively. Cerebellar iTBS increased the complexity of brain signals across multiple time scales in a network-specific manner identified through electroencephalography (EEG). We also demonstrated a region-specific shift in power of cortical oscillations towards higher frequencies consistent with the natural frequencies of targeted cortical areas. Our findings provide a novel mechanism and evidence by which the cerebellum contributes to multiple brain functions: specific cerebellar subregions control the temporal dynamics of the networks they are engaged in. PMID:27009405

Multiple concurrent temporal recalibrations driven by audiovisual stimuli with apparent physical differences.

PubMed

Yuan, Xiangyong; Bi, Cuihua; Huang, Xiting

2015-05-01

Out-of-synchrony experiences can easily recalibrate one's subjective simultaneity point in the direction of the experienced asynchrony. Although temporal adjustment of multiple audiovisual stimuli has been recently demonstrated to be spatially specific, perceptual grouping processes that organize separate audiovisual stimuli into distinctive "objects" may play a more important role in forming the basis for subsequent multiple temporal recalibrations. We investigated whether apparent physical differences between audiovisual pairs that make them distinct from each other can independently drive multiple concurrent temporal recalibrations regardless of spatial overlap. Experiment 1 verified that reducing the physical difference between two audiovisual pairs diminishes the multiple temporal recalibrations by exposing observers to two utterances with opposing temporal relationships spoken by one single speaker rather than two distinct speakers at the same location. Experiment 2 found that increasing the physical difference between two stimuli pairs can promote multiple temporal recalibrations by complicating their non-temporal dimensions (e.g., disks composed of two rather than one attribute and tones generated by multiplying two frequencies); however, these recalibration aftereffects were subtle. Experiment 3 further revealed that making the two audiovisual pairs differ in temporal structures (one transient and one gradual) was sufficient to drive concurrent temporal recalibration. These results confirm that the more audiovisual pairs physically differ, especially in temporal profile, the more likely multiple temporal perception adjustments will be content-constrained regardless of spatial overlap. These results indicate that multiple temporal recalibrations are based secondarily on the outcome of perceptual grouping processes.

The statistical power to detect cross-scale interactions at macroscales

USGS Publications Warehouse

Wagner, Tyler; Fergus, C. Emi; Stow, Craig A.; Cheruvelil, Kendra S.; Soranno, Patricia A.

2016-01-01

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

Response of Bacterioplankton Communities to Cadmium Exposure in Coastal Water Microcosms with High Temporal Variability

PubMed Central

Wang, Kai; Xiong, Jinbo; Chen, Xinxin; Zheng, Jialai; Hu, Changju; Yang, Yina; Zhu, Jianlin

2014-01-01

Multiple anthropogenic disturbances to bacterial diversity have been investigated in coastal ecosystems, in which temporal variability in the bacterioplankton community has been considered a ubiquitous process. However, far less is known about the temporal dynamics of a bacterioplankton community responding to pollution disturbances such as toxic metals. We used coastal water microcosms perturbed with 0, 10, 100, and 1,000 μg liter−1 of cadmium (Cd) for 2 weeks to investigate temporal variability, Cd-induced patterns, and their interaction in the coastal bacterioplankton community and to reveal whether the bacterial community structure would reflect the Cd gradient in a temporally varying system. Our results showed that the bacterioplankton community structure shifted along the Cd gradient consistently after a 4-day incubation, although it exhibited some resistance to Cd at low concentration (10 μg liter−1). A process akin to an arms race between temporal variability and Cd exposure was observed, and the temporal variability overwhelmed Cd-induced patterns in the bacterial community. The temporal succession of the bacterial community was correlated with pH, dissolved oxygen, NO3−-N, NO2−-N, PO43−-P, dissolved organic carbon, and chlorophyll a, and each of these parameters contributed more to community variance than Cd did. However, elevated Cd levels did decrease the temporal turnover rate of community. Furthermore, key taxa, affiliated to the families Flavobacteriaceae, Rhodobacteraceae, Erythrobacteraceae, Piscirickettsiaceae, and Alteromonadaceae, showed a high frequency of being associated with Cd levels during 2 weeks. This study provides direct evidence that specific Cd-induced patterns in bacterioplankton communities exist in highly varying manipulated coastal systems. Future investigations on an ecosystem scale across longer temporal scales are needed to validate the observed pattern. PMID:25326310

Controls for multi-scale temporal variation in methane flux of a subtropical tidal salt marsh

NASA Astrophysics Data System (ADS)

Li, H.

2016-12-01

Coastal wetlands provide critical carbon sequestration benefits, yet the production of methane (CH4) from these ecosystems can vary by an order of magnitude based on environmental and biological factors. Eddy covariance (EC) measurements for methane flux (FCH4) were performed in a subtropical tidal salt marsh of eastern China over 20 months. Spectral analysis techniques including the continuous wavelet transform, the wavelet coherence, the partial wavelet coherence and the multiple wavelet coherence were employed to analyze the periodicities and the main regulating factors of FCH4 in the tidal salt marsh. The annual budget of methane was 17.8 g C-CH4 m-2 yr-1, which was relatively high compared to those of most reported from inland wetland sites. In non-growing season, release of ebullition was the dominant driving mechanism for variability of FCH4 from hourly to monthly scales. There was no single dominant factor at short-term scale (half-day to 1-day) in growing season. It is worthwhile to note that tide was one of the most important factors regulating FCH4 at short time scale (half-day to 1-day). In comparison, the contribution of temperature to FCH4 at a short time scale (half-day to 1-day) was small due to its narrow range. In addition, plant-modulated transport and gross primary production also contributed to FCH4 at multiple temporal scales in this densely vegetated marsh, especially at weekly to monthly scales. Due to the complex interactive influences of tidal dynamics, temperature fluctuation, plant productivity, plant-mediated transport and release of ebullition on FCH4 exhibited no clear pattern of diurnal variation, but instead was highly variable.

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

PubMed Central

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

2017-01-01

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

Low-Cost Ultra-High Spatial and Temporal Resolution Mapping of Intertidal Rock Platforms

NASA Astrophysics Data System (ADS)

Bryson, M.; Johnson-Roberson, M.; Murphy, R.

2012-07-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time which could compliment field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at relatively course, sub-meter resolutions or with limited temporal resolutions and relatively high costs for small-scale environmental science and ecology studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric pipeline that was developed for constructing highresolution, 3D, photo-realistic terrain models of intertidal rocky shores. The processing pipeline uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine colour and topographic information at sub-centimeter resolutions over an area of approximately 100m, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rock platform at Cape Banks, Sydney, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.

Earthquake precursors: spatial-temporal gravity changes before the great earthquakes in the Sichuan-Yunnan area

NASA Astrophysics Data System (ADS)

Zhu, Yi-Qing; Liang, Wei-Feng; Zhang, Song

2018-01-01

Using multiple-scale mobile gravity data in the Sichuan-Yunnan area, we systematically analyzed the relationships between spatial-temporal gravity changes and the 2014 Ludian, Yunnan Province Ms6.5 earthquake and the 2014 Kangding Ms6.3, 2013 Lushan Ms7.0, and 2008 Wenchuan Ms8.0 earthquakes in Sichuan Province. Our main results are as follows. (1) Before the occurrence of large earthquakes, gravity anomalies occur in a large area around the epicenters. The directions of gravity change gradient belts usually agree roughly with the directions of the main fault zones of the study area. Such gravity changes might reflect the increase of crustal stress, as well as the significant active tectonic movements and surface deformations along fault zones, during the period of gestation of great earthquakes. (2) Continuous significant changes of the multiple-scale gravity fields, as well as greater gravity changes with larger time scales, can be regarded as medium-range precursors of large earthquakes. The subsequent large earthquakes always occur in the area where the gravity changes greatly. (3) The spatial-temporal gravity changes are very useful in determining the epicenter of coming large earthquakes. The large gravity networks are useful to determine the general areas of coming large earthquakes. However, the local gravity networks with high spatial-temporal resolution are suitable for determining the location of epicenters. Therefore, denser gravity observation networks are necessary for better forecasts of the epicenters of large earthquakes. (4) Using gravity changes from mobile observation data, we made medium-range forecasts of the Kangding, Ludian, Lushan, and Wenchuan earthquakes, with especially successful forecasts of the location of their epicenters. Based on the above discussions, we emphasize that medium-/long-term potential for large earthquakes might exist nowadays in some areas with significant gravity anomalies in the study region. Thus, the monitoring should be strengthened.

Multi-Temporal Multi-Sensor Analysis of Urbanization and Environmental/Climate Impact in China for Sustainable Urban Development

NASA Astrophysics Data System (ADS)

Ban, Yifang; Gong, Peng; Gamba, Paolo; Taubenbock, Hannes; Du, Peijun

2016-08-01

The overall objective of this research is to investigate multi-temporal, multi-scale, multi-sensor satellite data for analysis of urbanization and environmental/climate impact in China to support sustainable planning. Multi- temporal multi-scale SAR and optical data have been evaluated for urban information extraction using innovative methods and algorithms, including KTH- Pavia Urban Extractor, Pavia UEXT, and an "exclusion- inclusion" framework for urban extent extraction, and KTH-SEG, a novel object-based classification method for detailed urban land cover mapping. Various pixel- based and object-based change detection algorithms were also developed to extract urban changes. Several Chinese cities including Beijing, Shanghai and Guangzhou are selected as study areas. Spatio-temporal urbanization patterns and environmental impact at regional, metropolitan and city core were evaluated through ecosystem service, landscape metrics, spatial indices, and/or their combinations. The relationship between land surface temperature and land-cover classes was also analyzed.The urban extraction results showed that urban areas and small towns could be well extracted using multitemporal SAR data with the KTH-Pavia Urban Extractor and UEXT. The fusion of SAR data at multiple scales from multiple sensors was proven to improve urban extraction. For urban land cover mapping, the results show that the fusion of multitemporal SAR and optical data could produce detailed land cover maps with improved accuracy than that of SAR or optical data alone. Pixel-based and object-based change detection algorithms developed with the project were effective to extract urban changes. Comparing the urban land cover results from mulitemporal multisensor data, the environmental impact analysis indicates major losses for food supply, noise reduction, runoff mitigation, waste treatment and global climate regulation services through landscape structural changes in terms of decreases in service area, edge contamination and fragmentation. In terms ofclimate impact, the results indicate that land surface temperature can be related to land use/land cover classes.

Ultrafast all-optical imaging technique using low-temperature grown GaAs/AlxGa1 - xAs multiple-quantum-well semiconductor

NASA Astrophysics Data System (ADS)

Gao, Guilong; Tian, Jinshou; Wang, Tao; He, Kai; Zhang, Chunmin; Zhang, Jun; Chen, Shaorong; Jia, Hui; Yuan, Fenfang; Liang, Lingliang; Yan, Xin; Li, Shaohui; Wang, Chao; Yin, Fei

2017-11-01

We report and experimentally demonstrate an ultrafast all-optical imaging technique capable of single-shot ultrafast recording with a picosecond-scale temporal resolution and a micron-order two-dimensional spatial resolution. A GaAs/AlxGa1 - xAs multiple-quantum-well (MQW) semiconductor with a picosecond response time, grown using molecular beam epitaxy (MBE) at a low temperature (LT), is used for the first time in ultrafast imaging technology. The semiconductor transforms the signal beam information to the probe beam, the birefringent delay crystal time-serializes the input probe beam, and the beam displacer maps different polarization probe beams onto different detector locations, resulting in two frames with an approximately 9 ps temporal separation and approximately 25 lp/mm spatial resolution in the visible range.

Temporal Context in Speech Processing and Attentional Stream Selection: A Behavioral and Neural Perspective

ERIC Educational Resources Information Center

Golumbic, Elana M. Zion; Poeppel, David; Schroeder, Charles E.

2012-01-01

The human capacity for processing speech is remarkable, especially given that information in speech unfolds over multiple time scales concurrently. Similarly notable is our ability to filter out of extraneous sounds and focus our attention on one conversation, epitomized by the "Cocktail Party" effect. Yet, the neural mechanisms underlying on-line…

A framework for developing urban forest ecosystem services and goods indicators

Treesearch

Cynnamon Dobbs; Francisco J. Escobedo; Wayne C. Zipperer

2011-01-01

The social and ecological processes impacting on urban forests have been studied at multiple temporal and spatial scales in order to help us quantify, monitor, and value the ecosystem services that benefit people. Few studies have comprehensively analyzed the full suite of ecosystem services, goods (ESG), and ecosystem disservices provided by an urban forest....

Wildfire risk as a socioecological pathology

Treesearch

A Paige Fischer; Thomas A Spies; Toddi A Steelman; Cassandra Moseley; Bart R Johnson; John D Bailey; Alan A Ager; Patrick Bourgeron; Susan Charnley; Brandon M Collins; Jeff Kline; Jessica E Leahy; Jeremy S Littell; James DA Millington; Max Nielsen-Pincus; Christine S Olsen; Travis B Paveglio; Christopher I Roos; Michelle M Steen-Adams; Forrest R Stevens; Jelena Vukomanovic; Eric White; David MJS Bowman

2016-01-01

Wildfire risk in temperate forests has become a nearly intractable problem that can be characterized as a socioecological “pathology”: that is, a set of complex and problematic interactions among social and ecological systems across multiple spatial and temporal scales. Assessments of wildfire risk could benefit from recognizing and accounting for these interactions in...

Landscape epidemiology and control of pathogens with cryptic and long-distance dispersal: Sudden oak death in northern Californian forests

Treesearch

Joao A. N. Filipe; Richard C. Cobb; Ross K. Meentemeyer; Christopher A. Lee; Yana S. Valachovic; Alex R. Cook; David M. Rizzo; Christopher A. Gilligan

2012-01-01

Exotic pathogens and pests threaten ecosystem service, biodiversity, and crop security globally. If an invasive agent can disperse asymptomatically over long distances, multiple spatial and temporal scales interplay, making identification of effective strategies to regulate, monitor, and control disease extremely difficult. The management of outbreaks is also...

Multiple constraint analysis of regional land-surface carbon flux

Treesearch

D.P. Turner; M. Göckede; B.E. Law; W.D. Ritts; W.B. Cohen; Z. Yang; T. Hudiburg; R. Kennedy; M. Duane

2011-01-01

We applied and compared bottom-up (process model-based) and top-down (atmospheric inversion-based) scaling approaches to evaluate the spatial and temporal patterns of net ecosystem production (NEP) over a 2.5 × 105 km2 area (the state of Oregon) in the western United States. Both approaches indicated a carbon sink over this...

Doubly stochastic Poisson process models for precipitation at fine time-scales

NASA Astrophysics Data System (ADS)

Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao

2012-09-01

This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.

Spatial and temporal drivers of phenotypic diversity in polymorphic snakes.

PubMed

Cox, Christian L; Davis Rabosky, Alison R

2013-08-01

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

The Use of Census Migration Data to Approximate Human Movement Patterns across Temporal Scales

PubMed Central

Wesolowski, Amy; Buckee, Caroline O.; Pindolia, Deepa K.; Eagle, Nathan; Smith, David L.; Garcia, Andres J.; Tatem, Andrew J.

2013-01-01

Human movement plays a key role in economies and development, the delivery of services, and the spread of infectious diseases. However, it remains poorly quantified partly because reliable data are often lacking, particularly for low-income countries. The most widely available are migration data from human population censuses, which provide valuable information on relatively long timescale relocations across countries, but do not capture the shorter-scale patterns, trips less than a year, that make up the bulk of human movement. Census-derived migration data may provide valuable proxies for shorter-term movements however, as substantial migration between regions can be indicative of well connected places exhibiting high levels of movement at finer time scales, but this has never been examined in detail. Here, an extensive mobile phone usage data set for Kenya was processed to extract movements between counties in 2009 on weekly, monthly, and annual time scales and compared to data on change in residence from the national census conducted during the same time period. We find that the relative ordering across Kenyan counties for incoming, outgoing and between-county movements shows strong correlations. Moreover, the distributions of trip durations from both sources of data are similar, and a spatial interaction model fit to the data reveals the relationships of different parameters over a range of movement time scales. Significant relationships between census migration data and fine temporal scale movement patterns exist, and results suggest that census data can be used to approximate certain features of movement patterns across multiple temporal scales, extending the utility of census-derived migration data. PMID:23326367

Importance of Local and Regional Scales in Shaping Mycobacterial Abundance in Freshwater Lakes.

PubMed

Roguet, Adélaïde; Therial, Claire; Catherine, Arnaud; Bressy, Adèle; Varrault, Gilles; Bouhdamane, Lila; Tran, Viet; Lemaire, Bruno J; Vincon-Leite, Brigitte; Saad, Mohamed; Moulin, Laurent; Lucas, Françoise S

2018-05-01

Biogeographical studies considering the entire bacterial community may underestimate mechanisms of bacterial assemblages at lower taxonomic levels. In this context, the study aimed to identify factors affecting the spatial and temporal dynamic of the Mycobacterium, a genus widespread in aquatic ecosystems. Nontuberculous mycobacteria (NTM) density variations were quantified in the water column of freshwater lakes at the regional scale (annual monitoring of 49 lakes in the Paris area) and at the local scale (2-year monthly monitoring in Créteil Lake) by real-time quantitative PCR targeting the atpE gene. At the regional scale, mycobacteria densities in water samples ranged from 6.7 × 10 3 to 1.9 × 10 8 genome units per liter. Density variations were primarily explained by water pH, labile iron, and dispersal processes through the connection of the lakes to a river. In Créteil Lake, no spatial variation of mycobacterial densities was noticed over the 2-year monthly survey, except after large rainfall events. Indeed, storm sewer effluents locally and temporarily increased NTM densities in the water column. The temporal dynamic of the NTM densities in Créteil Lake was associated with suspended solid concentrations. No clear seasonal variation was noticed despite a shift in NTM densities observed over the 2012-2013 winter. Temporal NTM densities fluctuations were well predicted by the neutral community model, suggesting a random balance between loss and gain of mycobacterial taxa within Créteil Lake. This study highlights the importance of considering multiple spatial scales for understanding the spatio-temporal dynamic of bacterial populations in natural environments.

Evaluating the NOAA Coastal and Marine Ecological Classification Standard in estuarine systems: A Columbia River Estuary case study

NASA Astrophysics Data System (ADS)

Keefer, Matthew L.; Peery, Christopher A.; Wright, Nancy; Daigle, William R.; Caudill, Christopher C.; Clabough, Tami S.; Griffith, David W.; Zacharias, Mark A.

2008-06-01

A common first step in conservation planning and resource management is to identify and classify habitat types, and this has led to a proliferation of habitat classification systems. Ideally, classifications should be scientifically and conceptually rigorous, with broad applicability across spatial and temporal scales. Successful systems will also be flexible and adaptable, with a framework and supporting lexicon accessible to users from a variety of disciplines and locations. A new, continental-scale classification system for coastal and marine habitats—the Coastal and Marine Ecological Classification Standard (CMECS)—is currently being developed for North America by NatureServe and the National Oceanic and Atmospheric Administration (NOAA). CMECS is a nested, hierarchical framework that applies a uniform set of rules and terminology across multiple habitat scales using a combination of oceanographic (e.g. salinity, temperature), physiographic (e.g. depth, substratum), and biological (e.g. community type) criteria. Estuaries are arguably the most difficult marine environments to classify due to large spatio-temporal variability resulting in rapidly shifting benthic and water column conditions. We simultaneously collected data at eleven subtidal sites in the Columbia River Estuary (CRE) in fall 2004 to evaluate whether the estuarine component of CMECS could adequately classify habitats across several scales for representative sites within the estuary spanning a range of conditions. Using outputs from an acoustic Doppler current profiler (ADCP), CTD (conductivity, temperature, depth) sensor, and PONAR (benthic dredge) we concluded that the CMECS hierarchy provided a spatially explicit framework in which to integrate multiple parameters to define macro-habitats at the 100 m 2 to >1000 m 2 scales, or across several tiers of the CMECS system. The classification's strengths lie in its nested, hierarchical structure and in the development of a standardized, yet flexible classification lexicon. The application of the CMECS to other estuaries in North America should therefore identify similar habitat types at similar scales as we identified in the CRE. We also suggest that the CMECS could be improved by refining classification thresholds to better reflect ecological processes, by direct integration of temporal variability, and by more explicitly linking physical and biological processes with habitat patterns.

Concurrent temporal channels for auditory processing: Oscillatory neural entrainment reveals segregation of function at different scales

PubMed Central

Tian, Xing; Rowland, Jess; Poeppel, David

2017-01-01

Natural sounds convey perceptually relevant information over multiple timescales, and the necessary extraction of multi-timescale information requires the auditory system to work over distinct ranges. The simplest hypothesis suggests that temporal modulations are encoded in an equivalent manner within a reasonable intermediate range. We show that the human auditory system selectively and preferentially tracks acoustic dynamics concurrently at 2 timescales corresponding to the neurophysiological theta band (4–7 Hz) and gamma band ranges (31–45 Hz) but, contrary to expectation, not at the timescale corresponding to alpha (8–12 Hz), which has also been found to be related to auditory perception. Listeners heard synthetic acoustic stimuli with temporally modulated structures at 3 timescales (approximately 190-, approximately 100-, and approximately 30-ms modulation periods) and identified the stimuli while undergoing magnetoencephalography recording. There was strong intertrial phase coherence in the theta band for stimuli of all modulation rates and in the gamma band for stimuli with corresponding modulation rates. The alpha band did not respond in a similar manner. Classification analyses also revealed that oscillatory phase reliably tracked temporal dynamics but not equivalently across rates. Finally, mutual information analyses quantifying the relation between phase and cochlear-scaled correlations also showed preferential processing in 2 distinct regimes, with the alpha range again yielding different patterns. The results support the hypothesis that the human auditory system employs (at least) a 2-timescale processing mode, in which lower and higher perceptual sampling scales are segregated by an intermediate temporal regime in the alpha band that likely reflects different underlying computations. PMID:29095816

Improved spatial and temporal characteristics of ionospheric irregularities and polar mesospheric summer echoes using coherent MIMO and aperture synthesis radar imaging

NASA Astrophysics Data System (ADS)

Chau, J. L.; Urco, J. M.; Milla, M. A.; Vierinen, J.

2017-12-01

We have recently implemented Multiple-input multiple-output (MIMO) radar techniques to resolve temporal and spatial ambiguities of ionospheric and atmospheric irregularities, with improve capabilities than previously experiments using single-input multi-output (SIMO) techniques. SIMO techniques in the atmospheric and ionospheric coherent scatter radar field are usually called aperture synthesis radar imaging. Our implementations have done at the Jicamarca Radio Observatory (JRO) in Lima, Peru, and at the Middle Atmosphere Alomar Radar System (MAARSY) in Andenes, Norway, to study equatorial electrojet (EEJ) field-aligned irregularities and polar mesospheric summer echoes (PMSE), respectively. Figure 1 shows an example of a configuration used at MAARSY and the comparison between the SIMO and MIMO resulting antenna point spread functions, respectively. Although in this work we present the details of the implementations at each facility, we will focus on the observed peculiarities of each phenomenon, making emphasis in the underlying physical mechanisms that govern their existence and their spatial and temporal modulation. For example, what are the typical horizontal scales of PMSE variability in both intensity and wind field?

Spatiotemporal multivariate mixture models for Bayesian model selection in disease mapping.

PubMed

Lawson, A B; Carroll, R; Faes, C; Kirby, R S; Aregay, M; Watjou, K

2017-12-01

It is often the case that researchers wish to simultaneously explore the behavior of and estimate overall risk for multiple, related diseases with varying rarity while accounting for potential spatial and/or temporal correlation. In this paper, we propose a flexible class of multivariate spatio-temporal mixture models to fill this role. Further, these models offer flexibility with the potential for model selection as well as the ability to accommodate lifestyle, socio-economic, and physical environmental variables with spatial, temporal, or both structures. Here, we explore the capability of this approach via a large scale simulation study and examine a motivating data example involving three cancers in South Carolina. The results which are focused on four model variants suggest that all models possess the ability to recover simulation ground truth and display improved model fit over two baseline Knorr-Held spatio-temporal interaction model variants in a real data application.

Temporal coherence of the acoustic field forward propagated through a continental shelf with random internal waves.

PubMed

Gong, Zheng; Chen, Tianrun; Ratilal, Purnima; Makris, Nicholas C

2013-11-01

An analytical model derived from normal mode theory for the accumulated effects of range-dependent multiple forward scattering is applied to estimate the temporal coherence of the acoustic field forward propagated through a continental-shelf waveguide containing random three-dimensional internal waves. The modeled coherence time scale of narrow band low-frequency acoustic field fluctuations after propagating through a continental-shelf waveguide is shown to decay with a power-law of range to the -1/2 beyond roughly 1 km, decrease with increasing internal wave energy, to be consistent with measured acoustic coherence time scales. The model should provide a useful prediction of the acoustic coherence time scale as a function of internal wave energy in continental-shelf environments. The acoustic coherence time scale is an important parameter in remote sensing applications because it determines (i) the time window within which standard coherent processing such as matched filtering may be conducted, and (ii) the number of statistically independent fluctuations in a given measurement period that determines the variance reduction possible by stationary averaging.

Interstellar scintillation observations for PSR B0355+54

NASA Astrophysics Data System (ADS)

Xu, Y. H.; Lee, K. J.; Hao, L. F.; Wang, H. G.; Liu, Z. Y.; Yue, Y. L.; Yuan, J. P.; Li, Z. X.; Wang, M.; Dong, J.; Tan, J. J.; Chen, W.; Bai, J. M.

2018-06-01

In this paper, we report our investigation of pulsar scintillation phenomena by monitoring PSR B0355+54 at 2.25 GHz for three successive months using the Kunming 40-m radio telescope. We measured the dynamic spectrum, the two-dimensional correlation function and the secondary spectrum. These observations have a high signal-to-noise ratio (S/N ≥ 100). We detected scintillation arcs, which are rarely observable using such a small telescope. The sub-microsecond scale width of the scintillation arc indicates that the transverse scale of the structures on the scattering screen is as compact as astronomical unit size. Our monitoring shows that the scintillation bandwidth, the time-scale and the arc curvature of PSR B0355+54 were varying temporally. A plausible explanation would need to invoke a multiple-scattering-screen or multiple-scattering-structure scenario, in which different screens or ray paths dominate the scintillation process at different epochs.

Navigability of multiplex temporal network

NASA Astrophysics Data System (ADS)

Wang, Yan; Song, Qiao-Zhen

2017-01-01

Real world complex systems have multiple levels of relationships and in many cases, they need to be modeled as multiplex networks where the same nodes can interact with each other in different layers, such as social networks. However, social relationships only appear at prescribed times so the temporal structures of edge activations can also affect the dynamical processes located above them. To consider both factors are simultaneously, we introduce multiplex temporal networks and propose three different walk strategies to investigate the concurrent dynamics of random walks and the temporal structure of multiplex networks. Thus, we derive analytical results for the multiplex centrality and coverage function in multiplex temporal networks. By comparing them with the numerical results, we show how the underlying topology of the layers and the walk strategy affect the efficiency when exploring the networks. In particular, the most interesting result is the emergence of a super-diffusion process, where the time scale of the multiplex is faster than that of both layers acting separately.

Analysis of streamflow variability in Alpine catchments at multiple spatial and temporal scales

NASA Astrophysics Data System (ADS)

Pérez Ciria, T.; Chiogna, G.

2017-12-01

Alpine watersheds play a pivotal role in Europe for water provisioning and for hydropower production. In these catchments, temporal fluctuations of river discharge occur at multiple temporal scales due to natural as well as anthropogenic driving forces. In the last decades, modifications of the flow regime have been observed and their origin lies in the complex interplay between construction of dams for hydro power production, changes in water management policies and climatic changes. The alteration of the natural flow has negative impacts on the freshwater biodiversity and threatens the ecosystem integrity of the Alpine region. Therefore, understanding the temporal and spatial variability of river discharge has recently become a particular concern for environmental protection and represents a crucial contribution to achieve sustainable water resources management in the Alps. In this work, time series analysis is conducted for selected gauging stations in the Inn and the Adige catchments, which cover a large part of the central and eastern region of the Alps. We analyze the available time series using the continuous wavelet transform and change-point analyses for determining how and where changes have taken place. Although both catchments belong to different climatic zones of the Greater Alpine Region, streamflow properties share some similar characteristics. The comparison of the collected streamflow time series in the two catchments permits detecting gradients in the hydrological system dynamics that depend on station elevation, longitudinal location in the Alps and catchment area. This work evidences that human activities (e.g., water management practices and flood protection measures, changes in legislation and market regulation) have major impacts on streamflow and should be rigorously considered in hydrological models.

The Influence of temporal sampling regime on the WFD classification of catchments within the Eden Demonstration Test Catchment Project

NASA Astrophysics Data System (ADS)

Jonczyk, Jennine; Haygarth, Phil; Quinn, Paul; Reaney, Sim

2014-05-01

A high temporal resolution data set from the Eden Demonstration Test Catchment (DTC) project is used to investigate the processes causing pollution and the influence of temporal sampling regime on the WFD classification of three catchments. This data highlights WFD standards may not be fit for purpose. The Eden DTC project is part of a UK government-funded project designed to provide robust evidence regarding how diffuse pollution can be cost-effectively controlled to improve and maintain water quality in rural river catchments. The impact of multiple water quality parameters on ecosystems and sustainable food production are being studied at the catchment scale. Three focus catchments approximately 10 km2 each, have been selected to represent the different farming practices and geophysical characteristics across the Eden catchment, Northern England. A field experimental programme has been designed to monitor the dynamics of agricultural diffuse pollution at multiple scales using state of the art sensors providing continuous real time data. The data set, which includes Total Phosphorus and Total Reactive Phosphorus, Nitrate, Ammonium, pH, Conductivity, Turbidity and Chlorophyll a reveals the frequency and duration of nutrient concentration target exceedance which arises from the prevalence of storm events of increasing magnitude. This data set is sub-sampled at different time intervals to explore how different sampling regimes affects our understanding of nutrient dynamics and the ramification of the different regimes to WFD chemical status. This presentation seeks to identify an optimum temporal resolution of data for effective catchment management and to question the usefulness of the WFD status metric for determining health of a system. Criteria based on high frequency short duration events needs to be accounted for.

Aeolian and fluvial processes in dryland regions: the need for integrated studies

USGS Publications Warehouse

Belnap, Jayne; Munson, Seth M.; Field, Jason P.

2011-01-01

Aeolian and fluvial processes play a fundamental role in dryland regions of the world and have important environmental and ecological consequences from local to global scales. Although both processes operate over similar spatial and temporal scales and are likely strongly coupled in many dryland systems, aeolian and fluvial processes have traditionally been studied separately, making it difficult to assess their relative importance in drylands, as well as their potential for synergistic interaction. Land degradation by accelerated wind and water erosion is a major problem throughout the world's drylands, and although recent studies suggest that these processes likely interact across broad spatial and temporal scales to amplify the transport of soil resources from and within drylands, many researchers and land managers continue to view them as separate and unrelated processes. Here, we illustrate how aeolian and fluvial sediment transport is coupled at multiple spatial and temporal scales and highlight the need for these interrelated processes to be studied from a more integrated perspective that crosses traditional disciplinary boundaries. Special attention is given to how the growing threat of climate change and land-use disturbance will influence linkages between aeolian and fluvial processes in the future. We also present emerging directions for interdisciplinary needs within the aeolian and fluvial research communities that call for better integration across a broad range of traditional disciplines such as ecology, biogeochemistry, agronomy, and soil conservation.

Climate change and the eco-hydrology of fire: Will area burned increase in a warming western USA?

Treesearch

Donald McKenzie; Jeremy S. Littell

2017-01-01

Wildfire area is predicted to increase with global warming. Empirical statistical models and process-based simulations agree almost universally. The key relationship for this unanimity, observed at multiple spatial and temporal scales, is between drought and fire. Predictive models often focus on ecosystems in which this relationship appears to be particularly strong,...

Ecosystem-level consequences of symbiont partnerships in an N-fixing shrub from interior Alaskan floodplains

Treesearch

R.W. Ruess; M.D. Anderson; J.W. McFarland; K. Kielland; K. Olson; D.L. Taylor

2013-01-01

In long-lived N-fixing plants, environmental conditions affecting plant growth and N demand vary at multiple temporal and spatial scales, and symbiont assemblages on a given host and patterns of allocation to nodule activities have been shown to vary according to environmental factors, suggesting that hosts may alter partner choice and manipulate symbiont assemblages...

Predicted effects of gypsy moth defoliation and climate change on forest carbon dynamics in the New Jersey Pine Barrens

Treesearch

Alec M. Kretchun; Robert M. Scheller; Melissa S. Lucash; Kenneth L. Clark; John Hom; Steve Van Tuyl; Michael L. Fine

2014-01-01

Disturbance regimes within temperate forests can significantly impact carbon cycling. Additionally, projected climate change in combination with multiple, interacting disturbance effects may disrupt the capacity of forests to act as carbon sinks at large spatial and temporal scales. We used a spatially explicit forest succession and disturbance model, LANDIS-II, to...

Estimating forest ecosystem evapotranspiration at multiple temporal scales with a dimension analysis approach

Treesearch

Guoyi Zhou; Ge Sun; Xu Wang; Chuanyan Zhou; Steven G. McNulty; James M. Vose; Devendra M. Amatya

2008-01-01

It is critical that evapotranspiration (ET) be quantified accurately so that scientists can evaluate the effects of land management and global change on water availability, streamflow, nutrient and sediment loading, and ecosystem productivity in watersheds. The objective of this study was to derive a new semi-empirical ET modeled using a dimension analysis method that...

Spatial and temporal diet patterns of subadult and small adult striped bass in Massachusetts estuaries: Data, a synthesis, and trends across scales

USGS Publications Warehouse

Ferry, K.H.; Mather, Martha E.

2012-01-01

Subadult and small adult (375–475 mm total length) striped bass Morone saxatilis are abundant and represent an important component of the recovered U.S. Atlantic coast stocks. However, little is known about these large aggregations of striped bass during their annual foraging migrations to New England. A quantitative understanding of trends in the diets of subadult and small adult migrants is critical to research and management. Because of the complexity of the Massachusetts coast, we were able to compare diets at multiple spatial, temporal, and taxonomic scales and evaluate which of these provided the greatest insights into the foraging patterns of this size of fish. Specifically, during spring through autumn, we quantified the diets of 797 migratory striped bass collected from 13 Massachusetts estuaries distributed among three geographic regions in two biogeographic provinces. Our data provided three useful results. First, subadult and young adult striped bass ate a season-specific mixture of fish and invertebrates. For example, more juvenile Atlantic herring Clupea harengus were eaten in spring than in summer or autumn, more juvenile Atlantic menhaden Brevoortia tyrannus were eaten in autumn than in spring or summer, amphipods were eaten primarily in the southern biogeographic province, and shrimp Crangon sp. were eaten in all locations and seasons. Second, examining diets by season was essential because of the temporal variability in striped bass prey. Grouping prey by fish and invertebrates revealed the potential for predictable differences in growth across geographic locations and seasons, based on the output from simple bioenergetics simulations. Third, of the three spatial scales examined, region provided the most quantitative and interpretable ecological trends. Our results demonstrate the utility of comparing multiple scales to evaluate the best way to depict diet trends in a migrating predator that seasonally uses different geographic locations.

Electrophysiological models of neural processing.

PubMed

Nelson, Mark E

2011-01-01

The brain is an amazing information processing system that allows organisms to adaptively monitor and control complex dynamic interactions with their environment across multiple spatial and temporal scales. Mathematical modeling and computer simulation techniques have become essential tools in understanding diverse aspects of neural processing ranging from sub-millisecond temporal coding in the sound localization circuity of barn owls to long-term memory storage and retrieval in humans that can span decades. The processing capabilities of individual neurons lie at the core of these models, with the emphasis shifting upward and downward across different levels of biological organization depending on the nature of the questions being addressed. This review provides an introduction to the techniques for constructing biophysically based models of individual neurons and local networks. Topics include Hodgkin-Huxley-type models of macroscopic membrane currents, Markov models of individual ion-channel currents, compartmental models of neuronal morphology, and network models involving synaptic interactions among multiple neurons.

Approaches to advancescientific understanding of macrosystems ecology

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

Levy, Ofir; Ball, Becky; Bond-Lamberty, Benjamin

Macrosystem ecological studies inherently investigate processes that interact across multiple spatial and temporal scales, requiring intensive sampling and massive amounts of data from diverse sources to incorporate complex cross-scale and hierarchical interactions. Inherent challenges associated with these characteristics include high computational demands, data standardization and assimilation, identification of important processes and scales without prior knowledge, and the need for large, cross-disciplinary research teams that conduct long-term studies. Therefore, macrosystem ecology studies must utilize a unique set of approaches that are capable of encompassing these methodological characteristics and associated challenges. Several case studies demonstrate innovative methods used in current macrosystem ecologymore » studies.« less

Temporal variation and scaling of parameters for a monthly hydrologic model

NASA Astrophysics Data System (ADS)

Deng, Chao; Liu, Pan; Wang, Dingbao; Wang, Weiguang

2018-03-01

The temporal variation of model parameters is affected by the catchment conditions and has a significant impact on hydrological simulation. This study aims to evaluate the seasonality and downscaling of model parameter across time scales based on monthly and mean annual water balance models with a common model framework. Two parameters of the monthly model, i.e., k and m, are assumed to be time-variant at different months. Based on the hydrological data set from 121 MOPEX catchments in the United States, we firstly analyzed the correlation between parameters (k and m) and catchment properties (NDVI and frequency of rainfall events, α). The results show that parameter k is positively correlated with NDVI or α, while the correlation is opposite for parameter m, indicating that precipitation and vegetation affect monthly water balance by controlling temporal variation of parameters k and m. The multiple linear regression is then used to fit the relationship between ε and the means and coefficient of variations of parameters k and m. Based on the empirical equation and the correlations between the time-variant parameters and NDVI, the mean annual parameter ε is downscaled to monthly k and m. The results show that it has lower NSEs than these from model with time-variant k and m being calibrated through SCE-UA, while for several study catchments, it has higher NSEs than that of the model with constant parameters. The proposed method is feasible and provides a useful tool for temporal scaling of model parameter.

Multiscale analysis of river networks using the R package linbin

USGS Publications Warehouse

Welty, Ethan Z.; Torgersen, Christian E.; Brenkman, Samuel J.; Duda, Jeffrey J.; Armstrong, Jonathan B.

2015-01-01

Analytical tools are needed in riverine science and management to bridge the gap between GIS and statistical packages that were not designed for the directional and dendritic structure of streams. We introduce linbin, an R package developed for the analysis of riverscapes at multiple scales. With this software, riverine data on aquatic habitat and species distribution can be scaled and plotted automatically with respect to their position in the stream network or—in the case of temporal data—their position in time. The linbin package aggregates data into bins of different sizes as specified by the user. We provide case studies illustrating the use of the software for (1) exploring patterns at different scales by aggregating variables at a range of bin sizes, (2) comparing repeat observations by aggregating surveys into bins of common coverage, and (3) tailoring analysis to data with custom bin designs. Furthermore, we demonstrate the utility of linbin for summarizing patterns throughout an entire stream network, and we analyze the diel and seasonal movements of tagged fish past a stationary receiver to illustrate how linbin can be used with temporal data. In short, linbin enables more rapid analysis of complex data sets by fisheries managers and stream ecologists and can reveal underlying spatial and temporal patterns of fish distribution and habitat throughout a riverscape.

Visualization of the Eastern Renewable Generation Integration Study: Preprint

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

Gruchalla, Kenny; Novacheck, Joshua; Bloom, Aaron

The Eastern Renewable Generation Integration Study (ERGIS), explores the operational impacts of the wide spread adoption of wind and solar photovoltaics (PV) resources in the U.S. Eastern Interconnection and Quebec Interconnection (collectively, EI). In order to understand some of the economic and reliability challenges of managing hundreds of gigawatts of wind and PV generation, we developed state of the art tools, data, and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NREL's high-performance computing capabilities and new methodologies to model operations, we found that the EI, as simulated withmore » evolutionary change in 2026, could balance the variability and uncertainty of wind and PV at a 5-minute level under a variety of conditions. A large-scale display and a combination of multiple coordinated views and small multiples were used to visually analyze the four large highly multivariate scenarios with high spatial and temporal resolutions. state of the art tools, data, and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NRELs high-performance computing capabilities and new methodologies to model operations, we found that the EI, as simulated with evolutionary change in 2026, could balance the variability and uncertainty of wind and PV at a 5-minute level under a variety of conditions. A large-scale display and a combination of multiple coordinated views and small multiples were used to visually analyze the four large highly multivariate scenarios with high spatial and temporal resolutions.« less

The temporal spectrum of adult mosquito population fluctuations: conceptual and modeling implications.

PubMed

Jian, Yun; Silvestri, Sonia; Brown, Jeff; Hickman, Rick; Marani, Marco

2014-01-01

An improved understanding of mosquito population dynamics under natural environmental forcing requires adequate field observations spanning the full range of temporal scales over which mosquito abundance fluctuates in natural conditions. Here we analyze a 9-year daily time series of uninterrupted observations of adult mosquito abundance for multiple mosquito species in North Carolina to identify characteristic scales of temporal variability, the processes generating them, and the representativeness of observations at different sampling resolutions. We focus in particular on Aedes vexans and Culiseta melanura and, using a combination of spectral analysis and modeling, we find significant population fluctuations with characteristic periodicity between 2 days and several years. Population dynamical modelling suggests that the observed fast fluctuations scales (2 days-weeks) are importantly affected by a varying mosquito activity in response to rapid changes in meteorological conditions, a process neglected in most representations of mosquito population dynamics. We further suggest that the range of time scales over which adult mosquito population variability takes place can be divided into three main parts. At small time scales (indicatively 2 days-1 month) observed population fluctuations are mainly driven by behavioral responses to rapid changes in weather conditions. At intermediate scales (1 to several month) environmentally-forced fluctuations in generation times, mortality rates, and density dependence determine the population characteristic response times. At longer scales (annual to multi-annual) mosquito populations follow seasonal and inter-annual environmental changes. We conclude that observations of adult mosquito populations should be based on a sub-weekly sampling frequency and that predictive models of mosquito abundance must include behavioral dynamics to separate the effects of a varying mosquito activity from actual changes in the abundance of the underlying population.

Impact of playing American professional football on long-term brain function.

PubMed

Amen, Daniel G; Newberg, Andrew; Thatcher, Robert; Jin, Yi; Wu, Joseph; Keator, David; Willeumier, Kristen

2011-01-01

The authors recruited 100 active and former National Football League players, representing 27 teams and all positions. Players underwent a clinical history, brain SPECT imaging, qEEG, and multiple neuropsychological measures, including MicroCog. Relative to a healthy-comparison group, players showed global decreased perfusion, especially in the prefrontal, temporal, parietal, and occipital lobes, and cerebellar regions. Quantitative EEG findings were consistent, showing elevated slow waves in the frontal and temporal regions. Significant decreases from normal values were found in most neuropsychological tests. This is the first large-scale brain-imaging study to demonstrate significant differences consistent with a chronic brain trauma pattern in professional football players.

Influence of Temporal Context on Value in the Multiple-Chains and Successive-Encounters Procedures

ERIC Educational Resources Information Center

O'Daly, Matthew; Angulo, Samuel; Gipson, Cassandra; Fantino, Edmund

2006-01-01

This set of studies explored the influence of temporal context across multiple-chain and multiple-successive-encounters procedures. Following training with different temporal contexts, the value of stimuli sharing similar reinforcement schedules was assessed by presenting these stimuli in concurrent probes. The results for the multiple-chain…

Historical foundations and future directions in macrosystems ecology.

PubMed

Rose, Kevin C; Graves, Rose A; Hansen, Winslow D; Harvey, Brian J; Qiu, Jiangxiao; Wood, Stephen A; Ziter, Carly; Turner, Monica G

2017-02-01

Macrosystems ecology is an effort to understand ecological processes and interactions at the broadest spatial scales and has potential to help solve globally important social and ecological challenges. It is important to understand the intellectual legacies underpinning macrosystems ecology: How the subdiscipline fits within, builds upon, differs from and extends previous theories. We trace the rise of macrosystems ecology with respect to preceding theories and present a new hypothesis that integrates the multiple components of macrosystems theory. The spatio-temporal anthropogenic rescaling (STAR) hypothesis suggests that human activities are altering the scales of ecological processes, resulting in interactions at novel space-time scale combinations that are diverse and predictable. We articulate four predictions about how human actions are "expanding", "shrinking", "speeding up" and "slowing down" ecological processes and interactions, and thereby generating new scaling relationships for ecological patterns and processes. We provide examples of these rescaling processes and describe ecological consequences across terrestrial, freshwater and marine ecosystems. Rescaling depends in part on characteristics including connectivity, stability and heterogeneity. Our STAR hypothesis challenges traditional assumptions about how the spatial and temporal scales of processes and interactions operate in different types of ecosystems and provides a lens through which to understand macrosystem-scale environmental change. © 2016 John Wiley & Sons Ltd/CNRS.

Community males show multiple-perpetrator rape proclivity: development and preliminary validation of an interest scale.

PubMed

Alleyne, Emma; Gannon, Theresa A; Ó Ciardha, Caoilte; Wood, Jane L

2014-02-01

The literature on Multiple Perpetrator Rape (MPR) is scant; however, a significant proportion of sexual offending involves multiple perpetrators. In addition to the need for research with apprehended offenders of MPR, there is also a need to conduct research with members of the general public. Recent advances in the forensic literature have led to the development of self-report proclivity scales. These scales have enabled researchers to conduct evaluative studies sampling from members of the general public who may be perpetrators of sexual offenses and have remained undetected, or at highest risk of engaging in sexual offending. The current study describes the development and preliminary validation of the Multiple-Perpetrator Rape Interest Scale (M-PRIS), a vignette-based measure assessing community males' sexual arousal to MPR, behavioral propensity toward MPR and enjoyment of MPR. The findings show that the M-PRIS is a reliable measure of community males' sexual interest in MPR with high internal reliability and temporal stability. In a sample of university males we found that a large proportion (66%) did not emphatically reject an interest in MPR. We also found that rape-supportive cognitive distortions, antisocial attitudes, and high-risk sexual fantasies were predictors of sexual interest in MPR. We discuss these findings and the implications for further research employing proclivity measures referencing theory development and clinical practice.

Period Concatenation Underlies Interactions between Gamma and Beta Rhythms in Neocortex

PubMed Central

Roopun, Anita K.; Kramer, Mark A.; Carracedo, Lucy M.; Kaiser, Marcus; Davies, Ceri H.; Traub, Roger D.; Kopell, Nancy J.; Whittington, Miles A.

2008-01-01

The neocortex generates rhythmic electrical activity over a frequency range covering many decades. Specific cognitive and motor states are associated with oscillations in discrete frequency bands within this range, but it is not known whether interactions and transitions between distinct frequencies are of functional importance. When coexpressed rhythms have frequencies that differ by a factor of two or more interactions can be seen in terms of phase synchronization. Larger frequency differences can result in interactions in the form of nesting of faster frequencies within slower ones by a process of amplitude modulation. It is not known how coexpressed rhythms, whose frequencies differ by less than a factor of two may interact. Here we show that two frequencies (gamma – 40 Hz and beta2 – 25 Hz), coexpressed in superficial and deep cortical laminae with low temporal interaction, can combine to generate a third frequency (beta1 – 15 Hz) showing strong temporal interaction. The process occurs via period concatenation, with basic rhythm-generating microcircuits underlying gamma and beta2 rhythms forming the building blocks of the beta1 rhythm by a process of addition. The mean ratio of adjacent frequency components was a constant – approximately the golden mean – which served to both minimize temporal interactions, and permit multiple transitions, between frequencies. The resulting temporal landscape may provide a framework for multiplexing – parallel information processing on multiple temporal scales. PMID:18946516

Video repairing under variable illumination using cyclic motions.

PubMed

Jia, Jiaya; Tai, Yu-Wing; Wu, Tai-Pang; Tang, Chi-Keung

2006-05-01

This paper presents a complete system capable of synthesizing a large number of pixels that are missing due to occlusion or damage in an uncalibrated input video. These missing pixels may correspond to the static background or cyclic motions of the captured scene. Our system employs user-assisted video layer segmentation, while the main processing in video repair is fully automatic. The input video is first decomposed into the color and illumination videos. The necessary temporal consistency is maintained by tensor voting in the spatio-temporal domain. Missing colors and illumination of the background are synthesized by applying image repairing. Finally, the occluded motions are inferred by spatio-temporal alignment of collected samples at multiple scales. We experimented on our system with some difficult examples with variable illumination, where the capturing camera can be stationary or in motion.

Scalable Preconditioners for Structure Preserving Discretizations of Maxwell Equations in First Order Form

DOE PAGES

Phillips, Edward Geoffrey; Shadid, John N.; Cyr, Eric C.

2018-05-01

Here, we report multiple physical time-scales can arise in electromagnetic simulations when dissipative effects are introduced through boundary conditions, when currents follow external time-scales, and when material parameters vary spatially. In such scenarios, the time-scales of interest may be much slower than the fastest time-scales supported by the Maxwell equations, therefore making implicit time integration an efficient approach. The use of implicit temporal discretizations results in linear systems in which fast time-scales, which severely constrain the stability of an explicit method, can manifest as so-called stiff modes. This study proposes a new block preconditioner for structure preserving (also termed physicsmore » compatible) discretizations of the Maxwell equations in first order form. The intent of the preconditioner is to enable the efficient solution of multiple-time-scale Maxwell type systems. An additional benefit of the developed preconditioner is that it requires only a traditional multigrid method for its subsolves and compares well against alternative approaches that rely on specialized edge-based multigrid routines that may not be readily available. Lastly, results demonstrate parallel scalability at large electromagnetic wave CFL numbers on a variety of test problems.« less

Scalable Preconditioners for Structure Preserving Discretizations of Maxwell Equations in First Order Form

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

Phillips, Edward Geoffrey; Shadid, John N.; Cyr, Eric C.

Here, we report multiple physical time-scales can arise in electromagnetic simulations when dissipative effects are introduced through boundary conditions, when currents follow external time-scales, and when material parameters vary spatially. In such scenarios, the time-scales of interest may be much slower than the fastest time-scales supported by the Maxwell equations, therefore making implicit time integration an efficient approach. The use of implicit temporal discretizations results in linear systems in which fast time-scales, which severely constrain the stability of an explicit method, can manifest as so-called stiff modes. This study proposes a new block preconditioner for structure preserving (also termed physicsmore » compatible) discretizations of the Maxwell equations in first order form. The intent of the preconditioner is to enable the efficient solution of multiple-time-scale Maxwell type systems. An additional benefit of the developed preconditioner is that it requires only a traditional multigrid method for its subsolves and compares well against alternative approaches that rely on specialized edge-based multigrid routines that may not be readily available. Lastly, results demonstrate parallel scalability at large electromagnetic wave CFL numbers on a variety of test problems.« less

From single steps to mass migration: the problem of scale in the movement ecology of the Serengeti wildebeest.

PubMed

Torney, Colin J; Hopcraft, J Grant C; Morrison, Thomas A; Couzin, Iain D; Levin, Simon A

2018-05-19

A central question in ecology is how to link processes that occur over different scales. The daily interactions of individual organisms ultimately determine community dynamics, population fluctuations and the functioning of entire ecosystems. Observations of these multiscale ecological processes are constrained by various technological, biological or logistical issues, and there are often vast discrepancies between the scale at which observation is possible and the scale of the question of interest. Animal movement is characterized by processes that act over multiple spatial and temporal scales. Second-by-second decisions accumulate to produce annual movement patterns. Individuals influence, and are influenced by, collective movement decisions, which then govern the spatial distribution of populations and the connectivity of meta-populations. While the field of movement ecology is experiencing unprecedented growth in the availability of movement data, there remain challenges in integrating observations with questions of ecological interest. In this article, we present the major challenges of addressing these issues within the context of the Serengeti wildebeest migration, a keystone ecological phenomena that crosses multiple scales of space, time and biological complexity.This article is part of the theme issue 'Collective movement ecology'. © 2018 The Author(s).

Satellite Remote Sensing of Harmful Algal Blooms (HABs) and a Potential Synthesized Framework

PubMed Central

Shen, Li; Xu, Huiping; Guo, Xulin

2012-01-01

Harmful algal blooms (HABs) are severe ecological disasters threatening aquatic systems throughout the World, which necessitate scientific efforts in detecting and monitoring them. Compared with traditional in situ point observations, satellite remote sensing is considered as a promising technique for studying HABs due to its advantages of large-scale, real-time, and long-term monitoring. The present review summarizes the suitability of current satellite data sources and different algorithms for detecting HABs. It also discusses the spatial scale issue of HABs. Based on the major problems identified from previous literature, including the unsystematic understanding of HABs, the insufficient incorporation of satellite remote sensing, and a lack of multiple oceanographic explanations of the mechanisms causing HABs, this review also attempts to provide a comprehensive understanding of the complicated mechanism of HABs impacted by multiple oceanographic factors. A potential synthesized framework can be established by combining multiple accessible satellite remote sensing approaches including visual interpretation, spectra analysis, parameters retrieval and spatial-temporal pattern analysis. This framework aims to lead to a systematic and comprehensive monitoring of HABs based on satellite remote sensing from multiple oceanographic perspectives. PMID:22969372

Moments in Time

PubMed Central

Wittmann, Marc

2011-01-01

It has been suggested that perception and action can be understood as evolving in temporal epochs or sequential processing units. Successive events are fused into units forming a unitary experience or “psychological present.” Studies have identified several temporal integration levels on different time scales which are fundamental for our understanding of behavior and subjective experience. In recent literature concerning the philosophy and neuroscience of consciousness these separate temporal processing levels are not always precisely distinguished. Therefore, empirical evidence from psychophysics and neuropsychology on these distinct temporal processing levels is presented and discussed within philosophical conceptualizations of time experience. On an elementary level, one can identify a functional moment, a basic temporal building block of perception in the range of milliseconds that defines simultaneity and succession. Below a certain threshold temporal order is not perceived, individual events are processed as co-temporal. On a second level, an experienced moment, which is based on temporal integration of up to a few seconds, has been reported in many qualitatively different experiments in perception and action. It has been suggested that this segmental processing mechanism creates temporal windows that provide a logistical basis for conscious representation and the experience of nowness. On a third level of integration, continuity of experience is enabled by working memory in the range of multiple seconds allowing the maintenance of cognitive operations and emotional feelings, leading to mental presence, a temporal window of an individual’s experienced presence. PMID:22022310

Systems Biophysics of Gene Expression

PubMed Central

Vilar, Jose M.G.; Saiz, Leonor

2013-01-01

Gene expression is a process central to any form of life. It involves multiple temporal and functional scales that extend from specific protein-DNA interactions to the coordinated regulation of multiple genes in response to intracellular and extracellular changes. This diversity in scales poses fundamental challenges to the use of traditional approaches to fully understand even the simplest gene expression systems. Recent advances in computational systems biophysics have provided promising avenues to reliably integrate the molecular detail of biophysical process into the system behavior. Here, we review recent advances in the description of gene regulation as a system of biophysical processes that extend from specific protein-DNA interactions to the combinatorial assembly of nucleoprotein complexes. There is now basic mechanistic understanding on how promoters controlled by multiple, local and distal, DNA binding sites for transcription factors can actively control transcriptional noise, cell-to-cell variability, and other properties of gene regulation, including precision and flexibility of the transcriptional responses. PMID:23790365

Software Architecture for a Virtual Environment for Nano Scale Assembly (VENSA).

PubMed

Lee, Yong-Gu; Lyons, Kevin W; Feng, Shaw C

2004-01-01

A Virtual Environment (VE) uses multiple computer-generated media to let a user experience situations that are temporally and spatially prohibiting. The information flow between the user and the VE is bidirectional and the user can influence the environment. The software development of a VE requires orchestrating multiple peripherals and computers in a synchronized way in real time. Although a multitude of useful software components for VEs exists, many of these are packaged within a complex framework and can not be used separately. In this paper, an architecture is presented which is designed to let multiple frameworks work together while being shielded from the application program. This architecture, which is called the Virtual Environment for Nano Scale Assembly (VENSA), has been constructed for interfacing with an optical tweezers instrument for nanotechnology development. However, this approach can be generalized for most virtual environments. Through the use of VENSA, the programmer can rely on existing solutions and concentrate more on the application software design.

Software Architecture for a Virtual Environment for Nano Scale Assembly (VENSA)

PubMed Central

Lee, Yong-Gu; Lyons, Kevin W.; Feng, Shaw C.

2004-01-01

A Virtual Environment (VE) uses multiple computer-generated media to let a user experience situations that are temporally and spatially prohibiting. The information flow between the user and the VE is bidirectional and the user can influence the environment. The software development of a VE requires orchestrating multiple peripherals and computers in a synchronized way in real time. Although a multitude of useful software components for VEs exists, many of these are packaged within a complex framework and can not be used separately. In this paper, an architecture is presented which is designed to let multiple frameworks work together while being shielded from the application program. This architecture, which is called the Virtual Environment for Nano Scale Assembly (VENSA), has been constructed for interfacing with an optical tweezers instrument for nanotechnology development. However, this approach can be generalized for most virtual environments. Through the use of VENSA, the programmer can rely on existing solutions and concentrate more on the application software design. PMID:27366610

Wisconsin Card Sorting Test performance and impulsivity in patients with temporal lobe epilepsy: suicidal risk and suicide attempts.

PubMed

Garcia Espinosa, Arlety; Andrade Machado, René; Borges González, Susana; García González, María Eugenia; Pérez Montoto, Ariadna; Toledo Sotomayor, Guillermo

2010-01-01

The goal of the study described here was to determine if executive dysfunction and impulsivity are related to risk for suicide and suicide attempts in patients with temporal lobe epilepsy. Forty-two patients with temporal lobe epilepsy were recruited. A detailed medical history, neurological examination, serial EEGs, Mini-International Neuropsychiatric Interview, executive function, and MRI were assessed. Multiple regression analysis was carried out to examine predictive associations between clinical variables and Wisconsin Card Sorting Test measures. Patients' scores on the Risk for Suicide Scale (n=24) were greater than 7, which means they had the highest relative risk for suicide attempts. Family history of psychiatric disease, current major depressive episode, left temporal lobe epilepsy, and perseverative responses and total errors on the Wisconsin Card Sorting Test increased by 6.3 and 7.5 suicide risk and suicide attempts, respectively. Executive dysfunction (specifically perseverative responses and more total errors) contributed greatly to suicide risk. Executive performance has a major impact on suicide risk and suicide attempts in patients with temporal lobe epilepsy. 2009 Elsevier Inc. All rights reserved.

