Multiple Space Scales Research Articles

Spatial and temporal scales of aquatic bacterial beta diversity

Understanding characteristic variation in aquatic bacterial community composition (BCC) across space and time can inform us about processes driving community assembly and the ability of bacterial communities to respond to perturbations. In this study, we synthesize BCC data from north temperate lakes to evaluate our current understanding of how BCC varies across multiple scales in time and space. A hierarchy of average similarity emerged with the highest similarity found among samples collected within the same lake, especially within the same basin, followed by similarity among samples collected through time within the same lake, and finally similarity among samples collected from different lakes. Using decay of similarity across time and space, we identified equivalent temporal (1 day) and spatial (10 m) scales of BCC variation. Finally, we identify an intriguing pattern of contrasting patterns of intra- and inter-annual BCC variation in two lakes. We argue our synthesis of spatio-temporal variation of aquatic BCC informs expectations for the response of aquatic bacterial communities to perturbation and environmental change. However, further long-term temporal observations will be needed to develop a general understanding of inter-annual BCC variation and our ability to use aquatic BCC as a sensitive metric of environmental change.

Multiscale Cancer Modeling

Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insights in the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community.

Risk assessment of MUSTANG project experimental site–Methodological development

Abstract One of the work packages of MUSTANG (MUltiple Space and Time scale Approach for the quaNtification of deep saline formations for CO 2 storaGe) EU project is dedicated to developing a generic methodology for risk assessment related to CO 2 in saline aquifers and applying the methodology to an experimental site. This paper presents the work done by OXAND regarding risk assessment and the application of a risk-based approach to the qualification of the storage site ultimately to provide guidelines for further industrial storage projects. The risk assessment process is presented, and illustrated with the data of an experimental site. The eight steps of the risk assessment process highlighted in the ISO 31000 are described in this paper: Risk management policy, establishment of the context, risk identification, risk estimation, risk evaluation, risk treatment, communication and consultation, and monitoring and review.

Progress towards a Unified Model of Corrosion with Porous Oxides

The oxide that develops on the surface of the metals like zinc is usually porous. Any further oxidation of the metal can happen only if the electrolyte percolates through the oxide and comes in contact with the metal and also if there is a provision for the cathodic reaction to happen elsewhere. The oxide layer thus changes the conditions of corrosion of a metal surface. Three different electrochemical models for atmospheric corrosion of a metal under an aerosol solution are described. The models described are part of the holistic approach to model corrosion where multiple scales of time and space occur due to the various physical phenomena. When coupled with the macroscopic holistic model of production, transport, and deposition of aerosols these models are expected to comprehensively predict the corrosion rates and state of surfaces over a wide range of conditions. Some representative results of the models are presented and important assumptions underlying the models are stated. Also conditions leading to passivation are identified by all the three models.

The Effects of Weather and Climate on the Seasonality of Influenza: What We Know and What We Need to Know

AbstractInfluenza is one of the most deadly of all airborne and upper‐respiratory infections. On average, 22,000 deaths and over 3 million hospitalizations in USA are attributed to influenza each year. The distinct seasonality of influenza suggests a climate connection, but the wide range of methodologies used to explore this connection makes it difficult to elucidate a definitive relationship. Much of what is known about the effects of weather and climate on the seasonality of influenza stems from research conducted by members of the public health and medical communities, with few contributions from other physical and social science fields. Most of these studies are either based on experiments conducted under controlled laboratory conditions or on the broad‐scale patterns of morbidity and mortality and their relationship to large‐scale climate signals. What remains largely unknown is the suitability of these results for the development of early warning systems and for determining the dynamics of viral transmission on multiple space and time scales.

