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1

A Population Prediction Strategy for Evolutionary Dynamic Multiobjective Optimization.

This paper investigates how to use prediction strategies to improve the performance of multiobjective evolutionary optimization algorithms in dealing with dynamic environments. Prediction-based methods have been applied to predict some isolated points in both dynamic single objective optimization and dynamic multiobjective optimization. We extend this idea to predict a whole population by considering the properties of continuous dynamic multiobjective optimization problems. In our approach, called population prediction strategy (PPS), a Pareto set is divided into two parts: a center point and a manifold. A sequence of center points is maintained to predict the next center, and the previous manifolds are used to estimate the next manifold. Thus, PPS could initialize a whole population by combining the predicted center and estimated manifold when a change is detected. We systematically compare PPS with a random initialization strategy and a hybrid initialization strategy on a variety of test instances with linear or nonlinear correlation between design variables. The statistical results show that PPS is promising for dealing with dynamic environments. PMID:23757532

Zhou, Aimin; Jin, Yaochu; Zhang, Qingfu

2013-02-26

2

Predicting population dynamics with analytical, simulation and supercomputer models

A set of epizootiological models describing the influence of a microsporidian disease on the population dynamics of an herbivorous insect demonstrate the similarities and differences between the three major approaches now available for ecological modeling. Simulation modeling allows the incorporation of randomness or the timing of discrete events in the temporal dynamics. More complex models incorporating both temporal and spatial dynamics in variable and heterogeneous environments require the use of supercomputers. Under a number of realistic circumstances, the qualitative predictions of the approaches may differ.

Onstad, D.W.

1987-07-01

3

Predicting population dynamics with analytical, simulation and supercomputer models

A set of epizootiological models describing the influence of a microsporidian disease on the population dynamics of an herbivorous insect demonstrate the similarities and differences between the three major approaches now available for ecological modeling. Simulation modeling allows the incorporation of randomness or the timing of discrete events in the temporal dynamics. More complex models incorporating both temporal and spatial

Onstad

1987-01-01

4

This chapter reviews aspects of population dynamics that may be conceptually important for biological control of mosquitoes. Density dependent population regulation among immature stages has important implications for biological control of mosquito populations, primarily because it can lead to compensatory or overcompensatory mortality due to additions of a biological control agent. This can result in control efforts leading to no change in the target population, or actual increases in the target population, respectively. Density dependent effects, and compensatory or overcompensatory mortality, appear to be most common in mosquitoes from container or highly ephemeral habitats. In permanent ground water habitats generalist predators appear to limit mosquito populations and so render mortality additive. Thus, biological control in permanent ground water habitats seems to have the highest likelihood of producing a satisfactory result. A central premise of classical biological control is that pest populations are reduced by enemies to stable equilibrium levels that are both below the pre-control equilibrium level, and well below the level producing detrimental effects. This premise results in predictions that successful biological control is likely to involve specialist enemies (usually parasitoids), with short generation times relative to the victim, high rates of successful search, rapid rates of increase, and needing only a few victims to complete their life cycle. These predictions largely fail for mosquito systems, in which successful biological control seems to be associated with generalist enemies that can kill a large portion of the target population, often causing local extinction, and can persist in the absence of the target organism. Biological control of mosquitoes appears to be inherently unstable, thus contrasting sharply with classical biological control. This review suggests a need for better data on density dependent regulation of mosquito populations.

Juliano, Steven A.

2007-01-01

5

Individual-based models (IBMs) are increasingly used to link the dynamics of individuals to higher levels of biological organization. Still, many IBMs are data hungry, species specific, and time-consuming to develop and analyze. Many of these issues would be resolved by using general theories of individual dynamics as the basis for IBMs. While such theories have frequently been examined at the individual level, few cross-level tests exist that also try to predict population dynamics. Here we performed a cross-level test of dynamic energy budget (DEB) theory by parameterizing an individual-based model using individual-level data of the water flea, Daphnia magna, and comparing the emerging population dynamics to independent data from population experiments. We found that DEB theory successfully predicted population growth rates and peak densities but failed to capture the decline phase. Further assumptions on food-dependent mortality of juveniles were needed to capture the population dynamics after the initial population peak. The resulting model then predicted, without further calibration, characteristic switches between small- and large-amplitude cycles, which have been observed for Daphnia. We conclude that cross-level tests help detect gaps in current individual-level theories and ultimately will lead to theory development and the establishment of a generic basis for individual-based models and ecology. PMID:23535615

Martin, Benjamin T; Jager, Tjalling; Nisbet, Roger M; Preuss, Thomas G; Grimm, Volker

2013-04-01

6

We developed stochastic matrix models to evaluate the effects of hydrologic alteration and variable mortality on the population dynamics of a lotic fish in a regulated river system. Models were applied to a representative lotic fish species, the flathead catfish (Pylodictis olivaris), for which two populations were examined: a native population from a regulated reach of the Coosa River (Alabama, USA) and an introduced population from an unregulated section of the Ocmulgee River (Georgia, USA). Size-classified matrix models were constructed for both populations, and residuals from catch-curve regressions were used as indices of year class strength (i.e., recruitment). A multiple regression model indicated that recruitment of flathead catfish in the Coosa River was positively related to the frequency of spring pulses between 283 and 566 m3/s. For the Ocmulgee River population, multiple regression models indicated that year class strength was negatively related to mean March discharge and positively related to June low flow. When the Coosa population was modeled to experience five consecutive years of favorable hydrologic conditions during a 50-year projection period, it exhibited a substantial spike in size and increased at an overall 0.2% annual rate. When modeled to experience five years of unfavorable hydrologic conditions, the Coosa population initially exhibited a decrease in size but later stabilized and increased at a 0.4% annual rate following the decline. When the Ocmulgee River population was modeled to experience five years of favorable conditions, it exhibited a substantial spike in size and increased at an overall 0.4% annual rate. After the Ocmulgee population experienced five years of unfavorable conditions, a sharp decline in population size was predicted. However, the population quickly recovered, with population size increasing at a 0.3% annual rate following the decline. In general, stochastic population growth in the Ocmulgee River was more erratic and variable than population growth in the Coosa River. We encourage ecologists to develop similar models for other lotic species, particularly in regulated river systems. Successful management of fish populations in regulated systems requires that we are able to predict how hydrology affects recruitment and will ultimately influence the population dynamics of fishes. PMID:20405801

Sakaris, Peter C; Irwin, Elise R

2010-03-01

7

We developed stochastic matrix models to evaluate the effects of hydrologic alteration and variable mortality on the population dynamics of a lotie fish in a regulated river system. Models were applied to a representative lotic fish species, the flathead catfish (Pylodictis olivaris), for which two populations were examined: a native population from a regulated reach of the Coosa River (Alabama, USA) and an introduced population from an unregulated section of the Ocmulgee River (Georgia, USA). Size-classified matrix models were constructed for both populations, and residuals from catch-curve regressions were used as indices of year class strength (i.e., recruitment). A multiple regression model indicated that recruitment of flathead catfish in the Coosa River was positively related to the frequency of spring pulses between 283 and 566 m3/s. For the Ocmulgee River population, multiple regression models indicated that year class strength was negatively related to mean March discharge and positively related to June low flow. When the Coosa population was modeled to experience five consecutive years of favorable hydrologic conditions during a 50-year projection period, it exhibited a substantial spike in size and increased at an overall 0.2% annual rate. When modeled to experience five years of unfavorable hydrologic conditions, the Coosa population initially exhibited a decrease in size but later stabilized and increased at a 0.4% annual rate following the decline. When the Ocmulgee River population was modeled to experience five years of favorable conditions, it exhibited a substantial spike in size and increased at an overall 0.4% annual rate. After the Ocmulgee population experienced five years of unfavorable conditions, a sharp decline in population size was predicted. However, the population quickly recovered, with population size increasing at a 0.3% annual rate following the decline. In general, stochastic population growth in the Ocmulgee River was more erratic and variable than population growth in the Coosa River. We encourage ecologists to develop similar models for other lotic species, particularly in regulated river systems. Successful management of fish populations in regulated systems requires that we are able to predict how hydrology affects recruitment and will ultimately influence the population dynamics of fishes. ?? 2010 by the Ecological Society of America.

Sakaris, P. C.; Irwin, E. R.

2010-01-01

8

Predicting Culex pipiens/restuans population dynamics by interval lagged weather data

Background Culex pipiens/restuans mosquitoes are important vectors for a variety of arthropod borne viral infections. In this study, the associations between 20 years of mosquito capture data and the time lagged environmental quantities daytime length, temperature, precipitation, relative humidity and wind speed were used to generate a predictive model for the population dynamics of this vector species. Methods Mosquito population in the study area was represented by averaged time series of mosquitos counts captured at 6 sites in Cook County (Illinois, USA). Cross-correlation maps (CCMs) were compiled to investigate the association between mosquito abundances and environmental quantities. The results obtained from the CCMs were incorporated into a Poisson regression to generate a predictive model. To optimize the predictive model the time lags obtained from the CCMs were adjusted using a genetic algorithm. Results CCMs for weekly data showed a highly positive correlation of mosquito abundances with daytime length 4 to 5 weeks prior to capture (quantified by a Spearman rank order correlation of rS?=?0.898) and with temperature during 2 weeks prior to capture (rS?=?0.870). Maximal negative correlations were found for wind speed averaged over 3 week prior to capture (rS?=??0.621). Cx. pipiens/restuans population dynamics was predicted by integrating the CCM results in Poisson regression models. They were used to simulate the average seasonal cycle of the mosquito abundance. Verification with observations resulted in a correlation of rS?=?0.899 for daily and rS?=?0.917 for weekly data. Applying the optimized models to the entire 20-years time series also resulted in a suitable fit with rS?=?0.876 for daily and rS?=?0.899 for weekly data. Conclusions The study demonstrates the application of interval lagged weather data to predict mosquito abundances with a feasible accuracy, especially when related to weekly Cx. pipiens/restuans populations.

2013-01-01

9

Bioreactor studies predict whole microbial population dynamics in oil sands tailings ponds.

Microorganisms in oil sands fluid fine tailings (FFT) are critical to biogeochemical elemental cycling as well as to the degradation of residual hydrocarbon constituents and subsequent methane and CO2 production. Microbial activity enhances particulate matter sedimentation rates and the dewatering of FFT materials, allowing water to be recycled back into bitumen extraction. A bulk of this evidence comes from bioreactor studies and has implications for engineering and environmental management of the FFT ponds. Yet, it is largely uncertain whether such laboratory populations are representative of whole field scale microbial communities. By using population ecology tools, we compared whole microbial communities present in FFT bioreactors to reference populations existing in Syncrude's West In Pit (WIP) tailings pond. Bacteria were found to be persistent in a sulfidic zone in both the oxic and anoxic bioreactors at all occasions tested. In contrast to the WIP, archaea only became predominant in bioreactors after 300 days, at which point analysis of similarity (global R statistic p<0.5) revealed no significant dissimilarities between the populations present in either system. A whole community succession pattern from bacterial dominated prevalence to a new assemblage predominated by archaea was suggested. These results have implications for the stepwise development of microbial model systems for predictive management of field scale FFT basins. PMID:22615052

Chi Fru, Ernest; Chen, Michael; Walshe, Gillian; Penner, Tara; Weisener, Christopher

2013-04-01

10

Stoichiometry and population dynamics

Population dynamics theory forms the quantitative core from which most ecologists have developed their intuition about how species interactions, heterogeneity, and biodiversity play out in time. Throughout its development, theoretical population biology has built on variants of the Lotka-Volterra equations and in nearly all cases has taken a single-currency approach to understanding population change, abstracting populations as aggregations of individuals

Tom Andersen; James J. Elser; Dag O. Hessen

2004-01-01

11

1.?Predation rate (PR) and kill rate are both fundamental statistics for understanding predation. However, relatively little is known about how these statistics relate to one another and how they relate to prey population dynamics. We assess these relationships across three systems where wolf-prey dynamics have been observed for 41 years (Isle Royale), 19 years (Banff) and 12 years (Yellowstone). 2.?To provide context for this empirical assessment, we developed theoretical predictions of the relationship between kill rate and PR under a broad range of predator-prey models including predator-dependent, ratio-dependent and Lotka-Volterra dynamics. 3.?The theoretical predictions indicate that kill rate can be related to PR in a variety of diverse ways (e.g. positive, negative, unrelated) that depend on the nature of predator-prey dynamics (e.g. structure of the functional response). These simulations also suggested that the ratio of predator-to-prey is a good predictor of prey growth rate. That result motivated us to assess the empirical relationship between the ratio and prey growth rate for each of the three study sites. 4.?The empirical relationships indicate that PR is not well predicted by kill rate, but is better predicted by the ratio of predator-to-prey. Kill rate is also a poor predictor of prey growth rate. However, PR and ratio of predator-to-prey each explained significant portions of variation in prey growth rate for two of the three study sites. 5.?Our analyses offer two general insights. First, Isle Royale, Banff and Yellowstone are similar insomuch as they all include wolves preying on large ungulates. However, they also differ in species diversity of predator and prey communities, exploitation by humans and the role of dispersal. Even with the benefit of our analysis, it remains difficult to judge whether to be more impressed by the similarities or differences. This difficulty nicely illustrates a fundamental property of ecological communities. Second, kill rate is the primary statistic for many traditional models of predation. However, our work suggests that kill rate and PR are similarly important for understanding why predation is such a complex process. PMID:21569029

Vucetich, John A; Hebblewhite, Mark; Smith, Douglas W; Peterson, Rolf O

2011-11-01

12

We expose here a detailed spatially explicit model of aphid population dynamics at the scale of a whole country (Metropolitan France). It is based on convection-diffusion-reaction equations, driven by abiotic and biotic factors. The target species is the grain aphid, Sitobion avenae F., considering both its winged and apterous morphs. In this preliminary work, simulations for year 2004 (an outbreak case) produced realistic aphid densities, and showed that both spatial and temporal S. avenae population dynamics can be represented as an irregular wave of population peak densities from southwest to northeast of the country, driven by gradients or differences in temperature, wheat phenology, and wheat surfaces. This wave pattern fits well to our knowledge of S. avenae phenology. The effects of three insecticide spray regimes were simulated in five different sites and showed that insecticide sprays were ineffective in terms of yield increase after wheat flowering. After suitable validation, which will require some further years of observations, the model will be used to forecast aphid densities in real time at any date or growth stage of the crop anywhere in the country. It will be the backbone of a decision support system, forecasting yield losses at the level of a field. The model intends then to complete the punctual forecasting provided by older models by a comprehensive spatial view on a large area and leads to the diminution of insecticide sprayings in wheat crops. PMID:24271722

Ciss, Mamadou; Parisey, Nicolas; Moreau, Fabrice; Dedryver, Charles-Antoine; Pierre, Jean-Sébastien

2014-04-01

13

Population Dynamics in Population Decline Society

In the previous reports [1, 2], we predicted population until 2060 as an initial value with population at 1965. The estimation from in 1970 to in 2000 accorded with investigation value. By which, reliability was provided for a predicted value after 2000. The birth rate in each age grade by the calculation after 2005 was actual birth rate in 2004.

Kazuharu Koide; Nobuo Noda; Hiroyuki Matsuura; Masahiro Nakano

2007-01-01

14

Spatial population dynamics: analyzing patterns and processes of population synchrony

The search for mechanisms behind spatial population synchrony is currently a major issue in population ecology. Theoretical studies highlight how synchronizing mechanisms such as dispersal, regionally correlated climatic variables and mobile enemies might interact with local dynamics to produce different patterns of spatial covariance. Specialized statistical methods, applied to large-scale survey data, aid in testing the theoretical predictions with empirical

Ottar N. Bjørnstad; Rolf A. Ims; Xavier Lambin

1999-01-01

15

Coupling between evolutionary and population dynamics in experimental microbial populations

NASA Astrophysics Data System (ADS)

It has been often been assumed that population dynamics and evolutionary dynamics occur at such different timescales that they are effectively de-coupled. This view has been challenged recently, due to observations of evolutionary changes occurring in short timescales. This has led to a growing interest in understanding eco-evolutionary dynamics of populations. In this context, recent theoretical models have predicted that coupling between population dynamics and evolutionary dynamics can have important effects for the evolution and stability of cooperation, and lead to extremely rich and varied dynamics. Here, we report our investigation of the eco-evolutionary dynamics of a cooperative social behavior, sucrose metabolism, in experimental yeast populations. We have devised an experimental strategy to visualize trajectories in the phase space formed by the population size (N) and the fraction of cooperator cells in the population (f). Our measurements confirm a strong coupling between evolutionary and population dynamics, and allowed us to characterize the bifurcation plots. We used this approach to investigate how sudden environmental changes affect the stability and recovery of populations, and therefore the stability of cooperation.

Sanchez, Alvaro; Gore, Jeff

2012-02-01

16

Imitation dynamics predict vaccinating behaviour.