The influence of lexical statistics on temporal lobe cortical dynamics during spoken word listening

PubMed Central

Cibelli, Emily S.; Leonard, Matthew K.; Johnson, Keith; Chang, Edward F.

2015-01-01

Neural representations of words are thought to have a complex spatio-temporal cortical basis. It has been suggested that spoken word recognition is not a process of feed-forward computations from phonetic to lexical forms, but rather involves the online integration of bottom-up input with stored lexical knowledge. Using direct neural recordings from the temporal lobe, we examined cortical responses to words and pseudowords. We found that neural populations were not only sensitive to lexical status (real vs. pseudo), but also to cohort size (number of words matching the phonetic input at each time point) and cohort frequency (lexical frequency of those words). These lexical variables modulated neural activity from the posterior to anterior temporal lobe, and also dynamically as the stimuli unfolded on a millisecond time scale. Our findings indicate that word recognition is not purely modular, but relies on rapid and online integration of multiple sources of lexical knowledge. PMID:26072003

A rigorous statistical framework for spatio-temporal pollution prediction and estimation of its long-term impact on health.

PubMed

Lee, Duncan; Mukhopadhyay, Sabyasachi; Rushworth, Alastair; Sahu, Sujit K

2017-04-01

In the United Kingdom, air pollution is linked to around 40000 premature deaths each year, but estimating its health effects is challenging in a spatio-temporal study. The challenges include spatial misalignment between the pollution and disease data; uncertainty in the estimated pollution surface; and complex residual spatio-temporal autocorrelation in the disease data. This article develops a two-stage model that addresses these issues. The first stage is a spatio-temporal fusion model linking modeled and measured pollution data, while the second stage links these predictions to the disease data. The methodology is motivated by a new five-year study investigating the effects of multiple pollutants on respiratory hospitalizations in England between 2007 and 2011, using pollution and disease data relating to local and unitary authorities on a monthly time scale. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Multi-Scale Models for the Scale Interaction of Organized Tropical Convection

NASA Astrophysics Data System (ADS)

Yang, Qiu

Assessing the upscale impact of organized tropical convection from small spatial and temporal scales is a research imperative, not only for having a better understanding of the multi-scale structures of dynamical and convective fields in the tropics, but also for eventually helping in the design of new parameterization strategies to improve the next-generation global climate models. Here self-consistent multi-scale models are derived systematically by following the multi-scale asymptotic methods and used to describe the hierarchical structures of tropical atmospheric flows. The advantages of using these multi-scale models lie in isolating the essential components of multi-scale interaction and providing assessment of the upscale impact of the small-scale fluctuations onto the large-scale mean flow through eddy flux divergences of momentum and temperature in a transparent fashion. Specifically, this thesis includes three research projects about multi-scale interaction of organized tropical convection, involving tropical flows at different scaling regimes and utilizing different multi-scale models correspondingly. Inspired by the observed variability of tropical convection on multiple temporal scales, including daily and intraseasonal time scales, the goal of the first project is to assess the intraseasonal impact of the diurnal cycle on the planetary-scale circulation such as the Hadley cell. As an extension of the first project, the goal of the second project is to assess the intraseasonal impact of the diurnal cycle over the Maritime Continent on the Madden-Julian Oscillation. In the third project, the goals are to simulate the baroclinic aspects of the ITCZ breakdown and assess its upscale impact on the planetary-scale circulation over the eastern Pacific. These simple multi-scale models should be useful to understand the scale interaction of organized tropical convection and help improve the parameterization of unresolved processes in global climate models.

Long-term Spatial Distribution Patterns of Protozoa in Connected Microhabitats

NASA Astrophysics Data System (ADS)

Taghon, G. L.; Tuorto, S. J.

2016-02-01

Studies of microbial ecosystems usually assume habitat homogeneity. Recent research, however, indicates that habitat structure varies at millimeter scales and that this patchiness affects abundance and behavior of microbes. In this study, two species of ciliated protozoa were maintained, together, for multiple generations in microfluidic devices consisting of arrays of interconnected microhabitats with differing resource availability. The species differed in their population dynamics and tendency to disperse among microhabitats. Both species coexisted for over 45 days, and their coexistence likely resulted from habitat selection at millimeter scales. We demonstrate that it is not only possible, but imperative, that detailed ecological phenomena of microbial systems be studied at the relevant spatial and temporal scales.

Subsurface Monitoring of CO2 Sequestration - A Review and Look Forward

NASA Astrophysics Data System (ADS)

Daley, T. M.

2012-12-01

The injection of CO2 into subsurface formations is at least 50 years old with large-scale utilization of CO2 for enhanced oil recovery (CO2-EOR) beginning in the 1970s. Early monitoring efforts had limited measurements in available boreholes. With growing interest in CO2 sequestration beginning in the 1990's, along with growth in geophysical reservoir monitoring, small to mid-size sequestration monitoring projects began to appear. The overall goals of a subsurface monitoring plan are to provide measurement of CO2 induced changes in subsurface properties at a range of spatial and temporal scales. The range of spatial scales allows tracking of the location and saturation of the plume with varying detail, while finer temporal sampling (up to continuous) allows better understanding of dynamic processes (e.g. multi-phase flow) and constraining of reservoir models. Early monitoring of small scale pilots associated with CO2-EOR (e.g., the McElroy field and the Lost Hills field), developed many of the methodologies including tomographic imaging and multi-physics measurements. Large (reservoir) scale sequestration monitoring began with the Sleipner and Weyburn projects. Typically, large scale monitoring, such as 4D surface seismic, has limited temporal sampling due to costs. Smaller scale pilots can allow more frequent measurements as either individual time-lapse 'snapshots' or as continuous monitoring. Pilot monitoring examples include the Frio, Nagaoka and Otway pilots using repeated well logging, crosswell imaging, vertical seismic profiles and CASSM (continuous active-source seismic monitoring). For saline reservoir sequestration projects, there is typically integration of characterization and monitoring, since the sites are not pre-characterized resource developments (oil or gas), which reinforces the need for multi-scale measurements. As we move beyond pilot sites, we need to quantify CO2 plume and reservoir properties (e.g. pressure) over large scales, while still obtaining high resolution. Typically the high-resolution (spatial and temporal) tools are deployed in permanent or semi-permanent borehole installations, where special well design may be necessary, such as non-conductive casing for electrical surveys. Effective utilization of monitoring wells requires an approach of modular borehole monitoring (MBM) were multiple measurements can be made. An example is recent work at the Citronelle pilot injection site where an MBM package with seismic, fluid sampling and distributed fiber sensing was deployed. For future large scale sequestration monitoring, an adaptive borehole-monitoring program is proposed.

Extracting information in spike time patterns with wavelets and information theory.

PubMed

Lopes-dos-Santos, Vítor; Panzeri, Stefano; Kayser, Christoph; Diamond, Mathew E; Quian Quiroga, Rodrigo

2015-02-01

We present a new method to assess the information carried by temporal patterns in spike trains. The method first performs a wavelet decomposition of the spike trains, then uses Shannon information to select a subset of coefficients carrying information, and finally assesses timing information in terms of decoding performance: the ability to identify the presented stimuli from spike train patterns. We show that the method allows: 1) a robust assessment of the information carried by spike time patterns even when this is distributed across multiple time scales and time points; 2) an effective denoising of the raster plots that improves the estimate of stimulus tuning of spike trains; and 3) an assessment of the information carried by temporally coordinated spikes across neurons. Using simulated data, we demonstrate that the Wavelet-Information (WI) method performs better and is more robust to spike time-jitter, background noise, and sample size than well-established approaches, such as principal component analysis, direct estimates of information from digitized spike trains, or a metric-based method. Furthermore, when applied to real spike trains from monkey auditory cortex and from rat barrel cortex, the WI method allows extracting larger amounts of spike timing information. Importantly, the fact that the WI method incorporates multiple time scales makes it robust to the choice of partly arbitrary parameters such as temporal resolution, response window length, number of response features considered, and the number of available trials. These results highlight the potential of the proposed method for accurate and objective assessments of how spike timing encodes information. Copyright © 2015 the American Physiological Society.

A Trade-Off Study Revealing Nested Timescales of Constraint

PubMed Central

Wijnants, M. L.; Cox, R. F. A.; Hasselman, F.; Bosman, A. M. T.; Van Orden, G.

2012-01-01

This study investigates human performance in a cyclic Fitts task at three different scales of observation, either in the presence (difficult condition) or in the absence (easy condition) of a speed–accuracy trade-off. At the fastest scale, the harmonicity of the back and forth movements, which reflects the dissipation of mechanical energy, was measured within the timeframe of single trials. At an intermediate scale, speed and accuracy measures were determined over a trial. The slowest scale pertains to the temporal structure of movement variability, which evolves over multiple trials. In the difficult condition, reliable correlations across each of the measures corroborated a coupling of nested scales of performance. Participants who predominantly emphasized the speed-side of the trade-off (despite the instruction to be both fast and accurate) produced more harmonic movements and clearer 1/f scaling in the produced movement time series, but were less accurate and produced more random variability in the produced movement amplitudes (vice versa for more accurate participants). This implied that speed–accuracy trade-off was accompanied by a trade-off between temporal and spatial streams of 1/f scaling, as confirmed by entropy measures. In the easy condition, however, no trade-offs nor couplings among scales of performance were observed. Together, these results suggest that 1/f scaling is more than just a byproduct of cognition. These findings rather support the claim that interaction-dominant dynamics constitute a coordinative basis for goal-directed behavior. PMID:22654760

Fluid limit of nonintegrable continuous-time random walks in terms of fractional differential equations.

PubMed

Sánchez, R; Carreras, B A; van Milligen, B Ph

2005-01-01

The fluid limit of a recently introduced family of nonintegrable (nonlinear) continuous-time random walks is derived in terms of fractional differential equations. In this limit, it is shown that the formalism allows for the modeling of the interaction between multiple transport mechanisms with not only disparate spatial scales but also different temporal scales. For this reason, the resulting fluid equations may find application in the study of a large number of nonlinear multiscale transport problems, ranging from the study of self-organized criticality to the modeling of turbulent transport in fluids and plasmas.

OpenMP parallelization of a gridded SWAT (SWATG)

NASA Astrophysics Data System (ADS)

Zhang, Ying; Hou, Jinliang; Cao, Yongpan; Gu, Juan; Huang, Chunlin

2017-12-01

Large-scale, long-term and high spatial resolution simulation is a common issue in environmental modeling. A Gridded Hydrologic Response Unit (HRU)-based Soil and Water Assessment Tool (SWATG) that integrates grid modeling scheme with different spatial representations also presents such problems. The time-consuming problem affects applications of very high resolution large-scale watershed modeling. The OpenMP (Open Multi-Processing) parallel application interface is integrated with SWATG (called SWATGP) to accelerate grid modeling based on the HRU level. Such parallel implementation takes better advantage of the computational power of a shared memory computer system. We conducted two experiments at multiple temporal and spatial scales of hydrological modeling using SWATG and SWATGP on a high-end server. At 500-m resolution, SWATGP was found to be up to nine times faster than SWATG in modeling over a roughly 2000 km2 watershed with 1 CPU and a 15 thread configuration. The study results demonstrate that parallel models save considerable time relative to traditional sequential simulation runs. Parallel computations of environmental models are beneficial for model applications, especially at large spatial and temporal scales and at high resolutions. The proposed SWATGP model is thus a promising tool for large-scale and high-resolution water resources research and management in addition to offering data fusion and model coupling ability.

Integrating hydrologic and geophysical data to constrain coastal surficial aquifer processes at multiple spatial and temporal scales

USGS Publications Warehouse

Schultz, Gregory M.; Ruppel, Carolyn; Fulton, Patrick; Hyndman, David W.; Day-Lewis, Frederick D.; Singha, Kamini

2007-01-01

Since 1997, repeated, coincident geophysical surveys and extensive hydrologic studies in shallow monitoring wells have been used to study static and dynamic processes associated with surface water-groundwater interaction at a range of spatial scales at the estuarine and ocean boundaries of an undeveloped, permeable barrier island in the Georgia part of the U.S. South Atlantic Bight. Because geophysical and hydrologic data measure different parameters, at different resolution and precision, and over vastly different spatial scales, reconciling the coincident data or even combining complementary inversion, hydrogeochemcial analyses and well-based groundwater monitoring, and, in some cases, limited vegetation mapping to demonstrate the utility of an integrative, multidisciplinary approach for elucidating groundwater processes at spatial scales (tens to thousands of meters) that are often difficult to capture with traditional hydrologic approaches. The case studies highlight regional aquifer characteristics, varying degrees of lateral saltwater intrusion at estuarine boundaries, complex subsurface salinity gradients at the ocean boundary, and imaging of submarsh groundwater discharge and possible free convection in the pore waters of a clastic marsh. This study also documents the use of geophysical techniques for detecting temporal changes in groundwater salinity regimes under natural (not forced) gradients at intratidal to interannual (1998-200 Southeastern U.S.A. drought) time scales.

Developing a multi-stressor gradient for coral reefs | Science ...

EPA Pesticide Factsheets

Coral reefs are often found near coastal waters where multiple anthropogenic stressors co-occur at areas of human disturbance. Developing coral reef biocriteria under the U.S. Clean Water Act requires relationships between anthropogenic stressors and coral reef condition to be established. Developing stressor gradients presents challenges including: stressors which co-occur but operate at different or unknown spatial and temporal scales, inconsistent data availability measuring stressor levels, and unknown effects on exposed reef biota. We are developing a generalized stressor model using Puerto Rico as case study location, to represent the cumulative spatial/temporal co-occurrence of multiple anthropogenic stressors. Our approach builds on multi-stressor research in streams and rivers, and focuses on three high-priority stressors identified by coral reef experts: land-based sources of pollution (LBSP), global climate change (GCC) related temperature anomalies, and fishing pressure. Landscape development intensity index, based on land use/land cover data, estimates human impact in watersheds adjacent to coral reefs and is proxy for LBSP. NOAA’s retrospective daily thermal anomaly data is used to determine GCC thermal anomalies. Fishing pressure is modeled using gear-specific and fishery landings data. Stressor data was adjusted to a common scale or weighted for relative importance, buffered to account for diminished impact further from source, and compared wit

From global change to a butterfly flapping: biophysics and behaviour affect tropical climate change impacts.

PubMed

Bonebrake, Timothy C; Boggs, Carol L; Stamberger, Jeannie A; Deutsch, Curtis A; Ehrlich, Paul R

2014-10-22

Difficulty in characterizing the relationship between climatic variability and climate change vulnerability arises when we consider the multiple scales at which this variation occurs, be it temporal (from minute to annual) or spatial (from centimetres to kilometres). We studied populations of a single widely distributed butterfly species, Chlosyne lacinia, to examine the physiological, morphological, thermoregulatory and biophysical underpinnings of adaptation to tropical and temperate climates. Microclimatic and morphological data along with a biophysical model documented the importance of solar radiation in predicting butterfly body temperature. We also integrated the biophysics with a physiologically based insect fitness model to quantify the influence of solar radiation, morphology and behaviour on warming impact projections. While warming is projected to have some detrimental impacts on tropical ectotherms, fitness impacts in this study are not as negative as models that assume body and air temperature equivalence would suggest. We additionally show that behavioural thermoregulation can diminish direct warming impacts, though indirect thermoregulatory consequences could further complicate predictions. With these results, at multiple spatial and temporal scales, we show the importance of biophysics and behaviour for studying biodiversity consequences of global climate change, and stress that tropical climate change impacts are likely to be context-dependent. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

From global change to a butterfly flapping: biophysics and behaviour affect tropical climate change impacts

PubMed Central

Bonebrake, Timothy C.; Boggs, Carol L.; Stamberger, Jeannie A.; Deutsch, Curtis A.; Ehrlich, Paul R.

2014-01-01

Difficulty in characterizing the relationship between climatic variability and climate change vulnerability arises when we consider the multiple scales at which this variation occurs, be it temporal (from minute to annual) or spatial (from centimetres to kilometres). We studied populations of a single widely distributed butterfly species, Chlosyne lacinia, to examine the physiological, morphological, thermoregulatory and biophysical underpinnings of adaptation to tropical and temperate climates. Microclimatic and morphological data along with a biophysical model documented the importance of solar radiation in predicting butterfly body temperature. We also integrated the biophysics with a physiologically based insect fitness model to quantify the influence of solar radiation, morphology and behaviour on warming impact projections. While warming is projected to have some detrimental impacts on tropical ectotherms, fitness impacts in this study are not as negative as models that assume body and air temperature equivalence would suggest. We additionally show that behavioural thermoregulation can diminish direct warming impacts, though indirect thermoregulatory consequences could further complicate predictions. With these results, at multiple spatial and temporal scales, we show the importance of biophysics and behaviour for studying biodiversity consequences of global climate change, and stress that tropical climate change impacts are likely to be context-dependent. PMID:25165769

The Resilience of Coral Reefs Across a Hierarchy of Spatial and Temporal scales

NASA Astrophysics Data System (ADS)

Mumby, P. J.

2016-02-01

Resilience is a dynamical property of ecosystems that integrates processes of recovery, disturbance and internal dynamics, including reinforcing feedbacks. As such, resilience is a useful framework to consider how ecosystems respond to multiple drivers occurring over multiple scales. Many insights have emerged recently including the way in which stressors can combine synergistically to deplete resilience. However, while recent advances have mapped resilience across seascapes, most studies have not captured emergent spatial dependencies and dynamics across the seascape (e.g., independent box models are run across the seascape in isolation). Here, we explore the dynamics that emerge when the seascape is `wired up' using data on larval dispersal, thereby giving a fully spatially-realistic model. We then consider how dynamics change across even larger, biogeographic scales, posing the question, `are there robust and global "rules of thumb" for the resilience of a single ecosystem?'. Answers to this question will help managers tailor their interventions and research needs for their own jurisdiction.

High spatiotemporal resolution monitoring of hydrological function across degraded peatlands in the south west UK.

NASA Astrophysics Data System (ADS)

Ashe, Josie; Luscombe, David; Grand-Clement, Emilie; Gatis, Naomi; Anderson, Karen; Brazier, Richard

2014-05-01

The Exmoor/Dartmoor Mires Project is a peatland restoration programme focused on the geoclimatically marginal blanket bogs of South West England. In order to better understand the hydrological functioning of degraded/restored peatlands and support land management decisions across these uplands, this study is providing robust spatially distributed, hydrological monitoring at a high temporal resolution and in near real time. This paper presents the conceptual framework and experimental design for three hydrological monitoring arrays situated in headwater catchments dominated by eroding and drained blanket peatland. Over 250 individual measurements are collected at a high temporal resolution (15 minute time-step) via sensors integrated within a remote telemetry system. These are sent directly to a dedicated server over VHF and GPRS mobile networks. Sensors arrays are distributed at varying spatial scales throughout the studied catchments and record multiple parameters including: water table depth, channel flow, temperature, conductivity and pH measurements. A full suite of meteorological sensors and ten spatially distributed automatic flow based water samplers are also connected to the telemetry system and controlled remotely. This paper will highlight the challenges and solutions to obtaining these data in exceptionally remote and harsh field conditions over long (multi annual) temporal scales.

Pilates exercise training vs. physical therapy for improving walking and balance in people with multiple sclerosis: a randomized controlled trial.

PubMed

Kalron, Alon; Rosenblum, Uri; Frid, Lior; Achiron, Anat

2017-03-01

Evaluate the effects of a Pilates exercise programme on walking and balance in people with multiple sclerosis and compare this exercise approach to conventional physical therapy sessions. Randomized controlled trial. Multiple Sclerosis Center, Sheba Medical Center, Tel-Hashomer, Israel. Forty-five people with multiple sclerosis, 29 females, mean age (SD) was 43.2 (11.6) years; mean Expanded Disability Status Scale (S.D) was 4.3 (1.3). Participants received 12 weekly training sessions of either Pilates ( n=22) or standardized physical therapy ( n=23) in an outpatient basis. Spatio-temporal parameters of walking and posturography parameters during static stance. Functional tests included the Time Up and Go Test, 2 and 6-minute walk test, Functional Reach Test, Berg Balance Scale and the Four Square Step Test. In addition, the following self-report forms included the Multiple Sclerosis Walking Scale and Modified Fatigue Impact Scale. At the termination, both groups had significantly increased their walking speed ( P=0.021) and mean step length ( P=0.023). According to the 2-minute and 6-minute walking tests, both groups at the end of the intervention program had increased their walking speed. Mean (SD) increase in the Pilates and physical therapy groups were 39.1 (78.3) and 25.3 (67.2) meters, respectively. There was no effect of group X time in all instrumented and clinical balance and gait measures. Pilates is a possible treatment option for people with multiple sclerosis in order to improve their walking and balance capabilities. However, this approach does not have any significant advantage over standardized physical therapy.

Rank Dynamics of Word Usage at Multiple Scales

NASA Astrophysics Data System (ADS)

Morales, José A.; Colman, Ewan; Sánchez, Sergio; Sánchez-Puig, Fernanda; Pineda, Carlos; Iñiguez, Gerardo; Cocho, Germinal; Flores, Jorge; Gershenson, Carlos

2018-05-01

The recent dramatic increase in online data availability has allowed researchers to explore human culture with unprecedented detail, such as the growth and diversification of language. In particular, it provides statistical tools to explore whether word use is similar across languages, and if so, whether these generic features appear at different scales of language structure. Here we use the Google Books N-grams dataset to analyze the temporal evolution of word usage in several languages. We apply measures proposed recently to study rank dynamics, such as the diversity of N-grams in a given rank, the probability that an N-gram changes rank between successive time intervals, the rank entropy, and the rank complexity. Using different methods, results show that there are generic properties for different languages at different scales, such as a core of words necessary to minimally understand a language. We also propose a null model to explore the relevance of linguistic structure across multiple scales, concluding that N-gram statistics cannot be reduced to word statistics. We expect our results to be useful in improving text prediction algorithms, as well as in shedding light on the large-scale features of language use, beyond linguistic and cultural differences across human populations.

Gyrokinetic theory for particle and energy transport in fusion plasmas

NASA Astrophysics Data System (ADS)

Falessi, Matteo Valerio; Zonca, Fulvio

2018-03-01

A set of equations is derived describing the macroscopic transport of particles and energy in a thermonuclear plasma on the energy confinement time. The equations thus derived allow studying collisional and turbulent transport self-consistently, retaining the effect of magnetic field geometry without postulating any scale separation between the reference state and fluctuations. Previously, assuming scale separation, transport equations have been derived from kinetic equations by means of multiple-scale perturbation analysis and spatio-temporal averaging. In this work, the evolution equations for the moments of the distribution function are obtained following the standard approach; meanwhile, gyrokinetic theory has been used to explicitly express the fluctuation induced fluxes. In this way, equations for the transport of particles and energy up to the transport time scale can be derived using standard first order gyrokinetics.

Functional Topography of Human Auditory Cortex

PubMed Central

Rauschecker, Josef P.

2016-01-01

Functional and anatomical studies have clearly demonstrated that auditory cortex is populated by multiple subfields. However, functional characterization of those fields has been largely the domain of animal electrophysiology, limiting the extent to which human and animal research can inform each other. In this study, we used high-resolution functional magnetic resonance imaging to characterize human auditory cortical subfields using a variety of low-level acoustic features in the spectral and temporal domains. Specifically, we show that topographic gradients of frequency preference, or tonotopy, extend along two axes in human auditory cortex, thus reconciling historical accounts of a tonotopic axis oriented medial to lateral along Heschl's gyrus and more recent findings emphasizing tonotopic organization along the anterior–posterior axis. Contradictory findings regarding topographic organization according to temporal modulation rate in acoustic stimuli, or “periodotopy,” are also addressed. Although isolated subregions show a preference for high rates of amplitude-modulated white noise (AMWN) in our data, large-scale “periodotopic” organization was not found. Organization by AM rate was correlated with dominant pitch percepts in AMWN in many regions. In short, our data expose early auditory cortex chiefly as a frequency analyzer, and spectral frequency, as imposed by the sensory receptor surface in the cochlea, seems to be the dominant feature governing large-scale topographic organization across human auditory cortex. SIGNIFICANCE STATEMENT In this study, we examine the nature of topographic organization in human auditory cortex with fMRI. Topographic organization by spectral frequency (tonotopy) extended in two directions: medial to lateral, consistent with early neuroimaging studies, and anterior to posterior, consistent with more recent reports. Large-scale organization by rates of temporal modulation (periodotopy) was correlated with confounding spectral content of amplitude-modulated white-noise stimuli. Together, our results suggest that the organization of human auditory cortex is driven primarily by its response to spectral acoustic features, and large-scale periodotopy spanning across multiple regions is not supported. This fundamental information regarding the functional organization of early auditory cortex will inform our growing understanding of speech perception and the processing of other complex sounds. PMID:26818527

Exploring Google Earth Engine platform for big data processing: classification of multi-temporal satellite imagery for crop mapping

NASA Astrophysics Data System (ADS)

Shelestov, Andrii; Lavreniuk, Mykola; Kussul, Nataliia; Novikov, Alexei; Skakun, Sergii

2017-02-01

Many applied problems arising in agricultural monitoring and food security require reliable crop maps at national or global scale. Large scale crop mapping requires processing and management of large amount of heterogeneous satellite imagery acquired by various sensors that consequently leads to a “Big Data” problem. The main objective of this study is to explore efficiency of using the Google Earth Engine (GEE) platform when classifying multi-temporal satellite imagery with potential to apply the platform for a larger scale (e.g. country level) and multiple sensors (e.g. Landsat-8 and Sentinel-2). In particular, multiple state-of-the-art classifiers available in the GEE platform are compared to produce a high resolution (30 m) crop classification map for a large territory ( 28,100 km2 and 1.0 M ha of cropland). Though this study does not involve large volumes of data, it does address efficiency of the GEE platform to effectively execute complex workflows of satellite data processing required with large scale applications such as crop mapping. The study discusses strengths and weaknesses of classifiers, assesses accuracies that can be achieved with different classifiers for the Ukrainian landscape, and compares them to the benchmark classifier using a neural network approach that was developed in our previous studies. The study is carried out for the Joint Experiment of Crop Assessment and Monitoring (JECAM) test site in Ukraine covering the Kyiv region (North of Ukraine) in 2013. We found that Google Earth Engine (GEE) provides very good performance in terms of enabling access to the remote sensing products through the cloud platform and providing pre-processing; however, in terms of classification accuracy, the neural network based approach outperformed support vector machine (SVM), decision tree and random forest classifiers available in GEE.

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

USGS Publications Warehouse

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

2015-01-01

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

Climatic and Landscape Influences on Fire Regimes from 1984 to 2010 in the Western United States

PubMed Central

Liu, Zhihua; Wimberly, Michael C.

2015-01-01

An improved understanding of the relative influences of climatic and landscape controls on multiple fire regime components is needed to enhance our understanding of modern fire regimes and how they will respond to future environmental change. To address this need, we analyzed the spatio-temporal patterns of fire occurrence, size, and severity of large fires (> 405 ha) in the western United States from 1984–2010. We assessed the associations of these fire regime components with environmental variables, including short-term climate anomalies, vegetation type, topography, and human influences, using boosted regression tree analysis. Results showed that large fire occurrence, size, and severity each exhibited distinctive spatial and spatio-temporal patterns, which were controlled by different sets of climate and landscape factors. Antecedent climate anomalies had the strongest influences on fire occurrence, resulting in the highest spatial synchrony. In contrast, climatic variability had weaker influences on fire size and severity and vegetation types were the most important environmental determinants of these fire regime components. Topography had moderately strong effects on both fire occurrence and severity, and human influence variables were most strongly associated with fire size. These results suggest a potential for the emergence of novel fire regimes due to the responses of fire regime components to multiple drivers at different spatial and temporal scales. Next-generation approaches for projecting future fire regimes should incorporate indirect climate effects on vegetation type changes as well as other landscape effects on multiple components of fire regimes. PMID:26465959

An Experimental Investigation of Intermittent Flow and Strain Burst Scaling Behavior in LiF Crystals During Microcompression Testing (Preprint)

DTIC Science & Technology

2010-01-01

or in more general terms, as a result of dislocation nucleation, motion, multiplication, and interaction). Nonetheless, state-of-the-art simulation ...computational power, together with under-developed physics within the simulation codes (i.e. cross-slip, climb, crystal rotations and patterning to...name a few), prevent realistic dislocation simulations over temporal and spatial domains that are readily accessible by experimental methods [9, 10

How Many Grid Points are Required for Time Accurate Simulations Scheme Selection and Scale-Discriminant Stabilization

DTIC Science & Technology

2015-11-24

spatial concerns: ¤ how well are gradients captured? (resolution requirement) spatial/temporal concerns: ¤ dispersion and dissipation error...distribution is unlimited. Gradient Capture vs. Resolution: Single Mode FFT: Solution/Derivative: Convergence: f x( )= sin(x) with x∈[0,2π ] df dx...distribution is unlimited. Gradient Capture vs. Resolution: 
 Multiple Modes FFT: Solution/Derivative: Convergence: 6 __ CD02 __ CD04 __ CD06

Structured Multi-level Data Fusion and Modelling of Heterogeneous Environmental Data for Future Internet Applications

NASA Astrophysics Data System (ADS)

Sabeur, Zoheir; Chakravarthy, Ajay; Bashevoy, Maxim; Modafferi, Stefano

2013-04-01

The rapid increase in environmental observations which are conducted by Small to Medium Enterprise communities and volunteers using affordable in situ sensors at various scales, in addition to the more established observatories set up by environmental and space agencies using airborne and space-borne sensing technologies is generating serious amounts of BIG data at ever increasing speeds. Furthermore, the emergence of Future Internet technologies and the urgent requirements for the deployment of specific enablers for the delivery of processed environmental knowledge in real-time with advanced situation awareness to citizens has reached paramount importance. Specifically, it has become highly critical now to build and provide services which automate the aggregation of data from various sources, while surmounting the semantic gaps, conflicts and heterogeneity in data sources. The early stage aggregation of data will enable the pre-processing of data from multiple sources while reconciling the temporal gaps in measurement time series, and aligning their respective a-synchronicities. This low level type of data fusion process needs to be automated and chained to more advanced level of data fusion services specialising in observation forecasts at spaces where sensing is not deployed; or at time slices where sensing has not taken place yet. As a result, multi-level fusion services are required among the families of specific enablers for monitoring environments and spaces in the Future Internet. These have been intially deployed and piloted in the ongoing ENVIROFI project of the FI-PPP programme [1]. Automated fusion and modelling of in situ and remote sensing data has been set up and the experimentation successfully conducted using RBF networks for the spatial fusion of water quality parameters measurements from satellite and stationary buoys in the Irish Sea. The RBF networks method scales for the spatial data fusion of multiple types of observation sources. This important approach provides a strong basis for the delivery of environmental observations at desired spatial and temporal scales to multiple users with various needs of spatial and temporal resolutions. It has also led to building robust future internet specific enablers on data fusion, which can indeed be used for multiple usage areas above and beyond the environmental domains of the Future Internet. In this paper, data and processing workflow scenarios shall be described. The fucntionalities of the multi-level fusion services shall be demonstrated and made accessible to the wider communities of the Fututre Internet. [1] The Environmental Observation Web and its Service Applications within the Future Internet. ENVIROFI IP. FP7-2011-ICT-IF Pr.No: 284898 http://www.envirofi.eu/

A non-earthcentric approach to life detection

NASA Technical Reports Server (NTRS)

Conrad, P. G.; Nealson, K. H.

2001-01-01

The ultimate goal of a comprehensive life detection strategy is never to miss life when we encounter it. To accomplish this goal, we must define life in universal, that is, non-Earthcentric, measurable terms. Next, we must understand the nature of biosignatures observed from the measured parameters of life. And finally, we must have a clear idea of the end-member states for the search--what does life, past life, or no life look like (in terms of the measured parameters) at multiple spatial and temporal scales? If we can approach these problems both in the laboratory and in the field on Earth, then we have a chance of being able to detect life elsewhere in our solar system. What are the required limits of detection at each of those scales? What spatial, spectral, and temporal resolutions are necessary to detect life? These questions are actively being investigated in our group, and in this report, we present our strategy and approach to non-Earthcentric life detection.

Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis.

PubMed

Williams, Alex H; Kim, Tony Hyun; Wang, Forea; Vyas, Saurabh; Ryu, Stephen I; Shenoy, Krishna V; Schnitzer, Mark; Kolda, Tamara G; Ganguli, Surya

2018-06-27

Perceptions, thoughts, and actions unfold over millisecond timescales, while learned behaviors can require many days to mature. While recent experimental advances enable large-scale and long-term neural recordings with high temporal fidelity, it remains a formidable challenge to extract unbiased and interpretable descriptions of how rapid single-trial circuit dynamics change slowly over many trials to mediate learning. We demonstrate a simple tensor component analysis (TCA) can meet this challenge by extracting three interconnected, low-dimensional descriptions of neural data: neuron factors, reflecting cell assemblies; temporal factors, reflecting rapid circuit dynamics mediating perceptions, thoughts, and actions within each trial; and trial factors, describing both long-term learning and trial-to-trial changes in cognitive state. We demonstrate the broad applicability of TCA by revealing insights into diverse datasets derived from artificial neural networks, large-scale calcium imaging of rodent prefrontal cortex during maze navigation, and multielectrode recordings of macaque motor cortex during brain machine interface learning. Copyright © 2018 Elsevier Inc. All rights reserved.

FATE-HD: A spatially and temporally explicit integrated model for predicting vegetation structure and diversity at regional scale

PubMed Central

Isabelle, Boulangeat; Damien, Georges; Wilfried, Thuiller

2014-01-01

During the last decade, despite strenuous efforts to develop new models and compare different approaches, few conclusions have been drawn on their ability to provide robust biodiversity projections in an environmental change context. The recurring suggestions are that models should explicitly (i) include spatiotemporal dynamics; (ii) consider multiple species in interactions; and (iii) account for the processes shaping biodiversity distribution. This paper presents a biodiversity model (FATE-HD) that meets this challenge at regional scale by combining phenomenological and process-based approaches and using well-defined plant functional groups. FATE-HD has been tested and validated in a French National Park, demonstrating its ability to simulate vegetation dynamics, structure and diversity in response to disturbances and climate change. The analysis demonstrated the importance of considering biotic interactions, spatio-temporal dynamics, and disturbances in addition to abiotic drivers to simulate vegetation dynamics. The distribution of pioneer trees was particularly improved, as were all undergrowth functional groups. PMID:24214499

Multiple plasmonically induced transparency for chip-scale bandpass filters in metallic nanowaveguides

NASA Astrophysics Data System (ADS)

Lu, Hua; Yue, Zengqi; Zhao, Jianlin

2018-05-01

We propose and investigate a new kind of bandpass filters based on the plasmonically induced transparency (PIT) effect in a special metal-insulator-metal (MIM) waveguide system. The finite element method (FEM) simulations illustrate that the obvious PIT response can be generated in the metallic nanostructure with the stub and coupled cavities. The lineshape and position of the PIT peak are particularly dependent on the lengths of the stub and coupled cavities, the waveguide width, as well as the coupling distance between the stub and coupled cavities. The numerical simulations are in accordance with the results obtained by the temporal coupled-mode theory. The multi-peak PIT effect can be achieved by integrating multiple coupled cavities into the plasmonic waveguide. This PIT response contributes to the flexible realization of chip-scale multi-channel bandpass filters, which could find crucial applications in highly integrated optical circuits for signal processing.

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

NASA Astrophysics Data System (ADS)

Price, Aaron; Lee, H.

2010-01-01

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

Environmental factors controlling forest evapotranspiration and surface conductance on a multi-temporal scale in growing seasons of a Siberian larch forest

NASA Astrophysics Data System (ADS)

Yoshida, Megumi; Ohta, Takeshi; Kotani, Ayumi; Maximov, Trofim

2010-12-01

SummaryThe water and energy fluxes in forests fluctuate on different temporal scales, reflecting the impact of environmental factors. We examined the temporal fluctuation of the turbulent fluxes, surface conductance ( Gs), and four environmental factors (photosynthetic photon flux density [ Q], vapour pressure deficit [ D], air temperature [ T], and volumetric soil water content [ θ]) in a Siberian larch forest, using wavelet power spectra. The responses of the latent heat flux ( λE) and Gs to the environmental factors were analysed using the wavelet scale-wise correlation coefficient (SWCC) on multiple temporal scales. The observation site is characterised by underlying permafrost and a relatively short growing season. Analysis was conducted from May to September in each of 8 years during 1998-2007. The relationships between Gs and the environmental factors were evaluated with restrictive functions of a Jarvis-type surface conductance model because Gs usually has non-linear relationships to ambient factors. According to the power spectra of each factor, the largest variation was seen on a diurnal timescale for λE, the sensible heat flux ( H), Gs, and Q, whereas D and T fluctuated from diurnal to inter-seasonal timescales, and θ varied significantly over periods longer than the inter-seasonal timescales. The SWCC indicated that λE and Gs respond differently to the same ambient factors due to their respective processes; namely, λE is affected by both atmospheric demand and land surface regulation, whereas Gs is affected only by the latter. λE correlated well with Q at all timescales, as well as with D and T on intra-seasonal to interannual scales and with θ on inter-seasonal to interannual timescales. The SWCC of Gs and Q showed two peaks, on diurnal and inter-seasonal to interannual timescales, reflecting the physiological processes of plants, and D affected Gs only on an intra-seasonal timescale, which is related to meteorological changes. T and θ regulated Gs only on inter-seasonal to interannual scales. These SWCC results for D and θ roughly match previous findings in Siberia. The SWCC also suggested that the recent extremely high soil water has damaged the ecosystem of the eastern Siberian forest. Neither λE nor Gs followed the high θ in the last few years, although the richer soil moisture enhanced them on a long-term temporal scale under the usual soil moisture condition in Siberia.

Effects of land use and seasonality on stream water quality in a small tropical catchment: The headwater of Córrego Água Limpa, São Paulo (Brazil).

PubMed

Rodrigues, Valdemir; Estrany, Joan; Ranzini, Mauricio; de Cicco, Valdir; Martín-Benito, José Mª Tarjuelo; Hedo, Javier; Lucas-Borja, Manuel E

2018-05-01

Stream water quality is controlled by the interaction of natural and anthropogenic factors over a range of temporal and spatial scales. Among these anthropogenic factors, land cover changes at catchment scale can affect stream water quality. This work aims to evaluate the influence of land use and seasonality on stream water quality in a representative tropical headwater catchment named as Córrego Água Limpa (Sao Paulo, Brasil), which is highly influenced by intensive agricultural activities and urban areas. Two systematic sampling approach campaigns were implemented with six sampling points along the stream of the headwater catchment to evaluate water quality during the rainy and dry seasons. Three replicates were collected at each sampling point in 2011. Electrical conductivity, nitrates, nitrites, sodium superoxide, Chemical Oxygen Demand (DQO), colour, turbidity, suspended solids, soluble solids and total solids were measured. Water quality parameters differed among sampling points, being lower at the headwater sampling point (0m above sea level), and then progressively higher until the last downstream sampling point (2500m above sea level). For the dry season, the mean discharge was 39.5ls -1 (from April to September) whereas 113.0ls -1 were averaged during the rainy season (from October to March). In addition, significant temporal and spatial differences were observed (P<0.05) for the fourteen parameters during the rainy and dry period. The study enhance significant relationships among land use and water quality and its temporal effect, showing seasonal differences between the land use and water quality connection, highlighting the importance of multiple spatial and temporal scales for understanding the impacts of human activities on catchment ecosystem services. Copyright © 2017 Elsevier B.V. All rights reserved.

Future climate risk from compound events

NASA Astrophysics Data System (ADS)

Zscheischler, Jakob; Westra, Seth; van den Hurk, Bart J. J. M.; Seneviratne, Sonia I.; Ward, Philip J.; Pitman, Andy; AghaKouchak, Amir; Bresch, David N.; Leonard, Michael; Wahl, Thomas; Zhang, Xuebin

2018-06-01

Floods, wildfires, heatwaves and droughts often result from a combination of interacting physical processes across multiple spatial and temporal scales. The combination of processes (climate drivers and hazards) leading to a significant impact is referred to as a `compound event'. Traditional risk assessment methods typically only consider one driver and/or hazard at a time, potentially leading to underestimation of risk, as the processes that cause extreme events often interact and are spatially and/or temporally dependent. Here we show how a better understanding of compound events may improve projections of potential high-impact events, and can provide a bridge between climate scientists, engineers, social scientists, impact modellers and decision-makers, who need to work closely together to understand these complex events.

Multilayer network modeling of integrated biological systems. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

NASA Astrophysics Data System (ADS)

De Domenico, Manlio

2018-03-01

Biological systems, from a cell to the human brain, are inherently complex. A powerful representation of such systems, described by an intricate web of relationships across multiple scales, is provided by complex networks. Recently, several studies are highlighting how simple networks - obtained by aggregating or neglecting temporal or categorical description of biological data - are not able to account for the richness of information characterizing biological systems. More complex models, namely multilayer networks, are needed to account for interdependencies, often varying across time, of biological interacting units within a cell, a tissue or parts of an organism.

Understanding Pitch Perception as a Hierarchical Process with Top-Down Modulation

PubMed Central

Balaguer-Ballester, Emili; Clark, Nicholas R.; Coath, Martin; Krumbholz, Katrin; Denham, Susan L.

2009-01-01

Pitch is one of the most important features of natural sounds, underlying the perception of melody in music and prosody in speech. However, the temporal dynamics of pitch processing are still poorly understood. Previous studies suggest that the auditory system uses a wide range of time scales to integrate pitch-related information and that the effective integration time is both task- and stimulus-dependent. None of the existing models of pitch processing can account for such task- and stimulus-dependent variations in processing time scales. This study presents an idealized neurocomputational model, which provides a unified account of the multiple time scales observed in pitch perception. The model is evaluated using a range of perceptual studies, which have not previously been accounted for by a single model, and new results from a neurophysiological experiment. In contrast to other approaches, the current model contains a hierarchy of integration stages and uses feedback to adapt the effective time scales of processing at each stage in response to changes in the input stimulus. The model has features in common with a hierarchical generative process and suggests a key role for efferent connections from central to sub-cortical areas in controlling the temporal dynamics of pitch processing. PMID:19266015

Decrease in gamma-band activity tracks sequence learning

PubMed Central

Madhavan, Radhika; Millman, Daniel; Tang, Hanlin; Crone, Nathan E.; Lenz, Fredrick A.; Tierney, Travis S.; Madsen, Joseph R.; Kreiman, Gabriel; Anderson, William S.

2015-01-01

Learning novel sequences constitutes an example of declarative memory formation, involving conscious recall of temporal events. Performance in sequence learning tasks improves with repetition and involves forming temporal associations over scales of seconds to minutes. To further understand the neural circuits underlying declarative sequence learning over trials, we tracked changes in intracranial field potentials (IFPs) recorded from 1142 electrodes implanted throughout temporal and frontal cortical areas in 14 human subjects, while they learned the temporal-order of multiple sequences of images over trials through repeated recall. We observed an increase in power in the gamma frequency band (30–100 Hz) in the recall phase, particularly in areas within the temporal lobe including the parahippocampal gyrus. The degree of this gamma power enhancement decreased over trials with improved sequence recall. Modulation of gamma power was directly correlated with the improvement in recall performance. When presenting new sequences, gamma power was reset to high values and decreased again after learning. These observations suggest that signals in the gamma frequency band may play a more prominent role during the early steps of the learning process rather than during the maintenance of memory traces. PMID:25653598

Evaluating Hierarchical Structure in Music Annotations

PubMed Central

McFee, Brian; Nieto, Oriol; Farbood, Morwaread M.; Bello, Juan Pablo

2017-01-01

Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for “flat” descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement. PMID:28824514

Multi-Scale Modeling in Morphogenesis: A Critical Analysis of the Cellular Potts Model

PubMed Central

Voss-Böhme, Anja

2012-01-01

Cellular Potts models (CPMs) are used as a modeling framework to elucidate mechanisms of biological development. They allow a spatial resolution below the cellular scale and are applied particularly when problems are studied where multiple spatial and temporal scales are involved. Despite the increasing usage of CPMs in theoretical biology, this model class has received little attention from mathematical theory. To narrow this gap, the CPMs are subjected to a theoretical study here. It is asked to which extent the updating rules establish an appropriate dynamical model of intercellular interactions and what the principal behavior at different time scales characterizes. It is shown that the longtime behavior of a CPM is degenerate in the sense that the cells consecutively die out, independent of the specific interdependence structure that characterizes the model. While CPMs are naturally defined on finite, spatially bounded lattices, possible extensions to spatially unbounded systems are explored to assess to which extent spatio-temporal limit procedures can be applied to describe the emergent behavior at the tissue scale. To elucidate the mechanistic structure of CPMs, the model class is integrated into a general multiscale framework. It is shown that the central role of the surface fluctuations, which subsume several cellular and intercellular factors, entails substantial limitations for a CPM's exploitation both as a mechanistic and as a phenomenological model. PMID:22984409

Scales of snow depth variability in high elevation rangeland sagebrush

NASA Astrophysics Data System (ADS)

Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.

2017-09-01

In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.

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

PubMed

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

2018-08-01

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

Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

PubMed Central

Mathur, Rohit; Xing, Jia; Gilliam, Robert; Sarwar, Golam; Hogrefe, Christian; Pleim, Jonathan; Pouliot, George; Roselle, Shawn; Spero, Tanya L.; Wong, David C.; Young, Jeffrey

2018-01-01

The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modelled processes were examined and enhanced to suitably represent the extended space and time scales for such applications. Hemispheric scale simulations with CMAQ and the Weather Research and Forecasting (WRF) model are performed for multiple years. Model capabilities for a range of applications including episodic long-range pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution-climate interactions are evaluated through detailed comparison with available surface, aloft, and remotely sensed observations. The expansion of CMAQ to simulate the hemispheric scales provides a framework to examine interactions between atmospheric processes occurring at various spatial and temporal scales with physical, chemical, and dynamical consistency. PMID:29681922

Preliminary validation of the Spanish version of the Multiple Stimulus Types Ambiguity Tolerance Scale (MSTAT-II).

PubMed

Arquero, José L; McLain, David L

2010-05-01

Despite widespread interest in ambiguity tolerance and other information-related individual differences, existing measures are conceptually dispersed and psychometrically weak. This paper presents the Spanish version of MSTAT-II, a short, stimulus-oriented, and psychometrically improved measure of an individual's orientation toward ambiguous stimuli. Results obtained reveal adequate reliability, validity, and temporal stability. These results support the use of MSTAT-II as an adequate measure of ambiguity tolerance.

Spatiotemporal Variation of Arctic Nearshore Fish Communities in Barrow, AK

NASA Astrophysics Data System (ADS)

Boswell, K. M.; Barton, M. B.; Lemoine, N. P.; Heintz, R.; Vollenweider, J.; Norcross, B.; Sousa, L.

2016-02-01

Climate change, oil and gas development, and increased transportation opportunities associated with retreating sea ice cover are likely to affect the processes underlying community development. Unfortunately, there is a paucity of information that prohibits establishing a baseline from which to examine biological and ecological changes. To address these concerns, we developed an intensive field sampling program using weekly beach seining for the six weeks following land-fast ice break-up during the summers of 2013-2015 (183 beach seine hauls totaling 37,303 fish) in three distinct water masses near Pt. Barrow, Alaska to examine how fish communities develop in the Arctic nearshore. Preliminary analyses indicate that inter-annual variability in temperature and salinity influence species composition observed in late summer, but it is unclear which factors operate on smaller temporal scales. We applied multivariate variance partitioning to quantify variation in community structure on multiple spatial and temporal scales during the summer season and identified several physicochemical parameters as important spatiotemporal drivers in structuring nearshore fish communities. Understanding how these drivers affect nearshore communities on the seasonal scale is an integral step to predict how these ecologically important ecosystems may shift in the face of Arctic climate change and continued development.

OMFIT Tokamak Profile Data Fitting and Physics Analysis

DOE PAGES

Logan, N. C.; Grierson, B. A.; Haskey, S. R.; ...

2018-01-22

Here, One Modeling Framework for Integrated Tasks (OMFIT) has been used to develop a consistent tool for interfacing with, mapping, visualizing, and fitting tokamak profile measurements. OMFIT is used to integrate the many diverse diagnostics on multiple tokamak devices into a regular data structure, consistently applying spatial and temporal treatments to each channel of data. Tokamak data are fundamentally time dependent and are treated so from the start, with front-loaded and logic-based manipulations such as filtering based on the identification of edge-localized modes (ELMs) that commonly scatter data. Fitting is general in its approach, and tailorable in its application inmore » order to address physics constraints and handle the multiple spatial and temporal scales involved. Although community standard one-dimensional fitting is supported, including scale length–fitting and fitting polynomial-exponential blends to capture the H-mode pedestal, OMFITprofiles includes two-dimensional (2-D) fitting using bivariate splines or radial basis functions. These 2-D fits produce regular evolutions in time, removing jitter that has historically been smoothed ad hoc in transport applications. Profiles interface directly with a wide variety of models within the OMFIT framework, providing the inputs for TRANSP, kinetic-EFIT 2-D equilibrium, and GPEC three-dimensional equilibrium calculations. he OMFITprofiles tool’s rapid and comprehensive analysis of dynamic plasma profiles thus provides the critical link between raw tokamak data and simulations necessary for physics understanding.« less

OMFIT Tokamak Profile Data Fitting and Physics Analysis

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

Logan, N. C.; Grierson, B. A.; Haskey, S. R.

Here, One Modeling Framework for Integrated Tasks (OMFIT) has been used to develop a consistent tool for interfacing with, mapping, visualizing, and fitting tokamak profile measurements. OMFIT is used to integrate the many diverse diagnostics on multiple tokamak devices into a regular data structure, consistently applying spatial and temporal treatments to each channel of data. Tokamak data are fundamentally time dependent and are treated so from the start, with front-loaded and logic-based manipulations such as filtering based on the identification of edge-localized modes (ELMs) that commonly scatter data. Fitting is general in its approach, and tailorable in its application inmore » order to address physics constraints and handle the multiple spatial and temporal scales involved. Although community standard one-dimensional fitting is supported, including scale length–fitting and fitting polynomial-exponential blends to capture the H-mode pedestal, OMFITprofiles includes two-dimensional (2-D) fitting using bivariate splines or radial basis functions. These 2-D fits produce regular evolutions in time, removing jitter that has historically been smoothed ad hoc in transport applications. Profiles interface directly with a wide variety of models within the OMFIT framework, providing the inputs for TRANSP, kinetic-EFIT 2-D equilibrium, and GPEC three-dimensional equilibrium calculations. he OMFITprofiles tool’s rapid and comprehensive analysis of dynamic plasma profiles thus provides the critical link between raw tokamak data and simulations necessary for physics understanding.« less

Identifying intervals of temporally invariant field-aligned currents from Swarm: Assessing the validity of single-spacecraft methods

NASA Astrophysics Data System (ADS)

Forsyth, C.; Rae, I. J.; Mann, I. R.; Pakhotin, I. P.

2017-03-01

Field-aligned currents (FACs) are a fundamental component of coupled solar wind-magnetosphere-ionosphere. By assuming that FACs can be approximated by stationary infinite current sheets that do not change on the spacecraft crossing time, single-spacecraft magnetic field measurements can be used to estimate the currents flowing in space. By combining data from multiple spacecraft on similar orbits, these stationarity assumptions can be tested. In this technical report, we present a new technique that combines cross correlation and linear fitting of multiple spacecraft measurements to determine the reliability of the FAC estimates. We show that this technique can identify those intervals in which the currents estimated from single-spacecraft techniques are both well correlated and have similar amplitudes, thus meeting the spatial and temporal stationarity requirements. Using data from European Space Agency's Swarm mission from 2014 to 2015, we show that larger-scale currents (>450 km) are well correlated and have a one-to-one fit up to 50% of the time, whereas small-scale (<50 km) currents show similar amplitudes only 1% of the time despite there being a good correlation 18% of the time. It is thus imperative to examine both the correlation and amplitude of the calculated FACs in order to assess both the validity of the underlying assumptions and hence ultimately the reliability of such single-spacecraft FAC estimates.

Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2016-10-02

Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) tomore » compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.« less

Interests of long-term hydrogeological observatories for characterizing and modelling heterogeneous groundwater systems at multiple temporal and spatial scales: the example of Ploemeur, a crystalline rock aquifer (Brittany).

NASA Astrophysics Data System (ADS)

Bour, Olivier; Longuervergne, Laurent; Le Borgne, Tanguy; Lavenant, Nicolas; de Dreuzy, Jean-Raynald; Schuite, Jonathan; Labasque, Thierry; Aquilina, Luc; Davy, Philippe

2017-04-01

Characterizing groundwater flows and surface interactions in heterogeneous groundwater systems such as crystalline fractured rock is often extremely complex. In particular, hydraulic properties are highly variable while groundwater chemical properties may vary both in space and time, especially due to the impact of groundwater abstraction. Here, we show the interest of hydrological observatories and long-term monitoring for characterizing hydrological processes occurring in a crystalline rock aquifer. We present results from the site of Ploemeur (French Brittany) that belongs to the network of hydrogeological sites H+ and the research infrastructure OZCAR, and where interdisciplinary and integrated research at multiple temporal and spatial scales has been developed for almost twenty years. This outstandingly heterogeneous crystalline rock aquifer is also used for groundwater supply since 1991. In particular, we show how cross-borehole flowmeter tests, pumping tests and a frequency domain analysis of groundwater levels allow quantifying the hydraulic properties of the aquifer at different scales. In addition, groundwater temperature evolution was used as an excellent tracer for characterizing groundwater flow. At the site scale, measurements of ground surface deformation through long-base tiltmeters provide robust estimates of aquifer storage and allow identifying the active structures, including those acting during recharge process. Finally, a numerical model of the watershed scale that combines hydraulic data and groundwater ages confirms the geometry of this complex aquifer and the consistency of the different datasets. In parallel, this hydrological observatory is also used for developing hydrogeophysical methods and to characterize groundwater transport and biogeochemical reactivity in the sub-surface. The Ploemeur hydrogeological observatory is a good example of the interest of focusing research activities on a site during long-term as it provides a thorough understanding of both hydrological and biogeochemical processes that can be extended to many heterogeneous aquifers.

Kite aerial photography for low-cost, ultra-high spatial resolution multi-spectral mapping of intertidal landscapes.

PubMed

Bryson, Mitch; Johnson-Roberson, Matthew; Murphy, Richard J; Bongiorno, Daniel

2013-01-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.

Remote Sensing, GIS, and Vector-Borne Disease

NASA Technical Reports Server (NTRS)

Beck, Louisa R.

2001-01-01

The concept of global climate change encompasses more than merely an alteration in temperature; it also includes spatial and temporal covariations in precipitation and humidity, and more frequent occurrence of extreme weather events. The impact of these variations, which can occur at a variety of temporal and spatial scales, could have a direct impact on disease transmission through their environmental consequences for pathogen, vector, and host survival, as well as indirectly through human demographic and behavioral responses. New and future sensor systems will allow scientists to investigate the relationships between climate change and environmental risk factors at multiple spatial, temporal and spectral scales. Higher spatial resolution will provide better opportunities for mapping urban features previously only possible with high resolution aerial photography. These opportunities include housing quality (e.g., Chagas'disease, leishmaniasis) and urban mosquito habitats (e.g., dengue fever, filariasis, LaCrosse encephalitis). There are or will be many new sensors that have higher spectral resolution, enabling scientists to acquire more information about parameters such as soil moisture, soil type, better vegetation discrimination, and ocean color, to name a few. Although soil moisture content is now detectable using Landsat, the new thermal, shortwave infrared, and radar sensors will be able to provide this information at a variety of scales not achievable using Landsat. Soil moisture could become a key component in transmission risk models for Lyme disease (tick survival), helminthiases (worm habitat), malaria (vector-breeding habitat), and schistosomiasis (snail habitat).

Kite Aerial Photography for Low-Cost, Ultra-high Spatial Resolution Multi-Spectral Mapping of Intertidal Landscapes

PubMed Central

Bryson, Mitch; Johnson-Roberson, Matthew; Murphy, Richard J.; Bongiorno, Daniel

2013-01-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales. PMID:24069206

Effect of spatial and temporal scales on habitat suitability modeling: A case study of Ommastrephes bartramii in the northwest pacific ocean

NASA Astrophysics Data System (ADS)

Gong, Caixia; Chen, Xinjun; Gao, Feng; Tian, Siquan

2014-12-01

Temporal and spatial scales play important roles in fishery ecology, and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution. The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling, with the western stock of winter-spring cohort of neon flying squid ( Ommastrephes bartramii) in the northwest Pacific Ocean as an example. In this study, the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature (SST) from remote sensing during August to October of 2003-2008 were used. We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales (0.5°, 1° and 2°), four longitude scales (0.5°, 1°, 2° and 4°), and three temporal scales (week, fortnight, and month). The coefficients of variation (CV) of the weekly, biweekly and monthly suitability index (SI) were compared to determine which temporal and spatial scales of SI model are more precise. This study shows that the optimal temporal and spatial scales with the lowest CV are month, and 0.5° latitude and 0.5° longitude for O. bartramii in the northwest Pacific Ocean. This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts. We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.

A Hierarchical and Dynamic Seascape Framework for Scaling and Comparing Ocean Biodiversity Observations

NASA Astrophysics Data System (ADS)

Kavanaugh, M.; Muller-Karger, F. E.; Montes, E.; Santora, J. A.; Chavez, F.; Messié, M.; Doney, S. C.