Variation in surface water–groundwater exchange with land use in an urban stream

Summary A suite of methods is being utilized in the Baltimore metropolitan area to develop an understanding of the interaction between groundwater and surface water at multiple space and time scales. As part of this effort, bromide tracer experiments were conducted over two 10-day periods in August 2007 and May 2008 along two sections (each approximately 900 m long) of Dead Run, a small urban stream located in Baltimore County, Maryland, to investigate the influence of distinct zones of riparian land cover on surface–subsurface exchange and transient storage under low and high baseflow conditions. Riparian land cover varied by reach along a gradient of land use spanning parkland, suburban/residential, commercial, institutional, and transportation, and included wooded, meadow, turf grass, and impervious cover. Under summer low baseflow conditions, surface water-groundwater exchange, defined by gross inflow and gross outflow, was larger and net inflow (gross inflow minus gross outflow) had greater spatial variability, than was observed under spring high baseflow conditions. In addition, the fraction of nominal travel time attributable to transient storage ( F med ) was lower and was more spatially variable under high baseflow conditions than under low baseflow conditions. The influence of baseflow condition on surface water–ground water exchange and transient storage was most evident in the subreaches with the least riparian forest cover and these effects are attributed to a lack of shading in reaches with little riparian forest cover. We suggest that under summer low baseflow conditions, the lack of shading allowed excess in-channel vegetation growth which acted as a transient storage zone and a conduit for outflow (i.e. uptake and evapotranspiration). Under spring high baseflow conditions the transient storage capacity of the channel was reduced because there was little in-channel vegetation.

On 1:2 resonant waves which arise between two stratified fluids of finite vertical extent in the presence of mean flow effects

A study is made of the profiles which arise on the interface of two fluids of different densities and which arise from the interaction of the first and second harmonics of the motion. The fluids are constrained above and below by impermeable plates and are subjected to the twin restoring forces of gravity and surface tension. The method of multiple scales in both space and time is employed to derive a system of coupled nonlinear partial differential equations which models the evolution of the interface. In addition, an examination of the stability of the interface profiles was undertaken. A fairly simple stability criterion was found and the waves were shown to be highly stable. These results therefore provide encouragement to experimentalists who might be able to generate these waves in the laboratory.

Large-scale coastal change in the Columbia River littoral cell: An overview

This overview introduces large-scale coastal change in the Columbia River littoral cell (CRLC). Covering 165 km of the southwest Washington and northwest Oregon coasts, the littoral cell is made up of wide low-sloping dissipative beaches, broad coastal dunes and barrier plains, three large estuaries, and is bounded by rocky headlands. The beaches and inner shelf are composed of fine-grained sand from the Columbia River and are exposed to a high-energy winter wave climate. Throughout the Holocene, the CRLC has undergone large fluctuations in shoreline change trends, responding to a variety of coastal change drivers, including changing rates of sea-level rise, infrequent, yet catastrophic, co-seismic subsidence events, a large regional sediment supply, inter-annual climatic fluctuations (El Niño cycles), seasonally varying wave climate, and numerous anthropogenic influences. Human influences on the CRLC include construction of over 200 dams in the Columbia River drainage basin, dredging of navigation channels removing sand to upland sites and offshore deep-water sites, and construction of large inlet jetties at the entrances to the Columbia River and Grays Harbor. The construction of these massive entrance jetties at the end of the 19th century has been the dominant driver of coastal change through most of the littoral cell over the last hundred years. Presently, some beaches in the littoral cell are eroding in response to nearshore sediment deficits resulting from a) ebb-jets of the confined entrances pushing the previously large, shallow ebb-tidal deltas offshore into deeper water, and b) waves dispersing the nearshore delta flanks initially onshore and then alongshore away from the jetties. This overview describes 1) the motivation for developing a system-wide understanding of sediment dynamics in the littoral cell at multiple time and space scales, 2) the formation and approach of the Southwest Washington Coastal Erosion Study, and 3) an introduction to the papers in this special issue.

Nutritional Systems Biology Modeling: From Molecular Mechanisms to Physiology

The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a “middle-out” strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from “-omics” signatures are identified as key elements of a successful systems biology modeling approach in nutrition research—one that integrates physiological mechanisms and data at multiple space and time scales.