There exists an interplay between vaccine coverage, disease prevalence and the vaccinating behaviour of individuals. Moreover, because of herd immunity, there is also a strategic interaction between individuals when they are deciding whether or not to vaccinate, because the probability that an individual becomes infected depends upon how many other individuals are vaccinated. To understand this potentially complex interplay, a game dynamic model is developed in which individuals adopt strategies according to an imitation dynamic (a learning process), and base vaccination decisions on disease prevalence and perceived risks of vaccines and disease. The model predicts that oscillations in vaccine uptake are more likely in populations where individuals imitate others more readily or where vaccinating behaviour is more sensitive to changes in disease prevalence. Oscillations are also more likely when the perceived risk of vaccines is high. The model reproduces salient features of the time evolution of vaccine uptake and disease prevalence during the whole-cell pertussis vaccine scare in England and Wales during the 1970s. This suggests that using game theoretical models to predict, and even manage, the population dynamics of vaccinating behaviour may be feasible. PMID:16087421

Bauch, Chris T

2005-08-22

17

Incidence rates in dynamic populations

The purpose of the present article is to explain the calculation of incidence rates in dynamic populations with the use of simple mathematical and statistical concepts. The first part will consider incidence rates in dynamic populations, and how they can best be taught in basic, intermediate and advanced courses. The second part will briefly explain how and why incidence rates are calculated in cohorts.

Vandenbroucke, Jan P; Pearce, Neil

2012-01-01

18

Agriculture has contributed to loss of vertebrate biodiversity in many regions, including the U.S. Corn Belt. Amphibian populations, in particular, have experienced widespread and often inexplicable declines, range reductions, and extinctions. However, few attempts have been made...

19

Two complementary paradigms for analysing population dynamics.

To understand why population growth rate is sometimes positive and sometimes negative, ecologists have adopted two main approaches. The most common approach is through the density paradigm by plotting population growth rate against population density. The second approach is through the mechanistic paradigm by plotting population growth rate against the relevant ecological processes affecting the population. The density paradigm is applied a posteriori, works sometimes but not always and is remarkably useless in solving management problems or in providing an understanding of why populations change in size. The mechanistic paradigm investigates the factors that supposedly drive density changes and is identical to Caughley's declining population paradigm of conservation biology. The assumption that we can uncover invariant relationships between population growth rate and some other variables is an article of faith. Numerous commercial fishery applications have failed to find the invariant relationships between stock and recruitment that are predicted by the density paradigm. Environmental variation is the rule, and non-equilibrial dynamics should force us to look for the mechanisms of population change. If multiple factors determine changes in population density, there can be no predictability in either of these paradigms and we will become environmental historians rather than scientists with useful generalizations for the population problems of this century. Defining our questions clearly and adopting an experimental approach with crisp alternative hypotheses and adequate controls will be essential to building useful generalizations for solving the practical problems of population management in fisheries, wildlife and conservation.

Krebs, Charles J

2002-01-01

20

Population dynamics of bacterial persistence.

Persistence is a prime example of phenotypic heterogeneity, where a microbial population splits into two distinct subpopulations with different growth and survival properties as a result of reversible phenotype switching. Specifically, persister cells grow more slowly than normal cells under unstressed growth conditions, but survive longer under stress conditions such as the treatment with bactericidal antibiotics. We analyze the population dynamics of such a population for several typical experimental scenarios, namely a constant environment, shifts between growth and stress conditions, and periodically switching environments. We use an approximation scheme that allows us to map the dynamics to a logistic equation for the subpopulation ratio and derive explicit analytical expressions for observable quantities that can be used to extract underlying dynamic parameters from experimental data. Our results provide a theoretical underpinning for the study of phenotypic switching, in particular for organisms where detailed mechanistic knowledge is scarce. PMID:23675428

Patra, Pintu; Klumpp, Stefan

2013-01-01

21

Modeling sandhill crane population dynamics

The impact of sport hunting on the Central Flyway population of sandhill cranes (Grus canadensis) has been a subject of controversy for several years. A recent study (Buller 1979) presented new and important information on sandhill crane population dynamics. The present report is intended to incorporate that and other information into a mathematical model for the purpose of assessing the long-range impact of hunting on the population of sandhill cranes.The model is a simple deterministic system that embodies density-dependent rates of survival and recruitment. The model employs four kinds of data: (1) spring population size of sandhill cranes, estimated from aerial surveys to be between 250,000 and 400,000 birds; (2) age composition in fall, estimated for 1974-76 to be 11.3% young; (3) annual harvest of cranes, estimated from a variety of sources to be about 5 to 7% of the spring population; and (4) age composition of harvested cranes, which was difficult to estimate but suggests that immatures were 2 to 4 times as vulnerable to hunting as adults.Because the true nature of sandhill crane population dynamics remains so poorly understood, it was necessary to try numerous (768 in all) combinations of survival and recruitment functions, and focus on the relatively few (37) that yielded population sizes and age structures comparable to those extant in the real population. Hunting was then applied to those simulated populations. In all combinations, hunting resulted in a lower asymptotic crane population, the decline ranging from 5 to 54%. The median decline was 22%, which suggests that a hunted sandhill crane population might be about three-fourths as large as it would be if left unhunted. Results apply to the aggregate of the three subspecies in the Central Flyway; individual subspecies or populations could be affected to a greater or lesser degree.

Johnson, D. H.

1979-01-01

22

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate.

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H.; Gambhir, Manoj; Fu, Joshua S.; Liu, Yang; Remais, Justin V.

2014-01-01

23

Evolutionary dynamics in structured populations.

Evolutionary dynamics shape the living world around us. At the centre of every evolutionary process is a population of reproducing individuals. The structure of that population affects evolutionary dynamics. The individuals can be molecules, cells, viruses, multicellular organisms or humans. Whenever the fitness of individuals depends on the relative abundance of phenotypes in the population, we are in the realm of evolutionary game theory. Evolutionary game theory is a general approach that can describe the competition of species in an ecosystem, the interaction between hosts and parasites, between viruses and cells, and also the spread of ideas and behaviours in the human population. In this perspective, we review the recent advances in evolutionary game dynamics with a particular emphasis on stochastic approaches in finite sized and structured populations. We give simple, fundamental laws that determine how natural selection chooses between competing strategies. We study the well-mixed population, evolutionary graph theory, games in phenotype space and evolutionary set theory. We apply these results to the evolution of cooperation. The mechanism that leads to the evolution of cooperation in these settings could be called 'spatial selection': cooperators prevail against defectors by clustering in physical or other spaces. PMID:20008382

Nowak, Martin A; Tarnita, Corina E; Antal, Tibor

2010-01-12

24

Dynamic Communicability Predicts Infectiousness

NASA Astrophysics Data System (ADS)

Using real, time-dependent social interaction data, we look at correlations between some recently proposed dynamic centrality measures and summaries from large-scale epidemic simulations. The evolving network arises from email exchanges. The centrality measures, which are relatively inexpensive to compute, assign rankings to individual nodes based on their ability to broadcast information over the dynamic topology. We compare these with node rankings based on infectiousness that arise when a full stochastic SI simulation is performed over the dynamic network. More precisely, we look at the proportion of the network that a node is able to infect over a fixed time period, and the length of time that it takes for a node to infect half the network. We find that the dynamic centrality measures are an excellent, and inexpensive, proxy for the full simulation-based measures.

Mantzaris, Alexander V.; Higham, Desmond J.

25

Population mixture model for nonlinear telomere dynamics

NASA Astrophysics Data System (ADS)

Telomeres are DNA repeats protecting chromosomal ends which shorten with each cell division, eventually leading to cessation of cell growth. We present a population mixture model that predicts an exponential decrease in telomere length with time. We analytically solve the dynamics of the telomere length distribution. The model provides an excellent fit to available telomere data and accounts for the previously unexplained observation of telomere elongation following stress and bone marrow transplantation, thereby providing insight into the nature of the telomere clock.

Itzkovitz, Shalev; Shlush, Liran I.; Gluck, Dan; Skorecki, Karl

2008-12-01

26

PREDICTING WILDLIFE POPULATION EFFECTS FROM MULTIPLE STRESSORS

The U.S. Environmental Protection Agency's National Health and Environmental Effects Research Laboratory (NHEERL) is developing tools for predicting risks of multiple stressors to wildlife populations, which support the development of risk-based protective criteria. NHEERL's res...

27

Flood trends and population dynamics

NASA Astrophysics Data System (ADS)

Since the earliest recorded civilizations, such as those in Mesopotamia and Egypt that developed in the fertile floodplains of the Tigris and Euphrates and Nile rivers, humans tend to settle in flood prone areas as they offer favorable conditions for economic development. However, floodplains are also exposed to flood disasters that might cause severe socio-economic and environmental damages not to mention losses of human lives. A flood event turns to be a disaster when it coincides with a vulnerable environment exceeding society's capacity to manage the adverse consequences. This presentation discusses the link between hydrological risk and population change by referring to the outcomes of scientific works recently carried out in Africa and Europe. More specifically, it is shown that the severity of flood disasters, currently affecting more than 100 million people a year, might be seriously exacerbated because of population change. In fact, flood exposure and/or vulnerability might increase because of rapid population growth (and its spatial and temporal dynamics, e.g. urbanization) in the African continent and because of population ageing in many European countries. Lastly, timely and economically sustainable actions to mitigate this increasing hydrological risk are critically evaluated.

Di Baldassarre, G.

2012-04-01

28

Evolutionary Dynamics and Diversity in Microbial Populations

NASA Astrophysics Data System (ADS)

Diseases such as flu and cancer adapt at an astonishing rate. In large part, viruses and cancers are so difficult to prevent because they are continually evolving. Controlling such ``evolutionary diseases'' requires a better understanding of the underlying evolutionary dynamics. It is conventionally assumed that adaptive mutations are rare and therefore will occur and sweep through the population in succession. Recent experiments using modern sequencing technologies have illuminated the many ways in which real population sequence data does not conform to the predictions of conventional theory. We consider a very simple model of asexual evolution and perform simulations in a range of parameters thought to be relevant for microbes and cancer. Simulation results reveal complex evolutionary dynamics typified by competition between lineages with different sets of adaptive mutations. This dynamical process leads to a distribution of mutant gene frequencies different than expected under the conventional assumption that adaptive mutations are rare. Simulated gene frequencies share several conspicuous features with data collected from laboratory-evolved yeast and the worldwide population of influenza.

Thompson, Joel; Fisher, Daniel

2013-03-01

29

Genomic predictability of interconnected biparental maize populations.

Intense structuring of plant breeding populations challenges the design of the training set (TS) in genomic selection (GS). An important open question is how the TS should be constructed from multiple related or unrelated small biparental families to predict progeny from individual crosses. Here, we used a set of five interconnected maize (Zea mays L.) populations of doubled-haploid (DH) lines derived from four parents to systematically investigate how the composition of the TS affects the prediction accuracy for lines from individual crosses. A total of 635 DH lines genotyped with 16,741 polymorphic SNPs were evaluated for five traits including Gibberella ear rot severity and three kernel yield component traits. The populations showed a genomic similarity pattern, which reflects the crossing scheme with a clear separation of full sibs, half sibs, and unrelated groups. Prediction accuracies within full-sib families of DH lines followed closely theoretical expectations, accounting for the influence of sample size and heritability of the trait. Prediction accuracies declined by 42% if full-sib DH lines were replaced by half-sib DH lines, but statistically significantly better results could be achieved if half-sib DH lines were available from both instead of only one parent of the validation population. Once both parents of the validation population were represented in the TS, including more crosses with a constant TS size did not increase accuracies. Unrelated crosses showing opposite linkage phases with the validation population resulted in negative or reduced prediction accuracies, if used alone or in combination with related families, respectively. We suggest identifying and excluding such crosses from the TS. Moreover, the observed variability among populations and traits suggests that these uncertainties must be taken into account in models optimizing the allocation of resources in GS. PMID:23535384

Riedelsheimer, Christian; Endelman, Jeffrey B; Stange, Michael; Sorrells, Mark E; Jannink, Jean-Luc; Melchinger, Albrecht E

2013-06-01

30

Genomic Predictability of Interconnected Biparental Maize Populations

Intense structuring of plant breeding populations challenges the design of the training set (TS) in genomic selection (GS). An important open question is how the TS should be constructed from multiple related or unrelated small biparental families to predict progeny from individual crosses. Here, we used a set of five interconnected maize (Zea mays L.) populations of doubled-haploid (DH) lines derived from four parents to systematically investigate how the composition of the TS affects the prediction accuracy for lines from individual crosses. A total of 635 DH lines genotyped with 16,741 polymorphic SNPs were evaluated for five traits including Gibberella ear rot severity and three kernel yield component traits. The populations showed a genomic similarity pattern, which reflects the crossing scheme with a clear separation of full sibs, half sibs, and unrelated groups. Prediction accuracies within full-sib families of DH lines followed closely theoretical expectations, accounting for the influence of sample size and heritability of the trait. Prediction accuracies declined by 42% if full-sib DH lines were replaced by half-sib DH lines, but statistically significantly better results could be achieved if half-sib DH lines were available from both instead of only one parent of the validation population. Once both parents of the validation population were represented in the TS, including more crosses with a constant TS size did not increase accuracies. Unrelated crosses showing opposite linkage phases with the validation population resulted in negative or reduced prediction accuracies, if used alone or in combination with related families, respectively. We suggest identifying and excluding such crosses from the TS. Moreover, the observed variability among populations and traits suggests that these uncertainties must be taken into account in models optimizing the allocation of resources in GS.

Riedelsheimer, Christian; Endelman, Jeffrey B.; Stange, Michael; Sorrells, Mark E.; Jannink, Jean-Luc; Melchinger, Albrecht E.

2013-01-01

31

Empirical Prediction Intervals for County Population Forecasts

Population forecasts entail a significant amount of uncertainty, especially for long-range horizons and for places with small\\u000a or rapidly changing populations. This uncertainty can be dealt with by presenting a range of projections or by developing\\u000a statistical prediction intervals. The latter can be based on models that incorporate the stochastic nature of the forecasting\\u000a process, on empirical analyses of past

Stefan Rayer; Stanley K. Smith; Jeff Tayman

2009-01-01

32

Sex in space: population dynamic consequences

Sex, so important in the reproduction of bigametic species, is nonetheless often ignored in explorations of the dynamics of populations. Using a growth model of dispersal-coupled populations we can keep track of fluctuations in numbers of females and males. The sexes may differ from each other in their ability to disperse and their sensitivity to population density. As a further complication, the breeding system is either monogamous or polygamous. We use the harmonic mean birth function to account for sex-ratio-dependent population growth in a Moran–Ricker population renewal process. Incorporating the spatial dimension stabilizes the dynamics of populations with monogamy as the breeding system, but does not stabilize the population dynamics of polygamous species. Most notably, in populations coupled with dispersal, where the sexes differ in their dispersal ability there are rarely stable and equal sex ratios. Rather, a two-point cycle, four-point cycle and eventually complex behaviour of sex-ratio dynamics will emerge with increasing birth rates. Monogamy often leads to less noisy sex-ratio dynamics than polygamy. In our model, the sex-ratio dynamics of coupled populations differ from those of an isolated population system, where a stable 50:50 sex ratio is achievable with equal density-dependence costs for females and males. When sexes match in their dispersal ability, population dynamics and sex-ratio dynamics of coupled populations collapse to those of isolated populations.

Ranta, E.; Kaitala, V.; m, J. Lindstr

1999-01-01

33

Population size predicts technological complexity in Oceania

Much human adaptation depends on the gradual accumulation of culturally transmitted knowledge and technology. Recent models of this process predict that large, well-connected populations will have more diverse and complex tool kits than small, isolated populations. While several examples of the loss of technology in small populations are consistent with this prediction, it found no support in two systematic quantitative tests. Both studies were based on data from continental populations in which contact rates were not available, and therefore these studies do not provide a test of the models. Here, we show that in Oceania, around the time of early European contact, islands with small populations had less complicated marine foraging technology. This finding suggests that explanations of existing cultural variation based on optimality models alone are incomplete because demography plays an important role in generating cumulative cultural adaptation. It also indicates that hominin populations with similar cognitive abilities may leave very different archaeological records, a conclusion that has important implications for our understanding of the origin of anatomically modern humans and their evolved psychology.

Kline, Michelle A.; Boyd, Robert

2010-01-01

34

A Quantitative Model of Honey Bee Colony Population Dynamics

Since 2006 the rate of honey bee colony failure has increased significantly. As an aid to testing hypotheses for the causes of colony failure we have developed a compartment model of honey bee colony population dynamics to explore the impact of different death rates of forager bees on colony growth and development. The model predicts a critical threshold forager death rate beneath which colonies regulate a stable population size. If death rates are sustained higher than this threshold rapid population decline is predicted and colony failure is inevitable. The model also predicts that high forager death rates draw hive bees into the foraging population at much younger ages than normal, which acts to accelerate colony failure. The model suggests that colony failure can be understood in terms of observed principles of honey bee population dynamics, and provides a theoretical framework for experimental investigation of the problem.

Khoury, David S.; Myerscough, Mary R.; Barron, Andrew B.

2011-01-01

35

A quantitative model of honey bee colony population dynamics.