2016-02-01

The pelagic ocean is a complex system in which physical, chemical and biological processes interact to shape patterns on multiple spatial and temporal scales and levels of ecological organization. Monitoring and management of marine seascapes must consider a hierarchical and dynamic mosaic, where the boundaries, extent, and location of features change with time. As part of a Marine Biodiversity Observing Network demonstration project, we conducted a multiscale classification of dynamic coastal seascapes in the northeastern Pacific and Gulf of Mexico using multivariate satellite and modeled data. Synoptic patterns were validated using mooring and ship-based observations that spanned multiple trophic levels and were collected as part of several long-term monitoring programs, including the Monterey Bay and Florida Keys National Marine Sanctuaries. Seascape extent and habitat diversity varied as a function of both seasonal and interannual forcing. We discuss the patterns of in situ observations in the context of seascape dynamics and the effect on rarefaction, spatial patchiness, and tracking and comparing ecosystems through time. A seascape framework presents an effective means to translate local biodiversity measurements to broader spatiotemporal scales, scales relevant for modeling the effects of global change and enabling whole-ecosystem management in the dynamic ocean.

Patients with Alzheimer disease with multiple microbleeds: relation with cerebrospinal fluid biomarkers and cognition.

PubMed

Goos, Jeroen D C; Kester, M I; Barkhof, Frederik; Klein, Martin; Blankenstein, Marinus A; Scheltens, Philip; van der Flier, Wiesje M

2009-11-01

Microbleeds (MBs) are commonly observed in Alzheimer disease. A minority of patients has multiple MBs. We aimed to investigate associations of multiple MBs in Alzheimer disease with clinical and MRI characteristics and cerebrospinal fluid biomarkers. Patients with Alzheimer disease with multiple (>or=8) MBs on T2*-weighted MRI were matched for age, sex, and field strength with patients with Alzheimer disease without MBs on a 1:2 basis. We included 21 patients with multiple MBs (73+/-7 years, 33% female) and 42 patients without MBs (72+/-7 years, 38% female). Mini-Mental State Examination was used to assess dementia severity. Cognitive functions were assessed using neuropsychological tests. Medial temporal lobe atrophy (0 to 4), global cortical atrophy (0 to 3), and white matter hyperintensities (0 to 30) were assessed using visual rating scales. In a subset, apolipoprotein E genotype and cerebrospinal fluid amyloid beta 1-42, total tau and tau phosphorylated at threonine 181 were determined. Patients with multiple MBs performed worse on Mini-Mental State Examination (multiple MB: 17+/-7; no MB: 22+/-4, P<0.05) despite similar disease duration. Atrophy was not related to presence of MBs, but patients with multiple MBs had more white matter hyperintensities (multiple MB: 8.8+/-4.8; no MB: 3.2+/-3.6, P<0.05). Adjusted for age, sex, white matter hyperintensities, and medial temporal lobe atrophy, the multiple MB group additionally performed worse on Visual Association Test object naming and animal fluency. Patients with multiple MBs had lower cerebrospinal fluid amyloid beta 1-42 levels (307+/-61) than patients without MBs (505+/-201, P<0.05). Adjusted for the same covariates, total tau, and tau phosphorylated at threonine 181 were higher in the multiple MB group. Microbleeds are associated with the clinical manifestation and biochemical hallmarks of Alzheimer disease, suggesting possible involvement of MBs in the pathogenesis of Alzheimer disease.

Summary of types of radiation belt electron precipitation observed by BARREL

NASA Astrophysics Data System (ADS)

Halford, Alexa

2016-07-01

The Balloon Array for Relativistic Radiation belt Electron Loss (BARREL) was able to infer precipitation of radiation belt electrons on multiple time scales and due to multiple loss mechanisms. One storm will be specifically highlighted which occurred on 26 January 2013 when a solar wind shock hit the Earth. Although MeV electrons were observed to be lost due to an EMIC wave event [Zhang et al in prep], and multiple periods of electron loss during substorms were observed [Rae et al submitted JGR, Mann et al in prep], we will consider an event period where loss associated with multiple time scales, and thus possibly different loss mechanisms was observed from 1000 - 1200 UT on 26 January 2013. At about 1005 UT on 26 January 2013 an injection of radiation belt electrons followed by drift echoes for energies of ˜80 - 400 keV. BARREL observed X-rays with energies less than 180 keV associated with multiple temporal structures during the drift echo event period. The Van Allen Probes were at similar L-values but upwards of 2 hours away in MLT. Upper band chorus and ULF waves were observed during the event period. Throughout the beginning of the event period, microbursts were clearly observed. During this time lower band chorus waves as well as time domain structures were observed at Van Allen Probe A located upwards of 2 hours away in MLT. This large difference in MLT meant that neither potential loss mechanism was able to be clearly associated with the microbursts. As the lower band chorus and time domain structures were observed to recede, the microbursts were also observed to subside. ULF time scale modulation of the X-rays was also observed throughout most of the event period. We will examine if the ULF waves are the cause of the precipitation themselves, or are modulating the loss of particles from a secondary loss mechanism [Brito et al 2015 JGR, Rae et al Submitted JGR]. Although the 100s ms and ULF time scales are clearly observed, there is an ˜20 minute overarching structure observed in the X-rays at BARREL. This longer time scale appears to match the drift period of the ˜300 keV electrons observed by the Van Allen probes. However the inferred energy of the precipitating electrons is ˜150 keV. It is unclear what may be causing the ˜20 minute structure in the X-rays. At the time of writing this abstract, it is unclear if the drifting of the 300 keV electrons is related to the precipitation of the lower energy electrons (< 180 keV) or if it is just coincidence that they have the same temporal structure.

Comparing different methods for determining forest evapotranspiration and its components at multiple temporal scales.

PubMed

Tie, Qiang; Hu, Hongchang; Tian, Fuqiang; Holbrook, N Michele

2018-08-15

Accurately estimating forest evapotranspiration and its components is of great importance for hydrology, ecology, and meteorology. In this study, a comparison of methods for determining forest evapotranspiration and its components at annual, monthly, daily, and diurnal scales was conducted based on in situ measurements in the subhumid mountainous forest of North China. The goal of the study was to evaluate the accuracies and reliabilities of the different methods. The results indicate the following: (1) The sap flow upscaling procedure, taking into account diversities in forest types and tree species, produced component-based forest evapotranspiration estimate that agreed with eddy covariance-based estimate at the temporal scales of year, month, and day, while soil water budget-based forest evapotranspiration estimate was also qualitatively consistent with eddy covariance-based estimate at the daily scale; (2) At the annual scale, catchment water balance-based forest evapotranspiration estimate was significantly higher than eddy covariance-based estimate, which might probably result from non-negligible subsurface runoff caused by the widely distributed regolith and fractured bedrock under the ground; (3) At the sub-daily scale, the diurnal course of sap flow based-canopy transpiration estimate lagged significantly behind eddy covariance-based forest evapotranspiration estimate, which might physiologically be due to stem water storage and stem hydraulic conductivity. The results in this region may have much referential significance for forest evapotranspiration estimation and method evaluation in regions with similar environmental conditions. Copyright © 2018 Elsevier B.V. All rights reserved.

Creation of Synthetic Surface Temperature and Precipitation Ensembles Through A Computationally Efficient, Mixed Method Approach

NASA Astrophysics Data System (ADS)

Hartin, C.; Lynch, C.; Kravitz, B.; Link, R. P.; Bond-Lamberty, B. P.

2017-12-01

Typically, uncertainty quantification of internal variability relies on large ensembles of climate model runs under multiple forcing scenarios or perturbations in a parameter space. Computationally efficient, standard pattern scaling techniques only generate one realization and do not capture the complicated dynamics of the climate system (i.e., stochastic variations with a frequency-domain structure). In this study, we generate large ensembles of climate data with spatially and temporally coherent variability across a subselection of Coupled Model Intercomparison Project Phase 5 (CMIP5) models. First, for each CMIP5 model we apply a pattern emulation approach to derive the model response to external forcing. We take all the spatial and temporal variability that isn't explained by the emulator and decompose it into non-physically based structures through use of empirical orthogonal functions (EOFs). Then, we perform a Fourier decomposition of the EOF projection coefficients to capture the input fields' temporal autocorrelation so that our new emulated patterns reproduce the proper timescales of climate response and "memory" in the climate system. Through this 3-step process, we derive computationally efficient climate projections consistent with CMIP5 model trends and modes of variability, which address a number of deficiencies inherent in the ability of pattern scaling to reproduce complex climate model behavior.

Great Basin Integrated Landscape Monitoring Pilot Summary Report

USGS Publications Warehouse

Finn, Sean P.; Kitchell, Kate; Baer, Lori Anne; Bedford, David R.; Brooks, Matthew L.; Flint, Alan L.; Flint, Lorraine E.; Matchett, J.R.; Mathie, Amy; Miller, David M.; Pilliod, David S.; Torregrosa, Alicia; Woodward, Andrea

2010-01-01

The Great Basin Integrated Landscape Monitoring Pilot project (GBILM) was one of four regional pilots to implement the U.S. Geological Survey (USGS) Science Thrust on Integrated Landscape Monitoring (ILM) whose goal was to observe, understand, and predict landscape change and its implications on natural resources at multiple spatial and temporal scales and address priority natural resource management and policy issues. The Great Basin is undergoing rapid environmental change stemming from interactions among global climate trends, increasing human populations, expanding and accelerating land and water uses, invasive species, and altered fire regimes. GBLIM tested concepts and developed tools to store and analyze monitoring data, understand change at multiple scales, and forecast landscape change. The GBILM endeavored to develop and test a landscape-level monitoring approach in the Great Basin that integrates USGS disciplines, addresses priority management questions, catalogs and uses existing monitoring data, evaluates change at multiple scales, and contributes to development of regional monitoring strategies. GBILM functioned as an integrative team from 2005 to 2010, producing more than 35 science and data management products that addressed pressing ecosystem drivers and resource management agency needs in the region. This report summarizes the approaches and methods of this interdisciplinary effort, identifies and describes the products generated, and provides lessons learned during the project.

Soil organic matter dynamics and CO2 fluxes in relation to landscape scale processes: linking process understanding to regional scale carbon mass-balances

NASA Astrophysics Data System (ADS)

Van Oost, Kristof; Nadeu, Elisabet; Wiaux, François; Wang, Zhengang; Stevens, François; Vanclooster, Marnik; Tran, Anh; Bogaert, Patrick; Doetterl, Sebastian; Lambot, Sébastien; Van wesemael, Bas

2014-05-01

In this paper, we synthesize the main outcomes of a collaborative project (2009-2014) initiated at the UCL (Belgium). The main objective of the project was to increase our understanding of soil organic matter dynamics in complex landscapes and use this to improve predictions of regional scale soil carbon balances. In a first phase, the project characterized the emergent spatial variability in soil organic matter storage and key soil properties at the regional scale. Based on the integration of remote sensing, geomorphological and soil analysis techniques, we quantified the temporal and spatial variability of soil carbon stock and pool distribution at the local and regional scales. This work showed a linkage between lateral fluxes of C in relation with sediment transport and the spatial variation in carbon storage at multiple spatial scales. In a second phase, the project focused on characterizing key controlling factors and process interactions at the catena scale. In-situ experiments of soil CO2 respiration showed that the soil carbon response at the catena scale was spatially heterogeneous and was mainly controlled by the catenary variation of soil physical attributes (soil moisture, temperature, C quality). The hillslope scale characterization relied on advanced hydrogeophysical techniques such as GPR (Ground Penetrating Radar), EMI (Electromagnetic induction), ERT (Electrical Resistivity Tomography), and geophysical inversion and data mining tools. Finally, we report on the integration of these insights into a coupled and spatially explicit model and its application. Simulations showed that C stocks and redistribution of mass and energy fluxes are closely coupled, they induce structured spatial and temporal patterns with non negligible attached uncertainties. We discuss the main outcomes of these activities in relation to sink-source behavior and relevance of erosion processes for larger-scale C budgets.

Spatio-temporal scaling of channels in braided streams.

Treesearch

A.G. Hunt; G.E. Grant; V.K. Gupta

2006-01-01

The spatio-temporal scaling relationship for individual channels in braided streams is shown to be identical to the spatio-temporal scaling associated with constant Froude number, e.g., Fr = l. A means to derive this relationship is developed from a new theory of sediment transport. The mechanism by which the Fr = l condition apparently governs the scaling seems to...

Scaling properties of Arctic sea ice deformation in high-resolution viscous-plastic sea ice models and satellite observations

NASA Astrophysics Data System (ADS)

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2017-04-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very high grid resolution can resolve leads and deformation rates that are localised along Linear Kinematic Features (LKF). In a 1-km pan-Arctic sea ice-ocean simulation, the small scale sea-ice deformations in the Central Arctic are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS). A new coupled scaling analysis for data on Eulerian grids determines the spatial and the temporal scaling as well as the coupling between temporal and spatial scales. The spatial scaling of the modelled sea ice deformation implies multi-fractality. The spatial scaling is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling and its coupling to temporal scales with satellite observations and models with the modern elasto-brittle rheology challenges previous results with VP models at coarse resolution where no such scaling was found. The temporal scaling analysis, however, shows that the VP model does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Dynamics of particulate organic matter composition in coastal systems: Forcing of spatio-temporal variability at multi-systems scale

NASA Astrophysics Data System (ADS)

Liénart, Camilla; Savoye, Nicolas; David, Valérie; Ramond, Pierre; Rodriguez Tress, Paco; Hanquiez, Vincent; Marieu, Vincent; Aubert, Fabien; Aubin, Sébastien; Bichon, Sabrina; Boinet, Christophe; Bourasseau, Line; Bozec, Yann; Bréret, Martine; Breton, Elsa; Caparros, Jocelyne; Cariou, Thierry; Claquin, Pascal; Conan, Pascal; Corre, Anne-Marie; Costes, Laurence; Crouvoisier, Muriel; Del Amo, Yolanda; Derriennic, Hervé; Dindinaud, François; Duran, Robert; Durozier, Maïa; Devesa, Jérémy; Ferreira, Sophie; Feunteun, Eric; Garcia, Nicole; Geslin, Sandrine; Grossteffan, Emilie; Gueux, Aurore; Guillaudeau, Julien; Guillou, Gaël; Jolly, Orianne; Lachaussée, Nicolas; Lafont, Michel; Lagadec, Véronique; Lamoureux, Jézabel; Lauga, Béatrice; Lebreton, Benoît; Lecuyer, Eric; Lehodey, Jean-Paul; Leroux, Cédric; L'Helguen, Stéphane; Macé, Eric; Maria, Eric; Mousseau, Laure; Nowaczyk, Antoine; Pineau, Philippe; Petit, Franck; Pujo-Pay, Mireille; Raimbault, Patrick; Rimmelin-Maury, Peggy; Rouaud, Vanessa; Sauriau, Pierre-Guy; Sultan, Emmanuelle; Susperregui, Nicolas

2018-03-01

In costal systems, particulate organic matter (POM) results from a multiplicity of sources having their respective dynamics in terms of production, decomposition, transport and burial. The POM pool experiences thus considerable spatial and temporal variability. In order to better understand this variability, the present study employs statistical multivariate analyses to investigate links between POM composition and environmental forcings for a panel of twelve coastal systems distributed along the three maritime regions of France and monitored weekly to monthly for 1 to 8 years. At multi-system scale, two main gradients of POC composition have been identified: a 'Continent-Ocean' gradient associated with hydrodynamics, sedimentary dynamics and depth of the water column, and a gradient of trophic status related to nutrient availability. At local scale, seasonality of POC composition appears to be station-specific but still related to part of the above-mentioned forcings. A typology of systems was established by coupling spatial and temporal variability of POC composition. Four groups were highlighted: (1) the estuarine stations where POC composition is dominated by terrestrial POM and driven by hydrodynamics and sedimentary processes, (2) the oligotrophic systems, characterized by the contribution of diazotrophs due to low nutrient availability, and the marine meso/eutroph systems whose POC composition is (3) either deeply dominated by phytoplankton or (4) dominated by phytoplankton but where the contribution of continental and benthic POC is not negligible and is driven by hydrodynamics, sedimentary processes and the height of the water column. Finally, the present study provides several insights into the different forcings to POM composition and dynamics in temperate coastal systems at local and multi-system scales. This work also presents a methodological approach that establishes statistical links between forcings and POM composition, helping to gain more objectively insight of forcings.

Scaling Coastal Ecosystems to Oceanographic and Climatic Drivers: Making Sense of Community Variation on Rocky Shores Using the Comparative-Experimental Approach in Upwelling and Downwelling Systems

NASA Astrophysics Data System (ADS)

Menge, B. A.; Gouhier, T.; Chan, F.; Hacker, S.; Menge, D.; Nielsen, K. J.

2016-02-01

Ecology focuses increasingly on the issue of matching spatial and temporal scales responsible for ecosystem pattern and dynamics. Benthic coastal communities traditionally were studied at local scales using mostly short-term research, while environmental (oceanographic, climatic) drivers were investigated at large scales (e.g., regional to oceanic, mostly offshore) using combined snapshot and monitoring (time series) research. The comparative-experimental approach combines local-scale studies at multiple sites spanning large-scale environmental gradients in combination with monitoring of inner shelf oceanographic conditions including upwelling/downwelling wind forcing and their consequences (e.g., temperature), and inputs of subsidies (larvae, phytoplankton, detritus). Temporal scale varies depending on the questions, but can extend from years to decades. We discuss two examples of rocky intertidal ecosystem dynamics, one at a regional scale (California Current System, CCS) and one at an interhemispheric scale. In the upwelling-dominated CCS, 52% and 32% of the variance in local community structure (functional group abundances at 13 sites across 725 km) was explained by external factors (ecological subsidies, oceanographic conditions, geographic location), and species interactions, respectively. The interhemispheric study tested the intermittent upwelling hypothesis (IUH), which predicts that key ecological processes will vary unimodally along a persistent downwelling to persistent upwelling gradient. Using 14-22 sites, unimodal relationships between ecological subsidies (phytoplankton, prey recruitment), prey responses (barnacle colonization, mussel growth) and species interactions (competition rate, predation rate and effect) and the Bakun upwelling index calculated at each site accounted for 50% of the variance. Hence, external factors can account for about half of locally-expressed community structure and dynamics.

The correlation between symptomatic fatigue to definite measures of gait in people with multiple sclerosis.

PubMed

Kalron, Alon

2016-02-01

There is a general consensus relating to the multidimensional aspects of fatigue in people with multiple sclerosis (PwMS), however, the exact impact of this symptom on gait is not fully understood. Our primary aim was to examine the relationship between definite parameters of gait with self-reported symptomatic fatigue in PwMS according to their level of neurological impairment. Spatio-temporal parameters of gait were studied using an electronic walkway. The Multiple Sclerosis Walking Scale (MSWS-12) questionnaire, a patient-rated measure of walking ability was collected. The Modified Fatigue Impact Scale (MFIS) questionnaire was used to determine the level of symptomatic fatigue. One hundred and one PwMS (61 women) were included in the study analysis. Subjects were divided into mild and moderate neurological impaired groups. Fatigue was correlated with 5 (out of 14) spatiotemporal parameters. However, correlation scores were all <0.35, thus considered as weak correlations. In the mild group, the double support period was the only variable positively correlated to fatigue (Spearman's rho=0.28, P=0.05). In the moderate group, step and stride length were solely negatively correlated to fatigue (Spearman's rho=0.32, P=0.03). In contrast to the definite gait parameters, the MSWS-12 self-questionnaire was moderately positively correlated to the level of fatigue. Scores for the total, mild and moderate groups were 0.54, 0.57 and 0.51; P<0.01, respectively. The present results indicate that modifications in spatio-temporal parameters of gait are not closely related to symptomatic fatigue in PwMS. On the contrary, the self-reported MSWS-12 questionnaire is predisposed to level of fatigue in PwMS. Copyright © 2015 Elsevier B.V. All rights reserved.

[Neural Mechanisms Underlying the Processing of Temporal Information in Episodic Memory and Its Disturbance].

PubMed

Iwata, Saeko; Tsukiura, Takashi

2017-11-01

Episodic memory is defined as memory for personally experienced events, and includes memory content and contextual information of time and space. Previous neuroimaging and neuropsychological studies have demonstrated three possible roles of the temporal context in episodic memory. First, temporal information contributes to the arrangement of temporal order for sequential events in episodic memory, and this process is involved in the lateral prefrontal cortex. The second possible role of temporal information in episodic memory is the segregation between memories of multiple events, which are segregated by cues of different time information. The role of segregation is associated with the orbitofrontal regions including the orbitofrontal cortex and basal forebrain region. Third, temporal information in episodic memory plays an important role in the integration of multiple components into a coherent episodic memory, in which episodic components in the different modalities are combined by temporal information as an index. The role of integration is mediated by the medial temporal lobe including the hippocampus and parahippocampal gyrus. Thus, temporal information in episodic memory could be represented in multiple stages, which are involved in a network of the lateral prefrontal, orbitofrontal, and medial temporal lobe regions.

Seeking Temporal Predictability in Speech: Comparing Statistical Approaches on 18 World Languages.

PubMed

Jadoul, Yannick; Ravignani, Andrea; Thompson, Bill; Filippi, Piera; de Boer, Bart

2016-01-01

Temporal regularities in speech, such as interdependencies in the timing of speech events, are thought to scaffold early acquisition of the building blocks in speech. By providing on-line clues to the location and duration of upcoming syllables, temporal structure may aid segmentation and clustering of continuous speech into separable units. This hypothesis tacitly assumes that learners exploit predictability in the temporal structure of speech. Existing measures of speech timing tend to focus on first-order regularities among adjacent units, and are overly sensitive to idiosyncrasies in the data they describe. Here, we compare several statistical methods on a sample of 18 languages, testing whether syllable occurrence is predictable over time. Rather than looking for differences between languages, we aim to find across languages (using clearly defined acoustic, rather than orthographic, measures), temporal predictability in the speech signal which could be exploited by a language learner. First, we analyse distributional regularities using two novel techniques: a Bayesian ideal learner analysis, and a simple distributional measure. Second, we model higher-order temporal structure-regularities arising in an ordered series of syllable timings-testing the hypothesis that non-adjacent temporal structures may explain the gap between subjectively-perceived temporal regularities, and the absence of universally-accepted lower-order objective measures. Together, our analyses provide limited evidence for predictability at different time scales, though higher-order predictability is difficult to reliably infer. We conclude that temporal predictability in speech may well arise from a combination of individually weak perceptual cues at multiple structural levels, but is challenging to pinpoint.

Seeking Temporal Predictability in Speech: Comparing Statistical Approaches on 18 World Languages

PubMed Central

Jadoul, Yannick; Ravignani, Andrea; Thompson, Bill; Filippi, Piera; de Boer, Bart

2016-01-01

Temporal regularities in speech, such as interdependencies in the timing of speech events, are thought to scaffold early acquisition of the building blocks in speech. By providing on-line clues to the location and duration of upcoming syllables, temporal structure may aid segmentation and clustering of continuous speech into separable units. This hypothesis tacitly assumes that learners exploit predictability in the temporal structure of speech. Existing measures of speech timing tend to focus on first-order regularities among adjacent units, and are overly sensitive to idiosyncrasies in the data they describe. Here, we compare several statistical methods on a sample of 18 languages, testing whether syllable occurrence is predictable over time. Rather than looking for differences between languages, we aim to find across languages (using clearly defined acoustic, rather than orthographic, measures), temporal predictability in the speech signal which could be exploited by a language learner. First, we analyse distributional regularities using two novel techniques: a Bayesian ideal learner analysis, and a simple distributional measure. Second, we model higher-order temporal structure—regularities arising in an ordered series of syllable timings—testing the hypothesis that non-adjacent temporal structures may explain the gap between subjectively-perceived temporal regularities, and the absence of universally-accepted lower-order objective measures. Together, our analyses provide limited evidence for predictability at different time scales, though higher-order predictability is difficult to reliably infer. We conclude that temporal predictability in speech may well arise from a combination of individually weak perceptual cues at multiple structural levels, but is challenging to pinpoint. PMID:27994544

Structural Controllability and Controlling Centrality of Temporal Networks

PubMed Central

Pan, Yujian; Li, Xiang

2014-01-01

Temporal networks are such networks where nodes and interactions may appear and disappear at various time scales. With the evidence of ubiquity of temporal networks in our economy, nature and society, it's urgent and significant to focus on its structural controllability as well as the corresponding characteristics, which nowadays is still an untouched topic. We develop graphic tools to study the structural controllability as well as its characteristics, identifying the intrinsic mechanism of the ability of individuals in controlling a dynamic and large-scale temporal network. Classifying temporal trees of a temporal network into different types, we give (both upper and lower) analytical bounds of the controlling centrality, which are verified by numerical simulations of both artificial and empirical temporal networks. We find that the positive relationship between aggregated degree and controlling centrality as well as the scale-free distribution of node's controlling centrality are virtually independent of the time scale and types of datasets, meaning the inherent robustness and heterogeneity of the controlling centrality of nodes within temporal networks. PMID:24747676

Coupling Poisson rectangular pulse and multiplicative microcanonical random cascade models to generate sub-daily precipitation timeseries

NASA Astrophysics Data System (ADS)

Pohle, Ina; Niebisch, Michael; Müller, Hannes; Schümberg, Sabine; Zha, Tingting; Maurer, Thomas; Hinz, Christoph

2018-07-01

To simulate the impacts of within-storm rainfall variabilities on fast hydrological processes, long precipitation time series with high temporal resolution are required. Due to limited availability of observed data such time series are typically obtained from stochastic models. However, most existing rainfall models are limited in their ability to conserve rainfall event statistics which are relevant for hydrological processes. Poisson rectangular pulse models are widely applied to generate long time series of alternating precipitation events durations and mean intensities as well as interstorm period durations. Multiplicative microcanonical random cascade (MRC) models are used to disaggregate precipitation time series from coarse to fine temporal resolution. To overcome the inconsistencies between the temporal structure of the Poisson rectangular pulse model and the MRC model, we developed a new coupling approach by introducing two modifications to the MRC model. These modifications comprise (a) a modified cascade model ("constrained cascade") which preserves the event durations generated by the Poisson rectangular model by constraining the first and last interval of a precipitation event to contain precipitation and (b) continuous sigmoid functions of the multiplicative weights to consider the scale-dependency in the disaggregation of precipitation events of different durations. The constrained cascade model was evaluated in its ability to disaggregate observed precipitation events in comparison to existing MRC models. For that, we used a 20-year record of hourly precipitation at six stations across Germany. The constrained cascade model showed a pronounced better agreement with the observed data in terms of both the temporal pattern of the precipitation time series (e.g. the dry and wet spell durations and autocorrelations) and event characteristics (e.g. intra-event intermittency and intensity fluctuation within events). The constrained cascade model also slightly outperformed the other MRC models with respect to the intensity-frequency relationship. To assess the performance of the coupled Poisson rectangular pulse and constrained cascade model, precipitation events were stochastically generated by the Poisson rectangular pulse model and then disaggregated by the constrained cascade model. We found that the coupled model performs satisfactorily in terms of the temporal pattern of the precipitation time series, event characteristics and the intensity-frequency relationship.

A Constellation of CubeSat InSAR Sensors for Rapid-Revisit Surface Deformation Studies

NASA Astrophysics Data System (ADS)

Wye, L.; Lee, S.; Yun, S. H.; Zebker, H. A.; Stock, J. D.; Wicks, C. W., Jr.; Doe, R.

2016-12-01

The 2007 NRC Decadal Survey for Earth Sciences highlights three major Earth surface deformation themes: 1) solid-earth hazards and dynamics; 2) human health and security; and 3) land-use change, ecosystem dynamics and biodiversity. Space-based interferometric synthetic aperture radar (InSAR) is a key change detection tool for addressing these themes. Here, we describe the mission and radar payload design for a constellation of S-band InSAR sensors specifically designed to provide the global, high temporal resolution, sub-cm level deformation accuracy needed to address some of the major Earth system goals. InSAR observations with high temporal resolution are needed to properly monitor certain nonlinearly time-varying features (e.g., unstable volcanoes, active fault lines, and heavily-used groundwater or hydrocarbon reservoirs). Good temporal coverage is also needed to reduce atmospheric artifacts by allowing multiple acquisitions to be averaged together, since each individual SAR measurement is corrupted by up to several cm of atmospheric noise. A single InSAR platform is limited in how often it can observe a given scene without sacrificing global spatial coverage. Multiple InSAR platforms provide the spatial-temporal flexibility required to maximize the science return. However, building and launching multiple InSAR platforms is cost-prohibitive for traditional satellites. SRI International (SRI) and our collaborators are working to exploit developments in nanosatellite technology, in particular the emergence of the CubeSat standard, to provide high-cadence InSAR capabilities in an affordable package. The CubeSat Imaging Radar for Earth Science (CIRES) subsystem, a prototype SAR elec­tronics package developed by SRI with support from a 2014 NASA ESTO ACT award, is specifically scaled to be a drop-in radar solution for resource-limited delivery systems like CubeSats and small airborne vehicles. Here, we present our mission concept and flow-down requirements for a constellation of 6U InSAR sensors that individually approach the performance capabilities of existing instruments, but collectively surpass the temporal coverage capabilities of single-platform sensors. We discuss the key applications addressed by this constellation and the capabilities that the constellation enables.

Multi-scale responses of soil stability and invasive plants to removal of non-native grazers from an arid conservation reserve

USGS Publications Warehouse

Beever, Erik A.; Huso, Manuela M. P.; Pyke, David A.

2006-01-01

Disturbances and ecosystem recovery from disturbance both involve numerous processes that operate on multiple spatial and temporal scales. Few studies have investigated how gradients of disturbance intensity and ecosystem responses are distributed across multiple spatial resolutions and also how this relationship changes through time during recovery. We investigated how cover of non-native species and soil-aggregate stability (a measure of vulnerability to erosion by water) in surface and subsurface soils varied spatially during grazing by burros and cattle and whether patterns in these variables changed after grazer removal from Mojave National Preserve, California, USA. We compared distance from water and number of ungulate defecations — metrics of longer-term and recent grazing intensity, respectively, — as predictors of our response variables. We used information-theoretic analyses to compare hierarchical linear models that accounted for important covariates and allowed for interannual variation in the disturbance–response relationship at local and landscape scales. Soil stability was greater under perennial vegetation than in bare interspaces, and surface soil stability decreased with increasing numbers of ungulate defecations. Stability of surface samples was more affected by time since removal of grazers than was stability of subsurface samples, and subsurface soil stability in bare spaces was not related to grazing intensity, time since removal, or any of our other predictors. In the high rainfall year (2003) after cattle had been removed for 1–2 years, cover of all non-native plants averaged nine times higher than in the low-rainfall year (2002). Given the heterogeneity in distribution of large-herbivore impacts that we observed at several resolutions, hierarchical analyses provided a more complete understanding of the spatial and temporal complexities of disturbance and recovery processes in arid ecosystems.

Spatial patterns of native freshwater mussels in the Upper Mississippi River

USGS Publications Warehouse

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

2016-01-01

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

Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges

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

Fan, Jiwen; Wang, Yuan; Rosenfeld, Daniel

2016-11-01

Over the past decade, the number of studies that investigate aerosol-cloud interactions has increased considerably. Although tremendous progress has been made to improve our understanding of basic physical mechanisms of aerosol-cloud interactions and reduce their uncertainties in climate forcing, we are still in poor understanding of (1) some of the mechanisms that interact with each other over multiple spatial and temporal scales, (2) the feedback between microphysical and dynamical processes and between local-scale processes and large-scale circulations, and (3) the significance of cloud-aerosol interactions on weather systems as well as regional and global climate. This review focuses on recent theoreticalmore » studies and important mechanisms on aerosol-cloud interactions, and discusses the significances of aerosol impacts on raditative forcing and precipitation extremes associated with different cloud systems. Despite significant understanding has been gained about aerosol impacts on the main cloud types, there are still many unknowns especially associated with various deep convective systems. Therefore, large efforts are needed to escalate our understanding. Future directions should focus on obtaining concurrent measurements of aerosol properties, cloud microphysical and dynamic properties over a range of temporal and spatial scales collected over typical climate regimes and closure studies, as well as improving understanding and parameterizations of cloud microphysics such as ice nucleation, mixed-phase properties, and hydrometeor size and fall speed« less

Seeing the Song: Left Auditory Structures May Track Auditory-Visual Dynamic Alignment

PubMed Central

Mossbridge, Julia A.; Grabowecky, Marcia; Suzuki, Satoru

2013-01-01

Auditory and visual signals generated by a single source tend to be temporally correlated, such as the synchronous sounds of footsteps and the limb movements of a walker. Continuous tracking and comparison of the dynamics of auditory-visual streams is thus useful for the perceptual binding of information arising from a common source. Although language-related mechanisms have been implicated in the tracking of speech-related auditory-visual signals (e.g., speech sounds and lip movements), it is not well known what sensory mechanisms generally track ongoing auditory-visual synchrony for non-speech signals in a complex auditory-visual environment. To begin to address this question, we used music and visual displays that varied in the dynamics of multiple features (e.g., auditory loudness and pitch; visual luminance, color, size, motion, and organization) across multiple time scales. Auditory activity (monitored using auditory steady-state responses, ASSR) was selectively reduced in the left hemisphere when the music and dynamic visual displays were temporally misaligned. Importantly, ASSR was not affected when attentional engagement with the music was reduced, or when visual displays presented dynamics clearly dissimilar to the music. These results appear to suggest that left-lateralized auditory mechanisms are sensitive to auditory-visual temporal alignment, but perhaps only when the dynamics of auditory and visual streams are similar. These mechanisms may contribute to correct auditory-visual binding in a busy sensory environment. PMID:24194873

Multi-temporal change image inference towards false alarms reduction for an operational photogrammetric rockfall detection system

NASA Astrophysics Data System (ADS)

Partsinevelos, Panagiotis; Kallimani, Christina; Tripolitsiotis, Achilleas

2015-06-01

Rockfall incidents affect civil security and hamper the sustainable growth of hard to access mountainous areas due to casualties, injuries and infrastructure loss. Rockfall occurrences cannot be easily prevented, whereas previous studies for rockfall multiple sensor early detection systems have focused on large scale incidents. However, even a single rock may cause the loss of a human life along transportation routes thus, it is highly important to establish methods for the early detection of small-scale rockfall incidents. Terrestrial photogrammetric techniques are prone to a series of errors leading to false alarm incidents, including vegetation, wind, and non relevant change in the scene under consideration. In this study, photogrammetric monitoring of rockfall prone slopes is established and the resulting multi-temporal change imagery is processed in order to minimize false alarm incidents. Integration of remote sensing imagery analysis techniques is hereby applied to enhance early detection of a rockfall. Experimental data demonstrated that an operational system able to identify a 10-cm rock movement within a 10% false alarm rate is technically feasible.

Novel Flood Detection and Analysis Method Using Recurrence Property

NASA Astrophysics Data System (ADS)

Wendi, Dadiyorto; Merz, Bruno; Marwan, Norbert

2016-04-01

Temporal changes in flood hazard are known to be difficult to detect and attribute due to multiple drivers that include processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defence, river training, or land use change, could impact variably on space-time scales and influence or mask each other. Flood time series may show complex behavior that vary at a range of time scales and may cluster in time. This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazard in Germany. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic behavior to certain flood situations.

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

Efroymson, Rebecca Ann; Dale, Virginia H; Kline, Keith L

Indicators of the environmental sustainability of biofuel production, distribution, and use should be selected, measured, and interpreted with respect to the context in which they are used. These indicators include measures of soil quality, water quality and quantity, greenhouse-gas emissions, biodiversity, air quality, and vegetation productivity. Contextual considerations include the purpose for the sustainability analysis, the particular biofuel production and distribution system (including supply chain, management aspects, and system viability), policy conditions, stakeholder values, location, temporal influences, spatial scale, baselines, and reference scenarios. Recommendations presented in this paper include formulating the problem for particular analyses, selecting appropriate context-specific indicators ofmore » environmental sustainability, and developing indicators that can reflect multiple environmental properties at low cost within a defined context. In addition, contextual considerations such as technical objectives, varying values and perspectives of stakeholder groups, and availability and reliability of data need to be understood and considered. Sustainability indicators for biofuels are most useful if adequate historical data are available, information can be collected at appropriate spatial and temporal scales, organizations are committed to use indicator information in the decision-making process, and indicators can effectively guide behavior toward more sustainable practices.« less

Classification of epilepsy types through global network analysis of scalp electroencephalograms

NASA Astrophysics Data System (ADS)

Lee, Uncheol; Kim, Seunghwan; Jung, Ki-Young

2006-04-01

Epilepsy is a dynamic disease in which self-organization and emergent structures occur dynamically at multiple levels of neuronal integration. Therefore, the transient relationship within multichannel electroencephalograms (EEGs) is crucial for understanding epileptic processes. In this paper, we show that the global relationship within multichannel EEGs provides us with more useful information in classifying two different epilepsy types than pairwise relationships such as cross correlation. To demonstrate this, we determine the global network structure within channels of the scalp EEG based on the minimum spanning tree method. The topological dissimilarity of the network structures from different types of temporal lobe epilepsy is described in the form of the divergence rate and is computed for 11 patients with left (LTLE) and right temporal lobe epilepsy (RTLE). We find that patients with LTLE and RTLE exhibit different large scale network structures, which emerge at the epoch immediately before the seizure onset, not in the preceding epochs. Our results suggest that patients with the two different epilepsy types display distinct large scale dynamical networks with characteristic epileptic network structures.

Prey dispersal rate affects prey species composition and trait diversity in response to multiple predators in metacommunities.

PubMed

Howeth, Jennifer G; Leibold, Mathew A

2010-09-01

1. Recent studies indicate that large-scale spatial processes can alter local community structuring mechanisms to determine local and regional assemblages of predators and their prey. In metacommunities, this may occur when the functional diversity represented in the regional predator species pool interacts with the rate of prey dispersal among local communities to affect prey species diversity and trait composition at multiple scales. 2. Here, we test for effects of prey dispersal rate and spatially and temporally heterogeneous predation from functionally dissimilar predators on prey structure in pond mesocosm metacommunities. An experimental metacommunity consisted of three pond mesocosm communities supporting two differentially size-selective invertebrate predators and their zooplankton prey. In each metacommunity, two communities maintained constant predation and supported either Gyrinus sp. (Coleoptera) or Notonecta ungulata (Hemiptera) predators generating a spatial prey refuge while the third community supported alternating predation from Gyrinus sp. and N. ungulata generating a temporal prey refuge. Mesocosm metacommunities were connected at either low (0.7% day(-1)) or high (10% day(-1)) planktonic prey dispersal. The diversity, composition and body size of zooplankton prey were measured at local and regional (metacommunity) scales. 3. Metacommunities experiencing the low prey dispersal rate supported the greatest regional prey species diversity (H') and evenness (J'). Neither dispersal rate nor predation regime affected local prey diversity or evenness. The spatial prey refuge at low dispersal maintained the largest difference in species composition and body size diversity between communities under Gyrinus and Notonecta predation, suggesting that species sorting was operating at the low dispersal rate. There was no effect of dispersal rate on species diversity or body size distribution in the temporal prey refuge. 4. The frequency distribution, but not the range, of prey body sizes within communities depended upon prey dispersal rate and predator identity. Taken together, these results demonstrate that prey dispersal rate can moderate the strength of predation to influence prey species diversity and the local frequency distribution of prey traits in metacommunities supporting ecologically different predators.

Temporal Gillespie Algorithm: Fast Simulation of Contagion Processes on Time-Varying Networks

PubMed Central

Vestergaard, Christian L.; Génois, Mathieu

2015-01-01

Stochastic simulations are one of the cornerstones of the analysis of dynamical processes on complex networks, and are often the only accessible way to explore their behavior. The development of fast algorithms is paramount to allow large-scale simulations. The Gillespie algorithm can be used for fast simulation of stochastic processes, and variants of it have been applied to simulate dynamical processes on static networks. However, its adaptation to temporal networks remains non-trivial. We here present a temporal Gillespie algorithm that solves this problem. Our method is applicable to general Poisson (constant-rate) processes on temporal networks, stochastically exact, and up to multiple orders of magnitude faster than traditional simulation schemes based on rejection sampling. We also show how it can be extended to simulate non-Markovian processes. The algorithm is easily applicable in practice, and as an illustration we detail how to simulate both Poissonian and non-Markovian models of epidemic spreading. Namely, we provide pseudocode and its implementation in C++ for simulating the paradigmatic Susceptible-Infected-Susceptible and Susceptible-Infected-Recovered models and a Susceptible-Infected-Recovered model with non-constant recovery rates. For empirical networks, the temporal Gillespie algorithm is here typically from 10 to 100 times faster than rejection sampling. PMID:26517860

Temporal Gillespie Algorithm: Fast Simulation of Contagion Processes on Time-Varying Networks.

PubMed

Vestergaard, Christian L; Génois, Mathieu

2015-10-01

Stochastic simulations are one of the cornerstones of the analysis of dynamical processes on complex networks, and are often the only accessible way to explore their behavior. The development of fast algorithms is paramount to allow large-scale simulations. The Gillespie algorithm can be used for fast simulation of stochastic processes, and variants of it have been applied to simulate dynamical processes on static networks. However, its adaptation to temporal networks remains non-trivial. We here present a temporal Gillespie algorithm that solves this problem. Our method is applicable to general Poisson (constant-rate) processes on temporal networks, stochastically exact, and up to multiple orders of magnitude faster than traditional simulation schemes based on rejection sampling. We also show how it can be extended to simulate non-Markovian processes. The algorithm is easily applicable in practice, and as an illustration we detail how to simulate both Poissonian and non-Markovian models of epidemic spreading. Namely, we provide pseudocode and its implementation in C++ for simulating the paradigmatic Susceptible-Infected-Susceptible and Susceptible-Infected-Recovered models and a Susceptible-Infected-Recovered model with non-constant recovery rates. For empirical networks, the temporal Gillespie algorithm is here typically from 10 to 100 times faster than rejection sampling.

Avalanche Analysis from Multielectrode Ensemble Recordings in Cat, Monkey, and Human Cerebral Cortex during Wakefulness and Sleep

PubMed Central

Dehghani, Nima; Hatsopoulos, Nicholas G.; Haga, Zach D.; Parker, Rebecca A.; Greger, Bradley; Halgren, Eric; Cash, Sydney S.; Destexhe, Alain

2012-01-01

Self-organized critical states are found in many natural systems, from earthquakes to forest fires, they have also been observed in neural systems, particularly, in neuronal cultures. However, the presence of critical states in the awake brain remains controversial. Here, we compared avalanche analyses performed on different in vivo preparations during wakefulness, slow-wave sleep, and REM sleep, using high density electrode arrays in cat motor cortex (96 electrodes), monkey motor cortex and premotor cortex and human temporal cortex (96 electrodes) in epileptic patients. In neuronal avalanches defined from units (up to 160 single units), the size of avalanches never clearly scaled as power-law, but rather scaled exponentially or displayed intermediate scaling. We also analyzed the dynamics of local field potentials (LFPs) and in particular LFP negative peaks (nLFPs) among the different electrodes (up to 96 sites in temporal cortex or up to 128 sites in adjacent motor and premotor cortices). In this case, the avalanches defined from nLFPs displayed power-law scaling in double logarithmic representations, as reported previously in monkey. However, avalanche defined as positive LFP (pLFP) peaks, which are less directly related to neuronal firing, also displayed apparent power-law scaling. Closer examination of this scaling using the more reliable cumulative distribution function (CDF) and other rigorous statistical measures, did not confirm power-law scaling. The same pattern was seen for cats, monkey, and human, as well as for different brain states of wakefulness and sleep. We also tested other alternative distributions. Multiple exponential fitting yielded optimal fits of the avalanche dynamics with bi-exponential distributions. Collectively, these results show no clear evidence for power-law scaling or self-organized critical states in the awake and sleeping brain of mammals, from cat to man. PMID:22934053

Local variations in spatial synchrony of influenza epidemics.

PubMed

Stark, James H; Cummings, Derek A T; Ermentrout, Bard; Ostroff, Stephen; Sharma, Ravi; Stebbins, Samuel; Burke, Donald S; Wisniewski, Stephen R

2012-01-01

Understanding the mechanism of influenza spread across multiple geographic scales is not complete. While the mechanism of dissemination across regions and states of the United States has been described, understanding the determinants of dissemination between counties has not been elucidated. The paucity of high resolution spatial-temporal influenza incidence data to evaluate disease structure is often not available. We report on the underlying relationship between the spread of influenza and human movement between counties of one state. Significant synchrony in the timing of epidemics exists across the entire state and decay with distance (regional correlation=62%). Synchrony as a function of population size display evidence of hierarchical spread with more synchronized epidemics occurring among the most populated counties. A gravity model describing movement between two populations is a stronger predictor of influenza spread than adult movement to and from workplaces suggesting that non-routine and leisure travel drive local epidemics. These findings highlight the complex nature of influenza spread across multiple geographic scales.

Local Variations in Spatial Synchrony of Influenza Epidemics

PubMed Central

Stark, James H.; Cummings, Derek A. T.; Ermentrout, Bard; Ostroff, Stephen; Sharma, Ravi; Stebbins, Samuel; Burke, Donald S.; Wisniewski, Stephen R.

2012-01-01

Background Understanding the mechanism of influenza spread across multiple geographic scales is not complete. While the mechanism of dissemination across regions and states of the United States has been described, understanding the determinants of dissemination between counties has not been elucidated. The paucity of high resolution spatial-temporal influenza incidence data to evaluate disease structure is often not available. Methodology and Findings We report on the underlying relationship between the spread of influenza and human movement between counties of one state. Significant synchrony in the timing of epidemics exists across the entire state and decay with distance (regional correlation = 62%). Synchrony as a function of population size display evidence of hierarchical spread with more synchronized epidemics occurring among the most populated counties. A gravity model describing movement between two populations is a stronger predictor of influenza spread than adult movement to and from workplaces suggesting that non-routine and leisure travel drive local epidemics. Conclusions These findings highlight the complex nature of influenza spread across multiple geographic scales. PMID:22916274

Adaptive subdomain modeling: A multi-analysis technique for ocean circulation models

NASA Astrophysics Data System (ADS)

Altuntas, Alper; Baugh, John

2017-07-01

Many coastal and ocean processes of interest operate over large temporal and geographical scales and require a substantial amount of computational resources, particularly when engineering design and failure scenarios are also considered. This study presents an adaptive multi-analysis technique that improves the efficiency of these computations when multiple alternatives are being simulated. The technique, called adaptive subdomain modeling, concurrently analyzes any number of child domains, with each instance corresponding to a unique design or failure scenario, in addition to a full-scale parent domain providing the boundary conditions for its children. To contain the altered hydrodynamics originating from the modifications, the spatial extent of each child domain is adaptively adjusted during runtime depending on the response of the model. The technique is incorporated in ADCIRC++, a re-implementation of the popular ADCIRC ocean circulation model with an updated software architecture designed to facilitate this adaptive behavior and to utilize concurrent executions of multiple domains. The results of our case studies confirm that the method substantially reduces computational effort while maintaining accuracy.

Difference infiltrometer: a method to measure temporally variable infiltration rates during rainstorms

USGS Publications Warehouse

Moody, John A.; Ebel, Brian A.

2012-01-01

We developed a difference infiltrometer to measure time series of non-steady infiltration rates during rainstorms at the point scale. The infiltrometer uses two, tipping bucket rain gages. One gage measures rainfall onto, and the other measures runoff from, a small circular plot about 0.5-m in diameter. The small size allows the infiltration rate to be computed as the difference of the cumulative rainfall and cumulative runoff without having to route water through a large plot. Difference infiltrometers were deployed in an area burned by the 2010 Fourmile Canyon Fire near Boulder, Colorado, USA, and data were collected during the summer of 2011. The difference infiltrometer demonstrated the capability to capture different magnitudes of infiltration rates and temporal variability associated with convective (high intensity, short duration) and cyclonic (low intensity, long duration) rainstorms. Data from the difference infiltrometer were used to estimate saturated hydraulic conductivity of soil affected by the heat from a wildfire. The difference infiltrometer is portable and can be deployed in rugged, steep terrain and does not require the transport of water, as many rainfall simulators require, because it uses natural rainfall. It can be used to assess infiltration models, determine runoff coefficients, identify rainfall depth or rainfall intensity thresholds to initiate runoff, estimate parameters for infiltration models, and compare remediation treatments on disturbed landscapes. The difference infiltrometer can be linked with other types of soil monitoring equipment in long-term studies for detecting temporal and spatial variability at multiple time scales and in nested designs where it can be linked to hillslope and basin-scale runoff responses.

The joint space-time statistics of macroweather precipitation, space-time statistical factorization and macroweather models.

PubMed

Lovejoy, S; de Lima, M I P

2015-07-01

Over the range of time scales from about 10 days to 30-100 years, in addition to the familiar weather and climate regimes, there is an intermediate "macroweather" regime characterized by negative temporal fluctuation exponents: implying that fluctuations tend to cancel each other out so that averages tend to converge. We show theoretically and numerically that macroweather precipitation can be modeled by a stochastic weather-climate model (the Climate Extended Fractionally Integrated Flux, model, CEFIF) first proposed for macroweather temperatures and we show numerically that a four parameter space-time CEFIF model can approximately reproduce eight or so empirical space-time exponents. In spite of this success, CEFIF is theoretically and numerically difficult to manage. We therefore propose a simplified stochastic model in which the temporal behavior is modeled as a fractional Gaussian noise but the spatial behaviour as a multifractal (climate) cascade: a spatial extension of the recently introduced ScaLIng Macroweather Model, SLIMM. Both the CEFIF and this spatial SLIMM model have a property often implicitly assumed by climatologists that climate statistics can be "homogenized" by normalizing them with the standard deviation of the anomalies. Physically, it means that the spatial macroweather variability corresponds to different climate zones that multiplicatively modulate the local, temporal statistics. This simplified macroweather model provides a framework for macroweather forecasting that exploits the system's long range memory and spatial correlations; for it, the forecasting problem has been solved. We test this factorization property and the model with the help of three centennial, global scale precipitation products that we analyze jointly in space and in time.

Spatial-temporal consistency between gross primary productivity and solar-induced chlorophyll fluorescence of vegetation in China during 2007-2014

NASA Astrophysics Data System (ADS)

Ma, J.; Xiao, X.; Zhang, Y.; Chen, B.; Zhao, B.

2017-12-01

Great significance exists in accurately estimating spatial-temporal patterns of gross primary production (GPP) because of its important role in global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatially time-sires GPP. However, the estimation of the accuracy of GPP simulations from LUE at both spatial and temporal scales is still a challenging work. In this study, we simulated GPP of vegetation in China during 2007-2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images of 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPPVPM) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPPVPM and SIF data over both single year (2010) and multiple years (2007-2014) in China. Annual GPPVPM is significantly positive correlated with SIF (R2>0.43) spatially for all years during 2007-2014 and all seasons in 2010 (R2>0.37). GPP dynamic trends is high spatial-temporal heterogeneous in China during 2007-2014. The results of this study indicate that GPPVPM is temporally and spatially in line with SIF data, and space-borne SIF data have great potential in validating and parameterizing GPP estimation of LUE-based models.

Non-linear scale interactions in a forced turbulent boundary layer

NASA Astrophysics Data System (ADS)

Duvvuri, Subrahmanyam; McKeon, Beverley

2015-11-01

A strong phase-organizing influence exerted by a single synthetic large-scale spatio-temporal mode on directly-coupled (through triadic interactions) small scales in a turbulent boundary layer forced by a spatially-impulsive dynamic wall-roughness patch was previously demonstrated by the authors (J. Fluid Mech. 2015, vol. 767, R4). The experimental set-up was later enhanced to allow for simultaneous forcing of multiple scales in the flow. Results and analysis are presented from a new set of novel experiments where two distinct large scales are forced in the flow by a dynamic wall-roughness patch. The internal non-linear forcing of two other scales with triadic consistency to the artificially forced large scales, corresponding to sum and difference in wavenumbers, is dominated by the latter. This allows for a forcing-response (input-output) type analysis of the two triadic scales, and naturally lends itself to a resolvent operator based model (e.g. McKeon & Sharma, J. Fluid Mech. 2010, vol. 658, pp. 336-382) of the governing Navier-Stokes equations. The support of AFOSR (grant #FA 9550-12-1-0469, program manager D. Smith) is gratefully acknowledged.

Temporal Variation and Scaling of Hydrological Variables in a Typical Watershed

NASA Astrophysics Data System (ADS)

Yang, C.; Zhang, Y. K.; Liang, X.; Liu, J.

2016-12-01

Temporal variations of the main hydrological variables over 16 years were systematically investigated based on the results from an integrated hydrological modeling at the Sagehen Creek Watershed in northern Sierra Nevada. Temporal scaling of these variables and damping effects of the hydrological system as well as its subsystems, i.e., the land surface, unsaturated zone, and saturated zone, were analyzed with spectral analyses. It was found that the hydrological system may act as a cascade of hierarchical fractal filters which sequentially transfer a non-fractal or less correlated fractal hydrological signal to a more correlated fractal signal. Temporal scaling of infiltration (I), actual evapotraspiration (ET), recharge (R), baseflow (BF), streamflow (SF) exist and the temporal autocorrelation of these variables increase as water moves through the system. The degree of the damping effect of the subsystems is different and is strongest in the unsaturated zone compared with that of the land surface and saturated zone. The temporal scaling of the groundwater levels (h) also exists and is strongly affected by the river: the temporal autocorrelation of h near the river is similar to that of the river stage fluctuations and increases away from the river. There is a break in the temporal scaling of h near the river at low frequencies due to the effect of the river. Temporal variations of the soil moisture (θ) is more complicated: the value of the scaling exponent (β) for θ increases with depth as water moves downwards and its high-frequency fluctuations are damped by the unsaturated zone. The temporal fluctuations of precipitation (P) and I are fractional Gauss noise (fGn), those of ET, R, BF, and SF are fractional Brownian motion (fBm), and those of h away from the river are 2nd-order fBm based on the values of β obtained in this study. Keywords: Temporal variations, Scaling, Damping effect, Hydrological system.

Role of time in symbiotic systems

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

Agrawala, A.K.

1996-12-31

All systems have a dynamics which reflects the changes in the system in time and, therefore, have to maintain a notion of time, either explicitly or implicitly. Traditionally, the notion of time in constructed systems has been implicitly specified at design time through rigid structures such as sampled data systems which operate with a fixed time tick, feedback systems which are designed reflecting a fixed time scale for the dynamics of the system as well as the controller responses, etc. In biological systems, the sense of time is a key element but it is not rigidly structured, even though allmore » such systems have a clear notion of time. We define the notion of time in systems in terms of temporal locality, time scale and time horizon. Temporal locality gives the notion of the accuracy with which the system knows about the current time. Time scale reflects the scale indicating the smallest and the largest granularity considered. It also reflects the reaction time. The time horizon indicates the time beyond which the system considers to be distant future and may not take it into account in its actions. Note that the temporal locality, time scale and the time horizon may be different for different types of actions of a system, thereby permitting the system to use multiple notions of time concurrently. In multi agent systems each subsystem may have its own notion of time but when intentions take place a coordination is necessary. Such coordination requires that the notions of time for different agents of the system be consistent. Clearly, the consistency requirement in this case does not mean exactly identical but implies that different agents can coordinate their actions which must take place in time. When the actions only require a determinate ordering the required coordination is much less severe than the case requiring actions to take place at the same time.« less

Trade-offs across space, time, and ecosystem services

USGS Publications Warehouse

Rodriguez, J.P.; Beard, T.D.; Bennett, E.M.; Cumming, Graeme S.; Cork, S.J.; Agard, J.; Dobson, A.P.; Peterson, G.D.

2006-01-01

Ecosystem service (ES) trade-offs arise from management choices made by humans, which can change the type, magnitude, and relative mix of services provided by ecosystems. Trade-offs occur when the provision of one ES is reduced as a consequence of increased use of another ES. In some cases, a trade-off may be an explicit choice; but in others, trade-offs arise without premeditation or even awareness that they are taking place. Trade-offs in ES can be classified along three axes: spatial scale, temporal scale, and reversibility. Spatial scale refers to whether the effects of the trade-off are felt locally or at a distant location. Temporal scale refers to whether the effects take place relatively rapidly or slowly. Reversibility expresses the likelihood that the perturbed ES may return to its original state if the perturbation ceases. Across all four Millennium Ecosystem Assessment scenarios and selected case study examples, trade-off decisions show a preference for provisioning, regulating, or cultural services (in that order). Supporting services are more likely to be "taken for granted." Cultural ES are almost entirely unquantified in scenario modeling; therefore, the calculated model results do not fully capture losses of these services that occur in the scenarios. The quantitative scenario models primarily capture the services that are perceived by society as more important - provisioning and regulating ecosystem services - and thus do not fully capture trade-offs of cultural and supporting services. Successful management policies will be those that incorporate lessons learned from prior decisions into future management actions. Managers should complement their actions with monitoring programs that, in addition to monitoring the short-term provisions of services, also monitor the long-term evolution of slowly changing variables. Policies can then be developed to take into account ES trade-offs at multiple spatial and temporal scales. Successful strategies will recognize the inherent complexities of ecosystem management and will work to develop policies that minimize the effects of ES trade-offs. Copyright ?? 2006 by the author(s).