Through a glass less darkly—New approaches for studying the distribution, abundance and biology of Euphausiids

Euphausiids are vital components of many oceanic foodwebs. Due to their large size, they are key prey species for many vertebrates, and several species are subject to commercial fisheries. The best studied euphausiid species is Antarctic krill ( Euphausia superba ), and a considerable literature exists documenting its ecology. The abundance of Antarctic krill varies enormously over multiple time and space scales in the Southern Ocean. This variability is driven partly by physical processes, but also by the behaviour of the animals as individuals and as groups. It is likely that such variability also affects the populations of other large euphausiid species. In order to understand this variability, particularly in the context of rapid environmental change and expanding fisheries interests, we need to shift emphasis from conventional point- and transect-sampling conducted from brief research cruises—usually in summer—to basin-scale observations over extended time periods. Future studies of the large-scale biology of krill of all species will also need to consider how their growth, reproduction and behaviour might alter in response to predicted environmental changes such as decline in sea ice cover, rising temperature and acidification of the ocean. Paradoxically, to answer many outstanding questions in krill biology, there also needs to be a shift towards examining the three-dimensional dynamics of krill aggregations on very small space and timescales. This paper outlines some of the approaches that might enable us to make progress in understanding these key organisms at multiple spatial and temporal scales, approaches that in turn may leave us better able to manage krill populations into the future. Whilst the paper’s focus is primarily on Antarctic krill, the findings are applicable generally to other large, schooling euphausiid species.

Multi‐scale spatiotemporal analyses of moose–vehicle collisions: a case study in northern Vermont

Moose–vehicle collisions (MVCs) pose a serious safety and environmental concern in many regions of Europe and North America. For example, in the state of Vermont, one‐third of all reported MVCs resulted in motorist injury or fatality while collisions have increased from two in 1982 to 164 in 2002. Our work used a MVC dataset from 1983 to 1999 in the Northeastern Highlands of Vermont (four major roads) to perform space, time and spatiotemporal analyses and guide future mitigation strategies. An adapted kernel density estimator was implemented for exploratory analyses to detect high density collision hotspots on roads. The kernel in space showed seven major density peaks which varied in magnitude and spread between roads. The kernel estimator in time for all roads showed an exponentially increasing trend with annual periodicity and a seasonal cyclic component, where the majority of collisions occurred from May to October. Spatiotemporal kernel estimation exhibited discontinuous density hotspots in time and space suggesting changing animal movement patterns across roads. We used an adapted Ripley's K‐function to test the hypothesis that MVCs clustering occurred at multiple scales in space, in time and in space–time combined. Statistically significant spatial clustering was evident on all roads at spatial scales from 2 to 10 km. A more consistent clustering in time occurred on all roads at a scale distance of 5 years. Similar to the kernel estimation, annual periodicity was also evident. Positive space–time clustering was present at small spatial (5 km) and temporal scales (2 years) indicating that where MVCs occur is also influenced by when they occur. In retrospect, using multiple road lengths, and the combined kernel estimation and Ripley's K‐function in time and space, provided a powerful methodology to study varying spatiotemporal patterns of wildlife collisions along roads. This can greatly assist transportation planners in identifying optimal mitigation strategies along specific roads, such as deciding on location and spatial length for permanent and expensive measures (e.g. crossing structures and associated fencing) versus less permanent and inexpensive structures (e.g. wildlife signage and reduced speed limits).

Lakes and reservoirs as sentinels, integrators, and regulators of climate change

Climate change is generating complex responses in both natural and human ecosystems that vary in their geographic distribution, magnitude, and timing across the global landscape. One of the major issues that scientists and policy makers now confront is how to assess such massive changes over multiple scales of space and time. Lakes and reservoirs comprise a geographically distributed network of the lowest points in the surrounding landscape that make them important sentinels of climate change. Their physical, chemical, and biological responses to climate provide a variety of information‐rich signals. Their sediments archive and integrate these signals, enabling paleolimnologists to document changes over years to millennia. Lakes are also hot spots of carbon cycling in the landscape and as such are important regulators of climate change, processing terrestrial and atmospheric as well as aquatic carbon. We provide an overview of this concept of lakes and reservoirs as sentinels, integrators, and regulators of climate change, as well as of the need for scaling and modeling these responses in the context of global climate change. We conclude by providing a brief look to the future and the creation of globally networked sensors in lakes and reservoirs around the world.