Since 2006 the rate of honey bee colony failure has increased significantly. As an aid to testing hypotheses for the causes of colony failure we have developed a compartment model of honey bee colony population dynamics to explore the impact of different death rates of forager bees on colony growth and development. The model predicts a critical threshold forager death rate beneath which colonies regulate a stable population size. If death rates are sustained higher than this threshold rapid population decline is predicted and colony failure is inevitable. The model also predicts that high forager death rates draw hive bees into the foraging population at much younger ages than normal, which acts to accelerate colony failure. The model suggests that colony failure can be understood in terms of observed principles of honey bee population dynamics, and provides a theoretical framework for experimental investigation of the problem. PMID:21533156

Khoury, David S; Myerscough, Mary R; Barron, Andrew B

2011-01-01

36

Population Dynamics of Genetic Regulatory Networks

NASA Astrophysics Data System (ADS)

Unlike common objects in physics, a biological cell processes information. The cell interprets its genome and transforms the genomic information content, through the action of genetic regulatory networks, into proteins which in turn dictate its metabolism, functionality and morphology. Understanding the dynamics of a population of biological cells presents a unique challenge. It requires to link the intracellular dynamics of gene regulation, through the mechanism of cell division, to the level of the population. We present experiments studying adaptive dynamics of populations of genetically homogeneous microorganisms (yeast), grown for long durations under steady conditions. We focus on population dynamics that do not involve random genetic mutations. Our experiments follow the long-term dynamics of the population distributions and allow to quantify the correlations among generations. We focus on three interconnected issues: adaptation of genetically homogeneous populations following environmental changes, selection processes on the population and population variability and expression distributions. We show that while the population exhibits specific short-term responses to environmental inputs, it eventually adapts to a robust steady-state, largely independent of external conditions. Cycles of medium-switch show that the adapted state is imprinted in the population and that this memory is maintained for many generations. To further study population adaptation, we utilize the process of gene recruitment whereby a gene naturally regulated by a specific promoter is placed under a different regulatory system. This naturally occurring process has been recognized as a major driving force in evolution. We have recruited an essential gene to a foreign regulatory network and followed the population long-term dynamics. Rewiring of the regulatory network allows us to expose their complex dynamics and phase space structure.

Braun, Erez

2005-03-01

37

Fast Migration and Emergent Population Dynamics

NASA Astrophysics Data System (ADS)

We consider population dynamics on a network of patches, having the same local dynamics, with different population scales (carrying capacities). It is reasonable to assume that if the patches are coupled by very fast migration the whole system will look like an individual patch with a large effective carrying capacity. This is called a “well-mixed” system. We show that, in general, it is not true that the total population has the same dynamics as each local patch when the migration is fast. Different global dynamics can emerge, and usually must be figured out for each individual case. We give a general condition which must be satisfied for the total population to have the same dynamics as the constituent patches.

Khasin, Michael; Khain, Evgeniy; Sander, Leonard M.

2012-12-01

38

Virus Evolution and Population Dynamics

It is intuitive that the field of virology is a discipline integral to the medical sciences. The affiliation of virology with population and conservation biology may not be as apparent. However, viruses, and in particular, virus evolution, may both contribute to and be a significant tool to understand changes in host population structure. The impact of viruses is most notable

Mary Poss; Roman Biek; Allen Rodrigo

39

Population Dynamics, Demography, Dispersal and Spread of Bemisia tabaci

\\u000a Understanding the population-level processes of any pest insect is central to predicting temporal and spatial changes in abundance\\u000a and occurrence, as well as in developing effective pest management strategies, whether on single crops on individual farms\\u000a or multiple crops within agricultural landscapes. Four components drive population dynamics in the time-space continuum: birth\\u000a rates, death rates, immigration rates, and emigration rates.

Steven E. Naranjo; Steven J. Castle; Paul J. De Barro; Shu-Sheng Liu

40

Population Dynamics of Harmful Cyanobacteria

huge number is sufficient to cover an area of 1.000.000 km 2 in which the upper meter of the water column is populated by an extremely dense population of 1.000.000 cyanobacterial cells per millilitre of water. Adding another 20 days would suffice to cover the entire planet Earth with a dense surface bloom. A frightful thought! Why, then, are most

Jef Huisman; Florence D. HULOT

41

Modeling spatiotemporal dynamics of vole populations in Europe and America.

The mathematical models proposed and studied in the present paper provide a unified framework to understand complex dynamical patterns in vole populations in Europe and North America. We have extended the well-known model provided by Hanski and Turchin by incorporating the diffusion term and spatial heterogeneity and performed several mathematical and numerical analyses to explore the dynamics in space and time of the model. These models successfully predicted the observed rodent dynamics in these regions. An attempt has been made to bridge the gap between the field and theoretical studies carried out by Turchin and Hanski (1997) and Turchin and Ellner (2000). Simulation experiments, mainly two-dimensional parameter scans, show the importance of spatial heterogeneity in order to understand the poorly understood fluctuations in population densities of voles in Fennoscandia and Northern America. This study shed new light upon the dynamics of voles in these regions. The nonlinear analysis of vole data suggests that the dynamical shift is from stability to chaos. Diffusion driven model systems predict a new type of dynamics not yet observed in the field studies of vole populations carried out so far. This has been termed as chaotic in time and regular in space (CTRS). We observed CTRS dynamics in several simulation experiments. This directs us to expect that dynamics of this animal would be de-correlated in time and simultaneously mass extinctions might be possible at many spatial locations. PMID:19861132

Upadhyay, Ranjit Kumar; Kumari, Nitu; Rai, Vikas

2010-01-01

42

Population dynamics with and without selection

NASA Astrophysics Data System (ADS)

A model describing population dynamics is presented. We study the effect of selection pressure and inbreeding on the time evolution of the population and the chances of survival. We find that the selection is in general beneficial, enabling survival of a population whose size is declining. Inbreeding reduces the survival chances since it leads to clustering of individuals. We have also found, in agreement with biological data, that there is a threshold value of the initial size of the population, as well as of the habitat, below which the population will almost certainly become extinct. We present analytical and computer simulation approaches.

P?kalski, Andrzej; Sznajd-Weron, Katarzyna

2001-03-01

43

Population dynamics on heterogeneous bacterial substrates

NASA Astrophysics Data System (ADS)

How species invade new territories and how these range expansions influence the population's genotypes are important questions in the field of population genetics. The majority of work addressing these questions focuses on homogeneous environments. Much less is known about the population dynamics and population genetics when the environmental conditions are heterogeneous in space. To better understand range expansions in two-dimensional heterogeneous environments, we employ a system of bacteria and bacteriophage, the viruses of bacteria. Thereby, the bacteria constitute the environment in which a population of bacteriophages expands. The spread of phage constitutes itself in lysis of bacteria and thus formation of clear regions on bacterial lawns, called plaques. We study the population dynamics and genetics of the expanding page for various patterns of environments.

Mobius, Wolfram; Murray, Andrew W.; Nelson, David R.

2012-02-01

44

Invasion Waves in Populations with Excitable Dynamics

Whilst the most obvious mechanism for a biological invasion is the occupation of a new territory as a result of direct ingress by individuals of the invading population, a more subtle “invasion” may occur without significant motion of invading individuals if the population dynamics in a predator prey scenario has an “excitable” character. Here, “excitable” means that a local equilibrium

J. Brindley; V. H. Biktashev; M. A. Tsyganov

2005-01-01

45

Effects of virus on plant fecundity and population dynamics.

Microorganisms are ubiquitous and thought to regulate host populations. Although microorganisms can be pathogenic and affect components of fitness, few studies have examined their effects on wild plant populations. As individual traits might not contribute equally to changes in population growth rate, it is essential to examine the entire life cycle to determine how microorganisms affect host population dynamics. In this study, we used data from common garden experiments with plants from three Cucurbita pepo populations exposed to three virus treatments. These data were used to parameterize a deterministic matrix model, which allowed us to estimate the effect of virus on components of fitness and population growth rate. Virus did not reduce fruit number, but population growth rates varied among virus treatments and wild C. pepo populations. The effect of virus on population growth rate depended on virus species and wild C. pepo population. Contributions of life-history transitions and life-history traits to population growth rates varied among populations and virus treatments. However, this population-virus interaction was not evident when examining individual components of fitness. Thus, caution must be used when interpreting the effects of changes in individual traits, as single traits do not always predict population-level change accurately. PMID:24571200

Prendeville, Holly R; Tenhumberg, Brigitte; Pilson, Diana

2014-06-01

46

Stage-structured population models predict transient population dynamics if the population deviates from the stable stage distribution. Ecologists' interest in transient dynamics is growing because populations regularly deviate from the stable stage distribution, which can lead to transient dynamics that differ significantly from the stable stage dynamics. Because the structure of a population matrix (i.e., the number of life-history stages) can influence the predicted scale of the deviation, we explored the effect of matrix size on predicted transient dynamics and the resulting amplification of population size. First, we experimentally measured the transition rates between the different life-history stages and the adult fecundity and survival of the aphid, Acythosiphon pisum. Second, we used these data to parameterize models with different numbers of stages. Third, we compared model predictions with empirically measured transient population growth following the introduction of a single adult aphid. We find that the models with the largest number of life-history stages predicted the largest transient population growth rates, but in all models there was a considerable discrepancy between predicted and empirically measured transient peaks and a dramatic underestimation of final population sizes. For instance, the mean population size after 20 days was 2394 aphids compared to the highest predicted population size of 531 aphids; the predicted asymptotic growth rate (lamdamax) was consistent with the experiments. Possible explanations for this discrepancy are discussed. PMID:19694136

Tenhumberg, Brigitte; Tyre, Andrew J; Rebarber, Richard

2009-07-01

47

Medium Term Prediction of Chaotic Dynamics

We investigate medium term prediction of chaotic dynamics when the initial condition of the system is not well specified. Traditional methods can only predict on short time scales using the Lyapunov Exponent and often give poor results. We find the use of Symbolic Dynamics and Markov Chains illuminates the reason for the poor results of traditional methods and provides a

Christopher Strelioff; Alfred Hubler

2003-01-01

48

Hidden process models for animal population dynamics.

Hidden process models are a conceptually useful and practical way to simultaneously account for process variation in animal population dynamics and measurement errors in observations and estimates made on the population. Process variation, which can be both demographic and environmental, is modeled by linking a series of stochastic and deterministic subprocesses that characterize processes such as birth, survival, maturation, and movement. Observations of the population can be modeled as functions of true abundance with realistic probability distributions to describe observation or estimation error. Computer-intensive procedures, such as sequential Monte Carlo methods or Markov chain Monte Carlo, condition on the observed data to yield estimates of both the underlying true population abundances and the unknown population dynamics parameters. Formulation and fitting of a hidden process model are demonstrated for Sacramento River winter-run chinook salmon (Oncorhynchus tshawytsha). PMID:16705962

Newman, K B; Buckland, S T; Lindley, S T; Thomas, L; Fernández, C

2006-02-01

49

Seasonal predictions based on two dynamical models

Two dynamical models are used to perform a series of seasonal predictions. One model, referred to as GCM2, was designed as a general circulation model for climate studies, while the second one, SEF, was designed for numerical weather prediction. The seasonal predictions cover the 26?year period 1969–1994. For each of the four seasons, ensembles of six forecasts are produced with

Jacques Derome; Gilbert Brunet; André Plante; Normand Gagnon; George J. Boer; Francis W. Zwiers; Steven J. Lambert; Jian Sheng; Harold Ritchie

2001-01-01

50

Regime prediction and predictability in nonlinear dynamical systems

NASA Astrophysics Data System (ADS)

Prediction and predictability properties of nonlinear dynamical systems are diagnosed and analysed empirically using nonlinear time series analysis techniques. The notion of predictability is relaxed from accurate prediction of individual trajectories to a coarse-grained view in which only probabilities of visiting certain regions of state space or regimes are forecast. The regimes and the transition probabilities between them are determined simultaneously by fitting a hidden Markov model to a time series of the system. Predictive information is then refined by building a nearest-neighbour model of the regime posterior distribution. The ideas are exemplified on the stochastically forced Lorenz system.

Kwasniok, F.

2008-12-01

51

Mutator dynamics in sexual and asexual experimental populations of yeast

Background In asexual populations, mutators may be expected to hitchhike with associated beneficial mutations. In sexual populations, recombination is predicted to erode such associations, inhibiting mutator hitchhiking. To investigate the effect of recombination on mutators experimentally, we compared the frequency dynamics of a mutator allele (msh2?) in sexual and asexual populations of Saccharomyces cerevisiae. Results Mutator strains increased in frequency at the expense of wild-type strains in all asexual diploid populations, with some approaching fixation in 150 generations of propagation. Over the same period of time, mutators declined toward loss in all corresponding sexual diploid populations as well as in haploid populations propagated asexually. Conclusions We report the first experimental investigation of mutator dynamics in sexual populations. We show that a strong mutator quickly declines in sexual populations while hitchhiking to high frequency in asexual diploid populations, as predicted by theory. We also show that the msh2? mutator has a high and immediate realized cost that is alone sufficient to explain its decline in sexual populations. We postulate that this cost is indirect; namely, that it is due to a very high rate of recessive lethal or strongly deleterious mutation. However, we cannot rule out the possibility that msh2? also has unknown directly deleterious effects on fitness, and that these effects may differ between haploid asexual and sexual populations. Despite these reservations, our results prompt us to speculate that the short-term cost of highly deleterious recessive mutations can be as important as recombination in preventing mutator hitchhiking in sexual populations.

2011-01-01

52

Structural dynamics and ecology of flatfish populations

NASA Astrophysics Data System (ADS)

The concept of structure in populations of marine fishes is fundamental to how we manage and conduct research on these resources. The degree of population structure ranges widely among flatfishes. Although we know that large populations tend to be subdivided into local populations, based on morphological, meristic and reproductive characteristics, these data often conflict with evidence on genetic stock structure, due to the scale and organization of movement within the metapopulation. Movement of individuals between local subpopulations and colonization events on a macroecological scale are probably important to some flatfish populations. Dispersal of larvae is known to be a major factor affecting population mixing. Some flatfishes have planktonic stages of long duration and for these species there is often, but not always, little population structure; gene flow sometimes may be limited by oceanographic features, such as eddies and fronts. At the juvenile stage dispersal can result in colonization of under-utilized habitats; however, for flatfishes with strong habitat requirements, this type of event may be less likely when suitable habitats are fragmented. Complex population structure has major implications for management, e.g. lumping harvested populations with little gene flow can have detrimental local effects. Moreover, the issue of population structure and movement influences the interpretation of research data, where populations are generally treated as closed systems. There is currently a strong need for a multidisciplinary approach to study fish population dynamics and the structure of their populations. This research should involve molecular geneticists, population geneticists, animal behaviourists and ecologists. Migration mechanisms, colonization and extinction events, gene flow and density-dependent movements are subject areas of great importance to managing large harvested populations, but our understanding of them at ecological scales, at least for marine fishes, is at a rudimentary level.

Bailey, Kevin M.

1997-11-01

53

Dynamical Predictability of the Magnetosphere

NASA Astrophysics Data System (ADS)

The magnetosphere, driven by the turbulent solar wind, exhibits complex behavior consisting of global, regional and local features. The global features are in general captured by the geomagnetic indices and the regional and local features are measured by spacecraft-based imagers and ground-based instruments. The global dynamical behavior has been studied extensively using nonlinear dynamical techniques, such as phase space reconstruction from time series data. However the presence of a wide range of scales limits the ability of these techniques and a mean field approach is used to obtain an improved recostruction of the dynamics. In this technique the magnetospheric response is averaged over a number of nearest neighbors and it results into a dynamical description of the global features. This description is further improved by introducing weighted averaging, with the weights inversely proportional to the distances. The multiscale aspects can not be described within a dynamical framework and a Bayesian approach is used to compute the conditional probabilities from the correlated solar wind - magnetosphere data. The regional features of the dynamics is studied using the mutual information functions computed from the magnetic field data from the high latitude magnetometer stations. The spreads in the average mutual information show a good correlation with the solar wind convective electric field and sudden changes in the dynamic pressure. The distribution of scales in the magnetospheric dynamics is studied using an extensive data (more than 8.6 million) of the auroral electrojet index AL. The distributions of the waiting times deviate significantly from power law as well as stretched exponential distributions, and show a scaling with respect to the mean. This indicates a limited role of long term correlations in the magnetospheric dynamics.

Sharma, A.; Chen, J.; Veeramani, T.; Shao, X.

2006-12-01

54

Random Leslie matrices in population dynamics.

We generalize the concept of the population growth rate when a Leslie matrix has random elements (correlated or not), i.e., characterizing the disorder in the vital parameters. In general, we present a perturbative formalism to deal with linear non-negative random matrix difference equations, then the non-trivial effective eigenvalue of which defines the long-time asymptotic dynamics of the mean-value population vector state is presented as the effective growth rate. This effective eigenvalue is calculated from the smallest positive root of a secular polynomial. Analytical (exact and perturbative calculations) results are presented for several models of disorder. In particular, a 3 × 3 numerical example is applied to study the effective growth rate characterizing the long-time dynamics of a biological population model. The present analysis is a perturbative method for finding the effective growth rate in cases when the vital parameters may have negative covariances across populations. PMID:21076977

Cáceres, Manuel O; Cáceres-Saez, Iris

2011-09-01

55

Population dynamics of Arashiyama west Japanese macaques

Demographic data have been collected on the Arashiyama Japanese macaque population from 1954 until the present, through the\\u000a fissioning of the original group into two parts in 1966, and through the translocation of one of the two groups to Texas in\\u000a 1972. Population dynamics are reported for the Arashiyama West group in Texas during 1972 to 1979 and then compared

Linda Marie Fedigan; Harold Gouzoules; Sarah Gouzoules

1983-01-01

56

Multispecies population dynamics of prebiotic compositional assemblies.