Evaluating the transitional mosaic: frameworks of change from Neanderthals to Homo sapiens in eastern Europe

NASA Astrophysics Data System (ADS)

Davies, William; White, Dustin; Lewis, Mark; Stringer, Chris

2015-06-01

Defining varying spatial and temporal analytical scales is essential before evaluating the responses of late Neanderthals and early Homo sapiens to Abrupt Environmental Transitions (AETs) and environmental disasters for the period 130-25 ka. Recent advances in addressing the population histories and interactions (using both genetic and archaeological evidence) of Neanderthals and H. sapiens have encouraged consideration of more subtle dynamics of archaeological change. Descriptions of change based on methodologies pioneered some 160 years ago are no longer adequate to explain the patterning we now see in the record. New chronological results, using multiple dating methods, allow us to begin to unpick the spatial and temporal scales of change. Isochronic markers (such as specific volcanic eruptions) can be used to create temporal frameworks (lattices), and results from other dating techniques compared against them. A combination of chronological lattices and direct dating of diagnostic artefacts and human fossils permits us, for the first time, to have greater confidence in connecting human (recent hominin) species and their behavioural responses to environmental conditions, and in quantifying scales of change over time and space (time-transgression). The timing of innovations, particularly those in bone, antler and ivory, can be directly quantified and tested, and used to re-evaluate longstanding models of cultural change. This paper also uses these new chronologies to explore the ecologies of late Neanderthals and early H. sapiens: their population densities, mobilities, resources exploited and possible interactions. Environmental productivity estimates are used to generate new questions of potential population densities and mobilities, and thus the sensitivity of these groups to environmental perturbations. Scales and intensities of effect on environments from natural disasters and AETs (notably Heinrich Events and the Campanian Ignimbrite eruption) are defined as a scale from "proximal" to "distal," with local conditions (topographic shelter or exposure) serving to intensify or mitigate those effects.

Use of a handheld low-cost sensor to explore the effect of urban design features on local-scale spatial and temporal air quality variability.

PubMed

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.

Capturing temporal and spatial variability in the chemistry of shallow permafrost ponds

NASA Astrophysics Data System (ADS)

Morison, Matthew Q.; Macrae, Merrin L.; Petrone, Richard M.; Fishback, LeeAnn

2017-12-01

Across the circumpolar north, the fate of small freshwater ponds and lakes (< 1 km2) has been the subject of scientific interest due to their ubiquity in the landscape, capacity to exchange carbon and energy with the atmosphere, and their potential to inform researchers about past climates through sediment records. A changing climate has implications for the capacity of ponds and lakes to support organisms and store carbon, which in turn has important feedbacks to climate change. Thus, an improved understanding of pond biogeochemistry is needed. To characterize spatial and temporal patterns in water column chemistry, a suite of tundra ponds were examined to answer the following research questions: (1) does temporal variability exceed spatial variability? (2) If temporal variability exists, do all ponds (or groups of ponds) behave in a similar temporal pattern, linked to seasonal hydrologic drivers or precipitation events? Six shallow ponds located in the Hudson Bay Lowlands region were monitored between May and October 2015 (inclusive, spanning the entire open-water period). The ponds span a range of biophysical conditions including pond area, perimeter, depth, and shoreline development. Water samples were collected regularly, both bimonthly over the ice-free season and intensively during and following a large summer storm event. Samples were analysed for nitrogen speciation (NO3-, NH4+, dissolved organic nitrogen) and major ions (Cl-, SO42-, K+, Ca2+, Mg2+, Na+). Across all ponds, temporal variability (across the season and within a single rain event) exceeded spatial variability (variation among ponds) in concentrations of several major species (Cl-, SO42-, K+, Ca2+, Na+). Evapoconcentration and dilution of pond water with precipitation and runoff inputs were the dominant processes influencing a set of chemical species which are hydrologically driven (Cl-, Na+, K+, Mg2+, dissolved organic nitrogen), whereas the dissolved inorganic nitrogen species were likely mediated by processes within ponds. This work demonstrates the importance of understanding hydrologically driven chemodynamics in permafrost ponds on multiple scales (seasonal and event scale).

Measuring Paleolandscape Relief in Alluvial River Systems from the Stratigraphic Record

NASA Astrophysics Data System (ADS)

Hajek, E. A.; Trampush, S. M.; Chamberlin, E.; Greenberg, E.

2017-12-01

Aggradational alluvial river systems sometimes generate relief in the vicinity of their channel belts (i.e. alluvial ridges) and it has been proposed that this process may define important thresholds in river avulsion. The compensation scale can be used to estimate the maximum relief across a landscape and can be connected to the maximum scale of autogenic organization in experimental and numerical systems. Here we use the compensation scale - measured from outcrops of Upper Cretaceous and Paleogene fluvial deposits - to estimate the maximum relief that characterized ancient fluvial landscapes. In some cases, the compensation scale significantly exceeds the maximum channel depth observed in a deposit, suggesting that aggradational alluvial systems organize to sustain more relief than might be expected by looking only in the immediate vicinity of the active channel belt. Instead, these results indicate that in some systems, positive topographic relief generated by multiple alluvial ridge complexes and/or large-scale fan features may be associated with landscape-scale autogenic organization of channel networks that spans multiple cycles of channel avulsion. We compare channel and floodplain sedimentation patterns among the studied ancient fluvial systems in an effort to determine whether avulsion style, channel migration, or floodplain conditions influenced the maximum autogenic relief of ancient landscapes. Our results emphasize that alluvial channel networks may be organized at much larger spatial and temporal scales than previously realized and provide an avenue for understanding which types of river systems are likely to exhibit the largest range of autogenic dynamics.

Muscles innervated by a single motor neuron exhibit divergent synaptic properties on multiple time scales.

PubMed

Blitz, Dawn M; Pritchard, Amy E; Latimer, John K; Wakefield, Andrew T

2017-04-01

Adaptive changes in the output of neural circuits underlying rhythmic behaviors are relayed to muscles via motor neuron activity. Presynaptic and postsynaptic properties of neuromuscular junctions can impact the transformation from motor neuron activity to muscle response. Further, synaptic plasticity occurring on the time scale of inter-spike intervals can differ between multiple muscles innervated by the same motor neuron. In rhythmic behaviors, motor neuron bursts can elicit additional synaptic plasticity. However, it is unknown whether plasticity regulated by the longer time scale of inter-burst intervals also differs between synapses from the same neuron, and whether any such distinctions occur across a physiological activity range. To address these issues, we measured electrical responses in muscles innervated by a chewing circuit neuron, the lateral gastric (LG) motor neuron, in a well-characterized small motor system, the stomatogastric nervous system (STNS) of the Jonah crab, Cancer borealis In vitro and in vivo , sensory, hormonal and modulatory inputs elicit LG bursting consisting of inter-spike intervals of 50-250 ms and inter-burst intervals of 2-24 s. Muscles expressed similar facilitation measured with paired stimuli except at the shortest inter-spike interval. However, distinct decay time constants resulted in differences in temporal summation. In response to bursting activity, augmentation occurred to different extents and saturated at different inter-burst intervals. Further, augmentation interacted with facilitation, resulting in distinct intra-burst facilitation between muscles. Thus, responses of multiple target muscles diverge across a physiological activity range as a result of distinct synaptic properties sensitive to multiple time scales. © 2017. Published by The Company of Biologists Ltd.

Insights and Challenges to Integrating Data from Diverse Ecological Networks

NASA Astrophysics Data System (ADS)

Peters, D. P. C.

2014-12-01

Many of the most dramatic and surprising effects of global change occur across large spatial extents, from regions to continents, that impact multiple ecosystem types across a range of interacting spatial and temporal scales. The ability of ecologists and inter-disciplinary scientists to understand and predict these dynamics depend, in large part, on existing site-based research infrastructures that developed in response to historic events. Integrating these diverse sources of data is critical to addressing these broad-scale questions. A conceptual approach is presented to synthesize and integrate diverse sources and types of data from different networks of research sites. This approach focuses on developing derived data products through spatial and temporal aggregation that allow datasets collected with different methods to be compared. The approach is illustrated through the integration, analysis, and comparison of hundreds of long-term datasets from 50 ecological sites in the US that represent ecosystem types commonly found globally. New insights were found by comparing multiple sites using common derived data. In addition to "bringing to light" many dark data in a standardized, open access, easy-to-use format, a suite of lessons were learned that can be applied to up and coming research networks in the US and internationally. These lessons will be described along with the challenges, including cyber-infrastructure, cultural, and behavioral constraints associated with the use of big and little data, that may keep ecologists and inter-disciplinary scientists from taking full advantage of the vast amounts of existing and yet-to-be exposed data.

Collective synchronization of self/non-self discrimination in T cell activation, across multiple spatio-temporal scales

NASA Astrophysics Data System (ADS)

Altan-Bonnet, Gregoire

The immune system is a collection of cells whose function is to eradicate pathogenic infections and malignant tumors while protecting healthy tissues. Recent work has delineated key molecular and cellular mechanisms associated with the ability to discriminate self from non-self agents. For example, structural studies have quantified the biophysical characteristics of antigenic molecules (those prone to trigger lymphocyte activation and a subsequent immune response). However, such molecular mechanisms were found to be highly unreliable at the individual cellular level. We will present recent efforts to build experimentally validated computational models of the immune responses at the collective cell level. Such models have become critical to delineate how higher-level integration through nonlinear amplification in signal transduction, dynamic feedback in lymphocyte differentiation and cell-to-cell communication allows the immune system to enforce reliable self/non-self discrimination at the organism level. In particular, we will present recent results demonstrating how T cells tune their antigen discrimination according to cytokine cues, and how competition for cytokine within polyclonal populations of cells shape the repertoire of responding clones. Additionally, we will present recent theoretical and experimental results demonstrating how competition between diffusion and consumption of cytokines determine the range of cell-cell communications within lymphoid organs. Finally, we will discuss how biochemically explicit models, combined with quantitative experimental validation, unravel the relevance of new feedbacks for immune regulations across multiple spatial and temporal scales.

Ecosystem Processes at the Watershed Scale: Stability and Resilience of Catchment Spatial Structure and Function to Disturbance

NASA Astrophysics Data System (ADS)

Baron, J.; Mast, A.; Clow, D. W.; Wetherbee, G. A.

2014-12-01

Ecohydrological systems evolve spontaneously in response to geologic, hydroclimate and biodiversity drivers. The stability and resilience of these systems to multiple disturbances can be addressed over specific temporal extents, potentially embedded within long term transience in response to geologic or climate change. The limits of ecohydrological resilience of system state in terms of vegetation canopy and soil catenae and the space/time distribution of water, carbon and nutrient cycling is determined by a set of critical feedbacks and potential substitutions of plant functional forms in response to disturbance. The ability of forest systems to return to states functionally similar to states prior to major disturbance, or combinations of multiple disturbances, is a critical question given increasing hydroclimate extremes, biological invasions, and human disturbance. Over the past century, forest landscape ecological patterns appear to have the ability to recover from significant disturbance and re-establish similar hydrological and ecological function in humid, biodiverse regions such as the southern Appalachians, and potentially drier forest ecosystems. Understanding and prediction of past and future long term dynamics requires explicit representation of spatial and temporal feedbacks and dependencies between hydrological, ecosystem and geomorphic processes, and the spatial pattern of species or plant functional type (PFT). Comprehensive models of watershed ecohydrological resilience requires careful balance between the level of process and parameter detail between the interacting components, relative to the structure, organization, space and time scales of the landscape.

Inference and representations of hand actions through grasping synergies. Comment on "Grasping synergies: A motor-control approach to the mirror neuron mechanism" by D'Ausilio, Bartoli, and Maffongelli

NASA Astrophysics Data System (ADS)

Santello, Marco

2015-03-01

The concept of synergy, denoting the coordination of multiple elements working together toward a common goal, has been extensively studied to understand how the central nervous system (CNS) controls movement (for review see [5,9]). Although this definition is appealing in its simplicity, 'multiple elements', 'working together', and 'common goal' each take different meanings depending on the scale at which a given sensorimotor system is studied, whether the 'working together' is defined in spatial and/or temporal domains, and the hypothesized synergy's 'common goal'. For example, the elements involved in a synergy can be defined as single motor units, muscles, or joints. Similarly, the goal of a synergy may be defined as a means available to the CNS to 'simplify' the control of multiple elements, or to minimize a given cost function or movement feature - all of which may differ across tasks and tasks conditions. These considerations underscore the fact that a universally accepted definition of synergies and their functional role remains to be established (for review see [6]). Thus, the nature and functional role(s) of synergies is still debated in the literature. Nevertheless, it is generally agreed that the reduction in the number of independent degrees of freedom that is manifested through synergies emerges from the interaction of biomechanical and neural factors constraining the spatial and temporal coordination of multiple muscles.

Single-shot optical recording with sub-picosecond resolution spans record nanosecond lengths

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

Muir, Ryan; Heebner, John

With the advent of electronics, oscilloscopes and photodiodes are now routinely capable of measuring events well below nanosecond resolution. However, these electronic instruments do not currently measure events below 10 ps resolution. From Walden’s observation that there is an engineering tradeoff between electronic bit depth and temporal resolution in analog-to-digital converters, this technique is projected to have extremely poor fidelity if it is extended to record single events with picosecond resolution. While this constraint may be circumvented with extensive signal averaging or other multiple measurements approaches, rare events and nonrepetitive events cannot be observed with this technique. Techniques capable ofmore » measuring information in a single shot are often required. There is a general lack of available technologies that are easily scalable to long records with sub-picosecond resolution, and are simultaneously versatile in wavelength of operation. Since it is difficult to scale electronic methods to shorter resolutions, we instead aim to scale optical methods to longer records. Demonstrated optical recording methods that have achieved 1 ps resolution and long recording lengths rely on either time scaling to slow down the temporal information or, like Wien, perform time-to-space mapping so that fast events may be captured with a conventional camera.« less

Single-shot optical recording with sub-picosecond resolution spans record nanosecond lengths

DOE PAGES

Muir, Ryan; Heebner, John

2018-01-18

With the advent of electronics, oscilloscopes and photodiodes are now routinely capable of measuring events well below nanosecond resolution. However, these electronic instruments do not currently measure events below 10 ps resolution. From Walden’s observation that there is an engineering tradeoff between electronic bit depth and temporal resolution in analog-to-digital converters, this technique is projected to have extremely poor fidelity if it is extended to record single events with picosecond resolution. While this constraint may be circumvented with extensive signal averaging or other multiple measurements approaches, rare events and nonrepetitive events cannot be observed with this technique. Techniques capable ofmore » measuring information in a single shot are often required. There is a general lack of available technologies that are easily scalable to long records with sub-picosecond resolution, and are simultaneously versatile in wavelength of operation. Since it is difficult to scale electronic methods to shorter resolutions, we instead aim to scale optical methods to longer records. Demonstrated optical recording methods that have achieved 1 ps resolution and long recording lengths rely on either time scaling to slow down the temporal information or, like Wien, perform time-to-space mapping so that fast events may be captured with a conventional camera.« less

Decomposition of Sources of Errors in Seasonal Streamflow Forecasts in a Rainfall-Runoff Dominated Basin

NASA Astrophysics Data System (ADS)

Sinha, T.; Arumugam, S.

2012-12-01

Seasonal streamflow forecasts contingent on climate forecasts can be effectively utilized in updating water management plans and optimize generation of hydroelectric power. Streamflow in the rainfall-runoff dominated basins critically depend on forecasted precipitation in contrast to snow dominated basins, where initial hydrological conditions (IHCs) are more important. Since precipitation forecasts from Atmosphere-Ocean-General Circulation Models are available at coarse scale (~2.8° by 2.8°), spatial and temporal downscaling of such forecasts are required to implement land surface models, which typically runs on finer spatial and temporal scales. Consequently, multiple sources are introduced at various stages in predicting seasonal streamflow. Therefore, in this study, we addresses the following science questions: 1) How do we attribute the errors in monthly streamflow forecasts to various sources - (i) model errors, (ii) spatio-temporal downscaling, (iii) imprecise initial conditions, iv) no forecasts, and (iv) imprecise forecasts? and 2) How does monthly streamflow forecast errors propagate with different lead time over various seasons? In this study, the Variable Infiltration Capacity (VIC) model is calibrated over Apalachicola River at Chattahoochee, FL in the southeastern US and implemented with observed 1/8° daily forcings to estimate reference streamflow during 1981 to 2010. The VIC model is then forced with different schemes under updated IHCs prior to forecasting period to estimate relative mean square errors due to: a) temporally disaggregation, b) spatial downscaling, c) Reverse Ensemble Streamflow Prediction (imprecise IHCs), d) ESP (no forecasts), and e) ECHAM4.5 precipitation forecasts. Finally, error propagation under different schemes are analyzed with different lead time over different seasons.

Spatial and Temporal Variation of Meteorological Drought in the Parambikulam-Aliyar Basin, Tamil Nadu

NASA Astrophysics Data System (ADS)

Manikandan, M.; Tamilmani, D.

2015-09-01

The present study aims to investigate the spatial and temporal variation of meteorological drought in the Parambikulam-Aliyar basin, Tamil Nadu using the Standardized Precipitation Index (SPI) as an indicator of drought severity. The basin was divided into 97 grid-cells of 5 × 5 km with each grid correspondence to approximately 1.03 % of total area. Monthly rainfall data for the period of 40 years (1972-2011) from 28 rain gauge stations in the basin was spatially interpolated and gridded monthly rainfall was created. Regional representative of SPI values calculated from mean areal rainfall were used to analyse the temporal variation of drought at multiple time scales. Spatial variation of drought was analysed based on highest drought severity derived from the monthly gridded SPI values. Frequency analyse was applied to assess the recurrence pattern of drought severity. The temporal analysis of SPI indicated that moderate, severe and extreme droughts are common in the basin and spatial analysis of drought severity identified the areas most frequently affected by drought. The results of this study can be used for developing drought preparedness plan and formulating mitigation strategies for sustainable water resource management within the basin.

Measuring the relative resilience of subarctic lakes to global change: redundancies of functions within and across temporal scales

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Johnson, Richard K.

2013-01-01

1. Ecosystems at high altitudes and latitudes are expected to be particularly vulnerable to the effects of global change. We assessed the responses of littoral invertebrate communities to changing abiotic conditions in subarctic Swedish lakes with long-term data (1988–2010) and compared the responses of subarctic lakes with those of more southern, hemiboreal lakes. 2. We used a complex systems approach, based on multivariate time-series modelling, and identified dominant and distinct temporal frequencies in the data; that is, we tracked community change at distinct temporal scales. We determined the distribution of functional feeding groups of invertebrates within and across temporal scales. Within and cross-scale distributions of functions have been considered to confer resilience to ecosystems, despite changing environmental conditions. 3. Two patterns of temporal change within the invertebrate communities were identified that were consistent across the lakes. The first pattern was one of monotonic change associated with changing abiotic lake conditions. The second was one of showing fluctuation patterns largely unrelated to gradual environmental change. Thus, two dominant and distinct temporal frequencies (temporal scales) were present in all lakes analysed. 4. Although the contribution of individual feeding groups varied between subarctic and hemiboreal lakes, they shared overall similar functional attributes (richness, evenness, diversity) and redundancies of functions within and between the observed temporal scales. This highlights similar resilience characteristics in subarctic and hemiboreal lakes. 5. Synthesis and applications. The effects of global change can be particularly strong at a single scale in ecosystems. Over time, this can cause monotonic change in communities and eventually lead to a loss of important ecosystem services upon reaching a critical threshold. Dynamics at other spatial or temporal scales can be unrelated to environmental change. The relative ‘intactness’ of these scales that are unaffected by global change and the persistence of functions at those scales may safeguard the whole system from the potential loss of functions at the scale at which global change impacts can be substantial. Thus, an understanding of scale-specific processes provides managers with a realistic assessment of vulnerabilities and the relative resilience of ecosystems to environmental change. Explicit consideration of ‘intact’ and ‘affected’ scales in analyses of global change impacts provides opportunities to tailor more specific management plans.

Space Technology 5 Multi-point Observations of Field-aligned Currents: Temporal Variability of Meso-Scale Structures

NASA Technical Reports Server (NTRS)

Le, Guan; Wang, Yongli; Slavin, James A.; Strangeway, Robert J.

2007-01-01

Space Technology 5 (ST5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that meso-scale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of - 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are approx. 1 min for meso-scale currents and approx. 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Temporal Organization of Sound Information in Auditory Memory.

PubMed

Song, Kun; Luo, Huan

2017-01-01

Memory is a constructive and organizational process. Instead of being stored with all the fine details, external information is reorganized and structured at certain spatiotemporal scales. It is well acknowledged that time plays a central role in audition by segmenting sound inputs into temporal chunks of appropriate length. However, it remains largely unknown whether critical temporal structures exist to mediate sound representation in auditory memory. To address the issue, here we designed an auditory memory transferring study, by combining a previously developed unsupervised white noise memory paradigm with a reversed sound manipulation method. Specifically, we systematically measured the memory transferring from a random white noise sound to its locally temporal reversed version on various temporal scales in seven experiments. We demonstrate a U-shape memory-transferring pattern with the minimum value around temporal scale of 200 ms. Furthermore, neither auditory perceptual similarity nor physical similarity as a function of the manipulating temporal scale can account for the memory-transferring results. Our results suggest that sounds are not stored with all the fine spectrotemporal details but are organized and structured at discrete temporal chunks in long-term auditory memory representation.

Influence of temporal context on value in the multiple-chains and successive-encounters procedures.

PubMed

O'Daly, Matthew; Angulo, Samuel; Gipson, Cassandra; Fantino, Edmund

2006-05-01

This set of studies explored the influence of temporal context across multiple-chain and multiple-successive-encounters procedures. Following training with different temporal contexts, the value of stimuli sharing similar reinforcement schedules was assessed by presenting these stimuli in concurrent probes. The results for the multiple-chain schedule indicate that temporal context does impact the value of a conditioned reinforcer consistent with delay-reduction theory, such that a stimulus signaling a greater reduction in delay until reinforcement has greater value. Further, nonreinforced stimuli that are concurrently presented with the preferred terminal link also have greater value, consistent with value transfer. The effects of context on value for conditions with the multiple-successive-encounters procedure, however, appear to depend on whether the search schedule or alternate handling schedule was manipulated, as well as on whether the tested stimuli were the rich or lean schedules in their components. Overall, the results help delineate the conditions under which temporal context affects conditioned-reinforcement value (acting as a learning variable) and the conditions under which it does not (acting as a performance variable), an issue of relevance to theories of choice.

Multiscale Granger causality

NASA Astrophysics Data System (ADS)

Faes, Luca; Nollo, Giandomenico; Stramaglia, Sebastiano; Marinazzo, Daniele

2017-10-01

In the study of complex physical and biological systems represented by multivariate stochastic processes, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. While methods to assess the dynamic complexity of individual processes at different time scales are well established, multiscale analysis of directed interactions has never been formalized theoretically, and empirical evaluations are complicated by practical issues such as filtering and downsampling. Here we extend the very popular measure of Granger causality (GC), a prominent tool for assessing directed lagged interactions between joint processes, to quantify information transfer across multiple time scales. We show that the multiscale processing of a vector autoregressive (AR) process introduces a moving average (MA) component, and describe how to represent the resulting ARMA process using state space (SS) models and to combine the SS model parameters for computing exact GC values at arbitrarily large time scales. We exploit the theoretical formulation to identify peculiar features of multiscale GC in basic AR processes, and demonstrate with numerical simulations the much larger estimation accuracy of the SS approach compared to pure AR modeling of filtered and downsampled data. The improved computational reliability is exploited to disclose meaningful multiscale patterns of information transfer between global temperature and carbon dioxide concentration time series, both in paleoclimate and in recent years.

Impact of large-scale atmospheric refractive structures on optical wave propagation

NASA Astrophysics Data System (ADS)

Nunalee, Christopher G.; He, Ping; Basu, Sukanta; Vorontsov, Mikhail A.; Fiorino, Steven T.

2014-10-01

Conventional techniques used to model optical wave propagation through the Earth's atmosphere typically as- sume flow fields based on various empirical relationships. Unfortunately, these synthetic refractive index fields do not take into account the influence of transient macroscale and mesoscale (i.e. larger than turbulent microscale) atmospheric phenomena. Nevertheless, a number of atmospheric structures that are characterized by various spatial and temporal scales exist which have the potential to significantly impact refractive index fields, thereby resulting dramatic impacts on optical wave propagation characteristics. In this paper, we analyze a subset of spatio-temporal dynamics found to strongly affect optical waves propagating through these atmospheric struc- tures. Analysis of wave propagation was performed in the geometrical optics approximation using a standard ray tracing technique. Using a numerical weather prediction (NWP) approach, we simulate multiple realistic atmospheric events (e.g., island wakes, low-level jets, etc.), and estimate the associated refractivity fields prior to performing ray tracing simulations. By coupling NWP model output with ray tracing simulations, we demon- strate the ability to quantitatively assess the potential impacts of coherent atmospheric phenomena on optical ray propagation. Our results show a strong impact of spatio-temporal characteristics of the refractive index field on optical ray trajectories. Such correlations validate the effectiveness of NWP models as they offer a more comprehensive representation of atmospheric refractivity fields compared to conventional methods based on the assumption of horizontal homogeneity.

Trend Assessment of Spatio-Temporal Change of Tehran Heat Island Using Satellite Images

NASA Astrophysics Data System (ADS)

Saradjian, M. R.; Sherafati, Sh.

2015-12-01

Numerous investigations on Urban Heat Island (UHI) show that land cover change is the main factor of increasing Land Surface Temperature (LST) in urban areas, especially conversion of vegetation and bare soil to concrete, asphalt and other man-made structures. On the other hand, other human activities like those which cause to burning fossil fuels, that increase the amount of carbon dioxide, may raise temperature in global scale in comparison with small scales (urban areas). In this study, multiple satellite images with different spatial and temporal resolutions have been used to determine Land Surface Temperature (LST) variability in Tehran metropolitan area. High temporal resolution of AVHRR images have been used as the main data source when investigating temperature variability in the urban area. The analysis shows that UHI appears more significant at afternoon and night hours. But the urban class temperature is almost equal to its surrounding vegetation and bare soil classes at around noon. It also reveals that there is no specific difference in UHI intense during the days throughout the year. However, it can be concluded that in the process of city expansion in years, UHI has been grown both spatially and in magnitude. In order to locate land-cover types and relate them to LST, Thematic Mapper (TM) images have been exploited. The influence of elevation on the LST has also been studied, using digital elevation model derived from SRTM database.

Spatial structure and temporal evolution of energetic particle injections in the inner magnetosphere during the 14 July 2013 substorm event

DOE PAGES

Gkioulidou, Matina; Ohtani, S.; Mitchell, D. G.; ...

2015-03-20

Recent results by the Van Allen Probes mission showed that the occurrence of energetic ion injections inside geosynchronous orbit could be very frequent throughout the main phase of a geomagnetic storm. Understanding, therefore, the formation and evolution of energetic particle injections is critical in order to quantify their effect in the inner magnetosphere. We present a case study of a substorm event that occurred during a weak storm (Dst ~ –40 nT) on 14 July 2013. Van Allen Probe B, inside geosynchronous orbit, observed two energetic proton injections within 10 min, with different dipolarization signatures and duration. The first onemore » is a dispersionless, short-timescale injection pulse accompanied by a sharp dipolarization signature, while the second one is a dispersed, longer-timescale injection pulse accompanied by a gradual dipolarization signature. We combined ground magnetometer data from various stations and in situ particle and magnetic field data from multiple satellites in the inner magnetosphere and near-Earth plasma sheet to determine the spatial extent of these injections, their temporal evolution, and their effects in the inner magnetosphere. Our results indicate that there are different spatial and temporal scales at which injections can occur in the inner magnetosphere and depict the necessity of multipoint observations of both particle and magnetic field data in order to determine these scales.« less

Fluctuation scaling of quotation activities in the foreign exchange market

NASA Astrophysics Data System (ADS)

Sato, Aki-Hiro; Nishimura, Maiko; Hołyst, Janusz A.

2010-07-01

We study the scaling behavior of quotation activities for various currency pairs in the foreign exchange market. The components’ centrality is estimated from multiple time series and visualized as a currency pair network. The power-law relationship between a mean of quotation activity and its standard deviation for each currency pair is found. The scaling exponent α and the ratio between common and specific fluctuations η increase with the length of the observation time window Δt. The result means that although for Δt=1 (min), the market dynamics are governed by specific processes, and at a longer time scale Δt>100 (min) the common information flow becomes more important. We point out that quotation activities are not independently Poissonian for Δt=1 (min), and temporally or mutually correlated activities of quotations can happen even at this time scale. A stochastic model for the foreign exchange market based on a bipartite graph representation is proposed.

The 2008 North Atlantic Spring Bloom Experiment I: Overview and Strategy

NASA Astrophysics Data System (ADS)

D'Asaro, E. A.; Lee, C.; Perry, M.; Fennel, K.; Rehm, E.; Gray, A.; Briggs, N.; Gudmundsson, K.

2008-12-01

The 2008 North Atlantic Spring Bloom Experiment (NAB08) aimed to understand carbon export from this globally important event by combining a new generation of autonomous floats and gliders equipped with a new generation of sensors, and traditional and modern shipboard observational methods. Measurements were made from early April to late June 2008 in a region southeast of Iceland near the JGOFS and MLML sites. Although Sverdrup's classical explanation for the bloom is probably broadly correct, previous observations have revealed a large degree of spatial and temporal variability, often on scales of a few kilometers, which have made detailed tests of Sverdrup's hypothesis difficult. The experiment was designed to continuously sample the bloom and its temporal and spatial 'patchiness' from the pre-bloom, wintertime conditions through the Spring and early Summer. The spatial scales were sampled by 4 Seagliders operating together as a mobile array. Measurements were made in a Lagrangian, water-following coordinate system which minimized the effects of horizontal advection and most clearly separated temporal and spatial scales. The coordinate system was defined by two Lagrangian Floats, one of which was chosen as the center of the Seaglider array. Proper measurement of the bloom by the autonomous vehicles required a robust and redundant array of sensors measuring key physical, chemical and biological variables including temperature, salinity, spectral light, oxygen, multiple optical proxies for carbon (chlorophyll fluorescence, beam-c attenuation and optical backscatter coefficients) and nitrate. Redundant measurements were made whenever possible, with nearly identical sensors on many platforms and multiple sensors measuring similar quantities on the same platform. Such care is clearly necessary, since the current generation of biogeochemical sensor require considerable efforts in calibration and interpretation. The autonomous platforms provided good coverage in space and time, but could not sample the entire range of processes that control the bloom. More detailed measurements and multiple calibrations of the autonomous platforms were made on 4 cruises, particularly a 21-day Knorr cruise in May 2008 that included collaborators from five US and five international institutions. These measurements included nutrients; particulate organic carbon and nitrogen; characterization of plankton composition and physiology by size, imaging, genomics, HPLC pigments, absorption spectra, 14C-primary productivity, and variable fluorescence; particle flux from floating sediment traps; and ADCP and CTD measurements. The experiment clearly demonstrated the ability of autonomous platforms to make biogeochemically relevant measurements of blooms. Its success, however, required intensive shipboard support for sensor calibration and interpretation. Further development of sensor technology, validation protocols, and understanding is clearly required if these measurements are to made routinely and easily.

Flexible timing by temporal scaling of cortical responses

PubMed Central

Wang, Jing; Narain, Devika; Hosseini, Eghbal A.; Jazayeri, Mehrdad

2017-01-01

Musicians can perform at different tempos, speakers can control the cadence of their speech, and children can flexibly vary their temporal expectations of events. To understand the neural basis of such flexibility, we recorded from the medial frontal cortex of nonhuman primates trained to produce different time intervals with different effectors. Neural responses were heterogeneous, nonlinear and complex, and exhibited a remarkable form of temporal invariance: firing rate profiles were temporally scaled to match the produced intervals. Recording from downstream neurons in the caudate and thalamic neurons projecting to the medial frontal cortex indicated that this phenomenon originates within cortical networks. Recurrent neural network models trained to perform the task revealed that temporal scaling emerges from nonlinearities in the network and degree of scaling is controlled by the strength of external input. These findings demonstrate a simple and general mechanism for conferring temporal flexibility upon sensorimotor and cognitive functions. PMID:29203897

A computational theory of visual receptive fields.

PubMed

Lindeberg, Tony

2013-12-01

A receptive field constitutes a region in the visual field where a visual cell or a visual operator responds to visual stimuli. This paper presents a theory for what types of receptive field profiles can be regarded as natural for an idealized vision system, given a set of structural requirements on the first stages of visual processing that reflect symmetry properties of the surrounding world. These symmetry properties include (i) covariance properties under scale changes, affine image deformations, and Galilean transformations of space-time as occur for real-world image data as well as specific requirements of (ii) temporal causality implying that the future cannot be accessed and (iii) a time-recursive updating mechanism of a limited temporal buffer of the past as is necessary for a genuine real-time system. Fundamental structural requirements are also imposed to ensure (iv) mutual consistency and a proper handling of internal representations at different spatial and temporal scales. It is shown how a set of families of idealized receptive field profiles can be derived by necessity regarding spatial, spatio-chromatic, and spatio-temporal receptive fields in terms of Gaussian kernels, Gaussian derivatives, or closely related operators. Such image filters have been successfully used as a basis for expressing a large number of visual operations in computer vision, regarding feature detection, feature classification, motion estimation, object recognition, spatio-temporal recognition, and shape estimation. Hence, the associated so-called scale-space theory constitutes a both theoretically well-founded and general framework for expressing visual operations. There are very close similarities between receptive field profiles predicted from this scale-space theory and receptive field profiles found by cell recordings in biological vision. Among the family of receptive field profiles derived by necessity from the assumptions, idealized models with very good qualitative agreement are obtained for (i) spatial on-center/off-surround and off-center/on-surround receptive fields in the fovea and the LGN, (ii) simple cells with spatial directional preference in V1, (iii) spatio-chromatic double-opponent neurons in V1, (iv) space-time separable spatio-temporal receptive fields in the LGN and V1, and (v) non-separable space-time tilted receptive fields in V1, all within the same unified theory. In addition, the paper presents a more general framework for relating and interpreting these receptive fields conceptually and possibly predicting new receptive field profiles as well as for pre-wiring covariance under scaling, affine, and Galilean transformations into the representations of visual stimuli. This paper describes the basic structure of the necessity results concerning receptive field profiles regarding the mathematical foundation of the theory and outlines how the proposed theory could be used in further studies and modelling of biological vision. It is also shown how receptive field responses can be interpreted physically, as the superposition of relative variations of surface structure and illumination variations, given a logarithmic brightness scale, and how receptive field measurements will be invariant under multiplicative illumination variations and exposure control mechanisms.

The Temporal and Spatial Variability of the Confined Aquifer Head and Storage Properties in the San Luis Valley, Colorado Inferred From Multiple InSAR Missions

NASA Astrophysics Data System (ADS)

Chen, Jingyi; Knight, Rosemary; Zebker, Howard A.

2017-11-01

Interferometric Synthetic Aperture Radar (InSAR) data from multiple satellite missions were combined to study the temporal and spatial variability of head and storage properties in a confined aquifer system on a decadal time scale. The area of study was a 4,500 km2 agricultural basin in the San Luis Valley (SLV), Colorado. We had available previous analyses of C-band ERS-1/2 data from June 1992 to November 2000, and L-band ALOS PALSAR data from October 2009 to March 2011. We used C-band Envisat data to fill in the time period from November 2006 to July 2010. In processing the Envisat data, we successfully employed a phase interpolation between persistent scatterer pixels to reduce the impact of vegetation decorrelation, which can significantly reduce the quality of C-band InSAR data over agricultural basins. In comparing the results from the L-band ALOS data and C-band Envisat data in a 10 month overlapping time period, we found that the shorter wavelength of C-band InSAR allowed us to preserve small deformation signals that were not detectable using L-band ALOS data. A significant result was the finding that the elastic storage properties of the SLV confined aquifer system remained stable over the 20 year time period and vary slowly in space, allowing us to combine InSAR data acquired from multiple missions to fill the temporal and spatial gaps in well data. The InSAR estimated head levels were validated with well measurements, which indicate little permanent water-storage loss over the study time period in the SLV.

Multiple remote sensing data sources to assess spatio-temporal patterns of fire incidence over Campos Amazônicos Savanna Vegetation Enclave (Brazilian Amazon).

PubMed

Alves, Daniel Borini; Pérez-Cabello, Fernando

2017-12-01

Fire activity plays an important role in the past, present and future of Earth system behavior. Monitoring and assessing spatial and temporal fire dynamics have a fundamental relevance in the understanding of ecological processes and the human impacts on different landscapes and multiple spatial scales. This work analyzes the spatio-temporal distribution of burned areas in one of the biggest savanna vegetation enclaves in the southern Brazilian Amazon, from 2000 to 2016, deriving information from multiple remote sensing data sources (Landsat and MODIS surface reflectance, TRMM pluviometry and Vegetation Continuous Field tree cover layers). A fire scars database with 30 m spatial resolution was generated using a Landsat time series. MODIS daily surface reflectance was used for accurate dating of the fire scars. TRMM pluviometry data were analyzed to dynamically establish time limits of the yearly dry season and burning periods. Burned area extent, frequency and recurrence were quantified comparing the results annually/seasonally. Additionally, Vegetation Continuous Field tree cover layers were used to analyze fire incidence over different types of tree cover domains. In the last seventeen years, 1.03millionha were burned within the study area, distributed across 1432 fire occurrences, highlighting 2005, 2010 and 2014 as the most affected years. Middle dry season fires represent 86.21% of the total burned areas and 32.05% of fire occurrences, affecting larger amount of higher density tree surfaces than other burning periods. The results provide new insights into the analysis of burned areas of the neotropical savannas, spatially and statistically reinforcing important aspects linked to the seasonality patterns of fire incidence in this landscape. Copyright © 2017 Elsevier B.V. All rights reserved.

Ocean acidification in the coastal zone from an organism's perspective: multiple system parameters, frequency domains, and habitats.

PubMed

Waldbusser, George G; Salisbury, Joseph E

2014-01-01

Multiple natural and anthropogenic processes alter the carbonate chemistry of the coastal zone in ways that either exacerbate or mitigate ocean acidification effects. Freshwater inputs and multiple acid-base reactions change carbonate chemistry conditions, sometimes synergistically. The shallow nature of these systems results in strong benthic-pelagic coupling, and marine invertebrates at different life history stages rely on both benthic and pelagic habitats. Carbonate chemistry in coastal systems can be highly variable, responding to processes with temporal modes ranging from seconds to centuries. Identifying scales of variability relevant to levels of biological organization requires a fuller characterization of both the frequency and magnitude domains of processes contributing to or reducing acidification in pelagic and benthic habitats. We review the processes that contribute to coastal acidification with attention to timescales of variability and habitats relevant to marine bivalves.

Fast dictionary generation and searching for magnetic resonance fingerprinting.

PubMed

Jun Xie; Mengye Lyu; Jian Zhang; Hui, Edward S; Wu, Ed X; Ze Wang

2017-07-01

A super-fast dictionary generation and searching (DGS) algorithm was developed for MR parameter quantification using magnetic resonance fingerprinting (MRF). MRF is a new technique for simultaneously quantifying multiple MR parameters using one temporally resolved MR scan. But it has a multiplicative computation complexity, resulting in a big burden of dictionary generating, saving, and retrieving, which can easily be intractable for any state-of-art computers. Based on retrospective analysis of the dictionary matching object function, a multi-scale ZOOM like DGS algorithm, dubbed as MRF-ZOOM, was proposed. MRF ZOOM is quasi-parameter-separable so the multiplicative computation complexity is broken into additive one. Evaluations showed that MRF ZOOM was hundreds or thousands of times faster than the original MRF parameter quantification method even without counting the dictionary generation time in. Using real data, it yielded nearly the same results as produced by the original method. MRF ZOOM provides a super-fast solution for MR parameter quantification.

Predictability and hierarchy in Drosophila behavior.

PubMed

Berman, Gordon J; Bialek, William; Shaevitz, Joshua W

2016-10-18

Even the simplest of animals exhibit behavioral sequences with complex temporal dynamics. Prominent among the proposed organizing principles for these dynamics has been the idea of a hierarchy, wherein the movements an animal makes can be understood as a set of nested subclusters. Although this type of organization holds potential advantages in terms of motion control and neural circuitry, measurements demonstrating this for an animal's entire behavioral repertoire have been limited in scope and temporal complexity. Here, we use a recently developed unsupervised technique to discover and track the occurrence of all stereotyped behaviors performed by fruit flies moving in a shallow arena. Calculating the optimally predictive representation of the fly's future behaviors, we show that fly behavior exhibits multiple time scales and is organized into a hierarchical structure that is indicative of its underlying behavioral programs and its changing internal states.

Scale invariance of temporal order discrimination using complex, naturalistic events

PubMed Central

Kwok, Sze Chai; Macaluso, Emiliano

2015-01-01

Recent demonstrations of scale invariance in cognitive domains prompted us to investigate whether a scale-free pattern might exist in retrieving the temporal order of events from episodic memory. We present four experiments using an encoding-retrieval paradigm with naturalistic stimuli (movies or video clips). Our studies show that temporal order judgement retrieval times were negatively correlated with the temporal separation between two events in the movie. This relation held, irrespective of whether temporal distances were on the order of tens of minutes (Exp 1−2) or just a few seconds (Exp 3−4). Using the SIMPLE model, we factored in the retention delays between encoding and retrieval (delays of 24 h, 15 min, 1.5–2.5 s, and 0.5 s for Exp 1–4, respectively) and computed a temporal similarity score for each trial. We found a positive relation between similarity and retrieval times; that is, the more temporally similar two events, the slower the retrieval of their temporal order. Using Bayesian analysis, we confirmed the equivalence of the RT/similarity relation across all experiments, which included a vast range of temporal distances and retention delays. These results provide evidence for scale invariance during the retrieval of temporal order of episodic memories. PMID:25909581

Hydrological connectivity for riverine fish: measurement challenges and research opportunities

USGS Publications Warehouse

Fullerton, A.H.; Burnett, K.M.; Steel, E.A.; Flitcroft, R.L.; Pess, G.R.; Feist, B.E.; Torgersen, Christian E.; Miller, D.J.; Sanderson, B.L.

2010-01-01

In this review, we first summarize how hydrologic connectivity has been studied for riverine fish capable of moving long distances, and then identify research opportunities that have clear conservation significance. Migratory species, such as anadromous salmonids, are good model organisms for understanding ecological connectivity in rivers because the spatial scale over which movements occur among freshwater habitats is large enough to be easily observed with available techniques; they are often economically or culturally valuable with habitats that can be easily fragmented by human activities; and they integrate landscape conditions from multiple surrounding catchment(s) with in‐river conditions. Studies have focussed on three themes: (i) relatively stable connections (connections controlled by processes that act over broad spatio‐temporal scales >1000 km2 and >100 years); (ii) dynamic connections (connections controlled by processes acting over fine to moderate spatio‐temporal scales ∼1–1000 km2 and <1–100 years); and (iii) anthropogenic influences on hydrologic connectivity, including actions that disrupt or enhance natural connections experienced by fish.We outline eight challenges to understanding the role of connectivity in riverine fish ecology, organized under three foci: (i) addressing the constraints of river structure; (ii) embracing temporal complexity in hydrologic connectivity; and (iii) managing connectivity for riverine fishes. Challenges include the spatial structure of stream networks, the force and direction of flow, scale‐dependence of connectivity, shifting boundaries, complexity of behaviour and life histories and quantifying anthropogenic influence on connectivity and aligning management goals. As we discuss each challenge, we summarize relevant approaches in the literature and provide additional suggestions for improving research and management of connectivity for riverine fishes.Specifically, we suggest that rapid advances are possible in the following arenas: (i) incorporating network structure and river discharge into analyses; (ii) increasing explicit consideration of temporal complexity and fish behaviour in the scope of analyses; and (iii) parsing degrees of human and natural influences on connectivity and defining acceptable alterations. Multiscale analyses are most likely to identify dominant patterns of connections and disconnections, and the appropriate scale at which to focus conservation activities.

Space Technology 5 Multi-Point Observations of Temporal Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, Guan; Wang, Yongli; Slavin, James A.; Strangeway, Robert J.

2008-01-01

Space Technology 5 (ST5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that meso-scale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of approximately 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are approximately 1 min for meso-scale currents and approximately 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Space-time modeling of soil moisture

NASA Astrophysics Data System (ADS)

Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio

2017-11-01

A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.

Influence of atmospheric transport on ozone and trace- level toxic air contaminants over the northeastern United States

NASA Astrophysics Data System (ADS)

Brankov, Elvira

This thesis presents a methodology for examining the relationship between synoptic-scale atmospheric transport patterns and observed pollutant concentration levels. It involves calculating a large number of back-trajectories from the observational site and subjecting them to cluster analysis. The pollutant concentration data observed at that site are then segregated according to the back-trajectory clusters. If the pollutant observations extend over several seasons, it is important to filter out seasonal and long-term components from the time series data before pollutant cluster-segregation, because only the short-term component of the time series data is related to the synoptic-scale transport. Multiple comparison procedures are used to test for significant differences in the chemical composition of pollutant data associated with each cluster. This procedure is useful in indicating potential pollutant source regions and isolating meteorological regimes associated with pollutant transport from those regions. If many observational sites are available, the spatial and temporal scales of the pollution transport from a given direction can be extracted through the time-lagged inter- site correlation analysis of pollutant concentrations. The proposed methodology is applicable to any pollutant at any site if sufficiently abundant data set is available. This is illustrated through examination of five-year long time series data of ozone concentrations at several sites in the Northeast. The results provide evidence of ozone transport to these sites, revealing the characteristic spatial and temporal scales involved in the transport and identifying source regions for this pollutant. Problems related to statistical analyses of censored data are addressed in the second half of this thesis. Although censoring (reporting concentrations in a non-quantitative way) is typical for trace-level measurements, methods for statistical analysis, inference and interpretation of such data are complex and still under development. In this study, multiple comparison of censored data sets was required in order to examine the influence of synoptic- scale circulations on concentration levels of several trace-level toxic pollutants observed in the Northeast (e.g., As, Se, Mn, V, etc.). Since the traditional multiple comparison procedures are not readily applicable to such data sets, a Monte Carlo simulation study was performed to assess several nonparametric methods for multiple comparison of censored data sets. Application of an appropriate comparison procedure to clusters of toxic trace elements observed in the Northeast led to the identification of potential source regions and atmospheric patterns associated with the long-range transport of these pollutants. A method for comparison of proportions and elemental ratio calculations were used to confirm/clarify these inferences with a greater degree of confidence.

Validation of the Temporal Satisfaction with Life Scale in a Sample of Chinese University Students

ERIC Educational Resources Information Center

Ye, Shengquan

2007-01-01

The study aims at validating the Temporal Satisfaction With Life Scale (TSWLS; Pavot et al., 1998, "The Temporal Satisfaction With Life Scale", Journal of Personality Assessment 70, pp. 340-354) in a non-western context. Data from 646 Chinese university students (330 females and 316 males) supported the three-factor structure of the…

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

NASA Astrophysics Data System (ADS)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are weak, especially when more stringent conditions are imposed (i.e. when T is very high), except at the monthly scale.

Characterizing Urban Air Quality to Provide Actionable Information

NASA Astrophysics Data System (ADS)

Lary, D. J.

2017-12-01

The urbanization of national and global populations is associated with increasing challenges to creation of sustainable and livable communities. In urban environments, there is currently a lack of accurate actionable information on atmospheric composition on fine spatial and temporal scales. There is a pressing need to better characterize the complex spatial distribution of environmental features of cityscapes and improve understanding of their relationship to health and quality of life. This talk gives an overview of integrating sensing of atmospheric composition on multiple scales using a wide range of devices from distributed low cost-sensors, to aerial vehicles, to satellites. Machine learning plays a key role in providing both the cross-calibration and turning the exposure dosimetry into actionable insights for urban environments.

Ionospheric Multi-Point Measurements Using Tethered Satellite Sensors

NASA Technical Reports Server (NTRS)

Gilchrist, B. E.; Heelis, R. A.; Raitt, W. J.

1998-01-01

Many scientific questions concerning the distribution of electromagnetic fields and plasma structures in the ionosphere require measurements over relatively small temporal and spatial scales with as little ambiguity as possible. It is also often necessary to differentiate several geophysical parameters between horizontal and vertical gradients unambiguously. The availability of multiple tethered satellites or sensors, so-called "pearls-on-a-string," may make the necessary measurements practical. In this report we provide two examples of scientific questions which could benefit from such measurements (1) high-latitude magnetospheric-ionospheric coupling; and, (2) plasma structure impact on large and small-scale electrodynamics. Space tether state-of-the-art and special technical considerations addressing mission lifetime, sensor pointing, and multi-stream telemetry are reviewed.

Scaling Properties of Arctic Sea Ice Deformation in a High‐Resolution Viscous‐Plastic Sea Ice Model and in Satellite Observations

PubMed Central

Losch, Martin; Menemenlis, Dimitris

2018-01-01

Abstract Sea ice models with the traditional viscous‐plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan‐Arctic sea ice‐ocean simulation, the small‐scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data. PMID:29576996

Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations

NASA Astrophysics Data System (ADS)

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2018-01-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic sea ice-ocean simulation, the small-scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations.

PubMed

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2018-01-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic sea ice-ocean simulation, the small-scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Dynamic hydro-climatic networks in pristine and regulated rivers

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Variation in soil carbon dioxide efflux at two spatial scales in a topographically complex boreal forest

USGS Publications Warehouse

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.

Temporal scaling of the growth dependent optical properties of microalgae

NASA Astrophysics Data System (ADS)

Zhao, J. M.; Ma, C. Y.; Liu, L. H.

2018-07-01

The optical properties of microalgae are basic parameters for analyzing light field distribution in photobioreactors (PBRs). With the growth of microalgae cell, their optical properties will vary with growth time due to accumulation of pigment and lipid, cell division and metabolism. In this work, we report a temporal scaling behavior of the growth dependent optical properties of microalgae cell suspensions with both experimental and theoretical evidence presented. A new concept, the temporal scaling function (TSF), defined as the ratio of absorption or scattering cross-sections at growth phase to that at stationary phase, is introduced to characterize the temporal scaling behavior. The temporal evolution and temporal scaling characteristics of the absorption and scattering cross-sections of three example microalgae species, Chlorella vulgaris, Chlorella pyrenoidosa, and Chlorella protothecoides, were experimentally studied at spectral range 380-850 nm. It is shown that the TSFs of the absorption and scattering cross-sections for different microalgae species are approximately constant at different wavelength, which confirms theoretical predictions very well. With the aid of the temporal scaling relation, the optical properties at any growth time can be calculated based on those measured at stationary phase, hence opens a new way to determine the time-dependent optical properties of microalgae. The findings of this work will help the understanding of time dependent optical properties of microalgae and facilitate their applications in light field analysis in PBRs design.

Pain, Fatigue, and Cognitive Symptoms Are Temporally Associated Within but Not Across Days in Multiple Sclerosis.

PubMed

Kratz, Anna L; Murphy, Susan L; Braley, Tiffany J

2017-11-01

To examine the temporal associations, within day and day to day, between pain, fatigue, depressed mood, and cognitive function in multiple sclerosis (MS). Repeated-measures study involving 7 days of ecological momentary assessment (EMA) of symptoms 5 times a day; multilevel mixed models were used to analyze data. Community. Ambulatory adults (N=107) with MS. Not applicable. EMA of pain, fatigue, depressed mood, and cognitive function rated on a 0 to 10 scale. Fatigue and pain were linked within day such that higher pain was associated with higher subsequent fatigue (B=.09, P=.04); likewise, higher fatigue was associated with higher pain in the following time frame (B=.05, P=.04). Poorer perceived cognitive function preceded increased subsequent pain (B=.08, P=.007) and fatigue (B=.10, P=.01) within day. Depressed mood was not temporally linked with other symptoms. In terms of day-to-day effects, a day of higher fatigue related to decreased next day fatigue (B=-.16, P=.01), and a day of higher depressed mood related to increased depressed mood the next day (B=.17, P=.01). There were no cross-symptom associations from one day to the next. Findings provide new insights on how common symptoms in MS relate to each other and vary within and over days. Pain and fatigue show evidence of a dynamic bidirectional relation over the course of a day, and worsening of perceived cognitive function preceded worsening of both pain and fatigue. Most temporal associations between symptoms occur within the course of a day, with relatively little carryover from one day to the next. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Disease and community structure: white-nose syndrome alters spatial and temporal niche partitioning in sympatric bat species

USGS Publications Warehouse

Jachowski, David S.; Dobony, Christopher A.; Coleman, Laci S.; Ford, W. Mark; Britzke, Eric R.; Rodrigue, Jane L.

2014-01-01

AimEmerging infectious diseases present a major perturbation with apparent direct effects such as reduced population density, extirpation and/or extinction. Comparatively less is known about the potential indirect effects of disease that likely alter community structure and larger ecosystem function. Since 2006, white-nose syndrome (WNS) has resulted in the loss of over 6 million hibernating bats in eastern North America. Considerable evidence exists concerning niche partitioning in sympatric bat species in this region, and the unprecedented, rapid decline in multiple species following WNS may provide an opportunity to observe a dramatic restructuring of the bat community.LocationWe conducted our study at Fort Drum Army Installation in Jefferson and Lewis counties, New York, USA, where WNS first impacted extant bat species in winter 2007–2008.MethodsAcoustical monitoring during 2003–2011 allowed us to test the hypothesis that spatial and temporal niche partitioning by bats was relaxed post-WNS.ResultsWe detected nine bat species pre- and post-WNS. Activity for most bat species declined post-WNS. Dramatic post-WNS declines in activity of little brown bat (Myotis lucifugus, MYLU), formerly the most abundant bat species in the region, were associated with complex, often species-specific responses by other species that generally favoured increased spatial and temporal overlap with MYLU.Main conclusionsIn addition to the obvious direct effects of disease on bat populations and activity levels, our results provide evidence that disease can have cascading indirect effects on community structure. Recent occurrence of WNS in North America, combined with multiple existing stressors, is resulting in dramatic shifts in temporal and spatial niche partitioning within bat communities. These changes might influence long-term population viability of some bat species as well as broader scale ecosystem structure and function.

Linking innovative measurement technologies (ConMon and Dataflow© systems) for high-resolution temporal and spatial dissolved oxygen criteria assessment.

PubMed

O'Leary, C A; Perry, E; Bayard, A; Wainger, L; Boynton, W R

2015-10-01

One consequence of nutrient-induced eutrophication in shallow estuarine waters is the occurrence of hypoxia and anoxia that has serious impacts on biota, habitats, and biogeochemical cycles of important elements. Because of the important role of dissolved oxygen (DO) on these ecosystem features, a variety of DO criteria have been established as indicators of system condition. However, DO dynamics are complex and vary on time scales ranging from diel to decadal and spatial scales from meters to multiple kilometers. Because of these complexities, determining DO criteria attainment or failure remains difficult. We propose a method for linking two common measurement technologies for shallow water DO criteria assessment using a Chesapeake Bay tributary as a test case. Dataflow© is a spatially intensive (30-60-m collection intervals) system used to map surface water conditions at the whole estuary scale, and ConMon is a high-frequency (15-min collection intervals) fixed station approach. The former technology is effective with spatial descriptions but poor regarding temporal resolution, while the latter provides excellent temporal but very limited spatial resolution. Our methodology for combining the strengths of these measurement technologies involved a sequence of steps. First, a statistical model of surface water DO dynamics, based on temporally intense ConMon data, was developed. The results of this model were used to calculate daily DO minimum concentrations. Second, this model was then inserted into Dataflow©-generated spatial maps of DO conditions and used to adjust measured DO concentrations to daily minimum concentrations. This information was used to assess DO criteria compliance at the full tributary scale. Model results indicated that it is vital to consider the short-term time scale DO criteria across both space and time concurrently. Large fluctuations in DO occurred within a 24-h time period, and DO dynamics varied across the length and width of the tributary. The overall result provided a more detailed and realistic characterization of the shallow water DO minimum conditions that have the potential to be extended to other tributaries and regions. Broader applications of this model include instantaneous DO criteria assessment, utilizing this model in combination with aerial remote sensing, and developing DO amplitude as an indicator of impaired water bodies.

Space Technology 5 (ST-5) Observations of Field-Aligned Currents: Temporal Variability

NASA Technical Reports Server (NTRS)

Le, Guan

2010-01-01

Space Technology 5 (ST-5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from STS. The data demonstrate that masoscale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of about 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are about I min for meso-scale currents and about 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Space Technology 5 (ST-5) Multipoint Observations of Temporal and Spatial Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, Guan

2010-01-01

Space Technology 5 (ST-5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that mesoscale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of about 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are about 1 min for meso-scale currents and about 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

The Temporal Focus Scale: Factor Structure and Association with Alcohol Use in a Sample of Northern Irish School Children

ERIC Educational Resources Information Center

McKay, Michael T.; Percy, Andrew; Goudie, Andrew J.; Sumnall, Harry R.; Cole, Jon C.

2012-01-01

The Temporal Focus Scale (TFS) is a 12-item self-report measure of cognitive engagement with the temporal domains of past, present and future. Developed in college student samples, a three-factor structure with adequate reliability and validity was documented in a series of independent studies. We tested the factor structure of the scale in a…

Classification and Weakly Supervised Pain Localization using Multiple Segment Representation.

PubMed

Sikka, Karan; Dhall, Abhinav; Bartlett, Marian Stewart

2014-10-01

Automatic pain recognition from videos is a vital clinical application and, owing to its spontaneous nature, poses interesting challenges to automatic facial expression recognition (AFER) research. Previous pain vs no-pain systems have highlighted two major challenges: (1) ground truth is provided for the sequence, but the presence or absence of the target expression for a given frame is unknown, and (2) the time point and the duration of the pain expression event(s) in each video are unknown. To address these issues we propose a novel framework (referred to as MS-MIL) where each sequence is represented as a bag containing multiple segments, and multiple instance learning (MIL) is employed to handle this weakly labeled data in the form of sequence level ground-truth. These segments are generated via multiple clustering of a sequence or running a multi-scale temporal scanning window, and are represented using a state-of-the-art Bag of Words (BoW) representation. This work extends the idea of detecting facial expressions through 'concept frames' to 'concept segments' and argues through extensive experiments that algorithms such as MIL are needed to reap the benefits of such representation. The key advantages of our approach are: (1) joint detection and localization of painful frames using only sequence-level ground-truth, (2) incorporation of temporal dynamics by representing the data not as individual frames but as segments, and (3) extraction of multiple segments, which is well suited to signals with uncertain temporal location and duration in the video. Extensive experiments on UNBC-McMaster Shoulder Pain dataset highlight the effectiveness of the approach by achieving competitive results on both tasks of pain classification and localization in videos. We also empirically evaluate the contributions of different components of MS-MIL. The paper also includes the visualization of discriminative facial patches, important for pain detection, as discovered by our algorithm and relates them to Action Units that have been associated with pain expression. We conclude the paper by demonstrating that MS-MIL yields a significant improvement on another spontaneous facial expression dataset, the FEEDTUM dataset.