Analysis of Dynamical Interrelations of Electrocardiogram Parameters

Mathematical modeling of human physiology is a tremendously ambitious task. The complexity of the problems often stimulates the use of innovative mathematical techniques that are able to capture accurately processes that occur at multiple scales in time and space. The main purpose was to present the analytical method for the analysis of dynamical interrelations of electrocardiogram parameters, cointegrating numeric time series to matrixes by each cardio-cycle. The dynamical interrelations were compared between healthy persons and persons with acute myocardial infarction, also during coronary angiography. The results indicated that ECG signal parameters dynamical interrelations, calculated for each cardio-cycle bring new clinical information, that is not visible in the initial data. Ill. 7, bibl. 13 (in English; summaries in English, Russian and Lithuanian).

Using Avida-ED for Teaching and Learning About Evolution in Undergraduate Introductory Biology Courses

Evolution is a complex subject that requires knowledge of basic biological concepts and the ability to connect them across multiple scales of time, space, and biological organization. Avida-ED is a digital evolution educational software environment designed for teaching and learning about evolution and the nature of science in undergraduate biology courses. This study describes our backward design approach to developing an instructional activity using Avida-ED for teaching and learning about evolution in a large-enrollment introductory biology course. Using multiple assessment instruments, we measured student knowledge and understanding of key principles of natural selection before and after instruction on evolution (including the Avida-ED activity). Assessment analysis revealed significant post-instruction learning gains, although certain evolutionary principles (most notably those including genetics concepts, such as the genetic origin of variation) remained particularly difficult for students, even after instruction. Students, however, demonstrated a good grasp of the genetic component of the evolutionary process in the context of a problem on Avida-ED. We propose that: (a) deep understanding of evolution requires complex systems thinking skills, such as connecting concepts across multiple levels of biological organization, and (b) well designed use of Avida-ED holds the potential to help learners build a meaningful and transferable understanding of the evolutionary process.

A Simple Dynamical Model with Features of Convective Momentum Transport

Abstract Convective momentum transport (CMT) plays a central role in interactions across multiple space and time scales. However, because of the multiscale nature of CMT, quantifying and parameterizing its effects is often a challenge. Here a simple dynamic model with features of CMT is systematically derived and studied. The model includes interactions between a large-scale zonal mean flow and convectively coupled gravity waves, and convection is parameterized using a multicloud model. The moist convective wave–mean flow interactions shown here have several interesting features that distinguish them from other classical wave–mean flow settings. First an intraseasonal oscillation of the mean flow and convectively coupled waves (CCWs) is described. The mean flow oscillates due to both upscale and downscale CMT, and the CCWs weaken, change their propagation direction, and strengthen as the mean flow oscillates. The basic mechanisms of this oscillation are corroborated by linear stability theory with different mean flow background states. Another case is set up to imitate the westerly wind burst phase of the Madden–Julian oscillation (MJO) in the simplified dynamic model. In this case, CMT first accelerates the zonal jet with the strongest westerly wind aloft, and then there is deceleration of the winds due to CMT; this occurs on an intraseasonal time scale and is in qualitative agreement with actual observations of the MJO. Also, in this case, a multiscale envelope of convection propagates westward with smaller-scale convection propagating eastward within the envelope. The simplified dynamic model is able to produce this variety of behavior even though it has only a single horizontal direction and no Coriolis effect.

Low- and high-frequency climate variability in eastern Beringia during the past 25 000 yearsThis article is one of a series of papers published in this Special Issue on the theme Polar Climate Stability Network.

We present new temperature and precipitation reconstructions for the past 25 000 cal. years BP from across eastern Beringia based on a network of pollen diagrams, an updated modern pollen calibration database, and an improved methodology using the modern analogue technique (MAT). Time series show July temperatures were around 4 °C lower during full glacial and January temperatures were about 2 °C lower than present. Annual temperatures rose beginning around 16 000 cal. years BP, reaching a maximum around 12 000 cal. year BP. The warming was more rapid in southern Beringia. Annual precipitation varied by 250 mm during the past 25 000 cal. years BP. Maps of reconstructed precipitation patterns show increasingly drier conditions since 12 000 cal. years BP. that vary regionally, suggesting Holocene atmospheric circulation changes at multiple time and space scales. Orbitally forced seasonality changes during the late glacial and early Holocene resulted in reversed seasonal temperature reconstructions due to methodological constraints using the MAT and (or) non-analogue conditions. The magnitude of millennial-scale climate variability in this region was greater during the last glacial and late glacial periods than during the past 8000 years.