Present life portrays a two-tier phenomenology: molecules compose supramolecular structures, such as cells or organisms, which in turn portray population behaviors, including selection, evolution and ecological dynamics. Prebiotic models have often focused on evolution in populations of self-replicating molecules, without explicitly invoking the intermediate molecular-to-supramolecular transition. Here, we explore a prebiotic model that allows one to relate parameters of chemical interaction networks within molecular assemblies to emergent population dynamics. We use the graded autocatalysis replication domain (GARD) model, which simulates the network dynamics within amphiphile-containing molecular assemblies, and exhibits quasi-stationary compositional states termed compotype species. These grow by catalyzed accretion, divide and propagate their compositional information to progeny in a replication-like manner. The model allows us to ask how molecular network parameters influence assembly evolution and population dynamics parameters. In 1000 computer simulations, each embodying different parameter set of the global chemical interaction network parameters, we observed a wide range of behaviors. These were analyzed by a multi species logistic model often used for analyzing population ecology (r-K or Lotka-Volterra competition model). We found that compotypes with a larger intrinsic molecular repertoire show a higher intrinsic growth (r) and lower carrying capacity (K), as well as lower replication fidelity. This supports a prebiotic scenario initiated by fast-replicating assemblies with a high molecular diversity, evolving into more faithful replicators with narrower molecular repertoires. PMID:24831416

Markovitch, Omer; Lancet, Doron

2014-09-21

57

Population dynamics of defensive symbionts in aphids.

Vertically transmitted micro-organisms can increase in frequency in host populations by providing net benefits to hosts. While laboratory studies have identified diverse beneficial effects conferred by inherited symbionts of insects, they have not explicitly examined the population dynamics of mutualist symbiont infection within populations. In the pea aphid, Acyrthosiphon pisum, the inherited facultative symbiont, Hamiltonella defensa, provides protection against parasitism by the wasp, Aphidius ervi. Despite a high fidelity of vertical transmission and direct benefits of infection accruing to parasitized aphids, Hamiltonella remains only at intermediate frequencies in natural populations. Here, we conducted population cage experiments to monitor the dynamics of Hamiltonella and of another common A. pisum symbiont, Serratia symbiotica, in the presence and absence of parasitism. We also conducted fitness assays of Hamiltonella-infected aphids to search for costs to infection in the absence of parasitism. In the population cages, we found that the frequency of A. pisum infected with Hamiltonella increased dramatically after repeated exposure to parasitism by A. ervi, indicating that selection pressures from natural enemies can lead to the increase of particular inherited symbionts in insect populations. In our laboratory fitness assays, we did not detect a cost to infection with Hamiltonella, but in the population cages not exposed to parasitism, we found a significant decline in the frequency of both Hamiltonella and Serratia. The declining frequencies of Hamiltonella-infected aphids in population cages in the absence of parasitism indicate a probable cost to infection and may explain why Hamiltonella remains at intermediate frequencies in natural populations. PMID:18029301

Oliver, Kerry M; Campos, Jaime; Moran, Nancy A; Hunter, Martha S

2008-02-01

58

HABIT FORMATION, DYNASTIC ALTRUISM, AND POPULATION DYNAMICS

We study the general equilibrium properties of two growth models with overlapping generations, habit formation and endogenous fertility. In the neoclassical model, habits modify the economy's growth rate and generate transitional dynamics in fertility; station- ary income per capita is associated with either increasing or decreasing population and output, depending on the strength of habits. In the AK speci…cation, growing

Andreas Schäfer; Simone Valentey

2010-01-01

59

Summary 1. Hypericum perforatum , St John's wort, is an invasive weed of natural and agro- ecosystems in south-eastern Australia. In previous work we used a long-term data set to determine which plant traits and environmental factors influence population growth and persistence in this species. These results were then used to parameterize an individual- based model of the population dynamics

Yvonne M. Buckley; David T. Briese; Mark Rees

2003-01-01

60

Dynamic Branch Prediction with Perceptrons

This paper presents a new method for branch prediction. The key idea is to use one of the simplest possible neural net- works, the perceptron, as an alternative to the commonly used two-bit counters. Our predictor achieves increased ac- curacy by making use of long branch histories, which are possible because the hardware resources for our method scale linearly with

Daniel A. Jiménez; Calvin Lin

2001-01-01

61

Dynamic Branch Prediction with Perceptrons

This paper presents a new method for branch prediction. The key idea is to use one of the simplest possible neural net- works, the perceptron, as an alternative to the commonly used two-bit counters. Our predictor achieves increased ac- curacy by making use of long branch histories, which are possible because the hardware resources for our method scale linearly with

Daniel A. Jim; Calvin Lin

2000-01-01

62

Population dynamics of king eiders breeding in northern Alaska

The North American population of king eiders (Somateria spectabilis) has declined by more than 50% since the late 1970s for unknown reasons. King eiders spend most of their lives in remote areas, forcing managers to make regulatory and conservation decisions based on very little information. We incorporated available published estimates of vital rates with new estimates to build a female, stage-based matrix population model for king eiders and examine the processes underlying population dynamics of king eiders breeding at 2 sites, Teshekpuk and Kuparuk, on the coastal plain of northern Alaska and wintering around the Bering Sea (2001–2010). We predicted a decreasing population (? = 0.981, 95% CI: 0.978–0.985), and that population growth was most sensitive to changes in adult female survival (sensitivity = 0.92). Low duckling survival may be a bottleneck to productivity (variation in ducking survival accounted for 66% of retrospective variation in ?). Adult survival was high (0.94) and invariant (? = 0.0002, 95% CI: 0.0000–0.0007); however, catastrophic events could have a major impact and we need to consider how to mitigate and manage threats to adult survival. A hypothetical oil spill affecting breeding females in a primary spring staging area resulted in a severe population decline; although, transient population dynamics were relatively stable. However, if no catastrophic events occur, the more variable reproductive parameters (duckling and nest survival) may be more responsive to management actions.

Bentzen, Rebecca L.; Powell, Abby N.

2012-01-01

63

Seismicity dynamics and earthquake predictability

NASA Astrophysics Data System (ADS)

Many factors complicate earthquake sequences, including the heterogeneity and self-similarity of the geological medium, the hierarchical structure of faults and stresses, and small-scale variations in the stresses from different sources. A seismic process is a type of nonlinear dissipative system demonstrating opposing trends towards order and chaos. Transitions from equilibrium to unstable equilibrium and local dynamic instability appear when there is an inflow of energy; reverse transitions appear when energy is dissipating. Several metastable areas of a different scale exist in the seismically active region before an earthquake. Some earthquakes are preceded by precursory phenomena of a different scale in space and time. These include long-term activation, seismic quiescence, foreshocks in the broad and narrow sense, hidden periodical vibrations, effects of the synchronization of seismic activity, and others. Such phenomena indicate that the dynamic system of lithosphere is moving to a new state - catastrophe. A number of examples of medium-term and short-term precursors is shown in this paper. However, no precursors identified to date are clear and unambiguous: the percentage of missed targets and false alarms is high. The weak fluctuations from outer and internal sources play a great role on the eve of an earthquake and the occurrence time of the future event depends on the collective behavior of triggers. The main task is to improve the methods of metastable zone detection and probabilistic forecasting.

Sobolev, G. A.

2011-02-01

64

Predicting and controlling the behaviour of microbial ecosystems demands a fundamental understanding of the factors controlling their dynamics. In the natural environment microbes typically live in small local populations with limited and unpredictable nutrient supply and high death rates. Here, we show that these conditions can produce oscillations in microbial population dynamics, even for a single population. For a large population, with deterministic growth dynamics, our model predicts transient (damped) oscillations. For a small population, demographic noise causes these oscillations to be sustained indefinitely. We show that the same mechanism can produce sustained stochastic oscillations in a two-species, nutrient-cycling microbial ecosystem. Our results suggest that oscillatory population dynamics may be a common feature of small microbial populations in the natural environment, even in the absence of complex interspecies interactions or spatial structuring. PMID:22935336

Khatri, Bhavin S; Free, Andrew; Allen, Rosalind J

2012-12-01

65

Dynamics of protein distributions in cell populations.

A population of cells exhibits wide phenotypic variation even if it is genetically homogeneous. In particular, individual cells differ from one another in the amount of protein they express under a given regulatory system under fixed conditions. Here we study how protein distributions in a population of the yeast S. cerevisiae are shaped by a balance of processes: protein production--an intracellular process--and protein dilution due to cell division--a population process. We measure protein distributions by employing reporter green fluorescence protein (gfp) under the regulation of the yeast GAL system under conditions where it is metabolically essential. Cell populations are grown in chemostats, thus allowing control of the environment and stable measurements of distribution dynamics over many generations. Despite the essential functional role of the GAL system in a pure galactose medium, steady-state distributions are found to be universally broad, with exponential tails and a large standard-deviation-to-mean ratio. Under several different perturbations the dynamics of the distribution is observed to be asymmetric, with a much longer time to build a wide expression distribution from below compared with a fast relaxation of the distribution toward steady state from above. These results show that the main features of the protein distributions are largely determined by population effects and are less sensitive to the intracellular biochemical noise. PMID:17021381

Brenner, Naama; Farkash, Keren; Braun, Erez

2006-09-01

66

Dynamics of protein distributions in cell populations

NASA Astrophysics Data System (ADS)

A population of cells exhibits wide phenotypic variation even if it is genetically homogeneous. In particular, individual cells differ from one another in the amount of protein they express under a given regulatory system under fixed conditions. Here we study how protein distributions in a population of the yeast S. cerevisiae are shaped by a balance of processes: protein production—an intracellular process—and protein dilution due to cell division—a population process. We measure protein distributions by employing reporter green fluorescence protein (gfp) under the regulation of the yeast GAL system under conditions where it is metabolically essential. Cell populations are grown in chemostats, thus allowing control of the environment and stable measurements of distribution dynamics over many generations. Despite the essential functional role of the GAL system in a pure galactose medium, steady-state distributions are found to be universally broad, with exponential tails and a large standard-deviation-to-mean ratio. Under several different perturbations the dynamics of the distribution is observed to be asymmetric, with a much longer time to build a wide expression distribution from below compared with a fast relaxation of the distribution toward steady state from above. These results show that the main features of the protein distributions are largely determined by population effects and are less sensitive to the intracellular biochemical noise.

Brenner, Naama; Farkash, Keren; Braun, Erez

2006-09-01

67

Developments in predicting the effective size of subdivided populations

The effective population size is the parameter that summarizes the magnitude of genetic drift and increase in inbreeding occurring in a population. In this paper, developments in the prediction equations for the effective size of populations subdivided under various models are reviewed, and extensions are made in several cases. Derivations are shown for some simple models, and the relationships among

Jinliang Wang; Armando Caballero

1999-01-01

68

Effect of Migration on Population Dynamics

NASA Astrophysics Data System (ADS)

Computer studies of evolution in migrating population are presented. The model is based on the Penna model. Migration for better living conditions does influence population dynamics in different locations. Examples of different scenarios of preferences to live in bigger or smaller populations (or environmental capacity, or living space available) are discussed. In the limiting case of low migration intensity, each location evolves independently according to its local rules and conditions, as expected. With increasing migration, the population distribution between locations changes, including the critical behavior of extinction of population for some locations for a specific set of the rules. Then, the deserted location may become populated again if the migration is still increasing as result of a pressure to move. The present version is devoted to the migration controlled exclusively by environmental factors, yet the model is primarily designed to describe both inherited mutations on environmental factors and can be used to study the effect of different races mixing, or recovery of environmental capacity of the fields when chasing 2 flocks of geese in a cyclic manner across 3 fields.

Magdo?, Maria S.

69

Galactic civilizations - Population dynamics and interstellar diffusion

NASA Technical Reports Server (NTRS)

A model is developed of the interstellar diffusion of galactic civilizations which takes into account the population dynamics of such civilizations. The problem is formulated in terms of potential theory, with a family of nonlinear partial differential and difference equations specifying population growth and diffusion for an organism with advantageous genes that undergoes random dispersal while increasing in population locally, and a population at zero population growth. In the case of nonlinear diffusion with growth and saturation, it is found that the colonization wavefront from the nearest independently arisen galactic civilization can have reached the earth only if its lifetime exceeds 2.6 million years, or 20 million years if discretization can be neglected. For zero population growth, the corresponding lifetime is 13 billion years. It is concluded that the earth is uncolonized not because interstellar spacefaring civilizations are rare, but because there are too many worlds to be colonized in the plausible colonization lifetime of nearby civilizations, and that there exist no very old galactic civilizations with a consistent policy of the conquest of inhabited worlds.

Newman, W. I.; Sagan, C.

1981-01-01

70

Ability of matrix models to explain the past and predict the future of plant populations.

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage-based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts' 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data-collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk-averse decisions than to expect precise forecasts from models. PMID:23565966

Crone, Elizabeth E; Ellis, Martha M; Morris, William F; Stanley, Amanda; Bell, Timothy; Bierzychudek, Paulette; Ehrlén, Johan; Kaye, Thomas N; Knight, Tiffany M; Lesica, Peter; Oostermeijer, Gerard; Quintana-Ascencio, Pedro F; Ticktin, Tamara; Valverde, Teresa; Williams, Jennifer L; Doak, Daniel F; Ganesan, Rengaian; McEachern, Kathyrn; Thorpe, Andrea S; Menges, Eric S

2013-10-01

71

Calculating evolutionary dynamics in structured populations.

Evolution is shaping the world around us. At the core of every evolutionary process is a population of reproducing individuals. The outcome of an evolutionary process depends on population structure. Here we provide a general formula for calculating evolutionary dynamics in a wide class of structured populations. This class includes the recently introduced "games in phenotype space" and "evolutionary set theory." There can be local interactions for determining the relative fitness of individuals, but we require global updating, which means all individuals compete uniformly for reproduction. We study the competition of two strategies in the context of an evolutionary game and determine which strategy is favored in the limit of weak selection. We derive an intuitive formula for the structure coefficient, sigma, and provide a method for efficient numerical calculation. PMID:20019806

Nathanson, Charles G; Tarnita, Corina E; Nowak, Martin A

2009-12-01

72

The replicator dynamics with n players and population structure.

The well-known replicator dynamics is usually applied to 2-player games and random matching. Here we allow for games with n players, and for population structures other than random matching. This more general application leads to a version of the replicator dynamics of which the standard 2-player, well-mixed version is a special case, and which allows us to explore the dynamic implications of population structure. The replicator dynamics also allows for a reformulation of the central theorem in Van Veelen (2009), which claims that inclusive fitness gives the correct prediction for games with generalized equal gains from switching (or, in other words, when fitness effects are additive). If we furthermore also assume that relatedness is constant during selection - which is a reasonable assumption in a setting with kin recognition - then inclusive fitness even becomes a parameter that determines the speed as well as the direction of selection. For games with unequal gains from switching, inclusive fitness can give the wrong prediction. With equal gains however, not only the sign, but also even the value of inclusive fitness becomes meaningful. PMID:21295593

van Veelen, Matthijs

2011-05-01

73

Adaptive dynamics for physiologically structured population models.

We develop a systematic toolbox for analyzing the adaptive dynamics of multidimensional traits in physiologically structured population models with point equilibria (sensu Dieckmann et al. in Theor. Popul. Biol. 63:309-338, 2003). Firstly, we show how the canonical equation of adaptive dynamics (Dieckmann and Law in J. Math. Biol. 34:579-612, 1996), an approximation for the rate of evolutionary change in characters under directional selection, can be extended so as to apply to general physiologically structured population models with multiple birth states. Secondly, we show that the invasion fitness function (up to and including second order terms, in the distances of the trait vectors to the singularity) for a community of N coexisting types near an evolutionarily singular point has a rational form, which is model-independent in the following sense: the form depends on the strategies of the residents and the invader, and on the second order partial derivatives of the one-resident fitness function at the singular point. This normal form holds for Lotka-Volterra models as well as for physiologically structured population models with multiple birth states, in discrete as well as continuous time and can thus be considered universal for the evolutionary dynamics in the neighbourhood of singular points. Only in the case of one-dimensional trait spaces or when N = 1 can the normal form be reduced to a Taylor polynomial. Lastly we show, in the form of a stylized recipe, how these results can be combined into a systematic approach for the analysis of the (large) class of evolutionary models that satisfy the above restrictions. PMID:17943289

Durinx, Michel; Metz, J A J Hans; Meszéna, Géza

2008-05-01

74

Population dynamics in Er3+-doped fluoride glasses

NASA Astrophysics Data System (ADS)

A detailed study of the energy-transfer processes in Er3+: flouride glasses with doping concentrations of 0.2-18 mol % is presented. Fluorescence wave forms for 11 erbium transitions were measured under 802-nm, 1.5-?m, 975-nm, 520-nm, and 403-nm excitation from a high-energy short-pulse source. The analysis of these data provided a physical understanding of the processes responsible for the temporal behavior of the populations of a large number of energy levels. A comprehensive nine-level rate-equation model of the Er3+ population dynamics in these fluoride glasses is developed. The model performs well in predicting the observed fluorescence behavior of the main fluorescing lines under all pumping conditions. The modeling process allowed 14 ion-ion energy-transfer processes that are important for the population dynamics in these fluoride glasses to be identified and their rate constants obtained. Noticeably, the inclusion of seven three-ion processes was found necessary in order to obtain good fits to the experimental fluorescence wave forms. It was also found that some three-ion processes have a significant effect on the population dynamics of the levels even in lower doping concentrations.