Overview of the Bushland Evapotranspiration and Agricultural Remote sensing EXperiment 2008 (BEAREX08): A field experiment evaluating methods for quantifying ET at multiple scales

NASA Astrophysics Data System (ADS)

Evett, Steven R.; Kustas, William P.; Gowda, Prasanna H.; Anderson, Martha C.; Prueger, John H.; Howell, Terry A.

2012-12-01

In 2008, scientists from seven federal and state institutions worked together to investigate temporal and spatial variations of evapotranspiration (ET) and surface energy balance in a semi-arid irrigated and dryland agricultural region of the Southern High Plains in the Texas Panhandle. This Bushland Evapotranspiration and Agricultural Remote sensing EXperiment 2008 (BEAREX08) involved determination of micrometeorological fluxes (surface energy balance) in four weighing lysimeter fields (each 4.7 ha) containing irrigated and dryland cotton and in nearby bare soil, wheat stubble and rangeland fields using nine eddy covariance stations, three large aperture scintillometers, and three Bowen ratio systems. In coordination with satellite overpasses, flux and remote sensing aircraft flew transects over the surrounding fields and region encompassing an area contributing fluxes from 10 to 30 km upwind of the USDA-ARS lysimeter site. Tethered balloon soundings were conducted over the irrigated fields to investigate the effect of advection on local boundary layer development. Local ET was measured using four large weighing lysimeters, while field scale estimates were made by soil water balance with a network of neutron probe profile water sites and from the stationary flux systems. Aircraft and satellite imagery were obtained at different spatial and temporal resolutions. Plot-scale experiments dealt with row orientation and crop height effects on spatial and temporal patterns of soil surface temperature, soil water content, soil heat flux, evaporation from soil in the interrow, plant transpiration and canopy and soil radiation fluxes. The BEAREX08 field experiment was unique in its assessment of ET fluxes over a broad range in spatial scales; comparing direct and indirect methods at local scales with remote sensing based methods and models using aircraft and satellite imagery at local to regional scales, and comparing mass balance-based ET ground truth with eddy covariance and remote sensing-based methods. Here we present an overview of the experiment and a summary of preliminary findings described in this special issue of AWR. Our understanding of the role of advection in the measurement and modeling of ET is advanced by these papers integrating measurements and model estimates.

Sampling scales define occupancy and underlying occupancy-abundance relationships in animals.

PubMed

Steenweg, Robin; Hebblewhite, Mark; Whittington, Jesse; Lukacs, Paul; McKelvey, Kevin

2018-01-01

Occupancy-abundance (OA) relationships are a foundational ecological phenomenon and field of study, and occupancy models are increasingly used to track population trends and understand ecological interactions. However, these two fields of ecological inquiry remain largely isolated, despite growing appreciation of the importance of integration. For example, using occupancy models to infer trends in abundance is predicated on positive OA relationships. Many occupancy studies collect data that violate geographical closure assumptions due to the choice of sampling scales and application to mobile organisms, which may change how occupancy and abundance are related. Little research, however, has explored how different occupancy sampling designs affect OA relationships. We develop a conceptual framework for understanding how sampling scales affect the definition of occupancy for mobile organisms, which drives OA relationships. We explore how spatial and temporal sampling scales, and the choice of sampling unit (areal vs. point sampling), affect OA relationships. We develop predictions using simulations, and test them using empirical occupancy data from remote cameras on 11 medium-large mammals. Surprisingly, our simulations demonstrate that when using point sampling, OA relationships are unaffected by spatial sampling grain (i.e., cell size). In contrast, when using areal sampling (e.g., species atlas data), OA relationships are affected by spatial grain. Furthermore, OA relationships are also affected by temporal sampling scales, where the curvature of the OA relationship increases with temporal sampling duration. Our empirical results support these predictions, showing that at any given abundance, the spatial grain of point sampling does not affect occupancy estimates, but longer surveys do increase occupancy estimates. For rare species (low occupancy), estimates of occupancy will quickly increase with longer surveys, even while abundance remains constant. Our results also clearly demonstrate that occupancy for mobile species without geographical closure is not true occupancy. The independence of occupancy estimates from spatial sampling grain depends on the sampling unit. Point-sampling surveys can, however, provide unbiased estimates of occupancy for multiple species simultaneously, irrespective of home-range size. The use of occupancy for trend monitoring needs to explicitly articulate how the chosen sampling scales define occupancy and affect the occupancy-abundance relationship. © 2017 by the Ecological Society of America.

Examining fire-induced forest changes using novel remote sensing technique: a case study in a mixed pine-oak forest

NASA Astrophysics Data System (ADS)

Meng, R.; Wu, J.; Zhao, F. R.; Cook, B.; Hanavan, R. P.; Serbin, S.

2017-12-01

Fire-induced forest changes has long been a central focus for forest ecology and global carbon cycling studies, and is becoming a pressing issue for global change biologists particularly with the projected increases in the frequency and intensity of fire with a warmer and drier climate. Compared with time-consuming and labor intensive field-based approaches, remote sensing offers a promising way to efficiently assess fire effects and monitor post-fire forest responses across a range of spatial and temporal scales. However, traditional remote sensing studies relying on simple optical spectral indices or coarse resolution imagery still face a number of technical challenges, including confusion or contamination of the signal by understory dynamics and mixed pixels with moderate to coarse resolution data (>= 30 m). As such, traditional remote sensing may not meet the increasing demand for more ecologically-meaningful monitoring and quantitation of fire-induced forest changes. Here we examined the use of novel remote sensing technique (i.e. airborne imaging spectroscopy and LiDAR measurement, very high spatial resolution (VHR) space-borne multi-spectral measurement, and high temporal-spatial resolution UAS-based (Unmanned Aerial System) imagery), in combination with field and phenocam measurements to map forest burn severity across spatial scales, quantify crown-scale post-fire forest recovery rate, and track fire-induced phenology changes in the burned areas. We focused on a mixed pine-oak forest undergoing multiple fire disturbances for the past several years in Long Island, NY as a case study. We demonstrate that (1) forest burn severity mapping from VHR remote sensing measurement can capture crown-scale heterogeneous fire patterns over large-scale; (2) the combination of VHR optical and structural measurements provides an efficient means to remotely sense species-level post-fire forest responses; (3) the UAS-based remote sensing enables monitoring of fire-induced forest phenology changes at unprecedented temporal and spatial resolutions. This work provides the methodological approach monitor fire-induced forest changes in a spatially explicit manner across scales, with important implications for fire-related forest management and for constraining/benchmarking process models.

Does robot-assisted gait training ameliorate gait abnormalities in multiple sclerosis? A pilot randomized-control trial.

PubMed

Straudi, S; Benedetti, M G; Venturini, E; Manca, M; Foti, C; Basaglia, N

2013-01-01

Gait disorders are common in multiple sclerosis (MS) and lead to a progressive reduction of function and quality of life. Test the effects of robot-assisted gait rehabilitation in MS subjects through a pilot randomized-controlled study. We enrolled MS subjects with Expanded Disability Status Scale scores within 4.5-6.5. The experimental group received 12 robot-assisted gait training sessions over 6 weeks. The control group received the same amount of conventional physiotherapy. Outcomes measures were both biomechanical assessment of gait, including kinematics and spatio-temporal parameters, and clinical test of walking endurance (six-minute walk test) and mobility (Up and Go Test). 16 subjects (n = 8 experimental group, n = 8 control group) were included in the final analysis. At baseline the two groups were similar in all variables, except for step length. Data showed walking endurance, as well as spatio-temporal gait parameters improvements after robot-assisted gait training. Pelvic antiversion and reduced hip extension during terminal stance ameliorated after aforementioned intervention. Robot-assisted gait training seems to be effective in increasing walking competency in MS subjects. Moreover, it could be helpful in restoring the kinematic of the hip and pelvis.

Vortex scaling ranges in two-dimensional turbulence

NASA Astrophysics Data System (ADS)

Burgess, B. H.; Dritschel, D. G.; Scott, R. K.

2017-11-01

We survey the role of coherent vortices in two-dimensional turbulence, including formation mechanisms, implications for classical similarity and inertial range theories, and characteristics of the vortex populations. We review early work on the spatial and temporal scaling properties of vortices in freely evolving turbulence and more recent developments, including a spatiotemporal scaling theory for vortices in the forced inverse energy cascade. We emphasize that Kraichnan-Batchelor similarity theories and vortex scaling theories are best viewed as complementary and together provide a more complete description of two-dimensional turbulence. In particular, similarity theory has a continued role in describing the weak filamentary sea between the vortices. Moreover, we locate both classical inertial and vortex scaling ranges within the broader framework of scaling in far-from-equilibrium systems, which generically exhibit multiple fixed point solutions with distinct scaling behaviour. We describe how stationary transport in a range of scales comoving with the dilatation of flow features, as measured by the growth in vortex area, constrains the vortex number density in both freely evolving and forced two-dimensional turbulence. The new theories for coherent vortices reveal previously hidden nontrivial scaling, point to new dynamical understanding, and provide a novel exciting window into two-dimensional turbulence.

Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

NASA Technical Reports Server (NTRS)

McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall

2008-01-01

The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify a variety of plant phenomena and improve monitoring capabilities.

Liquid crystal templating as an approach to spatially and temporally organise soft matter.

PubMed

van der Asdonk, Pim; Kouwer, Paul H J

2017-10-02

Chemistry quickly moves from a molecular science to a systems science. This requires spatial and temporal control over the organisation of molecules and molecular assemblies. Whilst Nature almost by default (transiently) organises her components at multiple different length scales, scientists struggle to realise even relatively straightforward patterns. In the past decades, supramolecular chemistry has taught us the rules to precisely engineer molecular assembly at the nanometre scale. At higher length scales, however, we are bound to top-down nanotechnology techniques to realise order. For soft, biological matter, many of these top-down techniques come with serious limitations since the molecules generally show low susceptibilities to the applied stimuli. A new method is based on liquid crystal templating. In this hierarchical approach, a liquid crystalline host serves as the scaffold to order polymers or assemblies. Being a liquid crystal, the host material can be ordered at many different length scales and on top of that, is highly susceptible to many external stimuli, which can even be used to manipulate the liquid crystal organisation in time. As a result, we anticipate large control over the organisation of the materials inside the liquid crystalline host. Recently, liquid crystal templating was also realised in water. This suddenly makes this tool highly applicable to start organising more delicate biological materials or even small organisms. We review the scope and limitations of liquid crystal templating and look out to where the technique may lead us.

Short-term Music Training Enhances Complex, Distributed Neural Communication during Music and Linguistic Tasks

PubMed Central

Carpentier, Sarah M.; Moreno, Sylvain; McIntosh, Anthony R.

2016-01-01

Musical training is frequently associated with benefits to linguistic abilities, and recent focus has been placed on possible benefits of bilingualism to lifelong executive functions; however, the neural mechanisms for such effects are unclear. The aim of this study was to gain better understanding of the whole-brain functional effects of music and second-language training that could support such previously observed cognitive transfer effects. We conducted a 28-day longitudinal study of monolingual English-speaking 4- to 6-year-old children randomly selected to receive daily music or French language training, excluding weekends. Children completed passive EEG music note and French vowel auditory oddball detection tasks before and after training. Brain signal complexity was measured on source waveforms at multiple temporal scales as an index of neural information processing and network communication load. Comparing pretraining with posttraining, musical training was associated with increased EEG complexity at coarse temporal scales during the music and French vowel tasks in widely distributed cortical regions. Conversely, very minimal decreases in complexity at fine scales and trends toward coarse-scale increases were displayed after French training during the tasks. Spectral analysis failed to distinguish between training types and found overall theta (3.5–7.5 Hz) power increases after all training forms, with spatially fewer decreases in power at higher frequencies (>10 Hz). These findings demonstrate that musical training increased diversity of brain network states to support domain-specific music skill acquisition and music-to-language transfer effects. PMID:27243611

Short-term Music Training Enhances Complex, Distributed Neural Communication during Music and Linguistic Tasks.

PubMed

Carpentier, Sarah M; Moreno, Sylvain; McIntosh, Anthony R

2016-10-01

Musical training is frequently associated with benefits to linguistic abilities, and recent focus has been placed on possible benefits of bilingualism to lifelong executive functions; however, the neural mechanisms for such effects are unclear. The aim of this study was to gain better understanding of the whole-brain functional effects of music and second-language training that could support such previously observed cognitive transfer effects. We conducted a 28-day longitudinal study of monolingual English-speaking 4- to 6-year-old children randomly selected to receive daily music or French language training, excluding weekends. Children completed passive EEG music note and French vowel auditory oddball detection tasks before and after training. Brain signal complexity was measured on source waveforms at multiple temporal scales as an index of neural information processing and network communication load. Comparing pretraining with posttraining, musical training was associated with increased EEG complexity at coarse temporal scales during the music and French vowel tasks in widely distributed cortical regions. Conversely, very minimal decreases in complexity at fine scales and trends toward coarse-scale increases were displayed after French training during the tasks. Spectral analysis failed to distinguish between training types and found overall theta (3.5-7.5 Hz) power increases after all training forms, with spatially fewer decreases in power at higher frequencies (>10 Hz). These findings demonstrate that musical training increased diversity of brain network states to support domain-specific music skill acquisition and music-to-language transfer effects.

Process scales in catchment science: a new synthesis

EPA Science Inventory

Concerns surrounding data resolution, choice of spatial and temporal scales in research design, and problems with extrapolation of processes across spatial and temporal scales differ greatly between scientific process-elucidation research and scenario exploration for watershed ma...

Interictal Epileptiform Discharges Impair Word Recall in Multiple Brain Areas

PubMed Central

Horak, Peter C.; Meisenhelter, Stephen; Song, Yinchen; Testorf, Markus E.; Kahana, Michael J.; Viles, Weston D.; Bujarski, Krzysztof A.; Connolly, Andrew C.; Robbins, Ashlee A.; Sperling, Michael R.; Sharan, Ashwini D.; Worrell, Gregory A.; Miller, Laura R.; Gross, Robert E.; Davis, Kathryn A.; Roberts, David W.; Lega, Bradley; Sheth, Sameer A.; Zaghloul, Kareem A.; Stein, Joel M.; Das, Sandhitsu R.; Rizzuto, Daniel S.; Jobst, Barbara C.

2016-01-01

Summary Objectives Interictal epileptiform discharges (IEDs) have been linked to memory impairment, but the spatial and temporal dynamics of this relationship remain elusive. In the present study, we aim to systematically characterize the brain areas and times at which IEDs affect memory. Methods Eighty epilepsy patients participated in a delayed free recall task while undergoing intracranial EEG monitoring. We analyzed the locations and timing of IEDs relative to the behavioral data in order to measure their effects on memory. Results Overall IED rates did not correlate with task performance across subjects (r = 0.03, p = 0.8). However, at a finer temporal scale, within-subject memory was negatively affected by IEDs during the encoding and recall periods of the task but not during the rest and distractor periods (p < 0.01, p < 0.001, p = 0.3, and p = 0.8 respectively). The effects of IEDs during encoding and recall were stronger in the left hemisphere than in the right (p < 0.05). Out of six brain areas analyzed, IEDs in the inferior temporal, medial temporal, and parietal areas significantly affected memory (false discovery rate < 0.05). Significance These findings reveal a network of brain areas sensitive to IEDs with key nodes in temporal as well as parietal lobes. They also demonstrate the time-dependent effects of IEDs in this network on memory. PMID:27935031

The joint space-time statistics of macroweather precipitation, space-time statistical factorization and macroweather models

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

Lovejoy, S., E-mail: lovejoy@physics.mcgill.ca; Lima, M. I. P. de; Department of Civil Engineering, University of Coimbra, 3030-788 Coimbra

2015-07-15

Over the range of time scales from about 10 days to 30–100 years, in addition to the familiar weather and climate regimes, there is an intermediate “macroweather” regime characterized by negative temporal fluctuation exponents: implying that fluctuations tend to cancel each other out so that averages tend to converge. We show theoretically and numerically that macroweather precipitation can be modeled by a stochastic weather-climate model (the Climate Extended Fractionally Integrated Flux, model, CEFIF) first proposed for macroweather temperatures and we show numerically that a four parameter space-time CEFIF model can approximately reproduce eight or so empirical space-time exponents. In spitemore » of this success, CEFIF is theoretically and numerically difficult to manage. We therefore propose a simplified stochastic model in which the temporal behavior is modeled as a fractional Gaussian noise but the spatial behaviour as a multifractal (climate) cascade: a spatial extension of the recently introduced ScaLIng Macroweather Model, SLIMM. Both the CEFIF and this spatial SLIMM model have a property often implicitly assumed by climatologists that climate statistics can be “homogenized” by normalizing them with the standard deviation of the anomalies. Physically, it means that the spatial macroweather variability corresponds to different climate zones that multiplicatively modulate the local, temporal statistics. This simplified macroweather model provides a framework for macroweather forecasting that exploits the system's long range memory and spatial correlations; for it, the forecasting problem has been solved. We test this factorization property and the model with the help of three centennial, global scale precipitation products that we analyze jointly in space and in time.« less

On the role of hydrogel structure and degradation in controlling the transport of cell-secreted matrix molecules for engineered cartilage.

PubMed

Dhote, Valentin; Skaalure, Stacey; Akalp, Umut; Roberts, Justine; Bryant, Stephanie J; Vernerey, Franck J

2013-03-01

Damage to cartilage caused by injury or disease can lead to pain and loss of mobility, diminishing one's quality of life. Because cartilage has a limited capacity for self-repair, tissue engineering strategies, such as cells encapsulated in synthetic hydrogels, are being investigated as a means to restore the damaged cartilage. However, strategies to date are suboptimal in part because designing degradable hydrogels is complicated by structural and temporal complexities of the gel and evolving tissue along multiple length scales. To address this problem, this study proposes a multi-scale mechanical model using a triphasic formulation (solid, fluid, unbound matrix molecules) based on a single chondrocyte releasing extracellular matrix molecules within a degrading hydrogel. This model describes the key players (cells, proteoglycans, collagen) of the biological system within the hydrogel encompassing different length scales. Two mechanisms are included: temporal changes of bulk properties due to hydrogel degradation, and matrix transport. Numerical results demonstrate that the temporal change of bulk properties is a decisive factor in the diffusion of unbound matrix molecules through the hydrogel. Transport of matrix molecules in the hydrogel contributes both to the development of the pericellular matrix and the extracellular matrix and is dependent on the relative size of matrix molecules and the hydrogel mesh. The numerical results also demonstrate that osmotic pressure, which leads to changes in mesh size, is a key parameter for achieving a larger diffusivity for matrix molecules in the hydrogel. The numerical model is confirmed with experimental results of matrix synthesis by chondrocytes in biodegradable poly(ethylene glycol)-based hydrogels. This model may ultimately be used to predict key hydrogel design parameters towards achieving optimal cartilage growth. Copyright © 2012 Elsevier Ltd. All rights reserved.

On the role of hydrogel structure and degradation in controlling the transport of cell-secreted matrix molecules for engineered cartilage

PubMed Central

Dhote, Valentin; Skaalure, Stacey; Akalp, Umut; Roberts, Justine; Bryant, Stephanie J.; Vernerey, Franck J.

2012-01-01

Damage to cartilage caused by injury or disease can lead to pain and loss of mobility, diminishing one’s quality of life. Because cartilage has a limited capacity for self-repair, tissue engineering strategies, such as cells encapsulated in synthetic hydrogels, are being investigated as a means to restore the damaged cartilage. However, strategies to date are suboptimal in part because designing degradable hydrogels is complicated by structural and temporal complexities of the gel and evolving tissue along multiple length scales. To address this problem, this study proposes a multi-scale mechanical model using a triphasic formulation (solid, fluid, unbound matrix molecules) based on a single chondrocyte releasing extracellular matrix molecules within a degrading hydrogel. This model describes the key players (cells, proteoglycans, collagen) of the biological system within the hydrogel encompassing different length scales. Two mechanisms are included: temporal changes of bulk properties due to hydrogel degradation, and matrix transport. Numerical results demonstrate that the temporal change of bulk properties is a decisive factor in the diffusion of unbound matrix molecules through the hydrogel. Transport of matrix molecules in the hydrogel contributes both to the development of the pericellular matrix and the extracellular matrix and is dependent on the relative size of matrix molecules and the hydrogel mesh. The numerical results also demonstrate that osmotic pressure, which leads to changes in mesh size, is a key parameter for achieving a larger diffusivity for matrix molecules in the hydrogel. The numerical model is confirmed with experimental results of matrix synthesis by chondrocytes in biodegradable poly(ethylene glycol)-based hydrogels. This model may ultimately be used to predict key hydrogel design parameters towards achieving optimal cartilage growth. PMID:23276516

Multi-scale computation methods: Their applications in lithium-ion battery research and development

NASA Astrophysics Data System (ADS)

Siqi, Shi; Jian, Gao; Yue, Liu; Yan, Zhao; Qu, Wu; Wangwei, Ju; Chuying, Ouyang; Ruijuan, Xiao

2016-01-01

Based upon advances in theoretical algorithms, modeling and simulations, and computer technologies, the rational design of materials, cells, devices, and packs in the field of lithium-ion batteries is being realized incrementally and will at some point trigger a paradigm revolution by combining calculations and experiments linked by a big shared database, enabling accelerated development of the whole industrial chain. Theory and multi-scale modeling and simulation, as supplements to experimental efforts, can help greatly to close some of the current experimental and technological gaps, as well as predict path-independent properties and help to fundamentally understand path-independent performance in multiple spatial and temporal scales. Project supported by the National Natural Science Foundation of China (Grant Nos. 51372228 and 11234013), the National High Technology Research and Development Program of China (Grant No. 2015AA034201), and Shanghai Pujiang Program, China (Grant No. 14PJ1403900).

Simple and Multiple Endmember Mixture Analysis in the Boreal Forest

NASA Technical Reports Server (NTRS)

Roberts, Dar A.; Gamon, John A.; Qiu, Hong-Lie

2000-01-01

A key scientific objective of the original Boreal Ecosystem-Atmospheric Study (BOREAS) field campaign (1993-1996) was to obtain the baseline data required for modeling and predicting fluxes of energy, mass, and trace gases in the boreal forest biome. These data sets are necessary to determine the sensitivity of the boreal forest biome to potential climatic changes and potential biophysical feedbacks on climate. A considerable volume of remotely sensed and supporting field data were acquired by numerous researchers to meet this objective. By design, remote sensing and modeling were considered critical components for scaling efforts, extending point measurements from flux towers and field sites over larger spatial and longer temporal scales. A major focus of the BOREAS Follow-on program was concerned with integrating the diverse remotely sensed and ground-based data sets to address specific questions such as carbon dynamics at local to regional scales.

Telescopic multi-resolution augmented reality

NASA Astrophysics Data System (ADS)

Jenkins, Jeffrey; Frenchi, Christopher; Szu, Harold

2014-05-01

To ensure a self-consistent scaling approximation, the underlying microscopic fluctuation components can naturally influence macroscopic means, which may give rise to emergent observable phenomena. In this paper, we describe a consistent macroscopic (cm-scale), mesoscopic (micron-scale), and microscopic (nano-scale) approach to introduce Telescopic Multi-Resolution (TMR) into current Augmented Reality (AR) visualization technology. We propose to couple TMR-AR by introducing an energy-matter interaction engine framework that is based on known Physics, Biology, Chemistry principles. An immediate payoff of TMR-AR is a self-consistent approximation of the interaction between microscopic observables and their direct effect on the macroscopic system that is driven by real-world measurements. Such an interdisciplinary approach enables us to achieve more than multiple scale, telescopic visualization of real and virtual information but also conducting thought experiments through AR. As a result of the consistency, this framework allows us to explore a large dimensionality parameter space of measured and unmeasured regions. Towards this direction, we explore how to build learnable libraries of biological, physical, and chemical mechanisms. Fusing analytical sensors with TMR-AR libraries provides a robust framework to optimize testing and evaluation through data-driven or virtual synthetic simulations. Visualizing mechanisms of interactions requires identification of observable image features that can indicate the presence of information in multiple spatial and temporal scales of analog data. The AR methodology was originally developed to enhance pilot-training as well as `make believe' entertainment industries in a user-friendly digital environment We believe TMR-AR can someday help us conduct thought experiments scientifically, to be pedagogically visualized in a zoom-in-and-out, consistent, multi-scale approximations.

Innovative Visualizations Shed Light on Avian Nocturnal Migration

PubMed Central

Farnsworth, Andrew; Aelterman, Bart; Alves, Jose A.; Azijn, Kevin; Bernstein, Garrett; Branco, Sérgio; Desmet, Peter; Dokter, Adriaan M.; Horton, Kyle; Kelling, Steve; Kelly, Jeffrey F.; Leijnse, Hidde; Rong, Jingjing; Sheldon, Daniel; Van den Broeck, Wouter; Van Den Meersche, Jan Klaas; Van Doren, Benjamin Mark; van Gasteren, Hans

2016-01-01

Globally, billions of flying animals undergo seasonal migrations, many of which occur at night. The temporal and spatial scales at which migrations occur and our inability to directly observe these nocturnal movements makes monitoring and characterizing this critical period in migratory animals’ life cycles difficult. Remote sensing, therefore, has played an important role in our understanding of large-scale nocturnal bird migrations. Weather surveillance radar networks in Europe and North America have great potential for long-term low-cost monitoring of bird migration at scales that have previously been impossible to achieve. Such long-term monitoring, however, poses a number of challenges for the ornithological and ecological communities: how does one take advantage of this vast data resource, integrate information across multiple sensors and large spatial and temporal scales, and visually represent the data for interpretation and dissemination, considering the dynamic nature of migration? We assembled an interdisciplinary team of ecologists, meteorologists, computer scientists, and graphic designers to develop two different flow visualizations, which are interactive and open source, in order to create novel representations of broad-front nocturnal bird migration to address a primary impediment to long-term, large-scale nocturnal migration monitoring. We have applied these visualization techniques to mass bird migration events recorded by two different weather surveillance radar networks covering regions in Europe and North America. These applications show the flexibility and portability of such an approach. The visualizations provide an intuitive representation of the scale and dynamics of these complex systems, are easily accessible for a broad interest group, and are biologically insightful. Additionally, they facilitate fundamental ecological research, conservation, mitigation of human–wildlife conflicts, improvement of meteorological products, and public outreach, education, and engagement. PMID:27557096

Innovative Visualizations Shed Light on Avian Nocturnal Migration.

PubMed

Shamoun-Baranes, Judy; Farnsworth, Andrew; Aelterman, Bart; Alves, Jose A; Azijn, Kevin; Bernstein, Garrett; Branco, Sérgio; Desmet, Peter; Dokter, Adriaan M; Horton, Kyle; Kelling, Steve; Kelly, Jeffrey F; Leijnse, Hidde; Rong, Jingjing; Sheldon, Daniel; Van den Broeck, Wouter; Van Den Meersche, Jan Klaas; Van Doren, Benjamin Mark; van Gasteren, Hans

2016-01-01

Globally, billions of flying animals undergo seasonal migrations, many of which occur at night. The temporal and spatial scales at which migrations occur and our inability to directly observe these nocturnal movements makes monitoring and characterizing this critical period in migratory animals' life cycles difficult. Remote sensing, therefore, has played an important role in our understanding of large-scale nocturnal bird migrations. Weather surveillance radar networks in Europe and North America have great potential for long-term low-cost monitoring of bird migration at scales that have previously been impossible to achieve. Such long-term monitoring, however, poses a number of challenges for the ornithological and ecological communities: how does one take advantage of this vast data resource, integrate information across multiple sensors and large spatial and temporal scales, and visually represent the data for interpretation and dissemination, considering the dynamic nature of migration? We assembled an interdisciplinary team of ecologists, meteorologists, computer scientists, and graphic designers to develop two different flow visualizations, which are interactive and open source, in order to create novel representations of broad-front nocturnal bird migration to address a primary impediment to long-term, large-scale nocturnal migration monitoring. We have applied these visualization techniques to mass bird migration events recorded by two different weather surveillance radar networks covering regions in Europe and North America. These applications show the flexibility and portability of such an approach. The visualizations provide an intuitive representation of the scale and dynamics of these complex systems, are easily accessible for a broad interest group, and are biologically insightful. Additionally, they facilitate fundamental ecological research, conservation, mitigation of human-wildlife conflicts, improvement of meteorological products, and public outreach, education, and engagement.

Upscaling Ameriflux observations to assess drought impacts on gross primary productivity across the Southwest

NASA Astrophysics Data System (ADS)

Barnes, M.; Moore, D. J.; Scott, R. L.; MacBean, N.; Ponce-Campos, G. E.; Breshears, D. D.

2017-12-01

Both satellite observations and eddy covariance estimates provide crucial information about the Earth's carbon, water and energy cycles. Continuous measurements from flux towers facilitate exploration of the exchange of carbon dioxide, water and energy between the land surface and the atmosphere at fine temporal and spatial scales, while satellite observations can fill in the large spatial gaps of in-situ measurements and provide long-term temporal continuity. The Southwest (Southwest United States and Northwest Mexico) and other semi-arid regions represent a key uncertainty in interannual variability in carbon uptake. Comparisons of existing global upscaled gross primary production (GPP) products with flux tower data at sites across the Southwest show widespread mischaracterization of seasonality in vegetation carbon uptake, resulting in large (up to 200%) errors in annual carbon uptake estimates. Here, remotely sensed and distributed meteorological inputs are used to upscale GPP estimates from 25 Ameriflux towers across the Southwest to the regional scale using a machine learning approach. Our random forest model incorporates two novel features that improve the spatial and temporal variability in GPP. First, we incorporate a multi-scalar drought index at multiple timescales to account for differential seasonality between ecosystem types. Second, our machine learning algorithm was trained on twenty five ecologically diverse sites to optimize both the monthly variability in and the seasonal cycle of GPP. The product and its components will be used to examine drought impacts on terrestrial carbon cycling across the Southwest including the effects of drought seasonality and on carbon uptake. Our spatially and temporally continuous upscaled GPP product drawing from both ground and satellite data over the Southwest region helps us understand linkages between the carbon and water cycles in semi-arid ecosystems and informs predictions of vegetation response to future climate conditions.

The Schaake shuffle: A method for reconstructing space-time variability in forecasted precipitation and temperature fields

USGS Publications Warehouse

Clark, M.R.; Gangopadhyay, S.; Hay, L.; Rajagopalan, B.; Wilby, R.

2004-01-01

A number of statistical methods that are used to provide local-scale ensemble forecasts of precipitation and temperature do not contain realistic spatial covariability between neighboring stations or realistic temporal persistence for subsequent forecast lead times. To demonstrate this point, output from a global-scale numerical weather prediction model is used in a stepwise multiple linear regression approach to downscale precipitation and temperature to individual stations located in and around four study basins in the United States. Output from the forecast model is downscaled for lead times up to 14 days. Residuals in the regression equation are modeled stochastically to provide 100 ensemble forecasts. The precipitation and temperature ensembles from this approach have a poor representation of the spatial variability and temporal persistence. The spatial correlations for downscaled output are considerably lower than observed spatial correlations at short forecast lead times (e.g., less than 5 days) when there is high accuracy in the forecasts. At longer forecast lead times, the downscaled spatial correlations are close to zero. Similarly, the observed temporal persistence is only partly present at short forecast lead times. A method is presented for reordering the ensemble output in order to recover the space-time variability in precipitation and temperature fields. In this approach, the ensemble members for a given forecast day are ranked and matched with the rank of precipitation and temperature data from days randomly selected from similar dates in the historical record. The ensembles are then reordered to correspond to the original order of the selection of historical data. Using this approach, the observed intersite correlations, intervariable correlations, and the observed temporal persistence are almost entirely recovered. This reordering methodology also has applications for recovering the space-time variability in modeled streamflow. ?? 2004 American Meteorological Society.

Mapping and Monitoring Stream Aquatic Habitat With a Narrow-Beam Green Lidar

NASA Astrophysics Data System (ADS)

McKean, J.; Wright, W.; Kinzel, P.; Isaak, D.

2006-12-01

Stream environments are structured by complex biophysical processes that operate across multiple spatial and temporal scales. Disentangling these multiscalar and multicausal relationships is difficult, but fundamental to understanding, managing, and monitoring channel aquatic ecosystems. Standard field wading surveys of stream physical habitat are limited by cost and logistics to relatively small, isolated samples. Traditional remotely sensed surveys, including methods such as photogrammetry and near-infrared lidar, suffer from attenuation by water and do not directly map submerged channel topography. The Experimental Advanced Airborne Research Lidar (EAARL) is a full-waveform lidar with a unique ability to simultaneously map, with relatively high resolution, subaqueous and subaerial topography and the vegetation canopy. We have used the EAARL instrument to investigate two dissimilar stream ecosystems. We mapped 40km of low gradient, meandering, gravel-bed streams in central Idaho that are spawning habitat for threatened Chinook salmon. We are using the continuous three-dimensional channel maps to quantitatively explore how channel features affect the distribution of salmon spawning at multiple spatial scales and how modern stream and floodplain topography is related to post-glacial valley evolution. In contrast, the Platte River in central Nebraska is a wide and shallow, sand-bedded river that provides habitat for migratory water birds, including endangered species such as the whooping crane and least tern. Multi-temporal EAARL data are being used to map and monitor the physical response of the Platte River to habitat improvement projects that include in-channel and riparian vegetation removal and river flow augmentation to limit vegetation encroachment.

Modeling fatigue.

PubMed

Sumner, Walton; Xu, Jin Zhong

2002-01-01

The American Board of Family Practice is developing a patient simulation program to evaluate diagnostic and management skills. The simulator must give temporally and physiologically reasonable answers to symptom questions such as "Have you been tired?" A three-step process generates symptom histories. In the first step, the simulator determines points in time where it should calculate instantaneous symptom status. In the second step, a Bayesian network implementing a roughly physiologic model of the symptom generates a value on a severity scale at each sampling time. Positive, zero, and negative values represent increased, normal, and decreased status, as applicable. The simulator plots these values over time. In the third step, another Bayesian network inspects this plot and reports how the symptom changed over time. This mechanism handles major trends, multiple and concurrent symptom causes, and gradually effective treatments. Other temporal insights, such as observations about short-term symptom relief, require complimentary mechanisms.

Differences in the efficacy of climate forcings explained by variations in atmospheric boundary layer depth.

PubMed

Davy, Richard; Esau, Igor

2016-05-25

The Earth has warmed in the last century and a large component of that warming has been attributed to increased anthropogenic greenhouse gases. There are also numerous processes that introduce strong, regionalized variations to the overall warming trend. However, the ability of a forcing to change the surface air temperature depends on its spatial and temporal distribution. Here we show that the efficacy of a forcing is determined by the effective heat capacity of the atmosphere, which in cold and dry climates is defined by the depth of the planetary boundary layer. This can vary by an order of magnitude on different temporal and spatial scales, and so we get a strongly amplified temperature response in shallow boundary layers. This must be accounted for to assess the efficacy of a climate forcing, and also implies that multiple climate forcings cannot be linearly combined to determine the temperature response.

The method of pulsed x-ray detection with a diode laser.

PubMed

Liu, Jun; Ouyang, Xiaoping; Zhang, Zhongbing; Sheng, Liang; Chen, Liang; Tan, Xinjian; Weng, Xiufeng

2016-12-01

A new class of pulsed X-ray detection methods by sensing carrier changes in a diode laser cavity has been presented and demonstrated. The proof-of-principle experiments on detecting pulsed X-ray temporal profile have been done through the diode laser with a multiple quantum well active layer. The result shows that our method can achieve the aim of detecting the temporal profile of a pulsed X-ray source. We predict that there is a minimum value for the pre-bias current of the diode laser by analyzing the carrier rate equation, which exists near the threshold current of the diode laser chip in experiments. This behaviour generally agrees with the characterizations of theoretical analysis. The relative sensitivity is estimated at about 3.3 × 10 -17 C ⋅ cm 2 . We have analyzed the time scale of about 10 ps response with both rate equation and Monte Carlo methods.

Online Visualization and Analysis of Global Half-Hourly Infrared Satellite Data

NASA Technical Reports Server (NTRS)

Liu, Zhong; Ostrenga, Dana; Leptoukh, Gregory

2011-01-01

nfrared (IR) images (approximately 11-micron channel) recorded by satellite sensors have been widely used in weather forecasting, research, and classroom education since the Nimbus program. Unlike visible images, IR imagery can reveal cloud features without sunlight illumination; therefore, they can be used to monitor weather phenomena day and night. With geostationary satellites deployed around the globe, it is possible to monitor weather events 24/7 at a temporal resolution that polar-orbiting satellites cannot achieve at the present time. When IR data from multiple geostationary satellites are merged to form a single product--also known as a merged product--it allows for observing weather on a global scale. Its high temporal resolution (e.g., every half hour) also makes it an ideal ancillary dataset for supporting other satellite missions, such as the Tropical Rainfall Measuring Mission (TRMM), etc., by providing additional background information about weather system evolution.

Differences in the efficacy of climate forcings explained by variations in atmospheric boundary layer depth

PubMed Central

Davy, Richard; Esau, Igor

2016-01-01

The Earth has warmed in the last century and a large component of that warming has been attributed to increased anthropogenic greenhouse gases. There are also numerous processes that introduce strong, regionalized variations to the overall warming trend. However, the ability of a forcing to change the surface air temperature depends on its spatial and temporal distribution. Here we show that the efficacy of a forcing is determined by the effective heat capacity of the atmosphere, which in cold and dry climates is defined by the depth of the planetary boundary layer. This can vary by an order of magnitude on different temporal and spatial scales, and so we get a strongly amplified temperature response in shallow boundary layers. This must be accounted for to assess the efficacy of a climate forcing, and also implies that multiple climate forcings cannot be linearly combined to determine the temperature response. PMID:27221757

The Wavelet ToolKat: A set of tools for the analysis of series through wavelet transforms. Application to the channel curvature and the slope control of three free meandering rivers in the Amazon basin.

NASA Astrophysics Data System (ADS)

Vaudor, Lise; Piegay, Herve; Wawrzyniak, Vincent; Spitoni, Marie

2016-04-01

The form and functioning of a geomorphic system result from processes operating at various spatial and temporal scales. Longitudinal channel characteristics thus exhibit complex patterns which vary according to the scale of study, might be periodic or segmented, and are generally blurred by noise. Describing the intricate, multiscale structure of such signals, and identifying at which scales the patterns are dominant and over which sub-reach, could help determine at which scales they should be investigated, and provide insights into the main controlling factors. Wavelet transforms aim at describing data at multiple scales (either in time or space), and are now exploited in geophysics for the analysis of nonstationary series of data. They provide a consistent, non-arbitrary, and multiscale description of a signal's variations and help explore potential causalities. Nevertheless, their use in fluvial geomorphology, notably to study longitudinal patterns, is hindered by a lack of user-friendly tools to help understand, implement, and interpret them. We have developed a free application, The Wavelet ToolKat, designed to facilitate the use of wavelet transforms on temporal or spatial series. We illustrate its usefulness describing longitudinal channel curvature and slope of three freely meandering rivers in the Amazon basin (the Purus, Juruá and Madre de Dios rivers), using topographic data generated from NASA's Shuttle Radar Topography Mission (SRTM) in 2000. Three types of wavelet transforms are used, with different purposes. Continuous Wavelet Transforms are used to identify in a non-arbitrary way the dominant scales and locations at which channel curvature and slope vary. Cross-wavelet transforms, and wavelet coherence and phase are used to identify scales and locations exhibiting significant channel curvature and slope co-variations. Maximal Overlap Discrete Wavelet Transforms decompose data into their variations at a series of scales and are used to provide smoothed descriptions of the series at the scales deemed relevant.

Assessment of flow regime alterations over a spectrum of temporal scales using wavelet-based approaches

NASA Astrophysics Data System (ADS)

Wu, Fu-Chun; Chang, Ching-Fu; Shiau, Jenq-Tzong

2015-05-01

The full range of natural flow regime is essential for sustaining the riverine ecosystems and biodiversity, yet there are still limited tools available for assessment of flow regime alterations over a spectrum of temporal scales. Wavelet analysis has proven useful for detecting hydrologic alterations at multiple scales via the wavelet power spectrum (WPS) series. The existing approach based on the global WPS (GWPS) ratio tends to be dominated by the rare high-power flows so that alterations of the more frequent low-power flows are often underrepresented. We devise a new approach based on individual deviations between WPS (DWPS) that are root-mean-squared to yield the global DWPS (GDWPS). We test these two approaches on the three reaches of the Feitsui Reservoir system (Taiwan) that are subjected to different classes of anthropogenic interventions. The GDWPS reveal unique features that are not detected with the GWPS ratios. We also segregate the effects of individual subflow components on the overall flow regime alterations using the subflow GDWPS. The results show that the daily hydropeaking waves below the reservoir not only intensified the flow oscillations at daily scale but most significantly eliminated subweekly flow variability. Alterations of flow regime were most severe below the diversion weir, where the residual hydropeaking resulted in a maximum impact at daily scale while the postdiversion null flows led to large hydrologic alterations over submonthly scales. The smallest impacts below the confluence reveal that the hydrologic alterations at scales longer than 2 days were substantially mitigated with the joining of the unregulated tributary flows, whereas the daily-scale hydrologic alteration was retained because of the hydropeaking inherited from the reservoir releases. The proposed DWPS approach unravels for the first time the details of flow regime alterations at these intermediate scales that are overridden by the low-frequency high-power flows when the long-term averaged GWPS are used.

Assessing the Vulnerability of Streams to Increased Frequency and Severity of Low Flows in the Southeastern United States

NASA Astrophysics Data System (ADS)

Konrad, C. P.

2014-12-01

A changing climate poses risks to the availability and quality of water resources. Among the risks, increased frequency and severity of low flow periods in streams would be significant for many in-stream and out-of-stream uses of water. While down-scaled climate projections serve as the basis for understanding impacts of climate change on hydrologic systems, a robust framework for risk assessment incorporates multiple dimensions of risks including the vulnerability of hydrologic systems to climate change impacts. Streamflow records from the southeastern US were examined to assess the vulnerability of streams to increased frequency and severity of low flows. Long-term (>50 years) records provide evidence of more frequent and severe low flows in more streams than would be expected from random chance. Trends in low flows appear to be a result of changes in the temporal distribution rather than the annual amount of preciptation and/or in evaporation. Base flow recession provides an indicator of a stream's vulnerability to such changes. Linkages between streamflow patterns across temporal scales can be used for understanding and asessing stream responses to the various possible expressions of a changing climate.

Spatially and temporally resolved exciton dynamics and transport in single nanostructures and assemblies

NASA Astrophysics Data System (ADS)

Huang, Libai

2015-03-01

The frontier in solar energy conversion now lies in learning how to integrate functional entities across multiple length scales to create optimal devices. To address this new frontier, I will discuss our recent efforts on elucidating multi-scale energy transfer, migration, and dissipation processes with simultaneous femtosecond temporal resolution and nanometer spatial resolution. We have developed ultrafast microscopy that combines ultrafast spectroscopy with optical microscopy to map exciton dynamics and transport with simultaneous ultrafast time resolution and diffraction-limited spatial resolution. We have employed pump-probe transient absorption microscopy to elucidate morphology and structure dependent exciton dynamics and transport in single nanostructures and molecular assemblies. More specifically, (1) We have applied transient absorption microscopy (TAM) to probe environmental and structure dependent exciton relaxation pathways in sing-walled carbon nanotubes (SWNTs) by mapping dynamics in individual pristine SWNTs with known structures. (2) We have systematically measured and modeled the optical properties of the Frenkel excitons in self-assembled porphyrin tubular aggregates that represent an analog to natural photosynthetic antennae. Using a combination of ultrafast optical microscopy and stochastic exciton modeling, we address exciton transport and relaxation pathways, especially those related to disorder.

The dark side of light at night: physiological, epidemiological, and ecological consequences.

PubMed

Navara, Kristen J; Nelson, Randy J

2007-10-01

Organisms must adapt to the temporal characteristics of their surroundings to successfully survive and reproduce. Variation in the daily light cycle, for example, acts through endocrine and neurobiological mechanisms to control several downstream physiological and behavioral processes. Interruptions in normal circadian light cycles and the resulting disruption of normal melatonin rhythms cause widespread disruptive effects involving multiple body systems, the results of which can have serious medical consequences for individuals, as well as large-scale ecological implications for populations. With the invention of electrical lights about a century ago, the temporal organization of the environment has been drastically altered for many species, including humans. In addition to the incidental exposure to light at night through light pollution, humans also engage in increasing amounts of shift-work, resulting in repeated and often long-term circadian disruption. The increasing prevalence of exposure to light at night has significant social, ecological, behavioral, and health consequences that are only now becoming apparent. This review addresses the complicated web of potential behavioral and physiological consequences resulting from exposure to light at night, as well as the large-scale medical and ecological implications that may result.

Neurophysiological basis of creativity in healthy elderly people: a multiscale entropy approach.

PubMed

Ueno, Kanji; Takahashi, Tetsuya; Takahashi, Koichi; Mizukami, Kimiko; Tanaka, Yuji; Wada, Yuji

2015-03-01

Creativity, which presumably involves various connections within and across different neural networks, reportedly underpins the mental well-being of older adults. Multiscale entropy (MSE) can characterize the complexity inherent in EEG dynamics with multiple temporal scales. It can therefore provide useful insight into neural networks. Given that background, we sought to clarify the neurophysiological bases of creativity in healthy elderly subjects by assessing EEG complexity with MSE, with emphasis on assessment of neural networks. We recorded resting state EEG of 20 healthy elderly subjects. MSE was calculated for each subject for continuous 20-s epochs. Their relevance to individual creativity was examined concurrently with intellectual function. Higher individual creativity was linked closely to increased EEG complexity across higher temporal scales, but no significant relation was found with intellectual function (IQ score). Considering the general "loss of complexity" theory of aging, our finding of increased EEG complexity in elderly people with heightened creativity supports the idea that creativity is associated with activated neural networks. Results reported here underscore the potential usefulness of MSE analysis for characterizing the neurophysiological bases of elderly people with heightened creativity. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Demeter-W

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

2017-09-27

Demeter-W, an open-access software written in Python, consists of extensible module packages. It is developed with statistical downscaling algorithms, to spatially and temporally downscale water demand data into finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. For better understanding of the driving forces and patterns for global water withdrawal, the researchers is able to utilize Demeter-W to reconstruct the data sets to examine the issues related to water withdrawals at fine spatial and temporal scales.

Endoscopic facelift of the frontal and temporal areas in multiple planes.

PubMed

Hu, Xiaogen; Ma, Haihuan; Xue, Zhiqiang; Qi, Huijie; Chen, Bo

2017-02-01

The detachment planes used in endoscopic facelifts play an important role in determining the results of facial rejuvenation. In this study, we introduced the use of multiple detachment planes for endoscopic facelifts of the frontal and temporal areas, and examined its outcome. This study included 47 patients (38 female, 9 male) who requested frontal and temporal facelifts from January 2009 to January 2014. The technique of dissection in multiple planes was used for all 47 patients. In this technique, the frontal dissection was first carried out in the subgaleal plane, before being changed to the subperiosteal plane about 2 cm above the eyebrow line. Temporal dissection was carried out in both the subcutaneous and subgaleal planes. After detachment, frontal and temporal fixations were achieved using nonabsorbable sutures, and the incisions were closed. During follow-up (ranging from 6-24 months after surgery), the patients were shown their pre- and postoperative images, and asked to rate their satisfaction with the procedure. Complications encountered were documented. All 47 patients had complete recovery without any serious complications. The patient satisfaction rate was 93.6%. Minor complications included dimpling at the suture site, asymmetry, overcorrection, transitory paralysis, late oedema, haematoma, infection, scarring and hair loss. These complications resolved spontaneously and were negligible after complete recovery. Dissection in multiple planes is valuable in frontal and temporal endoscopic facelifts. It may be worthwhile to introduce the use of this technique in frontal and temporal facelifts, as it may lead to improved outcomes. Copyright: © Singapore Medical Association

Channel disturbances and morpho-dynamics: linking hydraulics, topographic changes and human impacts in a highly dynamic wandering river at multiple temporal scales

NASA Astrophysics Data System (ADS)

Vericat, Damià; Llena, Manel; Muñoz, Efrén; Ramos, Ester; Béjar, María; Brasington, James; Gibbins, Chris; Batalla, Ramon J.; Tena, Álvaro; Martínez-Casasnovas, José A.; Wheaton, Joe

2015-04-01

Episodic erosion, transport and deposition of sediments produce changes in river's channel morphology. These changes, although are directly related to flow hydraulics and bed material availability, supply and transport, could also be highly influenced by structural and local human impacts. Dams cut the continuity of sediment transfer and alter flood magnitude and frequency. In-channel gravel mining, however, disturbs channel beds locally, with a direct influence in upstream and downstream reaches. In this paper we present some of the preliminary results obtained in the background of MorphSed (www.morphsed.es). Morphsed is analysing the morpho-sedimentary dynamics of a mountain fluvial system located in the foothills of the Pyrenees, Iberian Peninsula. The study system is suffering major local alterations due to gravel mining. Changes on bed topography along a 12-km river reach have been analysed at two temporal scales: (i) decadal or historical and (ii) flood-based or contemporary. The study reach has suffered natural and human channel disturbances (i.e. major flood events, and gravel extractions and channel embankments, respectively). Preliminary results show how gravel mining occurred after the large flood event registered in October 1982 created a sedimentary disequilibrium in the reach. Additionally, the channel was heavily constrained associated to channel narrowing by embankments. The river has reached a new dynamic equilibrium by means of bed coarsening and channel incision, and changing from a braided to a wandering pattern. Contemporary competent flood events, however, cause severe damages in some of the embankments (i.e. lateral erosion). Gravel extractions in these sites are performed to protect these infrastructures and, in turn, are influencing local channel morpho-dynamics, increasing the sedimentary disequilibrium, exacerbating local channel incision processes, and modifying channel roughness and sediment transport dynamics. 2d hydraulic models show as these contemporary extractions influence on the magnitude and variability of hydraulic forces and, in turn, modify the conveyance of water and sediments through the study reach. All these changes have a direct influence on the ecological status of the river at different temporal and spatial scales. These links will be a key goal for progress towards the understanding of the interactions between river bed disturbance and ecological responses at multiple scales, and provide the basis for an integrated methodology that can be used to aid prediction, management and restoration of human stressed fluvial systems.

Multi-source remotely sensed data fusion for improving land cover classification

NASA Astrophysics Data System (ADS)

Chen, Bin; Huang, Bo; Xu, Bing

2017-02-01

Although many advances have been made in past decades, land cover classification of fine-resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral features remains limited, and the contribution of different RS features to land cover classification accuracy remains uncertain. We proposed to improve land cover classification accuracy by integrating multi-source RS features through data fusion. We further investigated the effect of different RS features on classification performance. The results of fusing Landsat-8 Operational Land Imager (OLI) data with Moderate Resolution Imaging Spectroradiometer (MODIS), China Environment 1A series (HJ-1A), and Advanced Spaceborne Thermal Emission and Reflection (ASTER) digital elevation model (DEM) data, showed that the fused data integrating temporal, spectral, angular, and topographic features achieved better land cover classification accuracy than the original RS data. Compared with the topographic feature, the temporal and angular features extracted from the fused data played more important roles in classification performance, especially those temporal features containing abundant vegetation growth information, which markedly increased the overall classification accuracy. In addition, the multispectral and hyperspectral fusion successfully discriminated detailed forest types. Our study provides a straightforward strategy for hierarchical land cover classification by making full use of available RS data. All of these methods and findings could be useful for land cover classification at both regional and global scales.

Temporal stability of visually selective responses in intracranial field potentials recorded from human occipital and temporal lobes

PubMed Central

Bansal, Arjun K.; Singer, Jedediah M.; Anderson, William S.; Golby, Alexandra; Madsen, Joseph R.

2012-01-01

The cerebral cortex needs to maintain information for long time periods while at the same time being capable of learning and adapting to changes. The degree of stability of physiological signals in the human brain in response to external stimuli over temporal scales spanning hours to days remains unclear. Here, we quantitatively assessed the stability across sessions of visually selective intracranial field potentials (IFPs) elicited by brief flashes of visual stimuli presented to 27 subjects. The interval between sessions ranged from hours to multiple days. We considered electrodes that showed robust visual selectivity to different shapes; these electrodes were typically located in the inferior occipital gyrus, the inferior temporal cortex, and the fusiform gyrus. We found that IFP responses showed a strong degree of stability across sessions. This stability was evident in averaged responses as well as single-trial decoding analyses, at the image exemplar level as well as at the category level, across different parts of visual cortex, and for three different visual recognition tasks. These results establish a quantitative evaluation of the degree of stationarity of visually selective IFP responses within and across sessions and provide a baseline for studies of cortical plasticity and for the development of brain-machine interfaces. PMID:22956795

Coding of odors by temporal binding within a model network of the locust antennal lobe.

PubMed

Patel, Mainak J; Rangan, Aaditya V; Cai, David

2013-01-01

The locust olfactory system interfaces with the external world through antennal receptor neurons (ORNs), which represent odors in a distributed, combinatorial manner. ORN axons bundle together to form the antennal nerve, which relays sensory information centrally to the antennal lobe (AL). Within the AL, an odor generates a dynamically evolving ensemble of active cells, leading to a stimulus-specific temporal progression of neuronal spiking. This experimental observation has led to the hypothesis that an odor is encoded within the AL by a dynamically evolving trajectory of projection neuron (PN) activity that can be decoded piecewise to ascertain odor identity. In order to study information coding within the locust AL, we developed a scaled-down model of the locust AL using Hodgkin-Huxley-type neurons and biologically realistic connectivity parameters and current components. Using our model, we examined correlations in the precise timing of spikes across multiple neurons, and our results suggest an alternative to the dynamic trajectory hypothesis. We propose that the dynamical interplay of fast and slow inhibition within the locust AL induces temporally stable correlations in the spiking activity of an odor-dependent neural subset, giving rise to a temporal binding code that allows rapid stimulus detection by downstream elements.

Spatial and temporal trends from an air quality sensor network near a heavily trafficked intersection

NASA Astrophysics Data System (ADS)

Orlando, P.; Vo, D.; Giossi, C.; George, L.

2017-12-01

With the world-wide increase in urbanization and the increasing usage of combustion vehicles in urban areas, traffic-related air pollution is a growing health hazard. However, there are limited studies that examine the spatial and temporal impacts of traffic-related pollutants within cities. In particular, there are few studies that look at traffic management and its potential for pollution mitigation. In a previous study we examined roadway pollution and traffic parameters with one roadway station instrumented with standard measurement instruments. With the advent of low-cost air pollution sensors, we have expanded our work by observing multiple sites within a neighborhood to understand spatial and temporal exposures. We have deployed a high-density sensor network around urban arterial corridors in SE Portland, Oregon. This network consisted of ten nodes measuring CO, NO, NO2 and O3, and ten nodes measuring CO, CO2, VOC and PM2.5. The co-location of standard measurement instruments provided insight towards the utility of our low-cost sensor network, as the different nodes varied in cost, and potentially in quality. We have identified near-real-time temporal trends and local-scale spatial patterns during the summer of 2017. Meteorological and traffic data were included to further characterize these patterns, exploring the potential for pollution mitigation.

Scale considerations for ecosystem management

Treesearch

Jonathan B. Haufler; Thomas R. Crow; David Wilcove

1999-01-01

One of the difficult challenges facing ecosystem management is the determination of appropriate spatial and temporal scales to use. Scale in spatial sence includes considerations of both the size area or extent of an ecosystem management activity, as well as thedegree of resolution of mapped or measured data. In the temporal sense, scale concerns the duration of both...

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

PubMed Central

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

2006-01-01

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

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

PubMed

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

2006-03-27

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

Temporal variability of the wind from the star τ Boötis

NASA Astrophysics Data System (ADS)

Nicholson, B. A.; Vidotto, A. A.; Mengel, M.; Brookshaw, L.; Carter, B.; Petit, P.; Marsden, S. C.; Jeffers, S. V.; Fares, R.; BCool Collaboration

2016-06-01

We present new wind models for τ Boötis (τ Boo), a hot-Jupiter-host-star whose observable magnetic cycles makes it a uniquely useful target for our goal of monitoring the temporal variability of stellar winds and their exoplanetary impacts. Using spectropolarimetric observations from May 2009 to January 2015, the most extensive information of this type yet available, to reconstruct the stellar magnetic field, we produce multiple 3D magnetohydrodynamic stellar wind models. Our results show that characteristic changes in the large-scale magnetic field as the star undergoes magnetic cycles produce changes in the wind properties, both globally and locally at the position of the orbiting planet. Whilst the mass loss rate of the star varies by only a minimal amount (˜4 per cent), the rates of angular momentum loss and associated spin-down time-scales are seen to vary widely (up to ˜140 per cent), findings consistent with and extending previous research. In addition, we find that temporal variation in the global wind is governed mainly by changes in total magnetic flux rather than changes in wind plasma properties. The magnetic pressure varies with time and location and dominates the stellar wind pressure at the planetary orbit. By assuming a Jovian planetary magnetic field for τ Boo b, we nevertheless conclude that the planetary magnetosphere can remain stable in size for all observed stellar cycle epochs, despite significant changes in the stellar field and the resulting local space weather environment.

Double dissociation of social functioning in frontotemporal dementia

PubMed Central

Rankin, Katherine P.; Kramer, Joel H.; Mychack, Paula; Miller, Bruce L.