Tidal influence on surf zone ichthyofauna structure at three sandy beaches, southeastern Brazil

Natural assemblages show large variability at multiple scales in space and time as a consequence of several abiotic and biotic factors. This study was conducted in the surf zone of Arraial do Cabo (22º 58'S, 42º 01'W) and tested the hypothesis that the ichthyofauna composition and structure differ according to the tidal variation at three beaches with different morphodynamic characteristics. From September 2001 to August 2002 three monthly hauls were carried out at each beach during high (N = 6) and low tide (N = 6) with a beach seine (25 m length, 2,50 m height, 10 mm mesh). At Praia Grande and Prainha beaches, the number of species and individuals was higher during low tide. Also, CPUE (grams) at Praia Grande and Prainha was higher during high tide indicating a movement of many benthivore and piscivore species into the intertidal zone, due to the greater food availability. The fish community structure differed between Prainha and Praia Grande according to the tide in relation to fish biomass, which was higher at high tide, except for Praia dos Anjos (low tide) partially supporting the initial hypotheses. However, the number of individuals and species richness and diversity were higher during low tide, different from the proposed statement, as a reflex of juvenile individuals' abundance.

A self-growing hidden Markov tree for wafer map inspection

This paper presents an automatic identification of the defect spatial wafer map using a growing wavelet-based hidden Markov tree (gHMT) statistical model. The hierarchical tree-based model, gHMT, utilizes the growing and learning procedure to increase successively the size of the wavelet tree. It can characterize image processing masks from the defect spatial patterns. Like the standard hidden Markov tree, gHMT cannot only capture the statistical behavior of the real-world measurements at multiple scales in space and frequency but also has the ability to accurately identify the locations of the defect regions using the smallest possible size. These regions provide essential information and intrinsic features of each pattern. When all the possible defect patterns are modeled by gHMT, the maximum likelihood classifier is applied to the wavelet energy features extracted from each trained models. Accordingly, defect spatial patterns are identified. The effectiveness of the proposed classifier based on gHMT is illustrated through the experimental data from a wafer foundry plant. It can identify different defect patterns on wafers to help readers delve into the matter.

Measuring collective behaviour of multicellular ensembles: role of space-time scales

Living systems are spectacular examples of spatiotemporally organized structures. During the development of complex organization there is dynamic equilibrium between the local and global processes acting at the intra-and intercellular levels in multiple space and time scales. Although in modelling studies such spatiotemporal systems can be described by different space-time scales and at many organizational levels, the experimental quantities measured and predictions useful for practical applications are at a macroscopic (coarser or averaged) level/scale; these are limited by the resolution of the measuring method and experimental protocol. In this work, we address whether the spatiotemporal collective dynamics exhibited by a multiscale system can discriminate between,or be borne out by,the coarse-grained and averaged measurements done at different spatial and temporal scales. Using a simple model of a ring of cells, we show that measurements of both spatial and spatiotemporal average behaviour in this multicellular ensemble can mask the variety of collective dynamics observed at other space-time scales, and exhibit completely different behaviours. Such outcomes of measurements can lead to incomplete and incorrect understanding of physiological functions and pathogenesis in multicell ensembles.

Progress in single-molecule tracking spectroscopy

A topic of much current interest is the chemical reactivity in complex environments, involving dynamical processes spanning multiple scales in both time and space. While challenging to study using standard ensemble-averaged methods, it is amenable to investigations using single-molecule approaches. Ultimately, one would like to monitor the dynamics of individual molecules as they undergo chemical transformations through time-dependent spectroscopic studies, and to correlate various molecular properties with their immediate physical and chemical environments. This article provides an overview of the recent advances toward this goal and describes future developments and potential applications.