Bogdanov, V. K.; Booth, D. J.; Gibbs, W. E.; Javorniczky, J. S.; Newman, P. J.; Macfarlane, D. R.

2001-05-01

75

Learning stable, regularised latent models of neural population dynamics.

Ongoing advances in experimental technique are making commonplace simultaneous recordings of the activity of tens to hundreds of cortical neurons at high temporal resolution. Latent population models, including Gaussian-process factor analysis and hidden linear dynamical system (LDS) models, have proven effective at capturing the statistical structure of such data sets. They can be estimated efficiently, yield useful visualisations of population activity, and are also integral building-blocks of decoding algorithms for brain-machine interfaces (BMI). One practical challenge, particularly to LDS models, is that when parameters are learned using realistic volumes of data the resulting models often fail to reflect the true temporal continuity of the dynamics; and indeed may describe a biologically-implausible unstable population dynamic that is, it may predict neural activity that grows without bound. We propose a method for learning LDS models based on expectation maximisation that constrains parameters to yield stable systems and at the same time promotes capture of temporal structure by appropriate regularisation. We show that when only little training data is available our method yields LDS parameter estimates which provide a substantially better statistical description of the data than alternatives, whilst guaranteeing stable dynamics. We demonstrate our methods using both synthetic data and extracellular multi-electrode recordings from motor cortex. PMID:22663075

Buesing, Lars; Macke, Jakob H; Sahani, Maneesh

2012-01-01

76

API Requirements for Dynamic Graph Prediction

Given a large-scale time-evolving multi-modal and multi-relational complex network (a.k.a., a large-scale dynamic semantic graph), we want to implement algorithms that discover patterns of activities on the graph and learn predictive models of those discovered patterns. This document outlines the application programming interface (API) requirements for fast prototyping of feature extraction, learning, and prediction algorithms on large dynamic semantic graphs. Since our algorithms must operate on large-scale dynamic semantic graphs, we have chosen to use the graph API developed in the CASC Complex Networks Project. This API is supported on the back end by a semantic graph database (developed by Scott Kohn and his team). The advantages of using this API are (i) we have full-control of its development and (ii) the current API meets almost all of the requirements outlined in this document.

Gallagher, B; Eliassi-Rad, T

2006-10-13

77

Prediction of Type 1 Diabetes in the General Population

OBJECTIVE To evaluate the utility of GAD antibodies (GADAs) and islet antigen-2 antibodies (IA-2As) in prediction of type 1 diabetes over 27 years in the general population and to assess the 6-year rates of seroconversion. RESEARCH DESIGN AND METHODS A total of 3,475 nondiabetic subjects aged 3–18 years were sampled in 1980, and 2,375 subjects (68.3%) were resampled in 1986. All subjects were observed for development of diabetes to the end of 2007. GADAs and IA-2As were analyzed in all samples obtained in 1980 and 1986. RESULTS A total of 34 individuals (1.0%; 9 developed diabetes) initially had GADAs and 22 (0.6%; 9 developed diabetes) IA-2As. Seven subjects (0.2%) tested positive for both autoantibodies. The positive seroconversion rate over 6 years was 0.4% for GADAs and 0.2% for IA-2As, while the inverse seroconversion rates were 33 and 57%, respectively. Eighteen subjects (0.5%) developed type 1 diabetes after a median pre-diabetic period of 8.6 years (range 0.9–20.3). Initial positivity for GADAs and/or IA-2As had a sensitivity of 61% (95% CI 36–83) for type 1 diabetes. Combined positivity for GADAs and IA-2As had both a specificity and a positive predictive value of 100% (95% CI 59–100). CONCLUSIONS One-time screening for GADAs and IA-2As in the general childhood population in Finland would identify ?60% of those individuals who will develop type 1 diabetes over the next 27 years, and those subjects who have both autoantibodies carry an extremely high risk for diabetes. Both positive and inverse seroconversions do occur over time reflecting a dynamic process of ?-cell autoimmunity.

Knip, Mikael; Korhonen, Sari; Kulmala, Petri; Veijola, Riitta; Reunanen, Antti; Raitakari, Olli T.; Viikari, Jorma; Akerblom, Hans K.

2010-01-01

78

Hidden hysteresis - population dynamics can obscure gene network dynamics

Background Positive feedback is a common motif in gene regulatory networks. It can be used in synthetic networks as an amplifier to increase the level of gene expression, as well as a nonlinear module to create bistable gene networks that display hysteresis in response to a given stimulus. Using a synthetic positive feedback-based tetracycline sensor in E. coli, we show that the population dynamics of a cell culture has a profound effect on the observed hysteretic response of a population of cells with this synthetic gene circuit. Results The amount of observable hysteresis in a cell culture harboring the gene circuit depended on the initial concentration of cells within the culture. The magnitude of the hysteresis observed was inversely related to the dilution procedure used to inoculate the subcultures; the higher the dilution of the cell culture, lower was the observed hysteresis of that culture at steady state. Although the behavior of the gene circuit in individual cells did not change significantly in the different subcultures, the proportion of cells exhibiting high levels of steady-state gene expression did change. Although the interrelated kinetics of gene expression and cell growth are unpredictable at first sight, we were able to resolve the surprising dilution-dependent hysteresis as a result of two interrelated phenomena - the stochastic switching between the ON and OFF phenotypes that led to the cumulative failure of the gene circuit over time, and the nonlinear, logistic growth of the cell in the batch culture. Conclusions These findings reinforce the fact that population dynamics cannot be ignored in analyzing the dynamics of gene networks. Indeed population dynamics may play a significant role in the manifestation of bistability and hysteresis, and is an important consideration when designing synthetic gene circuits intended for long-term application.

2013-01-01

79

Assessing the dynamics of wild populations

Lotka's equations summarizing population dynamics can be approximated by functional models of the survivorship and reproductive curves, incorporating three stages of survival and reproduction, respectively. An abbreviated form uses a single reproductive parameter and two survival values. Survivorship and reproductive curves were fitted to data on northern fur seals (Callorhinus ursinus), domestic and feral sheep, white-tailed deer (Odocoileus virginianus), grizzly bears (Ursus arctos), African buffalo (Syncerus caffer), free-ranging horses, and fin whales (Balaenoptera physalus). Data for 10 species suggest a useful relationship between senescence parameters. A bias due to senescence may lead to serious underestimation of survival rates. Observed annual rates of increase of 18-20% for feral horses, 16% for southern fur seals (Arctocephalus gazella), and 60% for white-tailed deer are compatible with observed population parameters. 43 references, 11 figures, 3 tables.

Eberhardt, L.L.

1985-01-01

80

Dynamically hot galaxies. II - Global stellar populations

NASA Technical Reports Server (NTRS)

The global relationship between the stellar populations and the structural properties of dynamically hot galaxies (DHGs) is investigated using the same sample as was analyzed by Bender et al. (1992), which includes giant ellipticals, low-luminosity ellipticals, compact ellipticals, diffuse dwarf ellipticals, dwarf spheroidals, and bulges. It was found that all DHGs follow a single relationship between global stellar population (represented by Mg2 index or B-V color) and central velocity dispersion sigma(0), and that the Mg2-sigma(0) relation is significantly tighter than the relation between the Mg2 index and absolute luminosity. The relation between central Mg2 index and bulk B-V color was also found to be tight.

Bender, Ralf; Burstein, David; Faber, S. M.

1993-01-01

81

Monitoring microbial population dynamics at low densities

NASA Astrophysics Data System (ADS)

We propose a new and simple method for the measurement of microbial concentrations in highly diluted cultures. This method is based on an analysis of the intensity fluctuations of light scattered by microbial cells under laser illumination. Two possible measurement strategies are identified and compared using simulations and measurements of the concentration of gold nanoparticles. Based on this comparison, we show that the concentration of Escherichia coli and Saccharomyces cerevisiae cultures can be easily measured in situ across a concentration range that spans five orders of magnitude. The lowest measurable concentration is three orders of magnitude (1000×) smaller than in current optical density measurements. We show further that this method can also be used to measure the concentration of fluorescent microbial cells. In practice, this new method is well suited to monitor the dynamics of population growth at early colonization of a liquid culture medium. The dynamic data thus obtained are particularly relevant for microbial ecology studies.

Julou, Thomas; Desprat, Nicolas; Bensimon, David; Croquette, Vincent

2012-07-01

82

Effects of culling on mesopredator population dynamics.

Anthropogenic changes in land use and the extirpation of apex predators have facilitated explosive growth of mesopredator populations. Consequently, many species have been subjected to extensive control throughout portions of their range due to their integral role as generalist predators and reservoirs of zoonotic disease. Yet, few studies have monitored the effects of landscape composition or configuration on the demographic or behavioral response of mesopredators to population manipulation. During 2007 we removed 382 raccoons (Procyon lotor) from 30 forest patches throughout a fragmented agricultural ecosystem to test hypotheses regarding the effects of habitat isolation on population recovery and role of range expansion and dispersal in patch colonization of mesopredators in heterogeneous landscapes. Patches were allowed to recolonize naturally and demographic restructuring of patches was monitored from 2008-2010 using mark-recapture. An additional 25 control patches were monitored as a baseline measure of demography. After 3 years only 40% of experimental patches had returned to pre-removal densities. This stagnant recovery was driven by low colonization rates of females, resulting in little to no within-patch recruitment. Colonizing raccoons were predominantly young males, suggesting that dispersal, rather than range expansion, was the primary mechanism driving population recovery. Contrary to our prediction, neither landscape connectivity nor measured local habitat attributes influenced colonization rates, likely due to the high dispersal capability of raccoons and limited role of range expansion in patch colonization. Although culling is commonly used to control local populations of many mesopredators, we demonstrate that such practices create severe disruptions in population demography that may be counterproductive to disease management in fragmented landscapes due to an influx of dispersing males into depopulated areas. However, given the slow repopulation rates observed in our study, localized depopulation may be effective at reducing negative ecological impacts of mesopredators in fragmented landscapes at limited spatial and temporal scales. PMID:23527065

Beasley, James C; Olson, Zachary H; Beatty, William S; Dharmarajan, Guha; Rhodes, Olin E

2013-01-01

83

Effects of Culling on Mesopredator Population Dynamics

Anthropogenic changes in land use and the extirpation of apex predators have facilitated explosive growth of mesopredator populations. Consequently, many species have been subjected to extensive control throughout portions of their range due to their integral role as generalist predators and reservoirs of zoonotic disease. Yet, few studies have monitored the effects of landscape composition or configuration on the demographic or behavioral response of mesopredators to population manipulation. During 2007 we removed 382 raccoons (Procyon lotor) from 30 forest patches throughout a fragmented agricultural ecosystem to test hypotheses regarding the effects of habitat isolation on population recovery and role of range expansion and dispersal in patch colonization of mesopredators in heterogeneous landscapes. Patches were allowed to recolonize naturally and demographic restructuring of patches was monitored from 2008–2010 using mark-recapture. An additional 25 control patches were monitored as a baseline measure of demography. After 3 years only 40% of experimental patches had returned to pre-removal densities. This stagnant recovery was driven by low colonization rates of females, resulting in little to no within-patch recruitment. Colonizing raccoons were predominantly young males, suggesting that dispersal, rather than range expansion, was the primary mechanism driving population recovery. Contrary to our prediction, neither landscape connectivity nor measured local habitat attributes influenced colonization rates, likely due to the high dispersal capability of raccoons and limited role of range expansion in patch colonization. Although culling is commonly used to control local populations of many mesopredators, we demonstrate that such practices create severe disruptions in population demography that may be counterproductive to disease management in fragmented landscapes due to an influx of dispersing males into depopulated areas. However, given the slow repopulation rates observed in our study, localized depopulation may be effective at reducing negative ecological impacts of mesopredators in fragmented landscapes at limited spatial and temporal scales.

Beasley, James C.; Olson, Zachary H.; Beatty, William S.; Dharmarajan, Guha; Rhodes, Olin E.

2013-01-01

84

Progress in predictive management of deer populations in British woodlands

Research into the population ecology of red (Cervus elaphus) and roe (Capreolus capreolus) deer in woodland habitats in Great Britain over the last 25 years has led to the development of a predictive approach to woodland deer management.The results of the research are summarised and examples of the wide variation in population density, fertility and survival between and within red,

Brenda A. Mayle

1996-01-01

85

Prediction with measurement errors in finite populations

We address the problem of selecting the best linear unbiased predictor (BLUP) of the latent value (e.g., serum glucose fasting level) of sample subjects with heteroskedastic measurement errors. Using a simple example, we compare the usual mixed model BLUP to a similar predictor based on a mixed model framed in a finite population (FPMM) setup with two sources of variability, the first of which corresponds to simple random sampling and the second, to heteroskedastic measurement errors. Under this last approach, we show that when measurement errors are subject-specific, the BLUP shrinkage constants are based on a pooled measurement error variance as opposed to the individual ones generally considered for the usual mixed model BLUP. In contrast, when the heteroskedastic measurement errors are measurement condition-specific, the FPMM BLUP involves different shrinkage constants. We also show that in this setup, when measurement errors are subject-specific, the usual mixed model predictor is biased but has a smaller mean squared error than the FPMM BLUP which point to some difficulties in the interpretation of such predictors.

Singer, Julio M; Stanek, Edward J; Lencina, Viviana B; Gonzalez, Luz Mery; Li, Wenjun; Martino, Silvina San

2011-01-01

86

Assessing tiger population dynamics using photographic capture-recapture sampling

Although wide-ranging, elusive, large carnivore species, such as the tiger, are of scientific and conservation interest, rigorous inferences about their population dynamics are scarce because of methodological problems of sampling populations at the required spatial and temporal scales. We report the application of a rigorous, noninvasive method for assessing tiger population dynamics to test model-based predictions about population viability. We obtained photographic capture histories for 74 individual tigers during a nine-year study involving 5725 trap-nights of effort. These data were modeled under a likelihood-based, ?robust design? capture?recapture analytic framework. We explicitly modeled and estimated ecological parameters such as time-specific abundance, density, survival, recruitment, temporary emigration, and transience, using models that incorporated effects of factors such as individual heterogeneity, trap-response, and time on probabilities of photo-capturing tigers. The model estimated a random temporary emigration parameter of =K' =Y' 0.10 ? 0.069 (values are estimated mean ? SE). When scaled to an annual basis, tiger survival rates were estimated at S = 0.77 ? 0.051, and the estimated probability that a newly caught animal was a transient was = 0.18 ? 0.11. During the period when the sampled area was of constant size, the estimated population size Nt varied from 17 ? 1.7 to 31 ? 2.1 tigers, with a geometric mean rate of annual population change estimated as = 1.03 ? 0.020, representing a 3% annual increase. The estimated recruitment of new animals, Bt, varied from 0 ? 3.0 to 14 ? 2.9 tigers. Population density estimates, D, ranged from 7.33 ? 0.8 tigers/100 km2 to 21.73 ? 1.7 tigers/100 km2 during the study. Thus, despite substantial annual losses and temporal variation in recruitment, the tiger density remained at relatively high levels in Nagarahole. Our results are consistent with the hypothesis that protected wild tiger populations can remain healthy despite heavy mortalities because of their inherently high reproductive potential. The ability to model the entire photographic capture history data set and incorporate reduced-parameter models led to estimates of mean annual population change that were sufficiently precise to be useful. This efficient, noninvasive sampling approach can be used to rigorously investigate the population dynamics of tigers and other elusive, rare, wide-ranging animal species in which individuals can be identified from photographs or other means.

Karanth, K. U.; Nichols, J.D.; Kumar, N.S.; Hines, J.E.

2006-01-01

87

Dynamic analysis of a parasite population model

NASA Astrophysics Data System (ADS)

We study the dynamics of a model that describes the competitive interaction between an invading species (a parasite) and its antibodies in an living being. This model was recently used to examine the dynamical competition between Tripanosoma cruzi and its antibodies during the acute phase of Chagas' disease. Depending on the antibody properties, the model yields three types of outcomes, corresponding, respectively, to healing, chronic disease, and host death. Here, we study the dynamics of the parasite-antibody interaction with the help of simulations, obtaining phase trajectories and phase diagrams for the system. We show that, under certain conditions, the size of the parasite inoculation can be crucial for the infection outcome and that a retardation in the stimulated production of an antibody species may result in the parasite gaining a definitive advantage. We also find a criterion for the relative sizes of the parameters that are required if parasite-generated decoys are indeed to help the invasion. Decoys may also induce a qualitatively different outcome: a limit cycle for the antibody-parasite population phase trajectories.

Sibona, G. J.; Condat, C. A.

2002-03-01

88

Improvement of dynamic response prediction of helicopters

Purpose – This paper aims to focus on mathematical model development issues, necessary for a better prediction of dynamic responses of articulated rotor helicopters. Design\\/methodology\\/approach – The methodology is laid out based on model development for an articulated main rotor, using the theories of aeroelastisity, finite element and state-space represented indicial-based unsteady aerodynamics. The model is represented by a set

Farid Shahmiri; Fariborz Saghafi

2007-01-01

89

Predicting the future impact of droughts on ungulate populations in arid and semi-arid environments.