2009-01-01

Background Efforts to characterize changes in social functioning in frontotemporal dementia (FTD) have failed to elicit clear dissociation between frontal and temporal variants of the disease based on behavioral measures. Methods This study obtained premorbid and current first-degree relative ratings using an established measure of interpersonal functioning, the Interpersonal Adjectives Scales, to measure personality change in 16 patients with frontal variant (FLV) and 13 with temporal variant (TLV) FTD, and in a control group of 16 patients with AD. Results All three groups showed significant change over time in multiple domains, including increased introversion (FG) and submissiveness (HI). However, patients with both FTD subtypes evidenced significantly greater increases in overall interpersonal pathology vector length [VL] than did patients with AD, who remained within the normal range on all scores. Patients with FLV showed a 2 SD increase in submissiveness (HI), but their cold-heartedness (DE) change scores were not significantly different from those of patients with AD. Conversely, the TLV cold-heartedness (DE) score increased 2 SD compared to minimal change for the AD and FLV groups, yet change in submissiveness (HI) did not differentiate between AD and TLV groups. Conclusions The Interpersonal Adjectives Scales differentiated both FTD groups from patients with AD on the basis of both degree and direction of personality change. Also, the two subtypes of FTD showed distinctly different patterns of change in social functioning: patients with temporal variant shifted toward severe interpersonal coldness with mild loss of dominance, whereas patients with frontal variant showed the opposite pattern. PMID:12552042

Intelligent Fault Diagnosis of Rotary Machinery Based on Unsupervised Multiscale Representation Learning

NASA Astrophysics Data System (ADS)

Jiang, Guo-Qian; Xie, Ping; Wang, Xiao; Chen, Meng; He, Qun

2017-11-01

The performance of traditional vibration based fault diagnosis methods greatly depends on those handcrafted features extracted using signal processing algorithms, which require significant amounts of domain knowledge and human labor, and do not generalize well to new diagnosis domains. Recently, unsupervised representation learning provides an alternative promising solution to feature extraction in traditional fault diagnosis due to its superior learning ability from unlabeled data. Given that vibration signals usually contain multiple temporal structures, this paper proposes a multiscale representation learning (MSRL) framework to learn useful features directly from raw vibration signals, with the aim to capture rich and complementary fault pattern information at different scales. In our proposed approach, a coarse-grained procedure is first employed to obtain multiple scale signals from an original vibration signal. Then, sparse filtering, a newly developed unsupervised learning algorithm, is applied to automatically learn useful features from each scale signal, respectively, and then the learned features at each scale to be concatenated one by one to obtain multiscale representations. Finally, the multiscale representations are fed into a supervised classifier to achieve diagnosis results. Our proposed approach is evaluated using two different case studies: motor bearing and wind turbine gearbox fault diagnosis. Experimental results show that the proposed MSRL approach can take full advantages of the availability of unlabeled data to learn discriminative features and achieved better performance with higher accuracy and stability compared to the traditional approaches.

Past Asian Monsoon circulation from multiple tree-ring proxies and models (Invited)

NASA Astrophysics Data System (ADS)

Anchukaitis, K. J.; Herzog, M.; Hernandez, M.; Martin-Benito, D.; Gagen, M.; LeGrande, A. N.; Ummenhofer, C.; Buckley, B.; Cook, E. R.

2013-12-01

The Asian monsoon can be characterized in terms of precipitation variability as well as features of regional atmospheric circulation across a range of spatial and temporal scales. While multicentury time series of tree-ring widths at hundreds of sites across Asia provide estimates of past rainfall, the oxygen isotope ratios of annual rings at some of these sites can reveal broader regional atmosphere-ocean dynamics. Here we present a replicated, multicentury stable isotope series from Vietnam that integrates the influence of monsoon circulation on water isotopes. Stronger (weaker) monsoon flow over Indochina is associated with lower (higher) oxygen isotope values in our long-lived tropical conifers. Ring width and isotopes show particular coherence at multidecadal time scales, and together allow past precipitation amount and circulation strength to be disentangled. Combining multiple tree-ring proxies with simulations from isotope-enabled and paleoclimate general circulation models allows us to independently assess the mechanisms responsible for proxy formation and to evaluate how monsoon rainfall is influenced by ocean-atmosphere interactions at timescales from interannual to multidecadal.

Remote sensing of a coupled carbon-water-energy-radiation balances from the Globe to plot scales

NASA Astrophysics Data System (ADS)

Ryu, Y.; Jiang, C.; Huang, Y.; Kim, J.; Hwang, Y.; Kimm, H.; Kim, S.

2016-12-01

Advancements in near-surface and satellite remote sensing technologies have enabled us to monitor the global terrestrial ecosystems at multiple spatial and temporal scales. An emergent challenge is how to formulate a coupled water, carbon, energy, radiation, and nitrogen cycles from remote sensing. Here, we report Breathing Earth System Simulator (BESS), which coupled radiation (shortwave, longwave, PAR, diffuse PAR), carbon (gross primary productivity, ecosystem respiration, net ecosystem exchange), water (evaporation), and energy (latent and sensible heat) balances across the global land at 1 km resolution, 8 daily between 2000 and 2015 using multiple satellite remote sensing. The performance of BESS was tested against field observations (FLUXNET, BSRN) and other independent products (MPI-BGC, MODIS, GLASS). We found that the coupled model, BESS showed on par with, or better performance than the other products which computed land surface fluxes individually. Lastly, we show one plot-level study conducted in a paddy rice to demonstrate how to couple radiation, carbon, water, nitrogen balances with a series of near-surface spectral sensors.

A Relational Encoding of a Conceptual Model with Multiple Temporal Dimensions

NASA Astrophysics Data System (ADS)

Gubiani, Donatella; Montanari, Angelo

The theoretical interest and the practical relevance of a systematic treatment of multiple temporal dimensions is widely recognized in the database and information system communities. Nevertheless, most relational databases have no temporal support at all. A few of them provide a limited support, in terms of temporal data types and predicates, constructors, and functions for the management of time values (borrowed from the SQL standard). One (resp., two) temporal dimensions are supported by historical and transaction-time (resp., bitemporal) databases only. In this paper, we provide a relational encoding of a conceptual model featuring four temporal dimensions, namely, the classical valid and transaction times, plus the event and availability times. We focus our attention on the distinctive technical features of the proposed temporal extension of the relation model. In the last part of the paper, we briefly show how to implement it in a standard DBMS.

Classification of Farmland Landscape Structure in Multiple Scales

NASA Astrophysics Data System (ADS)

Jiang, P.; Cheng, Q.; Li, M.

2017-12-01

Farmland is one of the basic terrestrial resources that support the development and survival of human beings and thus plays a crucial role in the national security of every country. Pattern change is the intuitively spatial representation of the scale and quality variation of farmland. Through the characteristic development of spatial shapes as well as through changes in system structures, functions and so on, farmland landscape patterns may indicate the landscape health level. Currently, it is still difficult to perform positioning analyses of landscape pattern changes that reflect the landscape structure variations of farmland with an index model. Depending on a number of spatial properties such as locations and adjacency relations, distance decay, fringe effect, and on the model of patch-corridor-matrix that is applied, this study defines a type system of farmland landscape structure on the national, provincial, and city levels. According to such a definition, the classification model of farmland landscape-structure type at the pixel scale is developed and validated based on mathematical-morphology concepts and on spatial-analysis methods. Then, the laws that govern farmland landscape-pattern change in multiple scales are analyzed from the perspectives of spatial heterogeneity, spatio-temporal evolution, and function transformation. The result shows that the classification model of farmland landscape-structure type can reflect farmland landscape-pattern change and its effects on farmland production function. Moreover, farmland landscape change in different scales displayed significant disparity in zonality, both within specific regions and in urban-rural areas.

Linking definitions, mechanisms, and modeling of drought-induced tree death.

PubMed

Anderegg, William R L; Berry, Joseph A; Field, Christopher B

2012-12-01

Tree death from drought and heat stress is a critical and uncertain component in forest ecosystem responses to a changing climate. Recent research has illuminated how tree mortality is a complex cascade of changes involving interconnected plant systems over multiple timescales. Explicit consideration of the definitions, dynamics, and temporal and biological scales of tree mortality research can guide experimental and modeling approaches. In this review, we draw on the medical literature concerning human death to propose a water resource-based approach to tree mortality that considers the tree as a complex organism with a distinct growth strategy. This approach provides insight into mortality mechanisms at the tree and landscape scales and presents promising avenues into modeling tree death from drought and temperature stress. Copyright © 2012 Elsevier Ltd. All rights reserved.

Climates Past, Present, and Yet-to-Come Shape Climate Change Vulnerabilities.

PubMed

Nadeau, Christopher P; Urban, Mark C; Bridle, Jon R

2017-10-01

Climate change is altering life at multiple scales, from genes to ecosystems. Predicting the vulnerability of populations to climate change is crucial to mitigate negative impacts. We suggest that regional patterns of spatial and temporal climatic variation scaled to the traits of an organism can predict where and why populations are most vulnerable to climate change. Specifically, historical climatic variation affects the sensitivity and response capacity of populations to climate change by shaping traits and the genetic variation in those traits. Present and future climatic variation can affect both climate change exposure and population responses. We provide seven predictions for how climatic variation might affect the vulnerability of populations to climate change and suggest key directions for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluating groundwater flow using passive electrical measurements

NASA Astrophysics Data System (ADS)

Voytek, E.; Revil, A.; Singha, K.

2016-12-01

Accurate quantification of groundwater flow patterns, both in magnitude and direction, is a necessary component of evaluating any hydrologic system. Groundwater flow patterns are often determined using a dense network of wells or piezometers, which can be limited due to logistical or regulatory constraints. The self-potential (SP) method, a passive geophysical technique that relies on currents generated by water movement through porous materials, is a re-emerging alternative or addition to traditional piezometer networks. Naturally generated currents can be measured as voltage differences at the ground surface using only two electrodes, or a more complex electrode array. While the association between SP measurements and groundwater flow was observed as early as 1890s, the method has seen resurgence in hydrology since the governing equations were refined in the 1980s. The method can be used to analyze hydrologic processes at various temporal and spatial scales. Here we present the results of multiple SP surveys collected a multiple scales (1 to 10s of meters). Here single SP grid surveys are used to evaluate flow patterns through artic hillslopes at a discrete point in time. Additionally, a coupled groundwater and electrical model is used to analyze multiple SP data sets to evaluate seasonal changes in groundwater flow through an alpine meadow.

Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study

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.

Topographic Controls on Hillslope-Riparian Water Table Continuity in a set of Nested Catchments, Northern Rocky Mountains, Montana

NASA Astrophysics Data System (ADS)

Jencso, K. G.; McGlynn, B. L.; Gooseff, M. N.; Wondzell, S. M.; Bencala, K. E.; Payn, R. A.

2007-12-01

Understanding how hillslope and riparian water table dynamics influence catchment scale hydrologic response remains a challenge. In steep headwater catchments with shallow soils, topographic convergence and divergence (upslope accumulated area-UAA) is a hypothesized first-order control on the distribution of soil water and groundwater. To test the relationship between UAA and the longevity of hillslope-riparian-stream shallow groundwater connectivity, we quantified water table continuity based on 80+ recording wells distributed across 24 hillslope-riparian-stream cross-sections. Cross-section upstream catchment areas ranged in size from 0.41 to 17.2 km2, within the Tenderfoot Creek Experimental Forest (U.S. Forest Service), northern Rocky Mountains, Montana, USA. We quantified toe-slope UAA and the topographic index (TI = ln a/tanβ) with a Multiple-D- Infinity (area routing in multiple infinite downslope directions) flow accumulation algorithm analysis of 1, 3, 10, and 30m ALSM derived DEMs. Indices derived from the 10m DEM best characterized subsurface flow accumulation, highlighting the balance between the process of interest, topographic complexity, and optimal grid scale representation. Across the 24 transects, toe-slope UAA ranged from 600-40,000 m2, the TI ranged from 5-16, and riparian widths were between 0-60m. Patterns in shallow groundwater table fluctuations suggest hydrologic dynamics reflective of hillslope-riparian landscape setting. Specifically, correlations were observed between longevity of hillslope-riparian water table continuity and the size of the UAA (r2=0.84) and its topographic index (r2=.86). These observations highlight the temporal component of topographic-hydrologic relationships important for understanding threshold mediated hydrologic variables. We are working to quantify the characteristics and spatial distribution of hillslope-riparian sequences and their water table dynamics to temporally link runoff source areas to whole catchment hydrologic response.

Multiscale spatial and small-scale temporal variation in the composition of Riverine fish communities.

PubMed

Growns, Ivor; Astles, Karen; Gehrke, Peter

2006-03-01

We studied the multiscale (sites, river reaches and rivers) and short-term temporal (monthly) variability in a freshwater fish assemblage. We found that small-scale spatial variation and short-term temporal variability significantly influenced fish community structure in the Macquarie and Namoi Rivers. However, larger scale spatial differences between rivers were the largest source of variation in the data. The interaction between temporal change and spatial variation in fish community structure, whilst statistically significant, was smaller than the variation between rivers. This suggests that although the fish communities within each river changed between sampling occasions, the underlying differences between rivers were maintained. In contrast, the strongest interaction between temporal and spatial effects occurred at the smallest spatial scale, at the level of individual sites. This means whilst the composition of the fish assemblage at a given site may fluctuate, the magnitude of these changes is unlikely to affect larger scale differences between reaches within rivers or between rivers. These results suggest that sampling at any time within a single season will be sufficient to show spatial differences that occur over large spatial scales, such as comparisons between rivers or between biogeographical regions.

Sensitivity of peak flow to the change of rainfall temporal pattern due to warmer climate

NASA Astrophysics Data System (ADS)

Fadhel, Sherien; Rico-Ramirez, Miguel Angel; Han, Dawei

2018-05-01

The widely used design storms in urban drainage networks has different drawbacks. One of them is that the shape of the rainfall temporal pattern is fixed regardless of climate change. However, previous studies have shown that the temporal pattern may scale with temperature due to climate change, which consequently affects peak flow. Thus, in addition to the scaling of the rainfall volume, the scaling relationship for the rainfall temporal pattern with temperature needs to be investigated by deriving the scaling values for each fraction within storm events, which is lacking in many parts of the world including the UK. Therefore, this study analysed rainfall data from 28 gauges close to the study area with a 15-min resolution as well as the daily temperature data. It was found that, at warmer temperatures, the rainfall temporal pattern becomes less uniform, with more intensive peak rainfall during higher intensive times and weaker rainfall during less intensive times. This is the case for storms with and without seasonal separations. In addition, the scaling values for both the rainfall volume and the rainfall fractions (i.e. each segment of rainfall temporal pattern) for the summer season were found to be higher than the corresponding results for the winter season. Applying the derived scaling values for the temporal pattern of the summer season in a hydrodynamic sewer network model produced high percentage change of peak flow between the current and future climate. This study on the scaling of rainfall fractions is the first in the UK, and its findings are of importance to modellers and designers of sewer systems because it can provide more robust scenarios for flooding mitigation in urban areas.

Soil moisture observations using L-, C-, and X-band microwave radiometers

NASA Astrophysics Data System (ADS)

Bolten, John Dennis

The purpose of this thesis is to further the current understanding of soil moisture remote sensing under varying conditions using L-, C-, and X-band. Aircraft and satellite instruments are used to investigate the effects of frequency and spatial resolution on soil moisture sensitivity. The specific objectives of the research are to examine multi-scale observed and modeled microwave radiobrightness, evaluate new EOS Aqua Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperature and soil moisture retrievals, and examine future satellite-based technologies for soil moisture sensing. The cycling of Earth's water, energy and carbon is vital to understanding global climate. Over land, these processes are largely dependent on the amount of moisture within the top few centimeters of the soil. However, there are currently no methods available that can accurately characterize Earth's soil moisture layer at the spatial scales or temporal resolutions appropriate for climate modeling. The current work uses ground truth, satellite and aircraft remote sensing data from three large-scale field experiments having different land surface, topographic and climate conditions. A physically-based radiative transfer model is used to simulate the observed aircraft and satellite measurements using spatially and temporally co-located surface parameters. A robust analysis of surface heterogeneity and scaling is possible due to the combination of multiple datasets from a range of microwave frequencies and field conditions. Accurate characterization of spatial and temporal variability of soil moisture during the three field experiments is achieved through sensor calibration and algorithm validation. Comparisons of satellite observations and resampled aircraft observations are made using soil moisture from a Numerical Weather Prediction (NWP) model in order to further demonstrate a soil moisture correlation where point data was unavailable. The influence of vegetation, spatial scaling, and surface heterogeneity on multi-scale soil moisture prediction is presented. This work demonstrates that derived soil moisture using remote sensing provides a better coverage of soil moisture spatial variability than traditional in-situ sensors. Effects of spatial scale were shown to be less significant than frequency on soil moisture sensitivity. Retrievals of soil moisture using the current methods proved inadequate under some conditions; however, this study demonstrates the need for concurrent spaceborne frequencies including L-, C, and X-band.

Bioenergy Development Policy and Practice Must Recognize Potential Hydrologic Impacts: Lessons from the Americas.

PubMed

Watkins, David W; de Moraes, Márcia M G Alcoforado; Asbjornsen, Heidi; Mayer, Alex S; Licata, Julian; Lopez, Jose Gutierrez; Pypker, Thomas G; Molina, Vivianna Gamez; Marques, Guilherme Fernandes; Carneiro, Ana Cristina Guimaraes; Nuñez, Hector M; Önal, Hayri; da Nobrega Germano, Bruna

2015-12-01

Large-scale bioenergy production will affect the hydrologic cycle in multiple ways, including changes in canopy interception, evapotranspiration, infiltration, and the quantity and quality of surface runoff and groundwater recharge. As such, the water footprints of bioenergy sources vary significantly by type of feedstock, soil characteristics, cultivation practices, and hydro-climatic regime. Furthermore, water management implications of bioenergy production depend on existing land use, relative water availability, and competing water uses at a watershed scale. This paper reviews previous research on the water resource impacts of bioenergy production-from plot-scale hydrologic and nutrient cycling impacts to watershed and regional scale hydro-economic systems relationships. Primary gaps in knowledge that hinder policy development for integrated management of water-bioenergy systems are highlighted. Four case studies in the Americas are analyzed to illustrate relevant spatial and temporal scales for impact assessment, along with unique aspects of biofuel production compared to other agroforestry systems, such as energy-related conflicts and tradeoffs. Based on the case studies, the potential benefits of integrated resource management are assessed, as is the need for further case-specific research.

Bioenergy Development Policy and Practice Must Recognize Potential Hydrologic Impacts: Lessons from the Americas

NASA Astrophysics Data System (ADS)

Watkins, David W.; de Moraes, Márcia M. G. Alcoforado; Asbjornsen, Heidi; Mayer, Alex S.; Licata, Julian; Lopez, Jose Gutierrez; Pypker, Thomas G.; Molina, Vivianna Gamez; Marques, Guilherme Fernandes; Carneiro, Ana Cristina Guimaraes; Nuñez, Hector M.; Önal, Hayri; da Nobrega Germano, Bruna

2015-12-01

Large-scale bioenergy production will affect the hydrologic cycle in multiple ways, including changes in canopy interception, evapotranspiration, infiltration, and the quantity and quality of surface runoff and groundwater recharge. As such, the water footprints of bioenergy sources vary significantly by type of feedstock, soil characteristics, cultivation practices, and hydro-climatic regime. Furthermore, water management implications of bioenergy production depend on existing land use, relative water availability, and competing water uses at a watershed scale. This paper reviews previous research on the water resource impacts of bioenergy production—from plot-scale hydrologic and nutrient cycling impacts to watershed and regional scale hydro-economic systems relationships. Primary gaps in knowledge that hinder policy development for integrated management of water-bioenergy systems are highlighted. Four case studies in the Americas are analyzed to illustrate relevant spatial and temporal scales for impact assessment, along with unique aspects of biofuel production compared to other agroforestry systems, such as energy-related conflicts and tradeoffs. Based on the case studies, the potential benefits of integrated resource management are assessed, as is the need for further case-specific research.

Towards a physically-based multi-scale ecohydrological simulator for semi-arid regions

NASA Astrophysics Data System (ADS)

Caviedes-Voullième, Daniel; Josefik, Zoltan; Hinz, Christoph

2017-04-01

The use of numerical models as tools for describing and understanding complex ecohydrological systems has enabled to test hypothesis and propose fundamental, process-based explanations of the system system behaviour as a whole as well as its internal dynamics. Reaction-diffusion equations have been used to describe and generate organized pattern such as bands, spots, and labyrinths using simple feedback mechanisms and boundary conditions. Alternatively, pattern-matching cellular automaton models have been used to generate vegetation self-organization in arid and semi-arid regions also using simple description of surface hydrological processes. A key question is: How much physical realism is needed in order to adequately capture the pattern formation processes in semi-arid regions while reliably representing the water balance dynamics at the relevant time scales? In fact, redistribution of water by surface runoff at the hillslope scale occurs at temporal resolution of minutes while the vegetation development requires much lower temporal resolution and longer times spans. This generates a fundamental spatio-temporal multi-scale problem to be solved, for which high resolution rainfall and surface topography are required. Accordingly, the objective of this contribution is to provide proof-of-concept that governing processes can be described numerically at those multiple scales. The requirements for a simulating ecohydrological processes and pattern formation with increased physical realism are, amongst others: i. high resolution rainfall that adequately captures the triggers of growth as vegetation dynamics of arid regions respond as pulsed systems. ii. complex, natural topography in order to accurately model drainage patterns, as surface water redistribution is highly sensitive to topographic features. iii. microtopography and hydraulic roughness, as small scale variations do impact on large scale hillslope behaviour iv. moisture dependent infiltration as temporal dynamics of infiltration affects water storage under vegetation and in bare soil Despite the volume of research in this field, fundamental limitations still exist in the models regarding the aforementioned issues. Topography and hydrodynamics have been strongly simplified. Infiltration has been modelled as dependent on depth but independent of soil moisture. Temporal rainfall variability has only been addressed for seasonal rain. Spatial heterogenity of the topography as well as roughness and infiltration properties, has not been fully and explicitly represented. We hypothesize that physical processes must be robustly modelled and the drivers of complexity must be present with as much resolution as possible in order to provide the necessary realism to improve transient simulations, perhaps leading the way to virtual laboratories and, arguably, predictive tools. This work provides a first approach into a model with explicit hydrological processes represented by physically-based hydrodynamic models, coupled with well-accepted vegetation models. The model aims to enable new possibilities relating to spatiotemporal variability, arbitrary topography and representation of spatial heterogeneity, including sub-daily (in fact, arbitrary) temporal variability of rain as the main forcing of the model, explicit representation of infiltration processes, and various feedback mechanisms between the hydrodynamics and the vegetation. Preliminary testing strongly suggests that the model is viable, has the potential of producing new information of internal dynamics of the system, and allows to successfully aggregate many of the sources of complexity. Initial benchmarking of the model also reveals strengths to be exploited, thus providing an interesting research outlook, as well as weaknesses to be addressed in the immediate future.

Watershed-Scale Heterogeneity of the Biophysical Controls on Soil Respiration

NASA Astrophysics Data System (ADS)

Riveros, D. A.; Pacific, V. J.; McGlynn, B. L.; Welsch, D. L.; Epstein, H. E.; Muth, D. J.; Marshall, L.; Wraith, J.

2006-12-01

Large gaps exist in our understanding of the variability of soil respiration response to changing hydrologic conditions across spatial and temporal scales. Determining the linkages between the hydrologic cycle and the biophysical controls of soil respiration from the local point, to the plot, to the watershed scale is critical to understanding the dynamics of net ecosystem CO2 exchange (NEE). To study the biophysical controls of soil respiration, we measured soil CO2 concentration, soil CO2 flux, dissolved CO2 in stream water, soil moisture, soil temperature, groundwater dynamics, and precipitation at 20-minute intervals throughout the growing season at 4 sites and at weekly intervals at 62 sites covering the range of topographic position, slope, aspect, land cover, and upslope accumulated area conditions in a 555-ha subalpine watershed in central Montana. Our goal was to quantify watershed-scale heterogeneity in soil CO2 concentrations and surface efflux and gain understanding of the biophysical controls on soil respiration. We seek to improve our ability to evaluate and predict soil respiration responses to a dynamic hydrologic cycle across multiple temporal and spatial scales. We found that time lags between biophysical controls and soil respiration can occur from hourly to daily scales. The sensitivity of soil respiration to changes in environmental conditions is controlled by the antecedent soil moisture and by topographic position. At the watershed scale, significant differences in soil respiration exist between upland (dry) and lowland (wet) sites. However, differences in the magnitude and timing of soil respiration also exist within upland settings due to heterogeneity in soil temperature, soil moisture, and soil organic matter. Finally, we used a process-based model to simulate respiration at different times of the year across spatial locations. Our simulations highlight the importance of autotrophic and heterotrophic respiration (production) over diffusivity and soil physical properties (transport). Our work begins to address the disconnect between point, footprint, watershed scale estimates of ecosystem respiration and the role of a dynamic hydrologic cycle.

Large-scale recovery of an endangered amphibian despite ongoing exposure to multiple stressors

USGS Publications Warehouse

Knapp, Roland A.; Fellers, Gary M.; Kleeman, Patrick M.; Miller, David A. W.; Vrendenburg, Vance T.; Rosenblum, Erica Bree; Briggs, Cheryl J.

2016-01-01

Amphibians are one of the most threatened animal groups, with 32% of species at risk for extinction. Given this imperiled status, is the disappearance of a large fraction of the Earth’s amphibians inevitable, or are some declining species more resilient than is generally assumed? We address this question in a species that is emblematic of many declining amphibians, the endangered Sierra Nevada yellow-legged frog (Rana sierrae). Based on >7,000 frog surveys conducted across Yosemite National Park over a 20-y period, we show that, after decades of decline and despite ongoing exposure to multiple stressors, including introduced fish, the recently emerged disease chytridiomycosis, and pesticides, R. sierrae abundance increased sevenfold during the study and at a rate of 11% per year. These increases occurred in hundreds of populations throughout Yosemite, providing a rare example of amphibian recovery at an ecologically relevant spatial scale. Results from a laboratory experiment indicate that these increases may be in part because of reduced frog susceptibility to chytridiomycosis. The disappearance of nonnative fish from numerous water bodies after cessation of stocking also contributed to the recovery. The large-scale increases in R. sierrae abundance that we document suggest that, when habitats are relatively intact and stressors are reduced in their importance by active management or species’ adaptive responses, declines of some amphibians may be partially reversible, at least at a regional scale. Other studies conducted over similarly large temporal and spatial scales are critically needed to provide insight and generality about the reversibility of amphibian declines at a global scale.

Large-scale recovery of an endangered amphibian despite ongoing exposure to multiple stressors.

PubMed

Knapp, Roland A; Fellers, Gary M; Kleeman, Patrick M; Miller, David A W; Vredenburg, Vance T; Rosenblum, Erica Bree; Briggs, Cheryl J

2016-10-18

Amphibians are one of the most threatened animal groups, with 32% of species at risk for extinction. Given this imperiled status, is the disappearance of a large fraction of the Earth's amphibians inevitable, or are some declining species more resilient than is generally assumed? We address this question in a species that is emblematic of many declining amphibians, the endangered Sierra Nevada yellow-legged frog (Rana sierrae). Based on >7,000 frog surveys conducted across Yosemite National Park over a 20-y period, we show that, after decades of decline and despite ongoing exposure to multiple stressors, including introduced fish, the recently emerged disease chytridiomycosis, and pesticides, R. sierrae abundance increased sevenfold during the study and at a rate of 11% per year. These increases occurred in hundreds of populations throughout Yosemite, providing a rare example of amphibian recovery at an ecologically relevant spatial scale. Results from a laboratory experiment indicate that these increases may be in part because of reduced frog susceptibility to chytridiomycosis. The disappearance of nonnative fish from numerous water bodies after cessation of stocking also contributed to the recovery. The large-scale increases in R. sierrae abundance that we document suggest that, when habitats are relatively intact and stressors are reduced in their importance by active management or species' adaptive responses, declines of some amphibians may be partially reversible, at least at a regional scale. Other studies conducted over similarly large temporal and spatial scales are critically needed to provide insight and generality about the reversibility of amphibian declines at a global scale.

Large-scale recovery of an endangered amphibian despite ongoing exposure to multiple stressors

PubMed Central

Knapp, Roland A.; Fellers, Gary M.; Kleeman, Patrick M.; Miller, David A. W.; Rosenblum, Erica Bree; Briggs, Cheryl J.

2016-01-01

Amphibians are one of the most threatened animal groups, with 32% of species at risk for extinction. Given this imperiled status, is the disappearance of a large fraction of the Earth’s amphibians inevitable, or are some declining species more resilient than is generally assumed? We address this question in a species that is emblematic of many declining amphibians, the endangered Sierra Nevada yellow-legged frog (Rana sierrae). Based on >7,000 frog surveys conducted across Yosemite National Park over a 20-y period, we show that, after decades of decline and despite ongoing exposure to multiple stressors, including introduced fish, the recently emerged disease chytridiomycosis, and pesticides, R. sierrae abundance increased sevenfold during the study and at a rate of 11% per year. These increases occurred in hundreds of populations throughout Yosemite, providing a rare example of amphibian recovery at an ecologically relevant spatial scale. Results from a laboratory experiment indicate that these increases may be in part because of reduced frog susceptibility to chytridiomycosis. The disappearance of nonnative fish from numerous water bodies after cessation of stocking also contributed to the recovery. The large-scale increases in R. sierrae abundance that we document suggest that, when habitats are relatively intact and stressors are reduced in their importance by active management or species’ adaptive responses, declines of some amphibians may be partially reversible, at least at a regional scale. Other studies conducted over similarly large temporal and spatial scales are critically needed to provide insight and generality about the reversibility of amphibian declines at a global scale. PMID:27698128

Adaptive Numerical Algorithms in Space Weather Modeling

NASA Technical Reports Server (NTRS)

Toth, Gabor; vanderHolst, Bart; Sokolov, Igor V.; DeZeeuw, Darren; Gombosi, Tamas I.; Fang, Fang; Manchester, Ward B.; Meng, Xing; Nakib, Dalal; Powell, Kenneth G.;

epiDMS: Data Management and Analytics for Decision-Making From Epidemic Spread Simulation Ensembles.

PubMed

Liu, Sicong; Poccia, Silvestro; Candan, K Selçuk; Chowell, Gerardo; Sapino, Maria Luisa

2016-12-01

Carefully calibrated large-scale computational models of epidemic spread represent a powerful tool to support the decision-making process during epidemic emergencies. Epidemic models are being increasingly used for generating forecasts of the spatial-temporal progression of epidemics at different spatial scales and for assessing the likely impact of different intervention strategies. However, the management and analysis of simulation ensembles stemming from large-scale computational models pose challenges, particularly when dealing with multiple interdependent parameters, spanning multiple layers and geospatial frames, affected by complex dynamic processes operating at different resolutions. We describe and illustrate with examples a novel epidemic simulation data management system, epiDMS, that was developed to address the challenges that arise from the need to generate, search, visualize, and analyze, in a scalable manner, large volumes of epidemic simulation ensembles and observations during the progression of an epidemic. epiDMS is a publicly available system that facilitates management and analysis of large epidemic simulation ensembles. epiDMS aims to fill an important hole in decision-making during healthcare emergencies by enabling critical services with significant economic and health impact. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Groundwater-fed irrigation impacts spatially distributed temporal scaling behavior of the natural system: a spatio-temporal framework for understanding water management impacts

NASA Astrophysics Data System (ADS)

Condon, Laura E.; Maxwell, Reed M.

2014-03-01

Regional scale water management analysis increasingly relies on integrated modeling tools. Much recent work has focused on groundwater-surface water interactions and feedbacks. However, to our knowledge, no study has explicitly considered impacts of management operations on the temporal dynamics of the natural system. Here, we simulate twenty years of hourly moisture dependent, groundwater-fed irrigation using a three-dimensional, fully integrated, hydrologic model (ParFlow-CLM). Results highlight interconnections between irrigation demand, groundwater oscillation frequency and latent heat flux variability not previously demonstrated. Additionally, the three-dimensional model used allows for novel consideration of spatial patterns in temporal dynamics. Latent heat flux and water table depth both display spatial organization in temporal scaling, an important finding given the spatial homogeneity and weak scaling observed in atmospheric forcings. Pumping and irrigation amplify high frequency (sub-annual) variability while attenuating low frequency (inter-annual) variability. Irrigation also intensifies scaling within irrigated areas, essentially increasing temporal memory in both the surface and the subsurface. These findings demonstrate management impacts that extend beyond traditional water balance considerations to the fundamental behavior of the system itself. This is an important step to better understanding groundwater’s role as a buffer for natural variability and the impact that water management has on this capacity.

Temporal Dependency and the Structure of Early Looking.

PubMed

Messinger, Daniel S; Mattson, Whitney I; Todd, James Torrence; Gangi, Devon N; Myers, Nicholas D; Bahrick, Lorraine E

2017-01-01

Although looking time is used to assess infant perceptual and cognitive processing, little is known about the temporal structure of infant looking. To shed light on this temporal structure, 127 three-month-olds were assessed in an infant-controlled habituation procedure and presented with a pre-recorded display of a woman addressing the infant using infant-directed speech. Previous individual look durations positively predicted subsequent look durations over a six look window, suggesting a temporal dependency between successive infant looks. The previous look duration continued to predict the subsequent look duration after accounting for habituation-linked declines in look duration, and when looks were separated by an inter-trial interval in which no stimulus was displayed. Individual differences in temporal dependency, the strength of associations between consecutive look durations, are distinct from individual differences in mean infant look duration. Nevertheless, infants with stronger temporal dependency had briefer mean look durations, a potential index of stimulus processing. Temporal dependency was evident not only between individual infant looks but between the durations of successive habituation trials (total looking within a trial). Finally, temporal dependency was evident in associations between the last look at the habituation stimulus and the first look at a novel test stimulus. Thus temporal dependency was evident across multiple timescales (individual looks and trials comprised of multiple individual looks) and persisted across conditions including brief periods of no stimulus presentation and changes from a familiar to novel stimulus. Associations between consecutive look durations over multiple timescales and stimuli suggest a temporal structure of infant attention that has been largely ignored in previous work on infant looking.

Temporal Dependency and the Structure of Early Looking

PubMed Central

Messinger, Daniel S.; Mattson, Whitney I.; Todd, James Torrence; Gangi, Devon N.; Myers, Nicholas D.; Bahrick, Lorraine E.

2017-01-01

Although looking time is used to assess infant perceptual and cognitive processing, little is known about the temporal structure of infant looking. To shed light on this temporal structure, 127 three-month-olds were assessed in an infant-controlled habituation procedure and presented with a pre-recorded display of a woman addressing the infant using infant-directed speech. Previous individual look durations positively predicted subsequent look durations over a six look window, suggesting a temporal dependency between successive infant looks. The previous look duration continued to predict the subsequent look duration after accounting for habituation-linked declines in look duration, and when looks were separated by an inter-trial interval in which no stimulus was displayed. Individual differences in temporal dependency, the strength of associations between consecutive look durations, are distinct from individual differences in mean infant look duration. Nevertheless, infants with stronger temporal dependency had briefer mean look durations, a potential index of stimulus processing. Temporal dependency was evident not only between individual infant looks but between the durations of successive habituation trials (total looking within a trial). Finally, temporal dependency was evident in associations between the last look at the habituation stimulus and the first look at a novel test stimulus. Thus temporal dependency was evident across multiple timescales (individual looks and trials comprised of multiple individual looks) and persisted across conditions including brief periods of no stimulus presentation and changes from a familiar to novel stimulus. Associations between consecutive look durations over multiple timescales and stimuli suggest a temporal structure of infant attention that has been largely ignored in previous work on infant looking. PMID:28076362

Spatial/Temporal Variations of Crime: A Routine Activity Theory Perspective.

PubMed

de Melo, Silas Nogueira; Pereira, Débora V S; Andresen, Martin A; Matias, Lindon Fonseca

2018-05-01

Temporal and spatial patterns of crime in Campinas, Brazil, are analyzed considering the relevance of routine activity theory in a Latin American context. We use geo-referenced criminal event data, 2010-2013, analyzing spatial patterns using census tracts and temporal patterns considering seasons, months, days, and hours. Our analyses include difference in means tests, count-based regression models, and Kulldorff's scan test. We find that crime in Campinas, Brazil, exhibits both temporal and spatial-temporal patterns. However, the presence of these patterns at the different temporal scales varies by crime type. Specifically, not all crime types have statistically significant temporal patterns at all scales of analysis. As such, routine activity theory works well to explain temporal and spatial-temporal patterns of crime in Campinas, Brazil. However, local knowledge of Brazilian culture is necessary for understanding a portion of these crime patterns.

Predicting heavy episodic drinking using an extended temporal self-regulation theory.

PubMed

Black, Nicola; Mullan, Barbara; Sharpe, Louise

2017-10-01

Alcohol consumption contributes significantly to the global burden from disease and injury, and specific patterns of heavy episodic drinking contribute uniquely to this burden. Temporal self-regulation theory and the dual-process model describe similar theoretical constructs that might predict heavy episodic drinking. The aims of this study were to test the utility of temporal self-regulation theory in predicting heavy episodic drinking, and examine whether the theoretical relationships suggested by the dual-process model significantly extend temporal self-regulation theory. This was a predictive study with 149 Australian adults. Measures were questionnaires (self-report habit index, cues to action scale, purpose-made intention questionnaire, timeline follow-back questionnaire) and executive function tasks (Stroop, Tower of London, operation span). Participants completed measures of theoretical constructs at baseline and reported their alcohol consumption two weeks later. Data were analysed using hierarchical multiple linear regression. Temporal self-regulation theory significantly predicted heavy episodic drinking (R 2 =48.0-54.8%, p<0.001) and the hypothesised extension significantly improved the prediction of heavy episodic drinking frequency (ΔR 2 =4.5%, p=0.001) but not peak consumption (ΔR 2 =1.4%, p=0.181). Intention and behavioural prepotency directly predicted heavy episodic drinking (p<0.01). Planning ability moderated the intention-behaviour relationship and inhibitory control moderated the behavioural prepotency-behaviour relationship (p<0.05). Both temporal self-regulation theory and the extended temporal self-regulation theory provide good prediction of heavy episodic drinking. Intention, behavioural prepotency, planning ability and inhibitory control may be good targets for interventions designed to decrease heavy episodic drinking. Copyright © 2017 Elsevier Ltd. All rights reserved.

Seasonal climate signals from multiple tree ring metrics: A case study of Pinus ponderosa in the upper Columbia River Basin

NASA Astrophysics Data System (ADS)

Dannenberg, Matthew P.; Wise, Erika K.

2016-04-01

Projected changes in the seasonality of hydroclimatic regimes are likely to have important implications for water resources and terrestrial ecosystems in the U.S. Pacific Northwest. The tree ring record, which has frequently been used to position recent changes in a longer-term context, typically relies on signals embedded in the total ring width of tree rings. Additional climatic inferences at a subannual temporal scale can be made using alternative tree ring metrics such as earlywood and latewood widths and the density of tree ring latewood. Here we examine seasonal precipitation and temperature signals embedded in total ring width, earlywood width, adjusted latewood width, and blue intensity chronologies from a network of six Pinus ponderosa sites in and surrounding the upper Columbia River Basin of the U.S. Pacific Northwest. We also evaluate the potential for combining multiple tree ring metrics together in reconstructions of past cool- and warm-season precipitation. The common signal among all metrics and sites is related to warm-season precipitation. Earlywood and latewood widths differ primarily in their sensitivity to conditions in the year prior to growth. Total and earlywood widths from the lowest elevation sites also reflect cool-season moisture. Effective correlation analyses and composite-plus-scale tests suggest that combining multiple tree ring metrics together may improve reconstructions of warm-season precipitation. For cool-season precipitation, total ring width alone explains more variance than any other individual metric or combination of metrics. The composite-plus-scale tests show that variance-scaled precipitation reconstructions in the upper Columbia River Basin may be asymmetric in their ability to capture extreme events.

Quaternary geomorphology and modern coastal development in response to an inherent geologic framework: An example from Charleston, South Carolina

USGS Publications Warehouse

Harris, M.S.; Gayes, P.T.; Kindinger, J.L.; Flocks, J.G.; Krantz, D.E.; Donovan, P.

2005-01-01

Coastal landscapes evolve over wide-ranging spatial and temporal scales in response to physical and biological pro-cesses that interact with a wide range of variables. To develop better predictive models for these dynamic areas, we must understand the influence of these variables on coastal morphologies and ultimately how they influence coastal processes. This study defines the influence of geologic framework variability on a classic mixed-energy coastline, and establishes four categorical scales of spatial and temporal influence on the coastal system. The near-surface, geologic framework was delineated using high-resolution seismic profiles, shallow vibracores, detailed geomorphic maps, historical shorelines, aerial photographs, and existing studies, and compared to the long- and short-term development of two coastal compartments near Charleston, South Carolina. Although it is clear that the imprint of a mixed-energy tidal and wave signal (basin-scale) dictates formation of drumstick barriers and that immediate responses to wave climate are dramatic, island size, position, and longer-term dynamics are influenced by a series of inherent, complex near-surface stratigraphic geometries. Major near-surface Tertiary geometries influence inlet placement and drainage development (island-scale) through multiple interglacial cycles and overall channel morphology (local-scale). During the modern marine transgression, the halo of ebb-tidal deltas greatly influence inlet region dynamics, while truncated beach ridges and exposed, differentially erodable Cenozoic deposits in the active system influence historical shoreline dynamics and active shoreface morphologies (blockscale). This study concludes that the mixed-energy imprint of wave and tide theories dominates general coastal morphology, but that underlying stratigraphic influences on the coast provide site-specific, long-standing imprints on coastal evolution.

Wetland characteristics linked to broad-scale patterns in Culiseta melanura abundance and eastern equine encephalitis virus infection.

PubMed

Skaff, Nicholas K; Armstrong, Philip M; Andreadis, Theodore G; Cheruvelil, Kendra S

2017-10-18

Eastern equine encephalitis virus (EEEV) is an expanding mosquito-borne threat to humans and domestic animal populations in the northeastern United States. Outbreaks of EEEV are challenging to predict due to spatial and temporal uncertainty in the abundance and viral infection of Cs. melanura, the principal enzootic vector. EEEV activity may be closely linked to wetlands because they provide essential habitat for mosquito vectors and avian reservoir hosts. However, wetlands are not homogeneous and can vary by vegetation, connectivity, size, and inundation patterns. Wetlands may also have different effects on EEEV transmission depending on the assessed spatial scale. We investigated associations between wetland characteristics and Cs. melanura abundance and infection with EEEV at multiple spatial scales in Connecticut, USA. Our findings indicate that wetland vegetative characteristics have strong associations with Cs. melanura abundance. Deciduous and evergreen forested wetlands were associated with higher Cs. melanura abundance, likely because these wetlands provide suitable subterranean habitat for Cs. melanura development. In contrast, Cs. melanura abundance was negatively associated with emergent and scrub/shrub wetlands, and wetland connectivity to streams. These relationships were generally strongest at broad spatial scales. Additionally, the relationships between wetland characteristics and EEEV infection in Cs. melanura were generally weak. However, Cs. melanura abundance was strongly associated with EEEV infection, suggesting that wetland-associated changes in abundance may be indirectly linked to EEEV infection in Cs. melanura. Finally, we found that wet hydrological conditions during the transmission season and during the fall/winter preceding the transmission season were associated with higher Cs. melanura abundance and EEEV infection, indicating that wet conditions are favorable for EEEV transmission. These results expand the broad-scale understanding of the effects of wetlands on EEEV transmission and help to reduce the spatial and temporal uncertainty associated with EEEV outbreaks.

beta-diversity and species accumulation in antarctic coastal benthos: influence of habitat, distance and productivity on ecological connectivity.

PubMed

Thrush, Simon F; Hewitt, Judi E; Cummings, Vonda J; Norkko, Alf; Chiantore, Mariachiara

2010-07-30

High Antarctic coastal marine environments are comparatively pristine with strong environmental gradients, which make them important places to investigate biodiversity relationships. Defining how different environmental features contribute to shifts in beta-diversity is especially important as these shifts reflect both spatio-temporal variations in species richness and the degree of ecological separation between local and regional species pools. We used complementary techniques (species accumulation models, multivariate variance partitioning and generalized linear models) to assess how the roles of productivity, bio-physical habitat heterogeneity and connectivity change with spatial scales from metres to 100's of km. Our results demonstrated that the relative importance of specific processes influencing species accumulation and beta-diversity changed with increasing spatial scale, and that patterns were never driven by only one factor. Bio-physical habitat heterogeneity had a strong influence on beta-diversity at scales <290 km, while the effects of productivity were low and significant only at scales >40 km. Our analysis supports the emphasis on the analysis of diversity relationships across multiple spatial scales and highlights the unequal connectivity of individual sites to the regional species pool. This has important implications for resilience to habitat loss and community homogenisation, especially for Antarctic benthic communities where rates of recovery from disturbance are slow, there is a high ratio of poor-dispersing and brooding species, and high biogenic habitat heterogeneity and spatio-temporal variability in primary production make the system vulnerable to disturbance. Consequently, large areas need to be included within marine protected areas for effective management and conservation of these special ecosystems in the face of increasing anthropogenic disturbance.

Habitat traits and patterns of abundance of the purple sea urchin, Paracentrotus lividus (Lamarck, 1816), at multiple scales along the north Portuguese coast

NASA Astrophysics Data System (ADS)

Domínguez, Rula; Domínguez Godino, Jorge; Freitas, Cristiano; Machado, Inês; Bertocci, Iacopo

2015-03-01

Spatial and temporal patterns of abundance and distribution of sea urchins (Paracentrotus lividus) from intertidal rockpools of the north Portuguese coast were examined in relation to physical (surface, altitude, depth, topographic complexity and exposure) and biological (substrate cover by dominant organisms) habitat traits. The methodology was based on a multi-factorial design where the total number and the abundance of urchins in each of six size classes were sampled over a range of spatial scales, from 10s of cm to kms, and a temporal scale of five months. The results highlighted three main features of the studied system: (1) the largest proportion of variability of sea urchins occurred at the smallest scale examined; (2) urchins from different size classes showed different patterns of abundance in relation to habitat traits; (3) variables normally invoked as potential drivers of distribution of urchins at a range of scales, such as hydrodynamics and shore height, were relatively less important than other abiotic (i.e. pool area, pool mean depth calculated over five replicate measures and sand cover) and biological (i.e. space occupancy by the reef-forming polychaete Sabellaria alveolata and mussels vs. availability of bare rock) variables to provide a considerable contribution to the variability of sea urchins. Intertidal populations of sea urchins are abundant on many rocky shores, where they are socially and economically important as food resource and ecologically key as habitat modelers. This study provides new clues on relatively unstudied populations, with relevant implications for possible management decisions, including the implementation of protection schemes able to preserve the main recruitment, settlement and development areas of P. lividus.

Multiple Stressors in a Changing World: The Need for an Improved Perspective on Physiological Responses to the Dynamic Marine Environment.

PubMed

Gunderson, Alex R; Armstrong, Eric J; Stillman, Jonathon H

2016-01-01

Abiotic conditions (e.g., temperature and pH) fluctuate through time in most marine environments, sometimes passing intensity thresholds that induce physiological stress. Depending on habitat and season, the peak intensity of different abiotic stressors can occur in or out of phase with one another. Thus, some organisms are exposed to multiple stressors simultaneously, whereas others experience them sequentially. Understanding these physicochemical dynamics is critical because how organisms respond to multiple stressors depends on the magnitude and relative timing of each stressor. Here, we first discuss broad patterns of covariation between stressors in marine systems at various temporal scales. We then describe how these dynamics will influence physiological responses to multi-stressor exposures. Finally, we summarize how multi-stressor effects are currently assessed. We find that multi-stressor experiments have rarely incorporated naturalistic physicochemical variation into their designs, and emphasize the importance of doing so to make ecologically relevant inferences about physiological responses to global change.

Reflections on a vision for integrated research and monitoring after 15 years

USGS Publications Warehouse

Murdoch, Peter S.; McHale, Michael; Baron, Jill S.

2014-01-01

In May of 1998, Owen Bricker and his co-author Michael Ruggiero introduced a conceptual design for integrating the Nation’s environmental research and monitoring programs. The Framework for Integrated Monitoring and Related Research was an organizing strategy for relating data collected by various programs, at multiple spatial and temporal scales, and by multiple science disciplines to solve complex ecological issues that individual research or monitoring programs were not designed to address. The concept nested existing intensive monitoring and research stations within national and regional surveys, remotely sensed data, and inventories to produce a collaborative program for multi-scale, multi-network integrated environmental monitoring and research. Analyses of gaps in data needed for specific issues would drive decisions on network improvements or enhancements. Data contributions to the Framework from existing networks would help indicate critical research and monitoring programs to protect during budget reductions. Significant progress has been made since 1998 on refining the Framework strategy. Methods and models for projecting scientific information across spatial and temporal scales have been improved, and a few regional pilots of multi-scale data-integration concepts have been attempted. The links between science and decision-making are also slowly improving and being incorporated into science practice. Experiments with the Framework strategy since 1998 have revealed the foundational elements essential to its successful implementation, such as defining core measurements, establishing standards of data collection and management, integrating research and long-term monitoring, and describing baseline ecological conditions. They have also shown us the remaining challenges to establishing the Framework concept: protecting and enhancing critical long-term monitoring, filling gaps in measurement methods, improving science for decision support, and integrating the disparate integrated science efforts now underway. In the 15 years since the Bricker and Ruggiero (Ecol Appl 8(2):326–329, 1998) paper challenged us with a new paradigm for bringing sound and comprehensive science to environmental decisions, the scientific community can take pride in the progress that has been made, while also taking stock of the challenges ahead for completing the Framework vision.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Controlling multiple plasma channels created by a high-power femtosecond laser pulse

NASA Astrophysics Data System (ADS)

Kosareva, O. G.; Luo, Q.

2005-10-01

Femtosecond light filaments are comparatively long regions of the spatially and temporally localized radiation zones, which generate free electrons in the medium. At high pulse peak power multiple filaments are produced leading to stochastic plasma channels (Mlejnek et al.: PRL 83, 2938 (1999)). In both atmospheric long-distance propagation (Sprangle et al., PRE 66, 046418 (2002), Kasparian et al, Science 301, 61 (2003)) and focusing the radiation into condensed matter important issues are production of elongated plasma channels, as well as high conversion efficiency to the white light. We control stochastic plasma channels by changing the initial beam size or shape. The result is the increase in the plasma density and white light signal. Control by regular small-scale perturbations allows us to suppress atmospheric turbulence in air and create an array of well-arranged filaments in fused silica.

Hybrid inversions of CO2 fluxes at regional scale applied to network design

NASA Astrophysics Data System (ADS)

Kountouris, Panagiotis; Gerbig, Christoph; -Thomas Koch, Frank

2013-04-01

Long term observations of atmospheric greenhouse gas measuring stations, located at representative regions over the continent, improve our understanding of greenhouse gas sources and sinks. These mixing ratio measurements can be linked to surface fluxes by atmospheric transport inversions. Within the upcoming years new stations are to be deployed, which requires decision making tools with respect to the location and the density of the network. We are developing a method to assess potential greenhouse gas observing networks in terms of their ability to recover specific target quantities. As target quantities we use CO2 fluxes aggregated to specific spatial and temporal scales. We introduce a high resolution inverse modeling framework, which attempts to combine advantages from pixel based inversions with those of a carbon cycle data assimilation system (CCDAS). The hybrid inversion system consists of the Lagrangian transport model STILT, the diagnostic biosphere model VPRM and a Bayesian inversion scheme. We aim to retrieve the spatiotemporal distribution of net ecosystem exchange (NEE) at a high spatial resolution (10 km x 10 km) by inverting for spatially and temporally varying scaling factors for gross ecosystem exchange (GEE) and respiration (R) rather than solving for the fluxes themselves. Thus the state space includes parameters for controlling photosynthesis and respiration, but unlike in a CCDAS it allows for spatial and temporal variations, which can be expressed as NEE(x,y,t) = λG(x,y,t) GEE(x,y,t) + λR(x,y,t) R(x,y,t) . We apply spatially and temporally correlated uncertainties by using error covariance matrices with non-zero off-diagonal elements. Synthetic experiments will test our system and select the optimal a priori error covariance by using different spatial and temporal correlation lengths on the error statistics of the a priori covariance and comparing the optimized fluxes against the 'known truth'. As 'known truth' we use independent fluxes generated from a different biosphere model (BIOME-BGC). Initially we perform single-station inversions for Ochsenkopf tall tower located in Germany. Further expansion of the inversion framework to multiple stations and its application to network design will address the questions of how well a set of network stations can constrain a given target quantity, and whether there are objective criteria to select an optimal configuration for new stations that maximizes the uncertainty reduction.

Learning about Spatial and Temporal Scale: Current Research, Psychological Processes, and Classroom Implications

ERIC Educational Resources Information Center

Cheek, Kim A.; LaDue, Nicole D.; Shipley, Thomas F.

2017-01-01

Geoscientists analyze and integrate spatial and temporal information at a range of scales to understand Earth processes. Despite this, the concept of scale is ill defined and taught unevenly across the K-16 continuum. This literature review focuses on two meanings of scale: one as the magnitude of the extent of a dimension and the other as a…

Intrinsic vs. spurious long-range memory in high-frequency records of environmental radioactivity. Critical re-assessment and application to indoor 222Rn concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, R. V.; Potirakis, S. M.; Barbosa, S. M.; Matos, J. A. O.; Pereira, A. J. S. C.; Neves, L. J. P. F.

2015-05-01

The presence or absence of long-range correlations in the environmental radioactivity fluctuations has recently attracted considerable interest. Among a multiplicity of practically relevant applications, identifying and disentangling the environmental factors controlling the variable concentrations of the radioactive noble gas radon is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we present a critical re-assessment of a multiplicity of complementary methods that have been previously applied for evaluating the presence of long-range correlations and fractal scaling in environmental radon variations with a particular focus on the specific properties of the underlying time series. As an illustrative case study, we subsequently re-analyze two high-frequency records of indoor radon concentrations from Coimbra, Portugal, each of which spans several weeks of continuous measurements at a high temporal resolution of five minutes.Our results reveal that at the study site, radon concentrations exhibit complex multi-scale dynamics with qualitatively different properties at different time-scales: (i) essentially white noise in the high-frequency part (up to time-scales of about one hour), (ii) spurious indications of a non-stationary, apparently long-range correlated process (at time scales between some hours and one day) arising from marked periodic components, and (iii) low-frequency variability indicating a true long-range dependent process. In the presence of such multi-scale variability, common estimators of long-range memory in time series are prone to fail if applied to the raw data without previous separation of time-scales with qualitatively different dynamics.

High-Resolution Climate Data Visualization through GIS- and Web-based Data Portals

NASA Astrophysics Data System (ADS)

WANG, X.; Huang, G.

2017-12-01

Sound decisions on climate change adaptation rely on an in-depth assessment of potential climate change impacts at regional and local scales, which usually requires finer resolution climate projections at both spatial and temporal scales. However, effective downscaling of global climate projections is practically difficult due to the lack of computational resources and/or long-term reference data. Although a large volume of downscaled climate data has been make available to the public, how to understand and interpret the large-volume climate data and how to make use of the data to drive impact assessment and adaptation studies are still challenging for both impact researchers and decision makers. Such difficulties have become major barriers preventing informed climate change adaptation planning at regional scales. Therefore, this research will explore new GIS- and web-based technologies to help visualize the large-volume regional climate data with high spatiotemporal resolutions. A user-friendly public data portal, named Climate Change Data Portal (CCDP, http://ccdp.network), will be established to allow intuitive and open access to high-resolution regional climate projections at local scales. The CCDP offers functions of visual representation through geospatial maps and data downloading for a variety of climate variables (e.g., temperature, precipitation, relative humidity, solar radiation, and wind) at multiple spatial resolutions (i.e., 25 - 50 km) and temporal resolutions (i.e., annual, seasonal, monthly, daily, and hourly). The vast amount of information the CCDP encompasses can provide a crucial basis for assessing impacts of climate change on local communities and ecosystems and for supporting better decision making under a changing climate.

Collaborative Observation and Research (CORE) Watersheds: new strategies for tracking the regional effects of climate change on complex systems

NASA Astrophysics Data System (ADS)

Murdoch, P. S.

2007-12-01

The past 30 years of environmental research have shown that our world is not made up of discrete components acting independently, but rather of a mosaic of complex relations among air, land, water, living resources, and human activities. Recent warming of the climate is having a significant effect on the functioning of those systems. A national imperative is developing to quickly establish local, regional, and national systems for anticipating environmental degradation from a changing climate and developing cost-effective adaptation or mitigation strategies. In these circumstances, the debate over research versus monitoring becomes moot--there is a clear need for the integrated application of both across a range of temporal and spatial scales. A national framework that effectively addresses the multiple scales and complex multi-disciplinary processes of climate change is being assembled largely from existing programs through collaboration among Federal, State, local, and NGO organizations. The result will be an observation and research network capable of interpreting complex environmental changes at a range of spatial and temporal scales, but at less cost than if the network were funded as an independent initiative. A pilot implementation of the collaborative framework in the Delaware River Basin yielded multi-scale assessments of carbon storage and flux, and the effects of forest fragmentation and soil calcium depletion on ecosystem function. A prototype of a national climate-effects observation and research network linking research watersheds, regional surveys, remote sensing, and ecosystem modeling is being initiated in the Yukon River Basin where carbon flux associated with permafrost thaw could accelerate global warming.

Topographic mapping of a hierarchy of temporal receptive windows using a narrated story

PubMed Central

Lerner, Y.; Honey, C.J.; Silbert, L.J.; Hasson, U.