Droughts can have a severe impact on the dynamics of animal populations, particularly in semi-arid and arid environments where herbivore populations are strongly limited by resource availability. Increased drought intensity under projected climate change scenarios can be expected to reduce the viability of such populations, yet this impact has seldom been quantified. In this study, we aim to fill this gap and assess how the predicted worsening of droughts over the 21(st) century is likely to impact the population dynamics of twelve ungulate species occurring in arid and semi-arid habitats. Our results provide support to the hypotheses that more sedentary, grazing and mixed feeding species will be put at high risk from future increases in drought intensity, suggesting that management intervention under these conditions should be targeted towards species possessing these traits. Predictive population models for all sedentary, grazing or mixed feeding species in our study show that their probability of extinction dramatically increases under future emissions scenarios, and that this extinction risk is greater for smaller populations than larger ones. Our study highlights the importance of quantifying the current and future impacts of increasing extreme natural events on populations and species in order to improve our ability to mitigate predicted biodiversity loss under climate change. PMID:23284700

Duncan, Clare; Chauvenet, Aliénor L M; McRae, Louise M; Pettorelli, Nathalie

2012-01-01

90

Prediction and Control in a Dynamic Environment

The present study compared the accuracy of cue-outcome knowledge gained during prediction-based and control-based learning in stable and unstable dynamic environments. Participants either learnt to make cue-interventions in order to control an outcome, or learnt to predict the outcome from observing changes to the cue values. Study 1 (N?=?60) revealed that in tests of control, after a short period of familiarization, performance of Predictors was equivalent to Controllers. Study 2 (N?=?28) showed that Controllers showed equivalent task knowledge when to compared to Predictors. Though both Controllers and Predictors showed good performance at test, overall Controllers showed an advantage. The cue-outcome knowledge acquired during learning was sufficiently flexible to enable successful transfer to tests of control and prediction.

Osman, Magda; Speekenbrink, Maarten

2011-01-01

91

Predicting the dynamics of protein abundance.

Protein synthesis is finely regulated across all organisms, from bacteria to humans, and its integrity underpins many important processes. Emerging evidence suggests that the dynamic range of protein abundance is greater than that observed at the transcript level. Technological breakthroughs now mean that sequencing-based measurement of mRNA levels is routine, but protocols for measuring protein abundance remain both complex and expensive. This paper introduces a Bayesian network that integrates transcriptomic and proteomic data to predict protein abundance and to model the effects of its determinants. We aim to use this model to follow a molecular response over time, from condition-specific data, in order to understand adaptation during processes such as the cell cycle. With microarray data now available for many conditions, the general utility of a protein abundance predictor is broad. Whereas most quantitative proteomics studies have focused on higher organisms, we developed a predictive model of protein abundance for both Saccharomyces cerevisiae and Schizosaccharomyces pombe to explore the latitude at the protein level. Our predictor primarily relies on mRNA level, mRNA-protein interaction, mRNA folding energy and half-life, and tRNA adaptation. The combination of key features, allowing for the low certainty and uneven coverage of experimental observations, gives comparatively minor but robust prediction accuracy. The model substantially improved the analysis of protein regulation during the cell cycle: predicted protein abundance identified twice as many cell-cycle-associated proteins as experimental mRNA levels. Predicted protein abundance was more dynamic than observed mRNA expression, agreeing with experimental protein abundance from a human cell line. We illustrate how the same model can be used to predict the folding energy of mRNA when protein abundance is available, lending credence to the emerging view that mRNA folding affects translation efficiency. The software and data used in this research are available at http://bioinf.scmb.uq.edu.au/proteinabundance/. PMID:24532840

Mehdi, Ahmed M; Patrick, Ralph; Bailey, Timothy L; Bodén, Mikael

2014-05-01

92

Modeling Daphnia population dynamics and demography under natural conditions

Various approaches to modeling the population dynamics and demography of Daphnia have been published. These methods range from the simple egg-ratio method, to mathematically complex models based on partial differential equations and numerically complex individual-based Daphnia population models. The usefulness of these models in unraveling the population dynamics and demography of Daphnia under natural conditions is discussed. Next to this,

W. M. Mooij; S. Hülsmann; J. Vijverberg; A. Veen; E. H. R. R. Lammens

2003-01-01

93

Biotic Population Dynamics: Creative Biotic Patterns

NASA Astrophysics Data System (ADS)

We present empirical studies and computer models of population dynamics that demonstrate creative features and we speculate that these creative processes may underline evolution. Changes in population size of lynx, muskrat, beaver, salmon, and fox display diversification, episodic changes in pattern, novelty, and evidence for nonrandom causation. These features of creativity characterize bios, and rule out random, periodic, chaotic, and random walk patterns. Biotic patterns are also demonstrated in time series generated with multi-agent predator-prey simulations. These results indicate that evolutionary processes are continually operating. In contrast to standard evolutionary theory (random variation, competition for scarce resources, selection by survival of the fittest, and directionless, meaningless evolution), we propose that biological evolution is a creative development from simple to complex in which (1) causal actions generate biological variation; (2) bipolar feedback (synergy and antagonism, abundance and scarcity) generates information (diversification, novelty and complexity); (3) connections (of molecules, genes, species) construct systems in which simple processes have priority for survival but complex processes acquire supremacy.

Sabelli, Hector; Kovacevic, Lazar

94

Space and stochasticity in population dynamics

Organisms interact with each other mostly over local scales, so the local density experienced by an individual is of greater importance than the mean density in a population. This simple observation poses a tremendous challenge to theoretical ecology, and because nonlinear stochastic and spatial models cannot be solved exactly, much effort has been spent in seeking effective approximations. Several authors have observed that spatial population systems behave like deterministic nonspatial systems if dispersal averages the dynamics over a sufficiently large scale. We exploit this fact to develop an exact series expansion, which allows one to derive approximations of stochastic individual-based models without resorting to heuristic assumptions. Our approach makes it possible to calculate the corrections to mean-field models in the limit where the interaction range is large, and it provides insight into the performance of moment closure methods. With this approach, we demonstrate how the buildup of spatiotemporal correlations slows down the spread of an invasion, prolongs time lags associated with extinction debt, and leads to locally oscillating but globally stable coexistence of a host and a parasite.

Ovaskainen, Otso; Cornell, Stephen J.

2006-01-01

95

Population dynamics at digester overload conditions.

Two different case studies concerning potential overload situations of anaerobic digesters were investigated and mathematically modelled by means of the Anaerobic Digestion Model No. 1 (ADM1). The first scenario included a digester failure at a municipal WWTP which occurred during revision works of the upstream digester within a two-step digestion system when the sludge was directly by-passed to the 2nd-step reactor. Secondly, the non-occurrence of a highly expected upset situation in a lab-scale digester fed with cattle manure was investigated. ADM1 was utilized to derive indicators which were used to investigate the relationship between digester stability and biomass population dynamics. Conventional design parameters such as the organic loading rate appeared unsuitable for process description under dynamic conditions. Indicators reflecting the biokinetic state (e.g. F(net)/M(net) or the VFA/alkalinity ratio) are more adequate for the assessment of the stability of reactors in transient situations. PMID:19586768

Schoen, Michael A; Sperl, Daniel; Gadermaier, Maria; Goberna, Marta; Franke-Whittle, Ingrid; Insam, Heribert; Ablinger, Josef; Wett, Bernhard

2009-12-01

96

Background Skeeter Buster is a stochastic, spatially explicit simulation model of Aedes aegypti populations, designed to predict the outcome of vector population control methods. In this study, we apply the model to two specific locations, the cities of Iquitos, Peru, and Buenos Aires, Argentina. These two sites differ in the amount of field data that is available for location-specific customization. By comparing output from Skeeter Buster to field observations in these two cases we evaluate population dynamics predictions by Skeeter Buster with varying degrees of customization. Methodology/Principal Findings Skeeter Buster was customized to the Iquitos location by simulating the layout of houses and the associated distribution of water-holding containers, based on extensive surveys of Ae. aegypti populations and larval habitats that have been conducted in Iquitos for over 10 years. The model is calibrated by adjusting the food input into various types of containers to match their observed pupal productivity in the field. We contrast the output of this customized model to the data collected from the natural population, comparing pupal numbers and spatial distribution of pupae in the population. Our results show that Skeeter Buster replicates specific population dynamics and spatial structure of Ae. aegypti in Iquitos. We then show how Skeeter Buster can be customized for Buenos Aires, where we only had Ae. aegypti abundance data that was averaged across all locations. In the Argentina case Skeeter Buster provides a satisfactory simulation of temporal population dynamics across seasons. Conclusions This model can provide a faithful description of Ae. aegypti populations, through a process of location-specific customization that is contingent on the amount of data available from field collections. We discuss limitations presented by some specific components of the model such as the description of food dynamics and challenges that these limitations bring to model evaluation.

Legros, Mathieu; Magori, Krisztian; Morrison, Amy C.; Xu, Chonggang; Scott, Thomas W.; Lloyd, Alun L.; Gould, Fred

2011-01-01

97

Extreme Events: Dynamics, Statistics and Prediction

NASA Astrophysics Data System (ADS)

In this talk, I will review some recent work on extreme events, their causes and consequences. The review covers theoretical aspects of time series analysis and of extreme value theory, as well as of the deterministic modeling of extreme events, via continuous and discrete dynamic models. The applications include climatic, seismic and socio-economic events, along with their prediction. Two important results refer to (i) the complementarity of spectral analysis of a time series in terms of the continuous and the discrete part of its power spectrum; and (ii) the need for coupled modeling of natural and socio-economic systems. Both these results have implications for the study and prediction of natural hazards and their human impacts. US GDP data used in validating the vulnerability paradox found in a Non-Equilibrium Dynamical Model (NEDyM) for studying the impact of extreme events on a dynamic economy. The paradoxical result is that natural hazards affect more strongly an economy in expansion than when it is in a recession. The connection to the macroeconomic data is given by fluctuation-dissipation theory.

Ghil, M.

2013-05-01

98

Lattice dynamics of andalusite: Prediction and experiment

NASA Astrophysics Data System (ADS)

Static energy minimization calculations have been used to obtain a relaxed structure of andalusite using a core-shell model with a set of transferable potential parameters. Subsequent lattice dynamics calculations have been used to calculate the eigenvalues and the eigenvectors of the dynamical matrix. The results of these calculations are compared with experimental data obtained by inelastic neutron scattering experiments and powder FTIR spectroscopy and previously published single crystal infrared and Raman data. The agreement of the calculated with observed phonon frequencies at the ? point is satisfactory. The TO-LO splitting is modelled reasonably well. Coherent inelastic neutron scattering measurements have been made along one high symmetry direction up to energy transfers of 230 cm-1. The model predicts phonon dispersion curves which are in good qualitative agreement with experimental data, but the calculated frequencies are consistently too low by about 10 15%. Macroscopic thermodynamic properties were calculated from the phonon density of states. The calculated specific heat is in excellent agreement with previously published data. The transferable potential parameters in the predictive model used in the present study give, within certain limitations, a realistic description of the static and dynamic aspects of the andalusite structure.

Winkler, B.; Buehrer, W.

1990-12-01

99

Demographic Characteristics and Population Dynamical Patterns of Solitary Birds

In birds and many other animals, there are large interspecific differences in the magnitude of annual variation in population size. Using time-series data on populations of solitary bird species, we found that fluctuations in population size of solitary birds were affected by the deterministic characteristics of the population dynamics as well as the stochastic factors. In species with highly variable

Bernt-Erik Sæther; Steinar Engen; Erik Matthysen

2002-01-01

100

Predictive Coding of Dynamical Variables in Balanced Spiking Networks

Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated.

Boerlin, Martin; Machens, Christian K.; Deneve, Sophie

2013-01-01

101

Prospects for Dynamical Prediction of Meteorological Drought

NASA Astrophysics Data System (ADS)

The prospects for U.S. seasonal drought prediction are assessed by diagnosing simulation and hindcast skill of drought indicators for the period 1982-2008. The 6-month standardized precipitation index (SPI6) is used as the primary predictand for drought. The skill of unconditioned drought forecasts, reflecting the statistical persistence of the drought indicator alone, serves as the baseline against which the performance of dynamical methods are evaluated . Predictions that are conditioned on the state of global sea surface temperatures (SST) are assessed using atmospheric climate simulations conducted in so-called AMIP mode in which observed SSTs are specified. Predictions that are conditioned on the initial states of global ocean, atmosphere, and land surfaces are next analyzed using the NOAA Climate Forecast System (CFS). The results indicate that the inherent persistence of the drought indicator (SPI6), yields considerable seasonal skill, and there is critical prognostic information linked to how drought likelihoods relate to a region's annual cycle of precipitation. Dynamical models forced by the particular conditions of the observed global SSTs yield increased skill relative to this unconditional baseline skill, though improvements are principally realized in winter and are geographically confined to the southern U.S. where drought probabilities are sensitive to the phases of the El Niño Southern Oscillation. Fully coupled initialized model hindcasts are shown to yield little additional skill in seasonal drought predictions compared to AMIP simulations during winter, apparently due to the preponderance of the ENSO skill source. However, we show that initialized models appreciably improve on the AMIP skill alone during the spring and summer, presumably due to the increased importance of land surface feedbacks, the environment for which are initialized in the CFS.

Quan, X.; Hoerling, M. P.; Lyon, B.; Kumar, A.; Bell, M. A.; Tippett, M.; Wang, H.

2011-12-01

102

The route to extinction: population dynamics of a threatened butterfly

We compare results of field study and model analysis of two butterfly populations to evaluate the importance of alternative mechanisms causing changes in abundance. Although understanding and predicting population fluctuations is a central goal of population ecology, it is not often achieved because long-term abundance data are available for few populations in which mechanisms causing fluctuations also are known. Both

John F. McLaughlin; Jessica J. Hellmann; Carol L. Boggs; Paul R. Ehrlich

2002-01-01

103

Dynamics of Genome Rearrangement in Bacterial Populations

Genome structure variation has profound impacts on phenotype in organisms ranging from microbes to humans, yet little is known about how natural selection acts on genome arrangement. Pathogenic bacteria such as Yersinia pestis, which causes bubonic and pneumonic plague, often exhibit a high degree of genomic rearrangement. The recent availability of several Yersinia genomes offers an unprecedented opportunity to study the evolution of genome structure and arrangement. We introduce a set of statistical methods to study patterns of rearrangement in circular chromosomes and apply them to the Yersinia. We constructed a multiple alignment of eight Yersinia genomes using Mauve software to identify 78 conserved segments that are internally free from genome rearrangement. Based on the alignment, we applied Bayesian statistical methods to infer the phylogenetic inversion history of Yersinia. The sampling of genome arrangement reconstructions contains seven parsimonious tree topologies, each having different histories of 79 inversions. Topologies with a greater number of inversions also exist, but were sampled less frequently. The inversion phylogenies agree with results suggested by SNP patterns. We then analyzed reconstructed inversion histories to identify patterns of rearrangement. We confirm an over-representation of “symmetric inversions”—inversions with endpoints that are equally distant from the origin of chromosomal replication. Ancestral genome arrangements demonstrate moderate preference for replichore balance in Yersinia. We found that all inversions are shorter than expected under a neutral model, whereas inversions acting within a single replichore are much shorter than expected. We also found evidence for a canonical configuration of the origin and terminus of replication. Finally, breakpoint reuse analysis reveals that inversions with endpoints proximal to the origin of DNA replication are nearly three times more frequent. Our findings represent the first characterization of genome arrangement evolution in a bacterial population evolving outside laboratory conditions. Insight into the process of genomic rearrangement may further the understanding of pathogen population dynamics and selection on the architecture of circular bacterial chromosomes.

Darling, Aaron E.; Miklos, Istvan; Ragan, Mark A.

2008-01-01

104

Developments in the prediction of effective population size

Effective population size is a key parameter in evolutionary and quantitative genetics because it measures the rate of genetic drift and inbreeding. Predictive equations of effective size under a range of circumstances and some of their implications are reviewed in this paper. Derivations are made for the simplest cases, and the inter-relations between different formulae and methods are discussed.

Armando Caballero

1994-01-01

105

Effects of an invasive plant on population dynamics in toads.

When populations decline in response to unfavorable environmental change, the dynamics of their population growth shift. In populations that normally exhibit high levels of variation in recruitment and abundance, as do many amphibians, declines may be difficult to identify from natural fluctuations in abundance. However, the onset of declines may be evident from changes in population growth rate in sufficiently long time series of population data. With data from 23 years of study of a population of Fowler's toad (Anaxyrus [ = Bufo] fowleri) at Long Point, Ontario (1989-2011), we sought to identify such a shift in dynamics. We tested for trends in abundance to detect a change point in population dynamics and then tested among competing population models to identify associated intrinsic and extrinsic factors. The most informative models of population growth included terms for toad abundance and the extent of an invasive marsh plant, the common reed (Phragmites australis), throughout the toads' marshland breeding areas. Our results showed density-dependent growth in the toad population from 1989 through 2002. After 2002, however, we found progressive population decline in the toads associated with the spread of common reeds and consequent loss of toad breeding habitat. This resulted in reduced recruitment and population growth despite the lack of significant loss of adult habitat. Our results underscore the value of using long-term time series to identify shifts in population dynamics coincident with the advent of population decline. PMID:23692126

Greenberg, Daniel A; Green, David M

2013-10-01

106

Dynamics of epidemics outbreaks in heterogeneous populations

NASA Astrophysics Data System (ADS)

The dynamics of epidemic outbreaks have been investigated in recent years within two alternative theoretical paradigms. The key parameter of mean field type of models such as the SIR model is the basic reproduction number R0, the average number of secondary infections caused by one infected individual. Recently, scale free network models have received much attention as they account for the high variability in the number of social contacts involved. These models predict an infinite basic reproduction number in some cases. We investigate the impact of heterogeneities of contact rates in a generic model for epidemic outbreaks. We present a system in which both the time periods of being infectious and the time periods between transmissions are Poissonian processes. The heterogeneities are introduced by means of strongly variable contact rates. In contrast to scale free network models we observe a finite basic reproduction number and, counterintuitively a smaller overall epidemic outbreak as compared to the homogeneous system. Our study thus reveals that heterogeneities in contact rates do not necessarily facilitate the spread to infectious disease but may well attenuate it.