2011-01-01

Real life activities, such as watching a movie or engaging in conversation, unfold over many minutes. In the course of such activities the brain has to integrate information over multiple time scales. We recently proposed that the brain uses similar strategies for integrating information across space and over time. Drawing a parallel with spatial receptive fields (SRF), we defined the temporal receptive window(TRW) of a cortical microcircuit as the length of time prior to a response during which sensory information may affect that response. Our previous findings in the visual system are consistent with the hypothesis that TRWs become larger when moving from low-level sensory to high-level perceptual and cognitive areas. In this study, we mapped TRWs in auditory and language areas by measuring fMRI activity in subjects listening to a real life story scrambled at the time scales of words, sentences and paragraphs. Our results revealed a hierarchical topography of TRWs. In early auditory cortices (A1+), brain responses were driven mainly by the momentary incoming input and were similarly reliable across all scrambling conditions. In areas with an intermediate TRW, coherent information at the sentence time scale or longer was necessary to evoke reliable responses. At the apex of the TRW hierarchy we found parietal and frontal areas which responded reliably only when intact paragraphs were heard in a meaningful sequence. These results suggest that the time scale of processing is a functional property that may provide a general organizing principle for the human cerebral cortex. PMID:21414912

Neurophysiological Basis of Multi-Scale Entropy of Brain Complexity and Its Relationship With Functional Connectivity.

PubMed

Wang, Danny J J; Jann, Kay; Fan, Chang; Qiao, Yang; Zang, Yu-Feng; Lu, Hanbing; Yang, Yihong

2018-01-01

Recently, non-linear statistical measures such as multi-scale entropy (MSE) have been introduced as indices of the complexity of electrophysiology and fMRI time-series across multiple time scales. In this work, we investigated the neurophysiological underpinnings of complexity (MSE) of electrophysiology and fMRI signals and their relations to functional connectivity (FC). MSE and FC analyses were performed on simulated data using neural mass model based brain network model with the Brain Dynamics Toolbox, on animal models with concurrent recording of fMRI and electrophysiology in conjunction with pharmacological manipulations, and on resting-state fMRI data from the Human Connectome Project. Our results show that the complexity of regional electrophysiology and fMRI signals is positively correlated with network FC. The associations between MSE and FC are dependent on the temporal scales or frequencies, with higher associations between MSE and FC at lower temporal frequencies. Our results from theoretical modeling, animal experiment and human fMRI indicate that (1) Regional neural complexity and network FC may be two related aspects of brain's information processing: the more complex regional neural activity, the higher FC this region has with other brain regions; (2) MSE at high and low frequencies may represent local and distributed information processing across brain regions. Based on literature and our data, we propose that the complexity of regional neural signals may serve as an index of the brain's capacity of information processing-increased complexity may indicate greater transition or exploration between different states of brain networks, thereby a greater propensity for information processing.

Location Prediction Based on Transition Probability Matrices Constructing from Sequential Rules for Spatial-Temporal K-Anonymity Dataset

PubMed Central

Liu, Zhao; Zhu, Yunhong; Wu, Chenxue

2016-01-01

Spatial-temporal k-anonymity has become a mainstream approach among techniques for protection of users’ privacy in location-based services (LBS) applications, and has been applied to several variants such as LBS snapshot queries and continuous queries. Analyzing large-scale spatial-temporal anonymity sets may benefit several LBS applications. In this paper, we propose two location prediction methods based on transition probability matrices constructing from sequential rules for spatial-temporal k-anonymity dataset. First, we define single-step sequential rules mined from sequential spatial-temporal k-anonymity datasets generated from continuous LBS queries for multiple users. We then construct transition probability matrices from mined single-step sequential rules, and normalize the transition probabilities in the transition matrices. Next, we regard a mobility model for an LBS requester as a stationary stochastic process and compute the n-step transition probability matrices by raising the normalized transition probability matrices to the power n. Furthermore, we propose two location prediction methods: rough prediction and accurate prediction. The former achieves the probabilities of arriving at target locations along simple paths those include only current locations, target locations and transition steps. By iteratively combining the probabilities for simple paths with n steps and the probabilities for detailed paths with n-1 steps, the latter method calculates transition probabilities for detailed paths with n steps from current locations to target locations. Finally, we conduct extensive experiments, and correctness and flexibility of our proposed algorithm have been verified. PMID:27508502

Precision pharmacology for Alzheimer's disease.

PubMed

Hampel, Harald; Vergallo, Andrea; Aguilar, Lisi Flores; Benda, Norbert; Broich, Karl; Cuello, A Claudio; Cummings, Jeffrey; Dubois, Bruno; Federoff, Howard J; Fiandaca, Massimo; Genthon, Remy; Haberkamp, Marion; Karran, Eric; Mapstone, Mark; Perry, George; Schneider, Lon S; Welikovitch, Lindsay A; Woodcock, Janet; Baldacci, Filippo; Lista, Simone

2018-04-01

The complex multifactorial nature of polygenic Alzheimer's disease (AD) presents significant challenges for drug development. AD pathophysiology is progressing in a non-linear dynamic fashion across multiple systems levels - from molecules to organ systems - and through adaptation, to compensation, and decompensation to systems failure. Adaptation and compensation maintain homeostasis: a dynamic equilibrium resulting from the dynamic non-linear interaction between genome, epigenome, and environment. An individual vulnerability to stressors exists on the basis of individual triggers, drivers, and thresholds accounting for the initiation and failure of adaptive and compensatory responses. Consequently, the distinct pattern of AD pathophysiology in space and time must be investigated on the basis of the individual biological makeup. This requires the implementation of systems biology and neurophysiology to facilitate Precision Medicine (PM) and Precision Pharmacology (PP). The regulation of several processes at multiple levels of complexity from gene expression to cellular cycle to tissue repair and system-wide network activation has different time delays (temporal scale) according to the affected systems (spatial scale). The initial failure might originate and occur at every level potentially affecting the whole dynamic interrelated systems within an organism. Unraveling the spatial and temporal dynamics of non-linear pathophysiological mechanisms across the continuum of hierarchical self-organized systems levels and from systems homeostasis to systems failure is key to understand AD. Measuring and, possibly, controlling space- and time-scaled adaptive and compensatory responses occurring during AD will represent a crucial step to achieve the capacity to substantially modify the disease course and progression at the best suitable timepoints, thus counteracting disrupting critical pathophysiological inputs. This approach will provide the conceptual basis for effective disease-modifying pathway-based targeted therapies. PP is based on an exploratory and integrative strategy to complex diseases such as brain proteinopathies including AD, aimed at identifying simultaneous aberrant molecular pathways and predicting their temporal impact on the systems levels. The depiction of pathway-based molecular signatures of complex diseases contributes to the accurate and mechanistic stratification of distinct subcohorts of individuals at the earliest compensatory stage when treatment intervention may reverse, stop, or delay the disease. In addition, individualized drug selection may optimize treatment safety by decreasing risk and amplitude of side effects and adverse reactions. From a methodological point of view, comprehensive "omics"-based biomarkers will guide the exploration of spatio-temporal systems-wide morpho-functional shifts along the continuum of AD pathophysiology, from adaptation to irreversible failure. The Alzheimer Precision Medicine Initiative (APMI) and the APMI cohort program (APMI-CP) have commenced to facilitate a paradigm shift towards effective drug discovery and development in AD. Copyright © 2018 Elsevier Ltd. All rights reserved.

The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

NASA Astrophysics Data System (ADS)

Jiang, P.; Yu, Z.

2011-12-01

Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.

Stochastic extreme downscaling model for an assessment of changes in rainfall intensity-duration-frequency curves over South Korea using multiple regional climate models

NASA Astrophysics Data System (ADS)

So, Byung-Jin; Kim, Jin-Young; Kwon, Hyun-Han; Lima, Carlos H. R.

2017-10-01

A conditional copula function based downscaling model in a fully Bayesian framework is developed in this study to evaluate future changes in intensity-duration frequency (IDF) curves in South Korea. The model incorporates a quantile mapping approach for bias correction while integrated Bayesian inference allows accounting for parameter uncertainties. The proposed approach is used to temporally downscale expected changes in daily rainfall, inferred from multiple CORDEX-RCMs based on Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios, into sub-daily temporal scales. Among the CORDEX-RCMs, a noticeable increase in rainfall intensity is observed in the HadGem3-RA (9%), RegCM (28%), and SNU_WRF (13%) on average, whereas no noticeable changes are observed in the GRIMs (-2%) for the period 2020-2050. More specifically, a 5-30% increase in rainfall intensity is expected in all of the CORDEX-RCMs for 50-year return values under the RCP 8.5 scenario. Uncertainty in simulated rainfall intensity gradually decreases toward the longer durations, which is largely associated with the enhanced strength of the relationship with the 24-h annual maximum rainfalls (AMRs). A primary advantage of the proposed model is that projected changes in future rainfall intensities are well preserved.

Marine cyanophages exhibit local and regional biogeography.

PubMed

Marston, Marcia F; Taylor, Samantha; Sme, Noel; Parsons, Rachel J; Noyes, Timothy J E; Martiny, Jennifer B H

2013-05-01

Biogeographic patterns have been demonstrated for a wide range of microorganisms. Nevertheless, the biogeography of marine viruses has been slower to emerge. Here we investigate biogeographic patterns of marine cyanophages that infect Synechococcus sp. WH7803 across multiple spatial and temporal scales. We compared cyanophage myoviral communities from nine coastal sites in Southern New England (SNE), USA, one site in Long Island NY, and four sites from Bermuda's inshore waters by assaying cyanophage isolates using the myoviral g43 DNA polymerase gene. Cyanophage community composition varied temporally at each of the sites. Further, 6 years of sampling at one Narragansett Bay site revealed annual seasonal variations in community composition, driven by the seasonal reoccurrence of specific viral taxa. Although the four Bermuda communities were similar to one another, they were significantly different than the North American coastal communities, with almost no overlap of taxa between the two regions. Among the SNE sites, cyanophage community composition also varied significantly and was correlated with the body of water sampled (e.g. Narragansett Bay, Cape Cod Bay, Vineyard Sound), although here, the same viral taxa were found at multiple sites. This study demonstrates that marine cyanophages display striking seasonal and spatial biogeographic patterns. © 2012 Society for Applied Microbiology and Blackwell Publishing Ltd.

Temporal changes in native-exotic richness correlations during early post-fire succession

Treesearch

Qinfeng Guo

2017-01-01

The relationship between native and exotic richness has mostly been studied with respect to space (i.e., positive at larger scales, but negative or more variable at smaller scales) and its temporal patterns have rarely been investigated. Although some studies have monitored the temporal trends of both native and exotic richness, how these two groups of species might be...

Development and psychometric evaluation of the Personal Growth Initiative Scale-II.

PubMed

Robitschek, Christine; Ashton, Matthew W; Spering, Cynthia C; Geiger, Nathaniel; Byers, Danielle; Schotts, G Christian; Thoen, Megan A

2012-04-01

The original Personal Growth Initiative Scale (PGIS; Robitschek, 1998) was unidimensional, despite theory identifying multiple components (e.g., cognition and behavior) of personal growth initiative (PGI). The present research developed a multidimensional measure of the complex process of PGI, while retaining the brief and psychometrically sound properties of the original scale. Study 1 focused on scale development, including theoretical derivation of items, assessing factor structure, reducing number of items, and refining the scale length using samples of college students. Study 2 consisted of confirmatory factor analysis with 3 independent samples of college students and community members. Lastly, Study 3 assessed test-retest reliability over 1-, 2-, 4-, and 6-week periods and tests of concurrent and discriminant validity using samples of college students. The final measure, the Personal Growth Initiative Scale-II (PGIS-II), includes 4 subscales: Readiness for Change, Planfulness, Using Resources, and Intentional Behavior. These studies provide exploratory and confirmatory evidence for the 4-factor structure, strong internal consistency for the subscales and overall score across samples, acceptable temporal stability at all assessed intervals, and concurrent and discriminant validity of the PGIS-II. Future directions for research and clinical practice are discussed.

Spatial Modeling and Uncertainty Assessment of Fine Scale Surface Processes Based on Coarse Terrain Elevation Data

NASA Astrophysics Data System (ADS)

Rasera, L. G.; Mariethoz, G.; Lane, S. N.

2017-12-01

Frequent acquisition of high-resolution digital elevation models (HR-DEMs) over large areas is expensive and difficult. Satellite-derived low-resolution digital elevation models (LR-DEMs) provide extensive coverage of Earth's surface but at coarser spatial and temporal resolutions. Although useful for large scale problems, LR-DEMs are not suitable for modeling hydrologic and geomorphic processes at scales smaller than their spatial resolution. In this work, we present a multiple-point geostatistical approach for downscaling a target LR-DEM based on available high-resolution training data and recurrent high-resolution remote sensing images. The method aims at generating several equiprobable HR-DEMs conditioned to a given target LR-DEM by borrowing small scale topographic patterns from an analogue containing data at both coarse and fine scales. An application of the methodology is demonstrated by using an ensemble of simulated HR-DEMs as input to a flow-routing algorithm. The proposed framework enables a probabilistic assessment of the spatial structures generated by natural phenomena operating at scales finer than the available terrain elevation measurements. A case study in the Swiss Alps is provided to illustrate the methodology.

Linked 4-Way Multimodal Brain Differences in Schizophrenia in a Large Chinese Han Population.

PubMed

Liu, Shengfeng; Wang, Haiying; Song, Ming; Lv, Luxian; Cui, Yue; Liu, Yong; Fan, Lingzhong; Zuo, Nianming; Xu, Kaibin; Du, Yuhui; Yu, Qingbao; Luo, Na; Qi, Shile; Yang, Jian; Xie, Sangma; Li, Jian; Chen, Jun; Chen, Yunchun; Wang, Huaning; Guo, Hua; Wan, Ping; Yang, Yongfeng; Li, Peng; Lu, Lin; Yan, Hao; Yan, Jun; Wang, Huiling; Zhang, Hongxing; Zhang, Dai; Calhoun, Vince D; Jiang, Tianzi; Sui, Jing

2018-04-20

Multimodal fusion has been regarded as a promising tool to discover covarying patterns of multiple imaging types impaired in brain diseases, such as schizophrenia (SZ). In this article, we aim to investigate the covarying abnormalities underlying SZ in a large Chinese Han population (307 SZs, 298 healthy controls [HCs]). Four types of magnetic resonance imaging (MRI) features, including regional homogeneity (ReHo) from resting-state functional MRI, gray matter volume (GM) from structural MRI, fractional anisotropy (FA) from diffusion MRI, and functional network connectivity (FNC) resulted from group independent component analysis, were jointly analyzed by a data-driven multivariate fusion method. Results suggest that a widely distributed network disruption appears in SZ patients, with synchronous changes in both functional and structural regions, especially the basal ganglia network, salience network (SAN), and the frontoparietal network. Such a multimodal coalteration was also replicated in another independent Chinese sample (40 SZs, 66 HCs). Our results on auditory verbal hallucination (AVH) also provide evidence for the hypothesis that prefrontal hypoactivation and temporal hyperactivation in SZ may lead to failure of executive control and inhibition, which is relevant to AVH. In addition, impaired working memory performance was found associated with GM reduction and FA decrease in SZ in prefrontal and superior temporal area, in both discovery and replication datasets. In summary, by leveraging multiple imaging and clinical information into one framework to observe brain in multiple views, we can integrate multiple inferences about SZ from large-scale population and offer unique perspectives regarding the missing links between the brain function and structure that may not be achieved by separate unimodal analyses.

Towards a consistent framework to oversample multi-sensors, multi-species satellite data into a common grid

NASA Astrophysics Data System (ADS)

Sun, K.; Zhu, L.; Gonzalez Abad, G.; Nowlan, C. R.; Miller, C. E.; Huang, G.; Liu, X.; Chance, K.; Yang, K.

2017-12-01

It has been well demonstrated that regridding Level 2 products (satellite observations from individual footprints, or pixels) from multiple sensors/species onto regular spatial and temporal grids makes the data more accessible for scientific studies and can even lead to additional discoveries. However, synergizing multiple species retrieved from multiple satellite sensors faces many challenges, including differences in spatial coverage, viewing geometry, and data filtering criteria. These differences will lead to errors and biases if not treated carefully. Operational gridded products are often at 0.25°×0.25° resolution with a global scale, which is too coarse for local heterogeneous emission sources (e.g., urban areas), and at fixed temporal intervals (e.g., daily or monthly). We propose a consistent framework to fully use and properly weight the information of all possible individual satellite observations. A key aspect of this work is an accurate knowledge of the spatial response function (SRF) of the satellite Level 2 pixels. We found that the conventional overlap-area-weighting method (tessellation) is accurate only when the SRF is homogeneous within the parameterized pixel boundary and zero outside the boundary. There will be a tessellation error if the SRF is a smooth distribution, and if this distribution is not properly considered. On the other hand, discretizing the SRF at the destination grid will also induce errors. By balancing these error sources, we found that the SRF should be used in gridding OMI data to 0.2° for fine resolutions. Case studies by merging multiple species and wind data into 0.01° grid will be shown in the presentation.

How Much Is Too Little to Detect Impacts? A Case Study of a Nuclear Power Plant

PubMed Central

Széchy, Maria T. M.; Viana, Mariana S.; Curbelo-Fernandez, Maria P.; Lavrado, Helena P.; Junqueira, Andrea O. R.; Vilanova, Eduardo; Silva, Sérgio H. G.

2012-01-01

Several approaches have been proposed to assess impacts on natural assemblages. Ideally, the potentially impacted site and multiple reference sites are sampled through time, before and after the impact. Often, however, the lack of information regarding the potential overall impact, the lack of knowledge about the environment in many regions worldwide, budgets constraints and the increasing dimensions of human activities compromise the reliability of the impact assessment. We evaluated the impact, if any, and its extent of a nuclear power plant effluent on sessile epibiota assemblages using a suitable and feasible sampling design with no ‘before’ data and budget and logistic constraints. Assemblages were sampled at multiple times and at increasing distances from the point of the discharge of the effluent. There was a clear and localized effect of the power plant effluent (up to 100 m from the point of the discharge). However, depending on the time of the year, the impact reaches up to 600 m. We found a significantly lower richness of taxa in the Effluent site when compared to other sites. Furthermore, at all times, the variability of assemblages near the discharge was also smaller than in other sites. Although the sampling design used here (in particular the number of replicates) did not allow an unambiguously evaluation of the full extent of the impact in relation to its intensity and temporal variability, the multiple temporal and spatial scales used allowed the detection of some differences in the intensity of the impact, depending on the time of sampling. Our findings greatly contribute to increase the knowledge on the effects of multiple stressors caused by the effluent of a power plant and also have important implications for management strategies and conservation ecology, in general. PMID:23110117

How much is too little to detect impacts? A case study of a nuclear power plant.

PubMed

Mayer-Pinto, Mariana; Ignacio, Barbara L; Széchy, Maria T M; Viana, Mariana S; Curbelo-Fernandez, Maria P; Lavrado, Helena P; Junqueira, Andrea O R; Vilanova, Eduardo; Silva, Sérgio H G

2012-01-01

Several approaches have been proposed to assess impacts on natural assemblages. Ideally, the potentially impacted site and multiple reference sites are sampled through time, before and after the impact. Often, however, the lack of information regarding the potential overall impact, the lack of knowledge about the environment in many regions worldwide, budgets constraints and the increasing dimensions of human activities compromise the reliability of the impact assessment. We evaluated the impact, if any, and its extent of a nuclear power plant effluent on sessile epibiota assemblages using a suitable and feasible sampling design with no 'before' data and budget and logistic constraints. Assemblages were sampled at multiple times and at increasing distances from the point of the discharge of the effluent. There was a clear and localized effect of the power plant effluent (up to 100 m from the point of the discharge). However, depending on the time of the year, the impact reaches up to 600 m. We found a significantly lower richness of taxa in the Effluent site when compared to other sites. Furthermore, at all times, the variability of assemblages near the discharge was also smaller than in other sites. Although the sampling design used here (in particular the number of replicates) did not allow an unambiguously evaluation of the full extent of the impact in relation to its intensity and temporal variability, the multiple temporal and spatial scales used allowed the detection of some differences in the intensity of the impact, depending on the time of sampling. Our findings greatly contribute to increase the knowledge on the effects of multiple stressors caused by the effluent of a power plant and also have important implications for management strategies and conservation ecology, in general.

Space Technology 5 Multipoint Observations of Temporal and Spatial Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, G.; Wang, Y.; Slavin, J. A.; Strangeway, R. L.

2009-01-01

Space Technology 5 (ST5) is a constellation mission consisting of three microsatellites. It provides the first multipoint magnetic field measurements in low Earth orbit, which enables us to separate spatial and temporal variations. In this paper, we present a study of the temporal variability of field-aligned currents using the ST5 data. We examine the field-aligned current observations during and after a geomagnetic storm and compare the magnetic field profiles at the three spacecraft. The multipoint data demonstrate that mesoscale current structures, commonly embedded within large-scale current sheets, are very dynamic with highly variable current density and/or polarity in approx.10 min time scales. On the other hand, the data also show that the time scales for the currents to be relatively stable are approx.1 min for mesoscale currents and approx.10 min for large-scale currents. These temporal features are very likely associated with dynamic variations of their charge carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of mesoscale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

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

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.

Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

DOE PAGES

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.; ...

2018-02-09

Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

Temporal dynamics and impact of event interactions in cyber-social populations

NASA Astrophysics Data System (ADS)

Zhang, Yi-Qing; Li, Xiang

2013-03-01

The advance of information technologies provides powerful measures to digitize social interactions and facilitate quantitative investigations. To explore large-scale indoor interactions of a social population, we analyze 18 715 users' Wi-Fi access logs recorded in a Chinese university campus during 3 months, and define event interaction (EI) to characterize the concurrent interactions of multiple users inferred by their geographic coincidences—co-locating in the same small region at the same time. We propose three rules to construct a transmission graph, which depicts the topological and temporal features of event interactions. The vertex dynamics of transmission graph tells that the active durations of EIs fall into the truncated power-law distributions, which is independent on the number of involved individuals. The edge dynamics of transmission graph reports that the transmission durations present a truncated power-law pattern independent on the daily and weekly periodicities. Besides, in the aggregated transmission graph, low-degree vertices previously neglected in the aggregated static networks may participate in the large-degree EIs, which is verified by three data sets covering different sizes of social populations with various rendezvouses. This work highlights the temporal significance of event interactions in cyber-social populations.

Simultaneous application of multiple platforms (Glider, Scanfish, profiling mooring, CTD) to improve detection and quantification of temporal ocean dynamics

NASA Astrophysics Data System (ADS)

Meyer, D.; Prien, R. D.; Lips, U.; Naumann, M.; Liblik, T.; Schulz-Bull, D. E.

2016-02-01

Ocean dynamics are difficult to observe given the broad spectrum of temporal and spatial scales. Robotic technology can be used to address this issue, and help to investigate the variability of physical and biogeochemical processes. This work focuses on ocean robots and in particular on glider technology which seems to be one of the most promising oceanographic tools for future marine research. In this context, we present the results of an observational program conducted in the Baltic Sea combining a profiling mooring (GODESS - Gotland Deep Environmental Sampling Station) and glider technology (Slocum). The temporal variability is captured by the mooring, while the spatial variability is obtained from the glider sampling the surrounding area. Furthermore, classical CTD-measurements and an underwater vehicle (Scanfish) are used simultaneously by two different research vessels to validate and complement the observing network. The main aim of the study is to identify possible synergies between the different platforms and to get a better understanding of maximizing the information content of the data collected by this network. The value and the quality of the data of each individual platform is analyzed and their contribution to the performance of the network itself evaluated.

Multiscale responses of soil stability and invasive plants to removal of non-native grazers from an arid conservation reserve

USGS Publications Warehouse

Beever, E.A.; Huso, M.; Pyke, D.A.

2006-01-01

Disturbances and ecosystem recovery from disturbance both involve numerous processes that operate on multiple spatial and temporal scales. Few studies have investigated how gradients of disturbance intensity and ecosystem responses are distributed across multiple spatial resolutions and also how this relationship changes through time during recovery. We investigated how cover of non-native species and soil-aggregate stability (a measure of vulnerability to erosion by water) in surface and subsurface soils varied spatially during grazing by burros and cattle and whether patterns in these variables changed after grazer removal from Mojave National Preserve, California, USA. We compared distance from water and number of ungulate defecations - metrics of longer-term and recent grazing intensity, respectively, - as predictors of our response variables. We used information-theoretic analyses to compare hierarchical linear models that accounted for important covariates and allowed for interannual variation in the disturbance-response relationship at local and landscape scales. Soil stability was greater under perennial vegetation than in bare interspaces, and surface soil stability decreased with increasing numbers of ungulate defecations. Stability of surface samples was more affected by time since removal of grazers than was stability of subsurface samples, and subsurface soil stability in bare spaces was not related to grazing intensity, time since removal, or any of our other predictors. In the high rainfall year (2003) after cattle had been removed for 1-2 years, cover of all non-native plants averaged nine times higher than in the low-rainfall year (2002). Given the heterogeneity in distribution of large-herbivore impacts that we observed at several resolutions, hierarchical analyses provided a more complete understanding of the spatial and temporal complexities of disturbance and recovery processes in arid ecosystems. ?? 2006 Blackwell Publishing Ltd.

Landscape ecology: Past, present, and future [Chapter 4

Treesearch

Samuel A. Cushman; Jeffrey S. Evans; Kevin McGarigal

2010-01-01

In the preceding chapters we discussed the central role that spatial and temporal variability play in ecological systems, the importance of addressing these explicitly within ecological analyses and the resulting need to carefully consider spatial and temporal scale and scaling. Landscape ecology is the science of linking patterns and processes across scale in both...

Dynamic functional connectivity: Promise, issues, and interpretations

PubMed Central

Hutchison, R. Matthew; Womelsdorf, Thilo; Allen, Elena A.; Bandettini, Peter A.; Calhoun, Vince D.; Corbetta, Maurizio; Penna, Stefania Della; Duyn, Jeff H.; Glover, Gary H.; Gonzalez-Castillo, Javier; Handwerker, Daniel A.; Keilholz, Shella; Kiviniemi, Vesa; Leopold, David A.; de Pasquale, Francesco; Sporns, Olaf; Walter, Martin; Chang, Catie

2013-01-01

The brain must dynamically integrate, coordinate, and respond to internal and external stimuli across multiple time scales. Non-invasive measurements of brain activity with fMRI have greatly advanced our understanding of the large-scale functional organization supporting these fundamental features of brain function. Conclusions from previous resting-state fMRI investigations were based upon static descriptions of functional connectivity (FC), and only recently studies have begun to capitalize on the wealth of information contained within the temporal features of spontaneous BOLD FC. Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain. Here, we review recent findings, methodological considerations, neural and behavioral correlates, and future directions in the emerging field of dynamic FC investigations. PMID:23707587

The Study of Effects of Time Variations in the Earth's Gravity Field on Geodetic Satellites

NASA Technical Reports Server (NTRS)

Shum, C. K.

1998-01-01

The temporal variations in the Earth's gravity field are the consequences of complex interactions between atmosphere, ocean, solid Earth, hydrosphere and cryosphere. The signal ranges from several hours to 18.6 years to geological time scale. The direct and indirect consequences of these variations are manifested in such phenomena as changes in the global sea level and in the global climate pattern. These signals produce observable geodetic satellites. The primary objectives of the proposed effects on near-Earth orbiting investigation include (1) the improved determination of the time-varying gravity field parameters (scale from a few hour to 18.6 year and secular) using long-term satellite laser rs ranging (SLR) observations to multiple geodetic satellites, and (2) the enhanced understanding of these variations with their associated meteorological and geophysical consequences.

Spatially explicit modeling of particulate nutrient flux in Large global rivers

NASA Astrophysics Data System (ADS)

Cohen, S.; Kettner, A.; Mayorga, E.; Harrison, J. A.

2017-12-01

Water, sediment, nutrient and carbon fluxes along river networks have undergone considerable alterations in response to anthropogenic and climatic changes, with significant consequences to infrastructure, agriculture, water security, ecology and geomorphology worldwide. However, in a global setting, these changes in fluvial fluxes and their spatial and temporal characteristics are poorly constrained, due to the limited availability of continuous and long-term observations. We present results from a new global-scale particulate modeling framework (WBMsedNEWS) that combines the Global NEWS watershed nutrient export model with the spatially distributed WBMsed water and sediment model. We compare the model predictions against multiple observational datasets. The results indicate that the model is able to accurately predict particulate nutrient (Nitrogen, Phosphorus and Organic Carbon) fluxes on an annual time scale. Analysis of intra-basin nutrient dynamics and fluxes to global oceans is presented.

Physics of cardiac imaging with multiple-row detector CT.

PubMed

Mahesh, Mahadevappa; Cody, Dianna D

2007-01-01

Cardiac imaging with multiple-row detector computed tomography (CT) has become possible due to rapid advances in CT technologies. Images with high temporal and spatial resolution can be obtained with multiple-row detector CT scanners; however, the radiation dose associated with cardiac imaging is high. Understanding the physics of cardiac imaging with multiple-row detector CT scanners allows optimization of cardiac CT protocols in terms of image quality and radiation dose. Knowledge of the trade-offs between various scan parameters that affect image quality--such as temporal resolution, spatial resolution, and pitch--is the key to optimized cardiac CT protocols, which can minimize the radiation risks associated with these studies. Factors affecting temporal resolution include gantry rotation time, acquisition mode, and reconstruction method; factors affecting spatial resolution include detector size and reconstruction interval. Cardiac CT has the potential to become a reliable tool for noninvasive diagnosis and prevention of cardiac and coronary artery disease. (c) RSNA, 2007.

SCOPE : Future Formation-Flying Magnetospheric Satellite Mission

NASA Astrophysics Data System (ADS)

Saito, Yoshifumi

A formation flight satellite mission "SCOPE" is now under study aiming at launching in 2017. "SCOPE" stands for ‘cross Scale COupling in the Plasma universE'. The main purpose of this mission is to investigate the dynamic behaviors of plasma in the terrestrial magnetosphere that range over magnitudes of both temporal and spatial scales. The basic idea of the SCOPE mission is to distinguish temporal and spatial variations of physical processes by putting five formation flight spacecraft into the key regions of the Earth's magnetosphere. The formation consists of one large mother satellite and four small daughter satellites. Three of the four daughter satellites surround the mother satellite 3-dimensionally maintaining the mutual distances of variable ranges between 5 km and 5000 km. The fourth daughter satellite stays near the mother satellite with the distance between 5 km and 100 km. By this configuration, we can obtain both the macro-scale (1000 km - 5000 km) and micro-scale (¡ 100 km) information about the plasma disturbances at the same time. The launcher for SCOPE has been assumed to be M-V rocket (or its succession rocket) of JAXA. However, due to the termination of M-V rocket, we are now considering to use HIIA. The orbits of SCOPE satellites are all highly elliptical with its apogee 30Re from the Earth center. The inter-satellite link is used for telemetry/command operation as well as ranging to determine the relative orbits of the 5 satellites in small distances. The SCOPE mission is designed such that observational studies from the new perspective, the crossscale coupling, should be conducted. The orbit of the formation flight are designed such that the spacecraft will visit most of the key regions in the magnetosphere, including the bow shock, the magnetospheric boundary, the inner-magnetosphere, and the near-Earth magnetotail. The key issues for the realization of this mission are: (1) The need for high temporal resolution of electron measurements and quantitative wave field measurements at electron scales; (2) The need for full coverage over the energy range of interests with mass spectroscopy; (3) The need for coordinated space plasma observations by intercommunicated formation flying satellites; and (4) The need to resolve more than one-scale simultaneously. In order to cover the multiple (more than two) scales simultaneously, SCOPE and esa's Cross-Scale have started detailed discussion for the future collaboration. By this collaboration, SCOPE can reduce the number of the daughter satellites that can stay within 100 km throughout the mission life.

A scale-invariant internal representation of time.

PubMed

Shankar, Karthik H; Howard, Marc W

2012-01-01

We propose a principled way to construct an internal representation of the temporal stimulus history leading up to the present moment. A set of leaky integrators performs a Laplace transform on the stimulus function, and a linear operator approximates the inversion of the Laplace transform. The result is a representation of stimulus history that retains information about the temporal sequence of stimuli. This procedure naturally represents more recent stimuli more accurately than less recent stimuli; the decrement in accuracy is precisely scale invariant. This procedure also yields time cells that fire at specific latencies following the stimulus with a scale-invariant temporal spread. Combined with a simple associative memory, this representation gives rise to a moment-to-moment prediction that is also scale invariant in time. We propose that this scale-invariant representation of temporal stimulus history could serve as an underlying representation accessible to higher-level behavioral and cognitive mechanisms. In order to illustrate the potential utility of this scale-invariant representation in a variety of fields, we sketch applications using minimal performance functions to problems in classical conditioning, interval timing, scale-invariant learning in autoshaping, and the persistence of the recency effect in episodic memory across timescales.

Use of soil moisture dynamics and patterns at different spatio-temporal scales for the investigation of subsurface flow processes

NASA Astrophysics Data System (ADS)

Blume, T.; Zehe, E.; Bronstert, A.

2009-07-01

Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and binary indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study

PubMed Central

Vickers, T. Winston; Ernest, Holly B.; Boyce, Walter M.

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species. PMID:28609466

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study.

PubMed

Zeller, Katherine A; Vickers, T Winston; Ernest, Holly B; Boyce, Walter M

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species.

Clinical Correlations of Brain Lesion Location in Multiple Sclerosis: Voxel-Based Analysis of a Large Clinical Trial Dataset.

PubMed

Altermatt, Anna; Gaetano, Laura; Magon, Stefano; Häring, Dieter A; Tomic, Davorka; Wuerfel, Jens; Radue, Ernst-Wilhelm; Kappos, Ludwig; Sprenger, Till

2018-05-29

There is a limited correlation between white matter (WM) lesion load as determined by magnetic resonance imaging and disability in multiple sclerosis (MS). The reasons for this so-called clinico-radiological paradox are diverse and may, at least partly, relate to the fact that not just the overall lesion burden, but also the exact anatomical location of lesions predict the severity and type of disability. We aimed at studying the relationship between lesion distribution and disability using a voxel-based lesion probability mapping approach in a very large dataset of MS patients. T2-weighted lesion masks of 2348 relapsing-remitting MS patients were spatially normalized to standard stereotaxic space by non-linear registration. Relations between supratentorial WM lesion locations and disability measures were assessed using a non-parametric ANCOVA (Expanded Disability Status Scale [EDSS]; Multiple Sclerosis Functional Composite, and subscores; Modified Fatigue Impact Scale) or multinomial ordinal logistic regression (EDSS functional subscores). Data from 1907 (81%) patients were included in the analysis because of successful registration. The lesion mapping showed similar areas to be associated with the different disability scales: periventricular regions in temporal, frontal, and limbic lobes were predictive, mainly affecting the posterior thalamic radiation, the anterior, posterior, and superior parts of the corona radiata. In summary, significant associations between lesion location and clinical scores were found in periventricular areas. Such lesion clusters appear to be associated with impairment of different physical and cognitive abilities, probably because they affect commissural and long projection fibers, which are relevant WM pathways supporting many different brain functions.

Power-law Exponent in Multiplicative Langevin Equation with Temporally Correlated Noise

NASA Astrophysics Data System (ADS)

Morita, Satoru

2018-05-01

Power-law distributions are ubiquitous in nature. Random multiplicative processes are a basic model for the generation of power-law distributions. For discrete-time systems, the power-law exponent is known to decrease as the autocorrelation time of the multiplier increases. However, for continuous-time systems, it is not yet clear how the temporal correlation affects the power-law behavior. Herein, we analytically investigated a multiplicative Langevin equation with colored noise. We show that the power-law exponent depends on the details of the multiplicative noise, in contrast to the case of discrete-time systems.

Assessing Climate Risk on Agricultural Production: Insights Using Retrospective Analysis of Crop Insurance and Climatic Trends

NASA Astrophysics Data System (ADS)

Reyes, J. J.; Elias, E.; Eischens, A.; Shilts, M.; Rango, A.; Steele, R.

2017-12-01

The collaborative synthesis of existing datasets, such as long-term climate observations and farmers' crop insurance payments, can increase their overall collective value and societal application. The U.S. Department of Agriculture (USDA) Climate Hubs were created to develop and deliver science-based information and technologies to agricultural and natural resource managers to enable climate-informed decision-making. As part of this mission, Hubs work across USDA and other climate service agencies to synthesize existing information. The USDA Risk Management Agency (RMA) is responsible for overseeing the Federal crop insurance program which currently insures over $100 billion in crops annually. RMA hosts data describing the cause for loss (e.g. drought, wind, irrigation failure) and indemnity amount (i.e. total cost of loss) at multiple spatio-temporal scales (i.e. state, county, year, month). The objective of this paper is to link climate information with indemnities, and their associated cause of loss, to assess climate risk on agricultural production and provide regionally-relevant information to stakeholders to promote resilient working landscapes. We performed a retrospective trend analysis at the state-level for the American Southwest (SW). First, we assessed indemnity-only trends by cause of loss and crop type at varying temporal scales. Historical monthly weather data (i.e. precipitation and temperature) and long-term drought indices (e.g. Palmer Drought Severity Index) were then linked with indemnities and grouped by different causes of loss. Climatological ranks were used to integrate historical comparative intensity of acute and long-term climatic events. Heat and drought as causes of loss were most correlated with temperature and drought indicators, respectively. Across all SW states increasing indemnities were correlated with warmer conditions. Multiple statistical trend analyses suggest a framework is necessary to appropriately measure the biophysical signals in crop insurance trends taking into account spatio-temporal characteristics. Based on stakeholder feedback, we also developed a web-based information browser to visualize and assess indemnity trends providing useful and usable knowledge to support informed land management decisions and ecosystem resilience.

Patterns in Temporal Variability of Temperature, Oxygen and pH along an Environmental Gradient in a Coral Reef

PubMed Central

Guadayol, Òscar; Silbiger, Nyssa J.; Donahue, Megan J.; Thomas, Florence I. M.

2014-01-01

Spatial and temporal environmental variability are important drivers of ecological processes at all scales. As new tools allow the in situ exploration of individual responses to fluctuations, ecologically meaningful ways of characterizing environmental variability at organism scales are needed. We investigated the fine-scale spatial heterogeneity of high-frequency temporal variability in temperature, dissolved oxygen concentration, and pH experienced by benthic organisms in a shallow coastal coral reef. We used a spatio-temporal sampling design, consisting of 21 short-term time-series located along a reef flat-to-reef slope transect, coupled to a long-term station monitoring water column changes. Spectral analyses revealed sharp gradients in variance decomposed by frequency, as well as differences between physically-driven and biologically-reactive parameters. These results highlight the importance of environmental variance at organismal scales and present a new sampling scheme for exploring this variability in situ. PMID:24416364

Composition and daytime vertical distribution of the ichthyoplankton assemblage in the Central Cantabrian Sea shelf, during summer: An Eulerian study

NASA Astrophysics Data System (ADS)

Rodriguez, J. M.; Gonzalez-Pola, C.; Lopez-Urrutia, A.; Nogueira, E.

2011-09-01

During summer, wind driven coastal upwelling dominates in the Central Cantabrian Sea (southern Bay of Biscay). Nevertheless, atmospheric forcing is highly variable and wind pulses may cause noticeable and fast hydrographic responses in the shelf region. In this paper, the composition and vertical distribution of the summer ichthyoplankton assemblage during the daytime at a fixed station, located on the Central Cantabrian Sea shelf, are documented. Also, the impact of a short-time scale hydrographic event on the abundance and structure of the larval fish assemblage is examined. Significant small-scale temporal hydrographic variability was observed. Currents showed changes in speed and direction and significant changes in thermocline depth were also observed. A total of 34 taxa of fish larvae were identified. Engraulis encrasicolus eggs and larvae of the shelf-dwelling species Trachurus trachurus, Capros aper and E. encrasicolus dominated the ichthyoplankton assemblage. The distribution of E. encrasicolus eggs and fish larvae was vertically structured. E. encrasicolus egg concentration increased exponentially towards the surface. Fish larvae showed a subsurface peak of concentration and their vertical distribution was not conditioned by thermocline depths. The short term hydrographic event did not affect the vertical distribution of fish larvae but it accounted for significant temporal changes in larval fish assemblage structure and abundance. Results suggest that temperature and light intensity are important factors in the vertical distribution of fish larvae. They also indicate that the temporal monitoring of the larval fish assemblage in this region requires multiple sampling sites.

Metabarcoding reveals environmental factors influencing spatio-temporal variation in pelagic micro-eukaryotes.

PubMed

Brannock, Pamela M; Ortmann, Alice C; Moss, Anthony G; Halanych, Kenneth M

2016-08-01

Marine environments harbour a vast diversity of micro-eukaryotic organisms (protists and other small eukaryotes) that play important roles in structuring marine ecosystems. However, micro-eukaryote diversity is not well understood. Likewise, knowledge is limited regarding micro-eukaryote spatial and seasonal distribution, especially over long temporal scales. Given the importance of this group for mobilizing energy from lower trophic levels near the base of the food chain to larger organisms, assessing community stability, diversity and resilience is important to understand ecosystem health. Herein, we use a metabarcoding approach to examine pelagic micro-eukaryote communities over a 2.5-year time series. Bimonthly surface sampling (July 2009 to December 2011) was conducted at four locations within Mobile Bay (Bay) and along the Alabama continental shelf (Shelf). Alpha-diversity only showed significant differences in Shelf sites, with the greatest differences observed between summer and winter. Beta-diversity showed significant differences in community composition in relation to season and the Bay was dominated by diatoms, while the Shelf was characterized by dinoflagellates and copepods. The northern Gulf of Mexico is heavily influenced by the Mobile River Basin, which brings low-salinity nutrient-rich water mostly during winter and spring. Community composition was correlated with salinity, temperature and dissolved silicate. However, species interactions (e.g. predation and parasitism) may also contribute to the observed variation, especially on the Shelf, which warrants further exploration. Metabarcoding revealed clear patterns in surface pelagic micro-eukaryote communities that were consistent over multiple years, demonstrating how these techniques could be greatly beneficial to ecological monitoring and management over temporal scales. © 2016 John Wiley & Sons Ltd.

Radial Bias Is Not Necessary For Orientation Decoding

PubMed Central

Pratte, Michael S.; Sy, Jocelyn L.; Swisher, Jascha D.; Tong, Frank

2015-01-01

Multivariate pattern analysis can be used to decode the orientation of a viewed grating from fMRI signals in early visual areas. Although some studies have reported identifying multiple sources of the orientation information that make decoding possible, a recent study argued that orientation decoding is only possible because of a single source: a coarse-scale retinotopically organized preference for radial orientations. Here we aim to resolve these discrepant findings. We show that there were subtle, but critical, experimental design choices that led to the erroneous conclusion that a radial bias is the only source of orientation information in fMRI signals. In particular, we show that the reliance on a fast temporal-encoding paradigm for spatial mapping can be problematic, as effects of space and time become conflated and lead to distorted estimates of a voxel’s orientation or retinotopic preference. When we implement minor changes to the temporal paradigm or to the visual stimulus itself, by slowing the periodic rotation of the stimulus or by smoothing its contrast-energy profile, we find significant evidence of orientation information that does not originate from radial bias. In an additional block-paradigm experiment where space and time were not conflated, we apply a formal model comparison approach and find that many voxels exhibit more complex tuning properties than predicted by radial bias alone or in combination with other known coarse-scale biases. Our findings support the conclusion that radial bias is not necessary for orientation decoding. In addition, our study highlights potential limitations of using temporal phase-encoded fMRI designs for characterizing voxel tuning properties. PMID:26666900

Hot spots, hot moments and time-span of changes in drivers and their responses on carbon cycling in Europe

NASA Astrophysics Data System (ADS)

Tomelleri, E.; Forkel, M.; Fuchs, R.; Jung, M.; Mahecha, M. D.; Reichstein, M.; Weber, U.

2012-12-01

The objective of this study is to provide a complete quantitative assessment of the annual to decadal variability, hotspots of changes and the temporal magnitude of regional trends and variability for the main drivers of carbon cycle like climate and land use and their responses for Europe. For this purpose we used an harmonized climatic data set (ERA Interim and WATCH) and an historical land-use change reconstruction (HILDAv1, Fuchs in prep.). Both the data sets cover the period 1900-2010 and have a 0.25 deg spatial resolution. As driver response we used two different empirically up-scaled GPP fields: the first (MTE) obtained by the application of model trees (Jung et al. 2009) and a second (LUE) based on a light use efficiency model (Tomelleri in prep.). Both the approaches are based on the up-scaling of Fluxnet observations. The response fields have monthly temporal resolution and are limited to the period 1982-2011. We estimated break-points in time series of driver and response variables based on the method of Bai and Perron (2003) to identify changes in trends. This method was implemented in Verbesselt et al. 2010 and applied by deJong et al. 2011 to detect phenological and abrupt changes and trends in vegetation activity based on satellite-derived vegetation index time series. The analysis of drivers and responses allowed to identify the dominant factors driving the biosphere-atmosphere carbon exchange. The synchronous analysis of climatic drivers and land use change allowed us to explain most of the temporal and spatial variability showing that in the regions and time period where the most land use change occurred the climatic drivers are not sufficient to explain trends and oscillation in carbon cycling. The comparison of our analysis for the up-scaling methods shows some agreement: we found inconsistency in the spatial and temporal patterns in regions where the Fluxnet network is less dense. This can be explained by the conceptual difference in the up-scaling methods: while one is on pixel basis (MTE) the other (LUE) is up-scaling model parameters by bioclimatic regions. Our study shows the value of up-scaling methods for understanding the spatial-temporal variability of carbon cycling and how these are a valuable tool for spatial and temporal analysis. Furthermore, the use of climatic drivers and land-use change demonstrated the need of taking natural and anthropogenic drivers into consideration for explaining trends and oscillations. Possibly a further analysis including detailed management practices for forestry and agriculture would help in explaining the remaining variance. References: Bai, J., Perron, P.: Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 2003. Jung, M., Reichstein, M., and Bondeau, A.: Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model. Biogeosciences, 6, 2009. Verbesselt, J., Hyndman, R., Newnham, G., Culvenor, D.: Detecting trend and seasonal changes in satellite image time series. Remote Sensing of Environment,114(1), 2010. de Jong, R., Verbesselt, J., Schaepman, M.E., Bruin, S.: Trend changes in global greening and browning: contribution of short-term trends to longer-term change. Global Change Biology, 18, 2011.

Scale effects on the evapotranspiration estimation over a water-controlled Mediterranean ecosystem and its influence on hydrological modelling

NASA Astrophysics Data System (ADS)

Carpintero, Elisabet; González-Dugo, María P.; José Polo, María; Hain, Christopher; Nieto, Héctor; Gao, Feng; Andreu, Ana; Kustas, William; Anderson, Martha

2017-04-01

The integration of currently available satellite data into surface energy balance models can provide estimates of evapotranspiration (ET) with spatial and temporal resolutions determined by sensor characteristics. The use of data fusion techniques may increase the temporal resolution of these estimates using multiple satellites, providing a more frequent ET monitoring for hydrological purposes. The objective of this work is to analyze the effects of pixel resolution on the estimation of evapotranspiration using different remote sensing platforms, and to provide continuous monitoring of ET over a water-controlled ecosystem, the Holm oak savanna woodland known as dehesa. It is an agroforestry system with a complex canopy structure characterized by widely-spaced oak trees combined with crops, pasture and shrubs. The study was carried out during two years, 2013 and 2014, combining ET estimates at different spatial and temporal resolutions and applying data fusion techniques for a frequent monitoring of water use at fine spatial resolution. A global and daily ET product at 5 km resolution, developed with the ALEXI model using MODIS day-night temperature difference (Anderson et al., 2015a) was used as a starting point. The associated flux disaggregation scheme, DisALEXI (Norman et al., 2003), was later applied to constrain higher resolution ET from both MODIS and Landsat 7/8 images. The Climate Forecast System Reanalysis (CFSR) provided the meteorological data. Finally, a data fusion technique, the STARFM model (Gao et al., 2006), was applied to fuse MODIS and Landsat ET maps in order to obtain daily ET at 30 m resolution. These estimates were validated and analyzed at two different scales: at local scale over a dehesa experimental site and at watershed scale with a predominant Mediterranean oak savanna landscape, both located in Southern Spain. Local ET estimates from the modeling system were validated with measurements provided by an eddy covariance tower installed in the dehesa (38 ° 12 'N, 4 ° 17' W, 736 m a.s.l.). The results supported the ability of ALEXI/DisALEXI model to accurately estimate turbulent and radiative fluxes over this complex landscape, both at 1 Km and at 30 m spatial resolution. The application of the STARFM model gave significant improvement in capturing the spatio-temporal heterogeneity of ET over the different seasons, compared with traditional interpolation methods using MODIS and Landsat ET data. At basin scale, the physically-based distributed hydrological model WiMMed has been applied to evaluate ET estimates. This model focuses on the spatial interpolation of the meteorological variables and the physical modelling of the daily water balance at the cell and watershed scale, using daily streamflow rates measured at the watershed outlet for final comparison.

Spatio-temporal conditional inference and hypothesis tests for neural ensemble spiking precision

PubMed Central

Harrison, Matthew T.; Amarasingham, Asohan; Truccolo, Wilson

2014-01-01

The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spatio-temporal conditional inference (STCI) is introduced here as a semiparametric statistical framework for investigating the nature of precise spiking patterns from collections of neurons that is robust to arbitrarily complex and nonstationary coarse spiking dynamics. The main idea is to focus statistical modeling and inference, not on the full distribution of the data, but rather on families of conditional distributions of precise spiking given different types of coarse spiking. The framework is then used to develop families of hypothesis tests for probing the spatio-temporal precision of spiking patterns. Relationships among different conditional distributions are used to improve multiple hypothesis testing adjustments and to design novel Monte Carlo spike resampling algorithms. Of special note are algorithms that can locally jitter spike times while still preserving the instantaneous peri-stimulus time histogram (PSTH) or the instantaneous total spike count from a group of recorded neurons. The framework can also be used to test whether first-order maximum entropy models with possibly random and time-varying parameters can account for observed patterns of spiking. STCI provides a detailed example of the generic principle of conditional inference, which may be applicable in other areas of neurostatistical analysis. PMID:25380339

Observing large-scale temporal variability of ocean currents by satellite altimetry - With application to the Antarctic circumpolar current

NASA Technical Reports Server (NTRS)

Fu, L.-L.; Chelton, D. B.

1985-01-01

A new method is developed for studying large-scale temporal variability of ocean currents from satellite altimetric sea level measurements at intersections (crossovers) of ascending and descending orbit ground tracks. Using this method, sea level time series can be constructed from crossover sea level differences in small sample areas where altimetric crossovers are clustered. The method is applied to Seasat altimeter data to study the temporal evolution of the Antarctic Circumpolar Current (ACC) over the 3-month Seasat mission (July-October 1978). The results reveal a generally eastward acceleration of the ACC around the Southern Ocean with meridional disturbances which appear to be associated with bottom topographic features. This is the first direct observational evidence for large-scale coherence in the temporal variability of the ACC. It demonstrates the great potential of satellite altimetry for synoptic observation of temporal variability of the world ocean circulation.

The need to consider temporal variability when modelling exchange at the sediment-water interface

USGS Publications Warehouse

Rosenberry, Donald O.

2011-01-01

Most conceptual or numerical models of flows and processes at the sediment-water interface assume steady-state conditions and do not consider temporal variability. The steady-state assumption is required because temporal variability, if quantified at all, is usually determined on a seasonal or inter-annual scale. In order to design models that can incorporate finer-scale temporal resolution we first need to measure variability at a finer scale. Automated seepage meters that can measure flow across the sediment-water interface with temporal resolution of seconds to minutes were used in a variety of settings to characterize seepage response to rainfall, wind, and evapotranspiration. Results indicate that instantaneous seepage fluxes can be much larger than values commonly reported in the literature, although seepage does not always respond to hydrological processes. Additional study is needed to understand the reasons for the wide range and types of responses to these hydrologic and atmospheric events.

Assessing the role of urban developments on storm runoff response through multi-scale catchment experiments

NASA Astrophysics Data System (ADS)

Wilkinson, Mark; Owen, Gareth; Geris, Josie; Soulsby, Chris; Quinn, Paul

2015-04-01

Many communities across the world face the increasing challenge of balancing water quantity and quality issues with accommodating new growth and urban development. Urbanisation is typically associated with detrimental changes in water quality, sediment delivery, and effects on water storage and flow pathways (e.g. increases in flooding). In particular for mixed rural and urban catchments where the spatio-temporal variability of hydrological responses is high, there remains a key research challenge in evaluating the timing and magnitude of storage and flow pathways at multiple scales. This is of crucial importance for appropriate catchment management, for example to aid the design of Green Infrastructure (GI) to mitigate the risk of flooding, among other multiple benefits. The aim of this work was to (i) explore spatio-temporal storm runoff generation characteristics in multi-scale catchment experiments that contain rural and urban land use zones, and (ii) assess the (preliminary) impact of Sustainable Drainage (SuDs) as GI on high flow and flood characteristics. Our key research catchment, the Ouseburn in Northern England (55km2), has rural headwaters (15%) and an urban zone (45%) concentrated in the lower catchment area. There is an intermediate and increasingly expanding peri-urban zone (currently 40%), which is defined here as areas where rural and urban features coexist, alongside GIs. Such a structure is typical for most catchments with urban developments. We monitored spatial precipitation and multiscale nested (five gauges) runoff response, in addition to the storage dynamics in GIs for a period of 6 years (2007-2013). For a range of events, we examined the multiscale nested runoff characteristics (lag time and magnitude) of the rural and urban flow components, assessed how these integrated with changing land use and increasing scale, and discussed the implications for flood management in the catchment. The analyses indicated three distinctly different patterns in the timing and magnitude of the contributions of the different land use zones and their nested integrated runoff response at increasing scales. These can be clearly linked to variations in antecedent conditions and precipitation patterns. For low antecedent flow conditions, the main flood peak is dominated by urban origins (faster responding and larger in relative magnitude); for high antecedent flow conditions, rural (and peri-urban) sources are most dominant. A third type of response involves mixed events, where both rural and urban contributions interact and reinforce the peak flow response. Our analyses showed that the effectiveness of the GIs varied substantially between the different events, suggesting that their design could be improved by introducing variable drainage rates and strategic placements to allow for interactions with the stream network. However, more information is needed on the spatio-temporal variability in water sources, flow pathways and residence times. This is of particular importance to also assess other multiple benefits of GIs, including the impacts on water quality. These challenges are currently addressed in two new case study catchment in the North East of Scotland (10km2) which are undergoing major land use change from rural to urban. Here, integrated tracer and hydrometric data are being collected to characterise the integrated impacts of urbanisation and GIs on flow pathways (nature and length) and associated water quality.

GPI-anchored protein organization and dynamics at the cell surface

PubMed Central

Saha, Suvrajit; Anilkumar, Anupama Ambika; Mayor, Satyajit

2016-01-01

The surface of eukaryotic cells is a multi-component fluid bilayer in which glycosylphosphatidylinositol (GPI)-anchored proteins are an abundant constituent. In this review, we discuss the complex nature of the organization and dynamics of GPI-anchored proteins at multiple spatial and temporal scales. Different biophysical techniques have been utilized for understanding this organization, including fluorescence correlation spectroscopy, fluorescence recovery after photobleaching, single particle tracking, and a number of super resolution methods. Major insights into the organization and dynamics have also come from exploring the short-range interactions of GPI-anchored proteins by fluorescence (or Förster) resonance energy transfer microscopy. Based on the nanometer to micron scale organization, at the microsecond to the second time scale dynamics, a picture of the membrane bilayer emerges where the lipid bilayer appears inextricably intertwined with the underlying dynamic cytoskeleton. These observations have prompted a revision of the current models of plasma membrane organization, and suggest an active actin-membrane composite. PMID:26394904

The Italian version of the Inventory of Interpersonal Problems Personality Disorders Scales (IIP-47): psychometric properties and clinical usefulness as a screening measure.

PubMed

Ubbiali, Alessandro; Chiorri, Carlo; Donati, Deborah

2011-08-01

The Inventory of Interpersonal Problems-47 (IIP-47) is a brief and valid self-report measure for screening Personality Disorders (PDs). This study examined internal consistency, factor structure, criterion validity, temporal stability, and operating characteristics of the Italian version of the IIP-47 in two independent samples: PD subjects (n = 120) and nonclinical subjects (n = 475). Alpha coefficients ranged from .70 to .90. Multiple-Group Confirmatory Factor Analyses showed that the five-correlated-factor model reported in literature had the highest measurement invariance across the two groups. Criterion validity was supported by correlations among IIP-47 scale scores and scores on established measures of personality dimensions and pathology. Test-retest indices ranged from .71 to .95. PD subjects scored significantly higher than nonclinical subjects on all IIP-47 scales and cut-off scores for different levels of specificity and sensibility are reported. It is concluded that the psychometric properties of the original IIP-47 were preserved in its Italian version.

Extreme multi-basin flooding linked with extra-tropical cyclones

NASA Astrophysics Data System (ADS)

De Luca, Paolo; Hillier, John K.; Wilby, Robert L.; Quinn, Nevil W.; Harrigan, Shaun

2017-11-01

Fluvial floods are typically investigated as ‘events’ at the single basin-scale, hence flood management authorities may underestimate the threat of flooding across multiple basins driven by large-scale and nearly concurrent atmospheric event(s). We pilot a national-scale statistical analysis of the spatio-temporal characteristics of extreme multi-basin flooding (MBF) episodes, using peak river flow data for 260 basins in Great Britain (1975-2014), a sentinel region for storms impacting northwest and central Europe. During the most widespread MBF episode, 108 basins (~46% of the study area) recorded annual maximum (AMAX) discharge within a 16 day window. Such episodes are associated with persistent cyclonic and westerly atmospheric circulations, atmospheric rivers, and precipitation falling onto previously saturated ground, leading to hydrological response times <40 h and documented flood impacts. Furthermore, peak flows tend to occur after 0-13 days of very severe gales causing combined and spatially-distributed, yet differentially time-lagged, wind and flood damages. These findings have implications for emergency responders, insurers and contingency planners worldwide.

Computational Modeling of Airway and Pulmonary Vascular Structure and Function: Development of a “Lung Physiome”

PubMed Central

Tawhai, M. H.; Clark, A. R.; Donovan, G. M.; Burrowes, K. S.