Brockmann, Dirk; Morales-Gallardo, Alejandro; Geisel, Theo

2007-03-01

107

Experimental evidence of antiphase population dynamics in lasers

We report a direct experimental observation of antiphase oscillations in population dynamics in lasers. We show that these population oscillations are intrinsically related to the well-known antiphase polarization dynamics, i.e., the antiphase oscillations of two orthogonal polarization laser field states. We have used a class B Nd:YAG (yttrium aluminum garnet) laser.

Cabrera, Eduardo; Calderon, Oscar G.; Guerra, J.M. [Dpto. de Optica, Universidad Complutense de Madrid, Ciudad Universitaria s/n, 28040 Madrid (Spain)

2005-10-15

108

Monitoring coyote population dynamics by genotyping faeces

Reliable population estimates are necessary for effective conservation and management, and faecal genotyping has been used successfully to estimate the population size of several elusive mammalian species. Information such as changes in population size over time and survival rates, however, are often more useful for conservation biology than single popula- tion estimates. We evaluated the use of faecal genotyping as

L. R. P RUGH; C. E. R ITLAND; S. M. A RTHUR; C. J. KREBS

2005-01-01

109

Bias in genomic predictions for populations under selection.

Prediction of genetic merit or disease risk using genetic marker information is becoming a common practice for selection of livestock and plant species. For the successful application of genome-wide marker-assisted selection (GWMAS), genomic predictions should be accurate and unbiased. The effect of selection on bias and accuracy of genomic predictions was studied in two simulated animal populations under weak or strong selection and with several heritabilities. Prediction of genetic values was by best-linear unbiased prediction (BLUP) using data either from relatives summarized in pseudodata for genotyped individuals (multiple-step method) or using all available data jointly (single-step method). The single-step method combined genomic- and pedigree-based relationship matrices. Predictions by the multiple-step method were biased. Predictions by a single-step method were less biased and more accurate but under strong selection were less accurate. When genomic relationships were shifted by a constant, the single-step method was unbiased and the most accurate. The value of that constant, which adjusts for non-random selection of genotyped individuals, can be derived analytically. PMID:21767459

Vitezica, Z G; Aguilar, I; Misztal, I; Legarra, A

2011-10-01

110

Circuit theory predicts gene flow in plant and animal populations

Maintaining connectivity for broad-scale ecological processes like dispersal and gene flow is essential for conserving endangered species in fragmented landscapes. However, determining which habitats should be set aside to promote connectivity has been difficult because existing models cannot incorporate effects of multiple pathways linking populations. Here, we test an ecological connectivity model that overcomes this obstacle by borrowing from electrical circuit theory. The model vastly improves gene flow predictions because it simultaneously integrates all possible pathways connecting populations. When applied to data from threatened mammal and tree species, the model consistently outperformed conventional gene flow models, revealing that barriers were less important in structuring populations than previously thought. Circuit theory now provides the best-justified method to bridge landscape and genetic data, and holds much promise in ecology, evolution, and conservation planning.

McRae, Brad H.; Beier, Paul

2007-01-01

111

We present a population model to understand the effects of temperature and rainfall on the population dynamics of the southern house mosquito, Culex quinquefasciatus Say, along an elevational gradient in Hawaii. We use a novel approach to model the effects of temperature on population growth by dynamically incorporating developmental rate into the transition matrix, by using physiological ages of immatures instead of chronological age or stages. We also model the effects of rainfall on survival of immatures as the cumulative number of days below a certain rain threshold. Finally, we incorporate density dependence into the model as competition between immatures within breeding sites. Our model predicts the upper altitudinal distributions of Cx. quinquefasciatus on the Big Island of Hawaii for self-sustaining mosquito and migrating summer sink populations at 1,475 and 1,715 m above sea level, respectively. Our model predicts that mosquitoes at lower elevations can grow under a broader range of rainfall parameters than middle and high elevation populations. Density dependence in conjunction with the seasonal forcing imposed by temperature and rain creates cycles in the dynamics of the population that peak in the summer and early fall. The model provides a reasonable fit to the available data on mosquito abundance for the east side of Mauna Loa, Hawaii. The predictions of our model indicate the importance of abiotic conditions on mosquito dynamics and have important implications for the management of diseases transmitted by Cx. quinquefasciatus in Hawaii and elsewhere. PMID:15605655

Ahumada, Jorge A; Lapointe, Dennis; Samuel, Michael D

2004-11-01

112

Effects of weather and climate on the dynamics of animal population time series.

Weather is one of the most basic factors impacting animal populations, but the typical strength of such impacts on population dynamics is unknown. We incorporate weather and climate index data into analysis of 492 time series of mammals, birds and insects from the global population dynamics database. A conundrum is that a multitude of weather data may a priori be considered potentially important and hence present a risk of statistical over-fitting. We find that model selection or averaging alone could spuriously indicate that weather provides strong improvements to short-term population prediction accuracy. However, a block randomization test reveals that most improvements result from over-fitting. Weather and climate variables do, in general, improve predictions, but improvements were barely detectable despite the large number of datasets considered. Climate indices such as North Atlantic Oscillation are not better predictors of population change than local weather variables. Insect time series are typically less predictable than bird or mammal time series, although all taxonomic classes display low predictability. Our results are in line with the view that population dynamics is often too complex to allow resolving mechanisms from time series, but we argue that time series analysis can still be useful for estimating net environmental effects. PMID:20880886

Knape, Jonas; de Valpine, Perry

2011-04-01

113

Population Dynamics of Diploid and Hexaploid Populations of a Perennial Herb

Background and Aims Despite the recent enormous increase in the number of studies on polyploid species, no studies to date have explored the population dynamics of these taxa. It is thus not known whether the commonly reported differences in single life-history traits between taxa of different ploidy levels result in differences in population dynamics. Methods This study explores differences in single life-history traits and in the complete life cycle between populations of different ploidy levels and compares these differences with differences observed between different habitat types and years. Diploid and hexaploid populations of a perennial herb, Aster amellus, are used as the study system. Transition matrix models were used to describe the dynamics of the populations, and population growth rates, elasticity values and life-table response experiments were used to compare the dynamics between populations and years. Key Results The results indicate that between-year variation in population dynamics is much larger than variation between different ploidy levels and different habitat conditions. Significant differences exist, however, in the structure of the transition matrices, indicating that the dynamics of the different ploidy levels are different. Strong differences in probability of extinction of local populations were also found, with hexaploid populations having higher probability than diploid populations, indicating strong potential differences in persistence of these populations. Conclusions This is the first study on complete population dynamics of plants of different ploidy levels. This knowledge will help to understand the ability of new ploidy levels to spread into new areas and persist there, and the interactions of different ploidy levels in secondary contact zones. This knowledge will also contribute to understanding of interactions of different ploidy levels with other plant species or other interacting organisms such as pollinators or herbivores.

Munzbergova, Zuzana

2007-01-01

114

Modelling food and population dynamics in honey bee colonies.

Honey bees (Apis mellifera) are increasingly in demand as pollinators for various key agricultural food crops, but globally honey bee populations are in decline, and honey bee colony failure rates have increased. This scenario highlights a need to understand the conditions in which colonies flourish and in which colonies fail. To aid this investigation we present a compartment model of bee population dynamics to explore how food availability and bee death rates interact to determine colony growth and development. Our model uses simple differential equations to represent the transitions of eggs laid by the queen to brood, then hive bees and finally forager bees, and the process of social inhibition that regulates the rate at which hive bees begin to forage. We assume that food availability can influence both the number of brood successfully reared to adulthood and the rate at which bees transition from hive duties to foraging. The model predicts complex interactions between food availability and forager death rates in shaping colony fate. Low death rates and high food availability results in stable bee populations at equilibrium (with population size strongly determined by forager death rate) but consistently increasing food reserves. At higher death rates food stores in a colony settle at a finite equilibrium reflecting the balance of food collection and food use. When forager death rates exceed a critical threshold the colony fails but residual food remains. Our model presents a simple mathematical framework for exploring the interactions of food and forager mortality on colony fate, and provides the mathematical basis for more involved simulation models of hive performance. PMID:23667418

Khoury, David S; Barron, Andrew B; Myerscough, Mary R

2013-01-01

115

AIMS To assess the predictive value of a model-based approach for dose selection across paediatric populations in early clinical drug development. METHODS Abacavir was selected as a paradigm compound using data across a wide age range. Abacavir pharmacokinetics (PK) in children were analysed separately from infants and toddlers. Two independent models were obtained, and systemic exposure (AUC) was then simulated across populations based on the estimates from each model. Drug exposures in infants and toddlers were predicted using pharmacokinetic parameter distributions obtained from children, and the other way around. RESULTS The pharmacokinetic models (a two-compartment PK model for infants and toddlers and a one compartment PK model for children) accurately described the exposure in the population from which they were built. However, neither model predicted exposure in a different population: in infants, the median AUC (95%-CI) was estimated at 7.03 (6.72, 7.48) µg ml?1 h, whilst it was predicted at 5.75 (4.82, 6.26) µg ml?1 h; in children, the estimated median AUC was 6.96 (5.85, 7.91) µg ml?1 h, whilst the predicted value was 6.45 (5.80, 7.01) µg ml?1 h. CONCLUSIONS These findings suggest that the assumption of an identical (linear or nonlinear) correlation between pharmacokinetic parameters and demographic factors may not hold true across age groups. Whilst the use of modelling enables accurate characterization of pharmacokinetic properties, extrapolations based on such parameter estimates may have limited value due to differences in the impact of developmental growth across populations.

Cella, Massimo; Zhao, Wei; Jacqz-Aigrain, Evelyne; Burger, David; Danhof, Meindert; Pasqua, Oscar Della

2011-01-01

116

Modeling seasonal interactions in the population dynamics of migratory birds

Understanding the population dynamics of migratory birds requires understanding the relevant biological events that occur during breeding, migratory, and overwintering periods. The few available population models for passerine birds focus on breeding-season events, disregard or oversimplify events during nonbreeding periods, and ignore interactions that occur between periods of the annual cycle. Identifying and explicitly incorporating seasonal interactions into population models for migratory birds could provide important insights about when population limitation actually occurs in the annual cycle. We present a population model for the annual cycle of a migratory bird, based on the American Redstart (Setophaga ruticilla) but more generally applicable, that examines the importance of seasonal interactions by incorporating: (1) density dependence during the breeding and winter seasons, (2) a carry-over effect of winter habitat on breeding-season productivity, and (3) the effects of behavioral dominance on seasonal and habitat specific demographic rates. First, we show that habitat availability on both the wintering and breeding grounds can strongly affect equilibrium population size and sex ratio. Second, sex ratio dynamics, as mediated by behavioral dominance, can affect all other aspects of population dynamics. Third, carry-over effects can be strong, especially when winter events are limiting. These results suggest that understanding the population dynamics of migratory birds may require more consideration of the seasonal interactions induced by carry-over effects and density dependence in multiple seasons. This model provides a framework in which to explore more fully these seasonal dynamics and a context for estimation of life history parameters.

Runge, M.C.; Marra, P.P.

2005-01-01

117

Predictability of evolution depends nonmonotonically on population size

To gauge the relative importance of contingency and determinism in evolution is a fundamental problem that continues to motivate much theoretical and empirical research. In recent evolution experiments with microbes, this question has been explored by monitoring the repeatability of adaptive changes in replicate populations. Here, we present the results of an extensive computational study of evolutionary predictability based on an experimentally measured eight-locus fitness landscape for the filamentous fungus Aspergillus niger. To quantify predictability, we define entropy measures on observed mutational trajectories and endpoints. In contrast to the common expectation of increasingly deterministic evolution in large populations, we find that these entropies display an initial decrease and a subsequent increase with population size N, governed, respectively, by the scales N? and N?2, corresponding to the supply rates of single and double mutations, where ? denotes the mutation rate. The amplitude of this pattern is determined by ?. We show that these observations are generic by comparing our findings for the experimental fitness landscape to simulations on simple model landscapes.

Szendro, Ivan G.; Franke, Jasper; de Visser, J. Arjan G. M.; Krug, Joachim

2013-01-01

118

Applications of KAM theory to population dynamics.

Computer simulations have shown that several classes of population models, including the May host-parasitoid model and the Ginzburg-Taneyhill 'maternal-quality' single species population model, exhibit extremely complicated orbit structures. These structures include islands-around-islands, ad infinitum, with the smaller islands containing stable periodic points of higher period. We identify the mechanism that generates this complexity and we discuss some biological implications. PMID:22877229

Gidea, Marian; Meiss, James D; Ugarcovici, Ilie; Weiss, Howard

2011-01-01

119

Metal stresses affect the population dynamics of disease transmission in aquaculture species

The purpose of this study is to develop a mechanistic-based population dynamics of disease model to predict the effect of heavy-metal stresses on the susceptibility of the aquaculture species to pollution-associated infectious diseases. We link an ecologically based nonlinear epidemiological dynamics of host–parasite interactions with a deterministic susceptibility-infectious-mortality (SIM) model to evaluate the host susceptibility to the waterborne metal stressors.

Chung-Min Liao; Chao-Fang Chang; Ching-Hung Yeh; Szu-Chieh Chen; Kuo-Chin Chiang; Chia-Pin Chio; Berry Yun-Hua Chou; Li-John Jou; Guang-Wen Lien; Chieh-Ming Lin; Huan-Hsiang Shen; Guan-De Wu

2006-01-01

120

Predictive State Representations: A New Theory for Modeling Dynamical Systems

Modeling dynamical systems, both for con- trol purposes and to make predictions about their behavior, is ubiquitous in science and engineering. Predictive state representations (PSRs) are a recently introduced class of models for discrete-time dynamical systems. The key idea behind PSRs and the closely related OOMs (Jaeger's observable opera- tor models) is to represent the state of the system as

Satinder P. Singh; Michael R. James; Matthew R. Rudary

2004-01-01

121

Stage-Structured Population Dynamics of AEDES AEGYPTI

NASA Astrophysics Data System (ADS)

Aedes aegypti is the main vector in the transmission of dengue fever, a vector-borne disease affecting world population living in tropical and sub-tropical countries. Better understanding of the dynamics of its population growth will help in the efforts of controlling the spread of this disease. In looking at the population dynamics of Aedes aegypti, this paper explored the stage-structured modeling of the population growth of the mosquito using the matrix population model. The life cycle of the mosquito was divided into five stages: eggs, larvae, pupae, adult1 and adult2. Developmental rates were obtained for the average Malaysian temperature and these were used in constructing the transition matrix for the matrix model. The model, which was based only on temperature, projected that the population of Aedes aegypti will blow up with time, which is not realistic. For further work, other factors need to be taken into account to obtain a more realistic result.

Yusoff, Nuraini; Budin, Harun; Ismail, Salemah

122

AN INDIVIDUAL-BASED MODEL OF COTTUS POPULATION DYNAMICS

We explored population dynamics of a southern Appalachian population of Cottus bairdi using a spatially-explicit, individual-based model. The model follows daily growth, mortality, and spawning of individuals as a function of flow and temperature. We modeled movement of juveniles...

123

Applicability of the Fisher equation to bacterial population dynamics

The applicability of the Fisher equation, which combines diffusion with logistic nonlinearity, to population dynamics of bacterial colonies is studied with the help of explicit analytic solutions for the spatial distribution of a stationary bacterial population under a static mask. The mask protects bacteria from ultraviolet light. The solution, which is in terms of Jacobian elliptic functions, is used to

V. M. Kenkre; M. N. Kuperman

2003-01-01

124

Transoceanic Migration, Spatial Dynamics, and Population Linkages of White Sharks

The large-scale spatial dynamics and population structure of marine top predators are poorly known. We present electronic tag and photographic identification data showing a complex suite of behavioral patterns in white sharks. These include coastal return migrations and the fastest known transoceanic return migration among swimming fauna, which provide direct evidence of a link between widely separated populations in South

Ramón Bonfil; Michael Meÿer; Michael C. Scholl; Ryan Johnson; Shannon O'Brien; Herman Oosthuizen; Stephan Swanson; Deon Kotze; Michael Paterson

2005-01-01

125

How life history influences population dynamics in fluctuating environments.