2011-01-01

Computational models of lung structure and function necessarily span multiple spatial and temporal scales, i.e., dynamic molecular interactions give rise to whole organ function, and the link between these scales cannot be fully understood if only molecular or organ-level function is considered. Here, we review progress in constructing multiscale finite element models of lung structure and function that are aimed at providing a computational framework for bridging the spatial scales from molecular to whole organ. These include structural models of the intact lung, embedded models of the pulmonary airways that couple to model lung tissue, and models of the pulmonary vasculature that account for distinct structural differences at the extra- and intra-acinar levels. Biophysically based functional models for tissue deformation, pulmonary blood flow, and airway bronchoconstriction are also described. The development of these advanced multiscale models has led to a better understanding of complex physiological mechanisms that govern regional lung perfusion and emergent heterogeneity during bronchoconstriction. PMID:22011236

Large-scale marine ecosystem change and the conservation of marine mammals

USGS Publications Warehouse

O'Shea, T.J.; Odell, D.K.

2008-01-01

Papers in this Special Feature stem from a symposium on large-scale ecosystem change and the conservation of marine mammals convened at the 86th Annual Meeting of the American Society of Mammalogists in June 2006. Major changes are occurring in multiple aspects of the marine environment at unprecedented rates, within the life spans of some individual marine mammals. Drivers of change include shifts in climate, acoustic pollution, disturbances to trophic structure, fisheries interactions, harmful algal blooms, and environmental contaminants. This Special Feature provides an in-depth examination of 3 issues that are particularly troublesome. The 1st article notes the huge spatial and temporal scales of change to which marine mammals are showing ecological responses, and how these species can function as sentinels of such change. The 2nd paper describes the serious problems arising from conflicts with fisheries, and the 3rd contribution reviews the growing issues associated with underwater noise. ?? 2008 American Society of Mammalogists.

Exploring the brain on multiple scales with correlative two-photon and light sheet microscopy

NASA Astrophysics Data System (ADS)

Silvestri, Ludovico; Allegra Mascaro, Anna Letizia; Costantini, Irene; Sacconi, Leonardo; Pavone, Francesco S.

2014-02-01

One of the unique features of the brain is that its activity cannot be framed in a single spatio-temporal scale, but rather spans many orders of magnitude both in space and time. A single imaging technique can reveal only a small part of this complex machinery. To obtain a more comprehensive view of brain functionality, complementary approaches should be combined into a correlative framework. Here, we describe a method to integrate data from in vivo two-photon fluorescence imaging and ex vivo light sheet microscopy, taking advantage of blood vessels as reference chart. We show how the apical dendritic arbor of a single cortical pyramidal neuron imaged in living thy1-GFP-M mice can be found in the large-scale brain reconstruction obtained with light sheet microscopy. Starting from the apical portion, the whole pyramidal neuron can then be segmented. The correlative approach presented here allows contextualizing within a three-dimensional anatomic framework the neurons whose dynamics have been observed with high detail in vivo.

GPI-anchored protein organization and dynamics at the cell surface.

PubMed

Saha, Suvrajit; Anilkumar, Anupama Ambika; Mayor, Satyajit

2016-02-01

The surface of eukaryotic cells is a multi-component fluid bilayer in which glycosylphosphatidylinositol (GPI)-anchored proteins are an abundant constituent. In this review, we discuss the complex nature of the organization and dynamics of GPI-anchored proteins at multiple spatial and temporal scales. Different biophysical techniques have been utilized for understanding this organization, including fluorescence correlation spectroscopy, fluorescence recovery after photobleaching, single particle tracking, and a number of super resolution methods. Major insights into the organization and dynamics have also come from exploring the short-range interactions of GPI-anchored proteins by fluorescence (or Förster) resonance energy transfer microscopy. Based on the nanometer to micron scale organization, at the microsecond to the second time scale dynamics, a picture of the membrane bilayer emerges where the lipid bilayer appears inextricably intertwined with the underlying dynamic cytoskeleton. These observations have prompted a revision of the current models of plasma membrane organization, and suggest an active actin-membrane composite. Copyright © 2016 by the American Society for Biochemistry and Molecular Biology, Inc.

Spatial and temporal variability in growth of southern flounder (Paralichthys lethostigma)

USGS Publications Warehouse

Midway, Stephen R.; Wagner, Tyler; Arnott, Stephen A.; Biondo, Patrick; Martinez-Andrade, Fernando; Wadsworth, Thomas F.

2015-01-01

Delineation of stock structure is important for understanding the ecology and management of many fish populations, particularly those with wide-ranging distributions and high levels of harvest. Southern flounder (Paralichthys lethostigma) is a popular commercial and recreational species along the southeast Atlantic coast and Gulf of Mexico, USA. Recent studies have provided genetic and otolith morphology evidence that the Gulf of Mexico and Atlantic Ocean stocks differ. Using age and growth data from four states (Texas, Alabama, South Carolina, and North Carolina) we expanded upon the traditional von Bertalanffy model in order to compare growth rates of putative geographic stocks of southern flounder. We improved the model fitting process by adding a hierarchical Bayesian framework to allow each parameter to vary spatially or temporally as a random effect, as well as log transforming the three model parameters (L∞, K, andt0). Multiple comparisons of parameters showed that growth rates varied (even within states) for females, but less for males. Growth rates were also consistent through time, when long-term data were available. Since within-basin populations are thought to be genetically well-mixed, our results suggest that consistent small-scale environmental conditions (i.e., within estuaries) likely drive growth rates and should be considered when developing broader scale management plans.

Integrated Emergy and Economic Evaluation of Lotus-Root ...

EPA Pesticide Factsheets

Lotus (Neumbo nucifera, Gaertn) is the most important aquatic vegetable in China, with a cultivation history of over 3000 years. The emergy, energy, material, and money flows of three lotus root cultivation modes in Wanqingsha, Nansha District, Guangzhou, China were examined using Energy Systems Language models and emergy evaluation to better understand their ecological and economic characteristics on multiple spatial and temporal scales. The natural resource foundations, economic characteristics and sustainability of these modes were evaluated and compared. The results showed that although all three modes were highly dependent on purchased emergy inputs, their potential impacts as measured by the local (ELRL) and global (ELRW) environmental loading ratios were less than 1.2 and 0.7, respectively. The lotus-fish mode was the most sustainable with its emergy index of sustainable development (EISD) 2.09 and 2.13 times that of the pure lotus and lotus-shrimp modes, respectively. All three lotus-root production modes had superior economic viability, since their Output/Input ratio ranged from 2.56 to 4.95. The results indicated that agricultural systems may have different environmental impacts and sustainability characteristics at different spatial and temporal scales, and that these impacts and characteristics can be simultaneously explored using integrated emergy and economic evaluations. This study provides some major new insights about agriculture and its potenti

Recording High Resolution 3D Lagrangian Motions In Marine Dinoflagellates using Digital Holographic Microscopic Cinematography

NASA Astrophysics Data System (ADS)

Sheng, J.; Malkiel, E.; Katz, J.; Place, A. R.; Belas, R.

2006-11-01

Detailed data on swimming behavior and locomotion for dense population of dinoflagellates constitutes a key component to understanding cell migration, cell-cell interactions and predator-prey dynamics, all of which affect algae bloom dynamics. Due to the multi-dimensional nature of flagellated cell motions, spatial-temporal Lagrangian measurements of multiple cells in high concentration are very limited. Here we present detailed data on 3D Lagrangian motions for three marine dinoflagellates: Oxyrrhis marina, Karlodinium veneficum, and Pfiesteria piscicida, using digital holographic microscopic cinematography. The measurements are performed in a 5x5x25mm cuvette with cell densities varying from 50,000 ˜ 90,000 cells/ml. Approximately 200-500 cells are tracked simultaneously for 12s at 60fps in a sample volume of 1x1x5 mm at a spatial resolution of 0.4x0.4x2 μm. We fully resolve the longitudinal flagella (˜200nm) along with the Lagrangian trajectory of each organism. Species dependent swimming behavior are identified and categorized quantitatively by velocities, radii of curvature, and rotations of pitch. Statistics on locomotion, temporal & spatial scales, and diffusion rate show substantial differences between species. The scaling between turning radius and cell dimension can be explained by a distributed stokeslet model for a self-propelled body.

Understanding dynamic pattern and process across spatial scales in river systems using simultaneous deployments of in situ sensors

NASA Astrophysics Data System (ADS)

Wollheim, W. M.; Mulukutla, G.; Cook, C.; Carey, R. O.

2014-12-01

Biogeochemical conditions throughout aquatic landscapes are spatially varied and temporally dynamic due to interactions of upstream land use, climate, hydrologic responses, and internal aquatic processes. One of the key goals in aquatic ecosystem ecology is to parse the upstream influences of terrestrial and aquatic processes on local conditions, which becomes progressively more difficult as watershed size increases and as processes are altered by diverse human activities. Simultaneous deployments of high frequency, in situ aquatic sensors for multiple constituents (e.g. NO3-N, CDOM, turbidity, conductivity, D.O., water temperature, along with flow) offer a new approach for understanding patterns along the aquatic continuum. For this talk, we explore strategies for deployments within single watersheds to improve understanding of terrestrial and aquatic processes. We address applications regarding mobilization of non-point nutrient sources across temporal scales, interactions with land use and watershed size, and the importance of aquatic processes. We also explore ways in which simultaneous sensor deployments can be designed to improve parameterization and testing of river network biogeochemical models. We will provide several specific examples using conductivity, nitrate and carbon from ongoing sensor deployments in New England, USA. We expect that improved deployments of sensors and sensor networks will benefit the management of critical freshwater resources.

Spawning patterns of Pacific Lamprey in tributaries to the Willamette River, Oregon

USGS Publications Warehouse

Mayfield, M.P.; Schultz, Luke; Wyss, Lance A.; Clemens, B. J.; Schreck, Carl B.

2014-01-01

Addressing the ongoing decline of Pacific Lamprey Entosphenus tridentatus across its range along the west coast of North America requires an understanding of all life history phases. Currently, spawning surveys (redd counts) are a common tool used to monitor returning adult salmonids, but the methods are in their infancy for Pacific Lamprey. To better understand the spawning phase, our objective was to assess temporal spawning trends, redd abundance, habitat use, and spatial patterns of spawning at multiple spatial scales for Pacific Lamprey in the Willamette River basin, Oregon. Although redd density varied considerably across surveyed reaches, the observed temporal patterns of spawning were related to physical habitat and hydrologic conditions. As has been documented in studies in other basins in the Pacific Northwest, we found that redds were often constructed in pool tailouts dominated by gravel, similar to habitat used by spawning salmonids. Across the entire Willamette Basin, Pacific Lampreys appeared to select reaches with alluvial geology, likely because this is where gravel suitable for spawning accumulated. At the tributary scale, spawning patterns were not as strong, and in reaches with nonalluvial geology redds were more spatially clumped than in reaches with alluvial geology. These results can be used to help identify and conserve Pacific Lamprey spawning habitat across the Pacific Northwest.

Spatial and temporal demographic variation drives within-season fluctuations in sexual selection.

PubMed

Kasumovic, Michael M; Bruce, Matthew J; Andrade, Maydianne C B; Herberstein, Marie E

2008-09-01

Our understanding of selection in nature stems mainly from whole-season and cross-sectional estimates of selection gradients. These estimates suggest that selection is relatively constant within, but fluctuates between seasons. However, the strength of selection depends on demographics, and because demographics can vary within seasons, there is a gap in our understanding regarding the extent to which seasonal fluctuations in demographics may cause variation in selection. Here we use two populations of the golden orb-web spider (Nephila plumipes) that differ in density to examine how demographics change within a season and whether there are correlated shifts in selection. We demonstrate that there is within-season variation in sex ratio and density at multiple spatial and temporal scales. This variation led to changes in the competitive challenges that males encountered at different times of the season and was correlated with significant variation in selection gradients on male size and weight between sampling periods. We highlight the importance of understanding the biology of the organism under study to correctly determine the relevant scale in which to examine selection. We also argue that studies may underestimate the true variation in selection by averaging values, leading to misinterpretation of the effect of selection on phenotypic evolution.

Simulating smoke transport from wildland fires with a regional-scale air quality model: sensitivity to spatiotemporal allocation of fire emissions.

PubMed

Garcia-Menendez, Fernando; Hu, Yongtao; Odman, Mehmet T

2014-09-15

Air quality forecasts generated with chemical transport models can provide valuable information about the potential impacts of fires on pollutant levels. However, significant uncertainties are associated with fire-related emission estimates as well as their distribution on gridded modeling domains. In this study, we explore the sensitivity of fine particulate matter concentrations predicted by a regional-scale air quality model to the spatial and temporal allocation of fire emissions. The assessment was completed by simulating a fire-related smoke episode in which air quality throughout the Atlanta metropolitan area was affected on February 28, 2007. Sensitivity analyses were carried out to evaluate the significance of emission distribution among the model's vertical layers, along the horizontal plane, and into hourly inputs. Predicted PM2.5 concentrations were highly sensitive to emission injection altitude relative to planetary boundary layer height. Simulations were also responsive to the horizontal allocation of fire emissions and their distribution into single or multiple grid cells. Additionally, modeled concentrations were greatly sensitive to the temporal distribution of fire-related emissions. The analyses demonstrate that, in addition to adequate estimates of emitted mass, successfully modeling the impacts of fires on air quality depends on an accurate spatiotemporal allocation of emissions. Copyright © 2014 Elsevier B.V. All rights reserved.

Pattern Informatics Approach to Earthquake Forecasting in 3D

NASA Astrophysics Data System (ADS)

Toya, Y.; Tiampo, K. F.; Rundle, J. B.; Chen, C.; Li, H.; Klein, W.

2009-05-01

Natural seismicity is correlated across multiple spatial and temporal scales, but correlations in seismicity prior to a large earthquake are locally subtle (e.g. seismic quiescence) and often prominent in broad scale (e.g., seismic activation), resulting in local and regional seismicity patterns, e.g. a Mogi's donut. Recognizing that patterns in seismicity rate are reflecting the regional dynamics of the directly unobservable crustal stresses, the Pattern Informatics (PI) approach was introduced by Tiampo et al. in 2002 [Europhys. Lett., 60 (3), 481-487,] Rundle et al., 2002 [PNAS 99, suppl. 1, 2514-2521.] In this study, we expand the PI approach to forecasting earthquakes into the third, or vertical dimension, and illustrate its further improvement in the forecasting performance through case studies of both natural and synthetic data. The PI characterizes rapidly evolving spatio-temporal seismicity patterns as angular drifts of a unit state vector in a high dimensional correlation space, and systematically identifies anomalous shifts in seismic activity with respect to the regional background. 3D PI analysis is particularly advantageous over 2D analysis in resolving vertically overlapped seismicity anomalies in a highly complex tectonic environment. Case studies will help to illustrate some important properties of the PI forecasting tool. [Submitted to: Concurrency and Computation: Practice and Experience, Wiley, Special Issue: ACES2008.

Time-Ordered Networks Reveal Limitations to Information Flow in Ant Colonies

PubMed Central

Blonder, Benjamin; Dornhaus, Anna

2011-01-01

Background An important function of many complex networks is to inhibit or promote the transmission of disease, resources, or information between individuals. However, little is known about how the temporal dynamics of individual-level interactions affect these networks and constrain their function. Ant colonies are a model comparative system for understanding general principles linking individual-level interactions to network-level functions because interactions among individuals enable integration of multiple sources of information to collectively make decisions, and allocate tasks and resources. Methodology/Findings Here we show how the temporal and spatial dynamics of such individual interactions provide upper bounds to rates of colony-level information flow in the ant Temnothorax rugatulus. We develop a general framework for analyzing dynamic networks and a mathematical model that predicts how information flow scales with individual mobility and group size. Conclusions/Significance Using thousands of time-stamped interactions between uniquely marked ants in four colonies of a range of sizes, we demonstrate that observed maximum rates of information flow are always slower than predicted, and are constrained by regulation of individual mobility and contact rate. By accounting for the ordering and timing of interactions, we can resolve important difficulties with network sampling frequency and duration, enabling a broader understanding of interaction network functioning across systems and scales. PMID:21625450

Temporal scaling in information propagation.

PubMed

Huang, Junming; Li, Chao; Wang, Wen-Qiang; Shen, Hua-Wei; Li, Guojie; Cheng, Xue-Qi

2014-06-18

For the study of information propagation, one fundamental problem is uncovering universal laws governing the dynamics of information propagation. This problem, from the microscopic perspective, is formulated as estimating the propagation probability that a piece of information propagates from one individual to another. Such a propagation probability generally depends on two major classes of factors: the intrinsic attractiveness of information and the interactions between individuals. Despite the fact that the temporal effect of attractiveness is widely studied, temporal laws underlying individual interactions remain unclear, causing inaccurate prediction of information propagation on evolving social networks. In this report, we empirically study the dynamics of information propagation, using the dataset from a population-scale social media website. We discover a temporal scaling in information propagation: the probability a message propagates between two individuals decays with the length of time latency since their latest interaction, obeying a power-law rule. Leveraging the scaling law, we further propose a temporal model to estimate future propagation probabilities between individuals, reducing the error rate of information propagation prediction from 6.7% to 2.6% and improving viral marketing with 9.7% incremental customers.

Temporal scaling in information propagation

NASA Astrophysics Data System (ADS)

Huang, Junming; Li, Chao; Wang, Wen-Qiang; Shen, Hua-Wei; Li, Guojie; Cheng, Xue-Qi

2014-06-01

For the study of information propagation, one fundamental problem is uncovering universal laws governing the dynamics of information propagation. This problem, from the microscopic perspective, is formulated as estimating the propagation probability that a piece of information propagates from one individual to another. Such a propagation probability generally depends on two major classes of factors: the intrinsic attractiveness of information and the interactions between individuals. Despite the fact that the temporal effect of attractiveness is widely studied, temporal laws underlying individual interactions remain unclear, causing inaccurate prediction of information propagation on evolving social networks. In this report, we empirically study the dynamics of information propagation, using the dataset from a population-scale social media website. We discover a temporal scaling in information propagation: the probability a message propagates between two individuals decays with the length of time latency since their latest interaction, obeying a power-law rule. Leveraging the scaling law, we further propose a temporal model to estimate future propagation probabilities between individuals, reducing the error rate of information propagation prediction from 6.7% to 2.6% and improving viral marketing with 9.7% incremental customers.

Tracking Virus Particles in Fluorescence Microscopy Images Using Multi-Scale Detection and Multi-Frame Association.

PubMed

Jaiswal, Astha; Godinez, William J; Eils, Roland; Lehmann, Maik Jorg; Rohr, Karl

2015-11-01

Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.

Towards an eco-phylogenetic framework for infectious disease ecology.

PubMed

Fountain-Jones, Nicholas M; Pearse, William D; Escobar, Luis E; Alba-Casals, Ana; Carver, Scott; Davies, T Jonathan; Kraberger, Simona; Papeş, Monica; Vandegrift, Kurt; Worsley-Tonks, Katherine; Craft, Meggan E

2018-05-01

Identifying patterns and drivers of infectious disease dynamics across multiple scales is a fundamental challenge for modern science. There is growing awareness that it is necessary to incorporate multi-host and/or multi-parasite interactions to understand and predict current and future disease threats better, and new tools are needed to help address this task. Eco-phylogenetics (phylogenetic community ecology) provides one avenue for exploring multi-host multi-parasite systems, yet the incorporation of eco-phylogenetic concepts and methods into studies of host pathogen dynamics has lagged behind. Eco-phylogenetics is a transformative approach that uses evolutionary history to infer present-day dynamics. Here, we present an eco-phylogenetic framework to reveal insights into parasite communities and infectious disease dynamics across spatial and temporal scales. We illustrate how eco-phylogenetic methods can help untangle the mechanisms of host-parasite dynamics from individual (e.g. co-infection) to landscape scales (e.g. parasite/host community structure). An improved ecological understanding of multi-host and multi-pathogen dynamics across scales will increase our ability to predict disease threats. © 2017 Cambridge Philosophical Society.

Phylogenetic community structure: temporal variation in fish assemblage

PubMed Central

Santorelli, Sergio; Magnusson, William; Ferreira, Efrem; Caramaschi, Erica; Zuanon, Jansen; Amadio, Sidnéia

2014-01-01

Hypotheses about phylogenetic relationships among species allow inferences about the mechanisms that affect species coexistence. Nevertheless, most studies assume that phylogenetic patterns identified are stable over time. We used data on monthly samples of fish from a single lake over 10 years to show that the structure in phylogenetic assemblages varies over time and conclusions depend heavily on the time scale investigated. The data set was organized in guild structures and temporal scales (grouped at three temporal scales). Phylogenetic distance was measured as the mean pairwise distances (MPD) and as mean nearest-neighbor distance (MNTD). Both distances were based on counts of nodes. We compared the observed values of MPD and MNTD with values that were generated randomly using null model independent swap. A serial runs test was used to assess the temporal independence of indices over time. The phylogenetic pattern in the whole assemblage and the functional groups varied widely over time. Conclusions about phylogenetic clustering or dispersion depended on the temporal scales. Conclusions about the frequency with which biotic processes and environmental filters affect the local assembly do not depend only on taxonomic grouping and spatial scales. While these analyzes allow the assertion that all proposed patterns apply to the fish assemblages in the floodplain, the assessment of the relative importance of these processes, and how they vary depending on the temporal scale and functional group studied, cannot be determined with the effort commonly used. It appears that, at least in the system that we studied, the assemblages are forming and breaking continuously, resulting in various phylogeny-related structures that makes summarizing difficult. PMID:25360256

The advantages, and challenges, in using multiple techniques in the estimation of surface water-groundwater fluxes.

NASA Astrophysics Data System (ADS)

Shanafield, M.; Cook, P. G.

2014-12-01

When estimating surface water-groundwater fluxes, the use of complimentary techniques helps to fill in uncertainties in any individual method, and to potentially gain a better understanding of spatial and temporal variability in a system. It can also be a way of preventing the loss of data during infrequent and unpredictable flow events. For example, much of arid Australia relies on groundwater, which is recharged by streamflow through ephemeral streams during flood events. Three recent surface water/groundwater investigations from arid Australian systems provide good examples of how using multiple field and analysis techniques can help to more fully characterize surface water-groundwater fluxes, but can also result in conflicting values over varying spatial and temporal scales. In the Pilbara region of Western Australia, combining streambed radon measurements, vertical heat transport modeling, and a tracer test helped constrain very low streambed residence times, which are on the order of minutes. Spatial and temporal variability between the methods yielded hyporheic exchange estimates between 10-4 m2 s-1 and 4.2 x 10-2 m2 s-1. In South Australia, three-dimensional heat transport modeling captured heterogeneity within 20 square meters of streambed, identifying areas of sandy soil (flux rates of up to 3 m d-1) and clay (flux rates too slow to be accurately characterized). Streamflow front modeling showed similar flux rates, but averaged over 100 m long stream segments for a 1.6 km reach. Finally, in central Australia, several methods are used to decipher whether any of the flow down a highly ephemeral river contributes to regional groundwater recharge, showing that evaporation and evapotranspiration likely accounts for all of the infiltration into the perched aquifer. Lessons learned from these examples demonstrate the influences of the spatial and temporal variability between techniques on estimated fluxes.

Understanding the Patterns and Drivers of Air Pollution on Multiple Time Scales: The Case of Northern China.

PubMed

Liu, Yupeng; Wu, Jianguo; Yu, Deyong; Hao, Ruifang

2018-06-01

China's rapid economic growth during the past three decades has resulted in a number of environmental problems, including the deterioration of air quality. It is necessary to better understand how the spatial pattern of air pollutants varies with time scales and what drive these changes. To address these questions, this study focused on one of the most heavily air-polluted areas in North China. We first quantified the spatial pattern of air pollution, and then systematically examined the relationships of air pollution to several socioeconomic and climatic factors using the constraint line method, correlation analysis, and stepwise regression on decadal, annual, and seasonal scales. Our results indicate that PM 2.5 was the dominant air pollutant in the Beijing-Tianjin-Hebei region, while PM 2.5 and PM 10 were both important pollutants in the Agro-pastoral Transitional Zone (APTZ) region. Our statistical analyses suggest that energy consumption and gross domestic product (GDP) in the industry were the most important factors for air pollution on the decadal scale, but the impacts of climatic factors could also be significant. On the annual and seasonal scales, high wind speed, low relative humidity, and long sunshine duration constrained PM 2.5 accumulation; low wind speed and high relative humidity constrained PM 10 accumulation; and short sunshine duration and high wind speed constrained O 3 accumulation. Our study showed that analyses on multiple temporal scales are not only necessary to determine key drivers of air pollution, but also insightful for understanding the spatial patterns of air pollution, which was important for urban planning and air pollution control.

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

PubMed Central

Vaughn, Nicholas R.; Asner, Gregory P.; Smit, Izak P. J.; Riddel, Edward S.

2015-01-01

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50–450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques. PMID:26660502

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

PubMed

Vaughn, Nicholas R; Asner, Gregory P; Smit, Izak P J; Riddel, Edward S

2015-01-01

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

Understanding the Patterns and Drivers of Air Pollution on Multiple Time Scales: The Case of Northern China

NASA Astrophysics Data System (ADS)

Liu, Yupeng; Wu, Jianguo; Yu, Deyong; Hao, Ruifang

2018-06-01

China's rapid economic growth during the past three decades has resulted in a number of environmental problems, including the deterioration of air quality. It is necessary to better understand how the spatial pattern of air pollutants varies with time scales and what drive these changes. To address these questions, this study focused on one of the most heavily air-polluted areas in North China. We first quantified the spatial pattern of air pollution, and then systematically examined the relationships of air pollution to several socioeconomic and climatic factors using the constraint line method, correlation analysis, and stepwise regression on decadal, annual, and seasonal scales. Our results indicate that PM2.5 was the dominant air pollutant in the Beijing-Tianjin-Hebei region, while PM2.5 and PM10 were both important pollutants in the Agro-pastoral Transitional Zone (APTZ) region. Our statistical analyses suggest that energy consumption and gross domestic product (GDP) in the industry were the most important factors for air pollution on the decadal scale, but the impacts of climatic factors could also be significant. On the annual and seasonal scales, high wind speed, low relative humidity, and long sunshine duration constrained PM2.5 accumulation; low wind speed and high relative humidity constrained PM10 accumulation; and short sunshine duration and high wind speed constrained O3 accumulation. Our study showed that analyses on multiple temporal scales are not only necessary to determine key drivers of air pollution, but also insightful for understanding the spatial patterns of air pollution, which was important for urban planning and air pollution control.

Earthquake Clustering in Noisy Viscoelastic Systems

NASA Astrophysics Data System (ADS)

Dicaprio, C. J.; Simons, M.; Williams, C. A.; Kenner, S. J.

2006-12-01

Geologic studies show evidence for temporal clustering of earthquakes on certain fault systems. Since post- seismic deformation may result in a variable loading rate on a fault throughout the inter-seismic period, it is reasonable to expect that the rheology of the non-seismogenic lower crust and mantle lithosphere may play a role in controlling earthquake recurrence times. Previously, the role of rheology of the lithosphere on the seismic cycle had been studied with a one-dimensional spring-dashpot-slider model (Kenner and Simons [2005]). In this study we use the finite element code PyLith to construct a two-dimensional continuum model a strike-slip fault in an elastic medium overlying one or more linear Maxwell viscoelastic layers loaded in the far field by a constant velocity boundary condition. Taking advantage of the linear properties of the model, we use the finite element solution to one earthquake as a spatio-temporal Green's function. Multiple Green's function solutions, scaled by the size of each earthquake, are then summed to form an earthquake sequence. When the shear stress on the fault reaches a predefined yield stress it is allowed to slip, relieving all accumulated shear stress. Random variation in the fault yield stress from one earthquake to the next results in a temporally clustered earthquake sequence. The amount of clustering depends on a non-dimensional number, W, called the Wallace number. For models with one viscoelastic layer, W is equal to the standard deviation of the earthquake stress drop divided by the viscosity times the tectonic loading rate. This definition of W is modified from the original one used in Kenner and Simons [2005] by using the standard deviation of the stress drop instead of the mean stress drop. We also use a new, more appropriate, metric to measure the amount of temporal clustering of the system. W is the ratio of the viscoelastic relaxation rate of the system to the tectonic loading rate of the system. For values of W greater than the critical value of about 10, the clustered earthquake behavior is due to the rapid reloading of the fault due to viscoelastic recycling of stress. A model with multiple viscoelastic layers has more complex clustering behavior than a system with only one viscosity. In this case, multiple clustering modes exist; the size and mean period of which are influenced by the viscosities and relative thicknesses of the viscoelastic layers. Kenner, S.J. and Simons, M., (2005), Temporal cluster of major earthquakes along individual faults due to post-seismic reloading, Geophysical Journal International, 160, 179-194.

Sparse representation of whole-brain fMRI signals for identification of functional networks.

PubMed

Lv, Jinglei; Jiang, Xi; Li, Xiang; Zhu, Dajiang; Chen, Hanbo; Zhang, Tuo; Zhang, Shu; Hu, Xintao; Han, Junwei; Huang, Heng; Zhang, Jing; Guo, Lei; Liu, Tianming

2015-02-01

There have been several recent studies that used sparse representation for fMRI signal analysis and activation detection based on the assumption that each voxel's fMRI signal is linearly composed of sparse components. Previous studies have employed sparse coding to model functional networks in various modalities and scales. These prior contributions inspired the exploration of whether/how sparse representation can be used to identify functional networks in a voxel-wise way and on the whole brain scale. This paper presents a novel, alternative methodology of identifying multiple functional networks via sparse representation of whole-brain task-based fMRI signals. Our basic idea is that all fMRI signals within the whole brain of one subject are aggregated into a big data matrix, which is then factorized into an over-complete dictionary basis matrix and a reference weight matrix via an effective online dictionary learning algorithm. Our extensive experimental results have shown that this novel methodology can uncover multiple functional networks that can be well characterized and interpreted in spatial, temporal and frequency domains based on current brain science knowledge. Importantly, these well-characterized functional network components are quite reproducible in different brains. In general, our methods offer a novel, effective and unified solution to multiple fMRI data analysis tasks including activation detection, de-activation detection, and functional network identification. Copyright © 2014 Elsevier B.V. All rights reserved.

Multiple Scales in Fluid Dynamics and Meteorology: The DFG Priority Programme 1276 MetStröm

NASA Astrophysics Data System (ADS)

von Larcher, Th; Klein, R.

2012-04-01

Geophysical fluid motions are characterized by a very wide range of length and time scales, and by a rich collection of varying physical phenomena. The mathematical description of these motions reflects this multitude of scales and mechanisms in that it involves strong non-linearities and various scale-dependent singular limit regimes. Considerable progress has been made in recent years in the mathematical modelling and numerical simulation of such flows in detailed process studies, numerical weather forecasting, and climate research. One task of outstanding importance in this context has been and will remain for the foreseeable future the subgrid scale parameterization of the net effects of non-resolved processes that take place on spacio-temporal scales not resolvable even by the largest most recent supercomputers. Since the advent of numerical weather forecasting some 60 years ago, one simple but efficient means to achieve improved forecasting skills has been increased spacio-temporal resolution. This seems quite consistent with the concept of convergence of numerical methods in Applied Mathematics and Computational Fluid Dynamics (CFD) at a first glance. Yet, the very notion of increased resolution in atmosphere-ocean science is very different from the one used in Applied Mathematics: For the mathematician, increased resolution provides the benefit of getting closer to the ideal of a converged solution of some given partial differential equations. On the other hand, the atmosphere-ocean scientist would naturally refine the computational grid and adjust his mathematical model, such that it better represents the relevant physical processes that occur at smaller scales. This conceptual contradiction remains largely irrelevant as long as geophysical flow models operate with fixed computational grids and time steps and with subgrid scale parameterizations being optimized accordingly. The picture changes fundamentally when modern techniques from CFD involving spacio-temporal grid adaptivity get invoked in order to further improve the net efficiency in exploiting the given computational resources. In the setting of geophysical flow simulation one must then employ subgrid scale parameterizations that dynamically adapt to the changing grid sizes and time steps, implement ways to judiciously control and steer the newly available flexibility of resolution, and invent novel ways of quantifying the remaining errors. The DFG priority program MetStröm covers the expertise of Meteorology, Fluid Dynamics, and Applied Mathematics to develop model- as well as grid-adaptive numerical simulation concepts in multidisciplinary projects. The goal of this priority programme is to provide simulation models which combine scale-dependent (mathematical) descriptions of key physical processes with adaptive flow discretization schemes. Deterministic continuous approaches and discrete and/or stochastic closures and their possible interplay are taken into consideration. Research focuses on the theory and methodology of multiscale meteorological-fluid mechanics modelling. Accompanying reference experiments support model validation.

FAST TRACK PAPER: A construct of internal multiples from surface data only: the concept of virtual seismic events

NASA Astrophysics Data System (ADS)

Ikelle, Luc T.

2006-02-01

We here describe one way of constructing internal multiples from surface seismic data only. The key feature of our construct of internal multiples is the introduction of the concept of virtual seismic events. Virtual events here are events, which are not directly recorded in standard seismic data acquisition, but their existence allows us to construct internal multiples with scattering points at the sea surface; the standard construct of internal multiples does not include any scattering points at the sea surface. The mathematical and computational operations invoked in our construction of virtual events and internal multiples are similar to those encountered in the construction of free-surface multiples based on the Kirchhoff or Born scattering theory. For instance, our construct operates on one temporal frequency at a time, just like free-surface demultiple algorithms; other internal multiple constructs tend to require all frequencies for the computation of an internal multiple at a given frequency. It does not require any knowledge of the subsurface nor an explicit knowledge of specific interfaces that are responsible for the generation of internal multiples in seismic data. However, our construct requires that the data be divided into two, three or four windows to avoid generating primaries. This segmentation of the data also allows us to select a range of periods of internal multiples that one wishes to construct because, in the context of the attenuation of internal multiples, it is important to avoid generating short-period internal multiples that may constructively average to form primaries at the seismic scale.

Temporal Stability of Multiple Response Systems to 7.5% Carbon Dioxide Challenge

PubMed Central

Roberson-Nay, Roxann; Gorlin, Eugenia I.; Beadel, Jessica R.; Cash, Therese; Vrana, Scott; Teachman, Bethany A.

2017-01-01

Self-reported anxiety, and potentially physiological response, to maintained inhalation of carbon dioxide (CO2) enriched air shows promise as a putative marker of panic reactivity and vulnerability. Temporal stability of response systems during low-dose, steady-state CO2 breathing challenge is lacking. Outcomes on multiple levels were measured two times, one week apart, in 93 individuals. Stability was highest during the CO2 breathing phase compared to pre-CO2 and recovery phases, with anxiety ratings, respiratory rate, skin conductance level, and heart rate demonstrating good to excellent temporal stability (ICCs ≥ 0.71). Cognitive symptoms tied to panic were somewhat less stable (ICC = 0.58) than physical symptoms (ICC = 0.74) during CO2 breathing. Escape/avoidance behaviors and DSM-5 panic attacks were not stable. Large effect sizes between task phases also were observed. Overall, results suggest good-excellent levels of temporal stability for multiple outcomes during respiratory stimulation via 7.5% CO2. PMID:28163046

Mixed-order phase transition of the contact process near multiple junctions.

PubMed

Juhász, Róbert; Iglói, Ferenc

2017-02-01

We have studied the phase transition of the contact process near a multiple junction of M semi-infinite chains by Monte Carlo simulations. As opposed to the continuous transitions of the translationally invariant (M=2) and semi-infinite (M=1) system, the local order parameter is found to be discontinuous for M>2. Furthermore, the temporal correlation length diverges algebraically as the critical point is approached, but with different exponents on the two sides of the transition. In the active phase, the estimate is compatible with the bulk value, while in the inactive phase it exceeds the bulk value and increases with M. The unusual local critical behavior is explained by a scaling theory with an irrelevant variable, which becomes dangerous in the inactive phase. Quenched spatial disorder is found to make the transition continuous in agreement with earlier renormalization group results.

The Many Hazards of Trend Evaluation

NASA Astrophysics Data System (ADS)

Henebry, G. M.; de Beurs, K.; Zhang, X.; Kimball, J. S.; Small, C.

2014-12-01

Given the awareness in the scientific community of global scale drivers such as population growth, globalization, and climatic variation and change, many studies seek to identify temporal patterns in data that may be plausibly related to one or more aspect of global change. Here we explore two questions: "What constitutes a trend in a time series?" and "How can a trend be misinterpreted?" There are manifold hazards—both methodological and psychological—in detecting a trend, quantifying its magnitude, assessing its significance, identifying probable causes, and evaluating the implications of the trend. These hazards can combine to elevate the risk of misinterpreting the trend. In contrast, evaluation of multiple trends within a biogeophysical framework can attenuate the risk of misinterpretation. We review and illustrate these hazards and demonstrate the efficacy of an approach using multiple indicators detecting significant trends (MIDST) applied to time series of remote sensing data products.

Temporal Interactions between Cortical Rhythms

PubMed Central

Roopun, Anita K.; Kramer, Mark A.; Carracedo, Lucy M.; Kaiser, Marcus; Davies, Ceri H.; Traub, Roger D.; Kopell, Nancy J.; Whittington, Miles A.

2008-01-01

Multiple local neuronal circuits support different, discrete frequencies of network rhythm in neocortex. Relationships between different frequencies correspond to mechanisms designed to minimise interference, couple activity via stable phase interactions, and control the amplitude of one frequency relative to the phase of another. These mechanisms are proposed to form a framework for spectral information processing. Individual local circuits can also transform their frequency through changes in intrinsic neuronal properties and interactions with other oscillating microcircuits. Here we discuss a frequency transformation in which activity in two co-active local circuits may combine sequentially to generate a third frequency whose period is the concatenation sum of the original two. With such an interaction, the intrinsic periodicity in each component local circuit is preserved – alternate, single periods of each original rhythm form one period of a new frequency – suggesting a robust mechanism for combining information processed on multiple concurrent spatiotemporal scales. PMID:19225587

SIFT optimization and automation for matching images from multiple temporal sources

NASA Astrophysics Data System (ADS)

Castillo-Carrión, Sebastián; Guerrero-Ginel, José-Emilio

2017-05-01

Scale Invariant Feature Transformation (SIFT) was applied to extract tie-points from multiple source images. Although SIFT is reported to perform reliably under widely different radiometric and geometric conditions, using the default input parameters resulted in too few points being found. We found that the best solution was to focus on large features as these are more robust and not prone to scene changes over time, which constitutes a first approach to the automation of processes using mapping applications such as geometric correction, creation of orthophotos and 3D models generation. The optimization of five key SIFT parameters is proposed as a way of increasing the number of correct matches; the performance of SIFT is explored in different images and parameter values, finding optimization values which are corroborated using different validation imagery. The results show that the optimization model improves the performance of SIFT in correlating multitemporal images captured from different sources.

Musical Scales in Tone Sequences Improve Temporal Accuracy.

PubMed

Li, Min S; Di Luca, Massimiliano

2018-01-01

Predicting the time of stimulus onset is a key component in perception. Previous investigations of perceived timing have focused on the effect of stimulus properties such as rhythm and temporal irregularity, but the influence of non-temporal properties and their role in predicting stimulus timing has not been exhaustively considered. The present study aims to understand how a non-temporal pattern in a sequence of regularly timed stimuli could improve or bias the detection of temporal deviations. We presented interspersed sequences of 3, 4, 5, and 6 auditory tones where only the timing of the last stimulus could slightly deviate from isochrony. Participants reported whether the last tone was 'earlier' or 'later' relative to the expected regular timing. In two conditions, the tones composing the sequence were either organized into musical scales or they were random tones. In one experiment, all sequences ended with the same tone; in the other experiment, each sequence ended with a different tone. Results indicate higher discriminability of anisochrony with musical scales and with longer sequences, irrespective of the knowledge of the final tone. Such an outcome suggests that the predictability of non-temporal properties, as enabled by the musical scale pattern, can be a factor in determining the sensitivity of time judgments.

A Vision for the Future of Environmental Research: Creating Environmental Intelligence Centers

NASA Astrophysics Data System (ADS)

Barron, E. J.

2002-12-01

The nature of the environmental issues facing our nation demands a capability that allows us to enhance economic vitality, maintain environmental quality, and limit threats to life and property through more fundamental understanding of the Earth. It is "advanced" knowledge of how the system may respond that gives environmental information most of its power and utility. This fact is evident in the demand for new forecasting products, involving air quality, energy demand, water quality and quantity, ultraviolet radiation, and human health indexes. As we demonstrate feasibility and benefit, society is likely to demand a growing number of new operational forecast products on prediction time scales of days to decades into the future. The driving forces that govern our environment are widely recognized, involving primarily weather and climate, patterns of land use and land cover, and resource use with its associated waste products. The importance of these driving forces has been demonstrated by a decade of research on greenhouse gas emissions, ozone depletion and deforestation, and through the birth of Earth System Science. But, there are also major challenges. We find the strongest intersection between human activity, environmental stresses, system interactions and human decision-making in regional analysis coupled to larger spatial scales. In addition, most regions are influenced by multiple-stresses. Multiple, cumulative, and interactive stresses are clearly the most difficult to understand and hence the most difficult to assess and to manage. Currently, we are incapable of addressing these issues in a truly integrated fashion at global scales. The lack of an ability to combine global and regional forcing and to assess the response of the system to multiple stresses at the spatial and temporal scales of interest to humans limits our ability to assess the impacts of specific human perturbations, to assess advantages and risks, and to enhance economic and societal well being in the context of global, national and regional stewardship. These societal needs lead to a vision that uses a regional framework as a stepping-stone to a comprehensive national or global capability. The development of a comprehensive regional framework depends on a new approach to environmental research - the creation of regional Environmental Intelligence Centers. A key objective is to bring a demanding level of discipline to "forecasting" in a broad arena of environmental issues. The regional vision described above is designed to address a broad range of current and future environmental issues by creating a capability based on integrating diverse observing systems, making data readily accessible, developing an increasingly comprehensive predictive capability at the spatial and temporal scales appropriate for examining societal issues, and creating a vigorous intersection with decision-makers. With demonstrated success over a few large-scale regions of the U.S., this strategy will very likely grow into a national capability that far exceeds current capabilities.

Stochastic predation events and population persistence in bighorn sheep

PubMed Central

Festa-Bianchet, Marco; Coulson, Tim; Gaillard, Jean-Michel; Hogg, John T; Pelletier, Fanie

2006-01-01

Many studies have reported temporal changes in the relative importance of density-dependence and environmental stochasticity in affecting population growth rates, but they typically assume that the predominant factor limiting growth remains constant over long periods of time. Stochastic switches in limiting factors that persist for multiple time-steps have received little attention, but most wild populations may periodically experience such switches. Here, we consider the dynamics of three populations of individually marked bighorn sheep (Ovis canadensis) monitored for 24–28 years. Each population experienced one or two distinct cougar (Puma concolor) predation events leading to population declines. The onset and duration of predation events were stochastic and consistent with predation by specialist individuals. A realistic Markov chain model confirms that predation by specialist cougars can cause extinction of isolated populations. We suggest that such processes may be common. In such cases, predator–prey equilibria may only occur at large geographical and temporal scales, and are unlikely with increasing habitat fragmentation. PMID:16777749

Sensitivity to timing and order in human visual cortex

PubMed Central

Singer, Jedediah M.; Madsen, Joseph R.; Anderson, William S.

2014-01-01

Visual recognition takes a small fraction of a second and relies on the cascade of signals along the ventral visual stream. Given the rapid path through multiple processing steps between photoreceptors and higher visual areas, information must progress from stage to stage very quickly. This rapid progression of information suggests that fine temporal details of the neural response may be important to the brain's encoding of visual signals. We investigated how changes in the relative timing of incoming visual stimulation affect the representation of object information by recording intracranial field potentials along the human ventral visual stream while subjects recognized objects whose parts were presented with varying asynchrony. Visual responses along the ventral stream were sensitive to timing differences as small as 17 ms between parts. In particular, there was a strong dependency on the temporal order of stimulus presentation, even at short asynchronies. From these observations we infer that the neural representation of complex information in visual cortex can be modulated by rapid dynamics on scales of tens of milliseconds. PMID:25429116

Functional Imaging Biomarkers: Potential to Guide an Individualised Approach to Radiotherapy.

PubMed

Prestwich, R J D; Vaidyanathan, S; Scarsbrook, A F

2015-10-01

The identification of robust prognostic and predictive biomarkers would transform the ability to implement an individualised approach to radiotherapy. In this regard, there has been a surge of interest in the use of functional imaging to assess key underlying biological processes within tumours and their response to therapy. Importantly, functional imaging biomarkers hold the potential to evaluate tumour heterogeneity/biology both spatially and temporally. An ever-increasing range of functional imaging techniques is now available primarily involving positron emission tomography and magnetic resonance imaging. Small-scale studies across multiple tumour types have consistently been able to correlate changes in functional imaging parameters during radiotherapy with disease outcomes. Considerable challenges remain before the implementation of functional imaging biomarkers into routine clinical practice, including the inherent temporal variability of biological processes within tumours, reproducibility of imaging, determination of optimal imaging technique/combinations, timing during treatment and design of appropriate validation studies. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Spatial-temporal population dynamics across species range: from center to margin

USGS Publications Warehouse

Guo, Q.; Taper, M.L.; Schoenberger, M.; Brandl, J.

2005-01-01

Understanding the boundaries of species' ranges and the variations in population dynamics from the centre to margin of a species' range is critical. This study simulated spatial-temporal patterns of birth and death rates and migration across a species' range in different seasons. Our results demonstrated the importance of dispersal and migration in altering birth and death rates, balancing source and sink habitats, and governing expansion or contraction of species' ranges in changing environments. We also showed that the multiple equilibria of metapopulations across a species' range could be easily broken following climatic changes or physical disturbances either or local or regional. Although we refer to our models as describing the population dynamics across whole species' range, they should also apply to small-scale habitats (metapopulations) in which species abundance follows a humped pattern or to any ecosystem or landscape where strong central-marginal (C-M) environmental gradients exist. Conservation of both central and marginal populations would therefore be equally important considerations in making management decisions.

Spatial-temporal population dynamics across species range: From centre to margin

USGS Publications Warehouse

Guo, Q.; Taper, M.; Schoenberger, M.; Brandle, J.

2005-01-01

Understanding the boundaries of species' ranges and the variations in population dynamics from the centre to margin of a species' range is critical. This study simulated spatial-temporal patterns of birth and death rates and migration across a species' range in different seasons. Our results demonstrated the importance of dispersal and migration in altering birth and death rates, balancing source and sink habitats, and governing expansion or contraction of species' ranges in changing environments. We also showed that the multiple equilibria of metapopulations across a species' range could be easily broken following climatic changes or physical disturbances either local or regional. Although we refer to our models as describing the population dynamics across whole species' range, they should also apply to small-scale habitats (metapopulations) in which species abundance follows a humped pattern or to any ecosystem or landscape where strong central-marginal (C-M) environmental gradients exist. Conservation of both central and marginal populations would therefore be equally important considerations in making management decisions.

Mesolimbic Dopamine Signals the Value of Work

PubMed Central

Hamid, Arif A.; Pettibone, Jeffrey R.; Mabrouk, Omar S.; Hetrick, Vaughn L.; Schmidt, Robert; Vander Weele, Caitlin M.; Kennedy, Robert T.; Aragona, Brandon J.; Berke, Joshua D.

2015-01-01

Dopamine cell firing can encode errors in reward prediction, providing a learning signal to guide future behavior. Yet dopamine is also a key modulator of motivation, invigorating current behavior. Existing theories propose that fast (“phasic”) dopamine fluctuations support learning, while much slower (“tonic”) dopamine changes are involved in motivation. We examined dopamine release in the nucleus accumbens across multiple time scales, using complementary microdialysis and voltammetric methods during adaptive decision-making. We first show that minute-by-minute dopamine levels covary with reward rate and motivational vigor. We then show that second-by-second dopamine release encodes an estimate of temporally-discounted future reward (a value function). We demonstrate that changing dopamine immediately alters willingness to work, and reinforces preceding action choices by encoding temporal-difference reward prediction errors. Our results indicate that dopamine conveys a single, rapidly-evolving decision variable, the available reward for investment of effort, that is employed for both learning and motivational functions. PMID:26595651

Relating hyporheic fluxes, residence times, and redox-sensitive biogeochemical processes upstream of beaver dams

USGS Publications Warehouse

Briggs, Martin A.; Lautz, Laura; Hare, Danielle K.

2013-01-01

¨hler number seemed to overestimate the actual transition as indicated by multiple secondary electron acceptors, illustrating the gradient nature of anaerobic transition. Temporal flux variability in low-flux morphologies generated a much greater range in hyporheic redox conditions compared to high-flux zones, and chemical responses to changing flux rates were consistent with those predicted from the empirical relationship between redox condition and residence time. The Raz tracer revealed that hyporheic flow paths have strong net aerobic respiration, particularly at higher residence time, but this reactive exchange did not affect the net stream signal at the reach scale.

Deffuant model of opinion formation in one-dimensional multiplex networks

NASA Astrophysics Data System (ADS)

Shang, Yilun

2015-10-01

Complex systems in the real world often operate through multiple kinds of links connecting their constituents. In this paper we propose an opinion formation model under bounded confidence over multiplex networks, consisting of edges at different topological and temporal scales. We determine rigorously the critical confidence threshold by exploiting probability theory and network science when the nodes are arranged on the integers, {{Z}}, evolving in continuous time. It is found that the existence of ‘multiplexity’ impedes the convergence, and that working with the aggregated or summarized simplex network is inaccurate since it misses vital information. Analytical calculations are confirmed by extensive numerical simulations.

Tree physiology research in a changing world.

PubMed

Kaufmann, Merrill R.; Linder, Sune

1996-01-01

Changes in issues and advances in methodology have contributed to substantial progress in tree physiology research during the last several decades. Current research focuses on process interactions in complex systems and the integration of processes across multiple spatial and temporal scales. An increasingly important challenge for future research is assuring sustainability of production systems and forested ecosystems in the face of increased demands for natural resources and human disturbance of forests. Meeting this challenge requires significant shifts in research approach, including the study of limitations of productivity that may accompany achievement of system sustainability, and a focus on the biological capabilities of complex land bases altered by human activity.

Highly Unstable Double-Diffusive Finger Convection in a Hele-Shaw Cell: Baseline Experimental Data for Evaluation of Numerical Models

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

PRINGLE,SCOTT E.; COOPER,CLAY A.; GLASS JR.,ROBERT J.

An experimental investigation was conducted to study double-diffusive finger convection in a Hele-Shaw cell by layering a sucrose solution over a more-dense sodium chloride (NaCl) solution. The solutal Rayleigh numbers were on the order of 60,000, based upon the height of the cell (25 cm), and the buoyancy ratio was 1.2. A full-field light transmission technique was used to measure a dye tracer dissolved in the NaCl solution. They analyze the concentration fields to yield the temporal evolution of length scales associated with the vertical and horizontal finger structure as well as the mass flux. These measures show a rapidmore » progression through two early stages to a mature stage and finally a rundown period where mass flux decays rapidly. The data are useful for the development and evaluation of numerical simulators designed to model diffusion and convection of multiple components in porous media. The results are useful for correct formulation at both the process scale (the scale of the experiment) and effective scale (where the lab-scale processes are averaged-up to produce averaged parameters). A fundamental understanding of the fine-scale dynamics of double-diffusive finger convection is necessary in order to successfully parameterize large-scale systems.« less

LAPSUS: soil erosion - landscape evolution model

NASA Astrophysics Data System (ADS)

van Gorp, Wouter; Temme, Arnaud; Schoorl, Jeroen

2015-04-01

LAPSUS is a soil erosion - landscape evolution model which is capable of simulating landscape evolution of a gridded DEM by using multiple water, mass movement and human driven processes on multiple temporal and spatial scales. It is able to deal with a variety of human landscape interventions such as landuse management and tillage and it can model their interactions with natural processes. The complex spatially explicit feedbacks the model simulates demonstrate the importance of spatial interaction of human activity and erosion deposition patterns. In addition LAPSUS can model shallow landsliding, slope collapse, creep, solifluction, biological and frost weathering, fluvial behaviour. Furthermore, an algorithm to deal with natural depressions has been added and event-based modelling with an improved infiltration description and dust deposition has been pursued. LAPSUS has been used for case studies in many parts of the world and is continuously developing and expanding. it is now available for third-party and educational use. It has a comprehensive user interface and it is accompanied by a manual and exercises. The LAPSUS model is highly suitable to quantify and understand catchment-scale erosion processes. More information and a download link is available on www.lapsusmodel.nl.

Two-Photon Functional Imaging of the Auditory Cortex in Behaving Mice: From Neural Networks to Single Spines.

PubMed

Li, Ruijie; Wang, Meng; Yao, Jiwei; Liang, Shanshan; Liao, Xiang; Yang, Mengke; Zhang, Jianxiong; Yan, Junan; Jia, Hongbo; Chen, Xiaowei; Li, Xingyi

2018-01-01

In vivo two-photon Ca 2+ imaging is a powerful tool for recording neuronal activities during perceptual tasks and has been increasingly applied to behaving animals for acute or chronic experiments. However, the auditory cortex is not easily accessible to imaging because of the abundant temporal muscles, arteries around the ears and their lateral locations. Here, we report a protocol for two-photon Ca 2+ imaging in the auditory cortex of head-fixed behaving mice. By using a custom-made head fixation apparatus and a head-rotated fixation procedure, we achieved two-photon imaging and in combination with targeted cell-attached recordings of auditory cortical neurons in behaving mice. Using synthetic Ca 2+ indicators, we recorded the Ca 2+ transients at multiple scales, including neuronal populations, single neurons, dendrites and single spines, in auditory cortex during behavior. Furthermore, using genetically encoded Ca 2+ indicators (GECIs), we monitored the neuronal dynamics over days throughout the process of associative learning. Therefore, we achieved two-photon functional imaging at multiple scales in auditory cortex of behaving mice, which extends the tool box for investigating the neural basis of audition-related behaviors.

Two-Photon Functional Imaging of the Auditory Cortex in Behaving Mice: From Neural Networks to Single Spines

PubMed Central

Li, Ruijie; Wang, Meng; Yao, Jiwei; Liang, Shanshan; Liao, Xiang; Yang, Mengke; Zhang, Jianxiong; Yan, Junan; Jia, Hongbo; Chen, Xiaowei; Li, Xingyi

2018-01-01

In vivo two-photon Ca2+ imaging is a powerful tool for recording neuronal activities during perceptual tasks and has been increasingly applied to behaving animals for acute or chronic experiments. However, the auditory cortex is not easily accessible to imaging because of the abundant temporal muscles, arteries around the ears and their lateral locations. Here, we report a protocol for two-photon Ca2+ imaging in the auditory cortex of head-fixed behaving mice. By using a custom-made head fixation apparatus and a head-rotated fixation procedure, we achieved two-photon imaging and in combination with targeted cell-attached recordings of auditory cortical neurons in behaving mice. Using synthetic Ca2+ indicators, we recorded the Ca2+ transients at multiple scales, including neuronal populations, single neurons, dendrites and single spines, in auditory cortex during behavior. Furthermore, using genetically encoded Ca2+ indicators (GECIs), we monitored the neuronal dynamics over days throughout the process of associative learning. Therefore, we achieved two-photon functional imaging at multiple scales in auditory cortex of behaving mice, which extends the tool box for investigating the neural basis of audition-related behaviors. PMID:29740289

A Multiple-Label Guided Clustering Algorithm for Historical Document Dating and Localization.

PubMed

He, Sheng; Samara, Petros; Burgers, Jan; Schomaker, Lambert

2016-11-01

It is of essential importance for historians to know the date and place of origin of the documents they study. It would be a huge advancement for historical scholars if it would be possible to automatically estimate the geographical and temporal provenance of a handwritten document by inferring them from the handwriting style of such a document. We propose a multiple-label guided clustering algorithm to discover the correlations between the concrete low-level visual elements in historical documents and abstract labels, such as date and location. First, a novel descriptor, called histogram of orientations of handwritten strokes, is proposed to extract and describe the visual elements, which is built on a scale-invariant polar-feature space. In addition, the multi-label self-organizing map (MLSOM) is proposed to discover the correlations between the low-level visual elements and their labels in a single framework. Our proposed MLSOM can be used to predict the labels directly. Moreover, the MLSOM can also be considered as a pre-structured clustering method to build a codebook, which contains more discriminative information on date and geography. The experimental results on the medieval paleographic scale data set demonstrate that our method achieves state-of-the-art results.

Variability in Regularity: Mining Temporal Mobility Patterns in London, Singapore and Beijing Using Smart-Card Data

PubMed Central

Zhong, Chen; Batty, Michael; Manley, Ed; Wang, Jiaqiu; Wang, Zijia; Chen, Feng; Schmitt, Gerhard

2016-01-01

To discover regularities in human mobility is of fundamental importance to our understanding of urban dynamics, and essential to city and transport planning, urban management and policymaking. Previous research has revealed universal regularities at mainly aggregated spatio-temporal scales but when we zoom into finer scales, considerable heterogeneity and diversity is observed instead. The fundamental question we address in this paper is at what scales are the regularities we detect stable, explicable, and sustainable. This paper thus proposes a basic measure of variability to assess the stability of such regularities focusing mainly on changes over a range of temporal scales. We demonstrate this by comparing regularities in the urban mobility patterns in three world cities, namely London, Singapore and Beijing using one-week of smart-card data. The results show that variations in regularity scale as non-linear functions of the temporal resolution, which we measure over a scale from 1 minute to 24 hours thus reflecting the diurnal cycle of human mobility. A particularly dramatic increase in variability occurs up to the temporal scale of about 15 minutes in all three cities and this implies that limits exist when we look forward or backward with respect to making short-term predictions. The degree of regularity varies in fact from city to city with Beijing and Singapore showing higher regularity in comparison to London across all temporal scales. A detailed discussion is provided, which relates the analysis to various characteristics of the three cities. In summary, this work contributes to a deeper understanding of regularities in patterns of transit use from variations in volumes of travellers entering subway stations, it establishes a generic analytical framework for comparative studies using urban mobility data, and it provides key points for the management of variability by policy-makers intent on for making the travel experience more amenable. PMID:26872333