A major question in ecology is how age-specific variation in demographic parameters influences population dynamics. Based on long-term studies of growing populations of birds and mammals, we analyze population dynamics by using fluctuations in the total reproductive value of the population. This enables us to account for random fluctuations in age distribution. The influence of demographic and environmental stochasticity on the population dynamics of a species decreased with generation time. Variation in age-specific contributions to total reproductive value and to stochastic components of population dynamics was correlated with the position of the species along the slow-fast continuum of life-history variation. Younger age classes relative to the generation time accounted for larger contributions to the total reproductive value and to demographic stochasticity in "slow" than in "fast" species, in which many age classes contributed more equally. In contrast, fluctuations in population growth rate attributable to stochastic environmental variation involved a larger proportion of all age classes independent of life history. Thus, changes in population growth rates can be surprisingly well explained by basic species-specific life-history characteristics. PMID:24231536

Saether, Bernt-Erik; Coulson, Tim; Grøtan, Vidar; Engen, Steinar; Altwegg, Res; Armitage, Kenneth B; Barbraud, Christophe; Becker, Peter H; Blumstein, Daniel T; Dobson, F Stephen; Festa-Bianchet, Marco; Gaillard, Jean-Michel; Jenkins, Andrew; Jones, Carl; Nicoll, Malcolm A C; Norris, Ken; Oli, Madan K; Ozgul, Arpat; Weimerskirch, Henri

2013-12-01

126

Population dynamics of HIV-1 inferred from gene sequences.

A method for the estimation of population dynamic history from sequence data is described and used to investigate the past population dynamics of HIV-1 subtypes A and B. Using both gag and env gene alignments the effective population size of each subtype is estimated and found to be surprisingly small. This may be a result of the selective sweep of mutations through the population, or may indicate an important role of genetic drift in the fixation of mutations. The implications of these results for the spread of drug-resistant mutations and transmission dynamics, and also the roles of selection and recombination in shaping HIV-1 genetic diversity, are discussed. A larger estimated effective population size for subtype A may be the result of differences in time of origin, transmission dynamics, and/or population structure. To investigate the importance of population structure a model of population subdivision was fitted to each subtype, although the improvement in likelihood was found to be nonsignificant.

Grassly, N C; Harvey, P H; Holmes, E C

1999-01-01

127

Population dynamic consequences of competition within and between age classes

We investigate the population dynamics of a semivoltine species whose juvenile development takes two years to complete, and is followed by a very short reproductive adult stage. Reproduction is synchronized so at any given time the juvenile population consists of two cohorts. Coexistence of the two cohorts requires that the strength of intea-cohort competition exceeds that of inter-cohort competition, an

R. M. Nisbet; L. C. Onyiah

1994-01-01

128

Atlantic bluefin tuna: population dynamics, ecology, fisheries and management

Both old and new information on the biology and ecology of Atlantic bluefin tuna have confronted scientists with research challenges: research needs to be connected to current stock-assessment and management issues. We review recent studies on habitat, migrations and population structure, stressing the importance of electronic tagging results in the modification of our perception of bluefin tuna population dynamics and

Jean-Marc Fromentin; Joseph E Powers

2005-01-01

129

A Particle Population Control Method for Dynamic Monte Carlo

NASA Astrophysics Data System (ADS)

A general particle population control method has been derived from splitting and Russian Roulette for dynamic Monte Carlo particle transport. A well-known particle population control method, known as the particle population comb, has been shown to be a special case of this general method. This general method has been incorporated in Los Alamos National Laboratory's Monte Carlo Application Toolkit (MCATK) and examples of it's use are shown for both super-critical and sub-critical systems.

Sweezy, Jeremy; Nolen, Steve; Adams, Terry; Zukaitis, Anthony

2014-06-01

130

Landscape connectivity and predator–prey population dynamics

Landscapes are increasingly fragmented, and conservation programs have started to look at network approaches for maintaining\\u000a populations at a larger scale. We present an agent-based model of predator–prey dynamics where the agents (i.e. the individuals\\u000a of either the predator or prey population) are able to move between different patches in a landscaped network. We then analyze\\u000a population level and coexistence

Jacopo A. Baggio; Kehinde Salau; Marco A. Janssen; Michael L. Schoon; Örjan Bodin

2011-01-01

131

Persistence of populations at range edges relies on local population dynamics and fitness, in the case of geographically isolated populations of species with low dispersal potential. Focusing on spatial variations in demography helps to predict the long-term capability for persistence of populations across the geographical range of species' distribution. The demography of two ecological and phylogenetically close macroalgal species with different life history characteristics was investigated by using stochastic, stage-based matrix models. Populations of Ascophyllum nodosum and Fucus serratus were sampled for up to 4 years at central locations in France and at their southern range limits in Portugal. The stochastic population growth rate (?(s)) of A. nodosum was lower and more variable in central than in southern sites whilst for F. serratus this trend was reversed with ?(s) much lower and more variable in southern than in central populations. Individuals were larger in central than in southern populations for both species, which was reflected in the lower transition probabilities of individuals to larger size classes and higher probability of shrinkage in the southern populations. In both central and southern populations elasticity analysis (proportional sensitivity) of population growth rate showed that fertility elements had a small contribution to ?(s) that was more sensitive to changes in matrix transitions corresponding to survival. The highest elasticities were found for loop transitions in A. nodosum and for growth to larger size classes in F. serratus. Sensitivity analysis showed high selective pressure on individual growth for both species at both locations. The results of this study highlight the deterministic role of species-specific life-history traits in population demography across the geographical range of species. Additionally, this study demonstrates that individuals' life-transitions differ in vulnerability to environmental variability and shows the importance of vegetative compared to reproductive stages for the long-term persistence of populations. PMID:24651480

Araújo, Rita M; Serrão, Ester A; Sousa-Pinto, Isabel; Åberg, Per

2014-01-01

132

The evolutionary spread of cheater strategies can destabilize populations engaging in social cooperative behaviors, thus demonstrating that evolutionary changes can have profound implications for population dynamics. At the same time, the relative fitness of cooperative traits often depends upon population density, thus leading to the potential for bi-directional coupling between population density and the evolution of a cooperative trait. Despite the potential importance of these eco-evolutionary feedback loops in social species, they have not yet been demonstrated experimentally and their ecological implications are poorly understood. Here, we demonstrate the presence of a strong feedback loop between population dynamics and the evolutionary dynamics of a social microbial gene, SUC2, in laboratory yeast populations whose cooperative growth is mediated by the SUC2 gene. We directly visualize eco-evolutionary trajectories of hundreds of populations over 50–100 generations, allowing us to characterize the phase space describing the interplay of evolution and ecology in this system. Small populations collapse despite continual evolution towards increased cooperative allele frequencies; large populations with a sufficient number of cooperators “spiral” to a stable state of coexistence between cooperator and cheater strategies. The presence of cheaters does not significantly affect the equilibrium population density, but it does reduce the resilience of the population as well as its ability to adapt to a rapidly deteriorating environment. Our results demonstrate the potential ecological importance of coupling between evolutionary dynamics and the population dynamics of cooperatively growing organisms, particularly in microbes. Our study suggests that this interaction may need to be considered in order to explain intraspecific variability in cooperative behaviors, and also that this feedback between evolution and ecology can critically affect the demographic fate of those species that rely on cooperation for their survival.

Sanchez, Alvaro; Gore, Jeff

2013-01-01

133

Most animal populations have distinct breeding and non-breeding periods, yet the implications of seasonality on population dynamics are not well understood. Here, we introduce an experimental model system to study the population dynamics of two important consequences of seasonality: sequential density dependence and carry-over effects (COEs). Using a replicated seasonal population of Drosophila, we placed individuals at four densities in the non-breeding season and then, among those that survived, placed them to breed at three different densities. We show that COEs arising from variation in non-breeding density negatively impacts individual performance by reducing per capita breeding output by 29–77%, implying that non-lethal COEs can have a strong influence on population abundance. We then parametrized a bi-seasonal population model from the experimental results, and show that both sequential density dependence and COEs can stabilize long-term population dynamics and that COEs can reduce population size at low intrinsic rates of growth. Our results have important implications for predicting the successful colonization of new habitats, and for understanding the long-term persistence of seasonal populations in a wide range of taxa, including migratory organisms.

Betini, Gustavo S.; Griswold, Cortland K.; Norris, D. Ryan

2013-01-01

134

Parametric dynamic load prediction of a narrow gauge rocket sled

Dynamic load prediction of rocket sleds has been of interest to sled designers and analysts since the inception of the Holloman High Speed Test Track, (HHSTT). Dynamic loading along with thrust and aerodynamic loading is a primary contributor to sled design load cases. Dynamic loading comes directly from the rocket sled traversing the gap between the slipper and rail and

John Scott Furlow

2006-01-01

135

The assumptions and rationales of a computer model of phytoplankton population dynamic?

Abstract Predictions,of phytoplankton,growth,dynamics,and,nutrient,assimilation,by,a computer simulation,model,are,consistent,with,studies,of,field,and,laboratory,populations.,The model,simulates,population,dynamics,and,gross,physiology,of phytoplankton,species,in the epilimnion of a lake where algal growth is subject to temperature, light, and nutrient constraints and includes luxury consumption, end-product inhibition of both carbon fixa- tion and nutrient uptake, and species-specific differential efficiencies of nutrient assimila- tion. C : P, C : N, and N : P ratios of the algal cells

John T. Lehman; E. Likens

136

Cytonuclear dynamics in selfing populations under selection

We develop a mathematical model to delimit the role of natural selection in maintaining nuclear and cytoplasmic polymorphisms in selfing populations. We provide explicit time?dependent solutions for joint cytonuclear frequencies under any combination of constant fertility, viability, and gametic selection and exact analytical conditions for the maintenance of polymorphisms under joint cytonuclear selection. The equilibrium structure is determined by the relative magnitude of echo fitnesses, defined as the rate at which individuals survive and produce offspring with their own genotype. Both nuclear and cytoplasmic polymorphisms can be maintained under biologically meaningful conditions, although the majority of the parameter combinations will lead to fixation. The theoretical framework developed here should be very useful in formally dissecting the form and strength of selection on cytonuclear genotypes in populations with negligible levels of outcrossing.

Liu, Renyi; Asmussen, Marjorie A.

2007-01-01

137

Predictive Control for Dynamic Resource Allocation in Enterprise Data Centers

It is challenging to reduce resource over-provisioning for enterprise applications while maintaining service level objectives (SLOs) due to their time-varying and stochastic workloads. In this paper, we study the effect of prediction on dynamic resource allocation to virtualized servers running enterprise applications. We present predictive controllers using three different prediction algorithms based on a standard auto- regressive (AR) model, a

Wei Xu; Xiaoyun Zhu; Sharad Singhal; Zhikui Wang

2006-01-01

138

Extinction Rate Fragility in Population Dynamics

NASA Astrophysics Data System (ADS)

We study population extinction due to fluctuations in a system of coupled populations and find the logarithm Q of the extinction rate. The formulation turns out to be substantially different from that for the seemingly similar and extensively studied problem of the rate of interstate switching in nonequilibrium systems. This difference quite generally leads to the extinction rate fragility, where a very small perturbation can change the extinction rate exponentially strongly [1]. Formally, it means that the limit of Q for the perturbation going to zero differs from the value of Q calculated in the absence of the perturbation. The fragility is related to the discontinuity of the quasistationary extinction current. A general condition for the onset of fragility is derived. We show that one of the best-known models of epidemiology, the susceptible-infectious-susceptible model, is fragile to total population fluctuations. The analysis [1]is extended to incorporate external noise. The analytical results are fully confirmed by simulations.[1] M. Khasin and M. I. Dykman, Phys. Rev. Lett. 103 , 068101 (2009)

Khasin, Michael; Dykman, Mark

2010-03-01

139

Evolutionary games and population dynamics: maintenance of cooperation in public goods games

The emergence and abundance of cooperation in nature poses a tenacious and challenging puzzle to evolutionary biology. Cooperative behaviour seems to contradict Darwinian evolution because altruistic individuals increase the fitness of other members of the population at a cost to themselves. Thus, in the absence of supporting mechanisms, cooperation should decrease and vanish, as predicted by classical models for cooperation in evolutionary game theory, such as the Prisoner's Dilemma and public goods games. Traditional approaches to studying the problem of cooperation assume constant population sizes and thus neglect the ecology of the interacting individuals. Here, we incorporate ecological dynamics into evolutionary games and reveal a new mechanism for maintaining cooperation. In public goods games, cooperation can gain a foothold if the population density depends on the average population payoff. Decreasing population densities, due to defection leading to small payoffs, results in smaller interaction group sizes in which cooperation can be favoured. This feedback between ecological dynamics and game dynamics can generate stable coexistence of cooperators and defectors in public goods games. However, this mechanism fails for pairwise Prisoner's Dilemma interactions and the population is driven to extinction. Our model represents natural extension of replicator dynamics to populations of varying densities.

Hauert, Christoph; Holmes, Miranda; Doebeli, Michael

2006-01-01

140

The dynamics of sex ratio evolution dynamics of global population parameters.

Classical formalizations of the Fisherian theory of sex ratio evolution are based on the assumption that the number of grand offspring of a female serves as a measure of fitness. However, the classical population genetics approach also considers the contribution of male individuals to gene proliferation. The difference between the predictions of phenotypic and genetic models is that the phenotypic approach describes the primary sex ratio of 0.5 as the ESS value, while genetic models describe the stable state of a population by a combination of the stable states of the male and female subpopulations. In this paper, we formulate an alternative model of sex ratio evolution that is focused on the dynamics and quantitative properties of this process and that combine a rigorous genetic approach with a game theoretic strategic analysis. In the new model, females are the strategic agents and males are the passive carriers on unexpressed genes. Fitness functions in the new model are derived with respect to a "fitness exchange" effect, i.e. the contribution of male individuals to female fitness and vice versa. This new model shows that the dynamics of this system are complex and consist of two phases. The first, rapid, phase converges the system to a stable manifold (termed the male subpopulation equilibrium-MSE) where the male subpopulation state is in equilibrium, conditional on the current state of the female subpopulation. Double phase dynamics occur when the population state is not compatible with the current strategic composition of the population (determined by the value of the primary sex ratio) which can be caused by ecological factors. The trajectory of convergence to the MSE can be very complicated and may contain a dramatic change in the primary sex ratio. Thus, the primary sex ratio of 0.5 is unstable for perturbations of gene frequencies among male carriers. Therefore, the new model supports predictions of genetic models that the evolutionary stability of the sex ratio should be characterized by a combination of a stable value of the primary sex ratio and the male subpopulation equilibrium. PMID:22683379

Argasinski, Krzysztof

2012-09-21

141

In recent years, uses of high-resolution population distribution databases are increasing steadily for environmental, socioeconomic, public health, and disaster-related research and operations. With the development of daytime population distribution, temporal resolution of such databases has been improved. However, the lack of incorporation of transitional population, namely business and leisure travelers, leaves a significant population unaccounted for within the critical infrastructure networks, such as at transportation hubs. This paper presents two general methodologies for estimating passenger populations in airport and cruise port terminals at a high temporal resolution which can be incorporated into existing population distribution models. The methodologies are geographically scalable and are based on, and demonstrate how, two different transportation hubs with disparate temporal population dynamics can be modeled utilizing publicly available databases including novel data sources of flight activity from the Internet which are updated in near-real time. The airport population estimation model shows great potential for rapid implementation for a large collection of airports on a national scale, and the results suggest reasonable accuracy in the estimated passenger traffic. By incorporating population dynamics at high temporal resolutions into population distribution models, we hope to improve the estimates of populations exposed to or at risk to disasters, thereby improving emergency planning and response, and leading to more informed policy decisions.

Jochem, Warren C [ORNL; Sims, Kelly M [ORNL; Bright, Eddie A [ORNL; Urban, Marie L [ORNL; Rose, Amy N [ORNL; Coleman, Phil R [ORNL; Bhaduri, Budhendra L [ORNL

2013-01-01

142

Complex Population Dynamics in Mussels Arising from Density-Linked Stochasticity

Population fluctuations are generally attributed to the deterministic consequences of strong non-linear interactions among organisms, or the effects of random stochastic environmental variation superimposed upon the deterministic skeleton describing population change. Analysis of the population dynamics of the mussel Mytilus californianus taken in 16 plots over 18-years found no evidence that these processes explained observed strong fluctuations. Instead, population fluctuations arose because environmental stochasticity varied with abundance, which we term density-linked stochasticity. This phenomenon arises from biologically relevant mechanisms: recruitment variation and transmission of disturbance among neighboring individuals. Density-linked stochasticity is probably present frequently in populations, as it arises naturally from several general ecological processes, including stage structure variation with density, ontogenetic niche shifts, and local transmission of stochastic perturbations. More thoroughly characterizing and interpreting deviations from the mean behavior of a system will lead to better ecological prediction and improved insight into the important processes affecting populations and ecosystems.

Wootton, J. Timothy; Forester, James D.

2013-01-01

143

A model of stem cell population dynamics: in silico analysis and in vivo validation.

The proper renewal and maintenance of tissues by stem cell populations is simultaneously influenced by anatomical constraints, cell proliferation dynamics and cell fate specification. However, their relative influence is difficult to examine in vivo. To address this difficulty we built, as a test case, a cell-centered state-based computational model of key behaviors that govern germline development in C. elegans, and used it to drive simulations of cell population dynamics under a variety of perturbations. Our analysis provided unexpected possible explanations for laboratory observations, including certain 'all-or-none' phenotypes and complex differentiation patterns. The simulations also offered insights into niche-association dynamics and the interplay between cell cycle and cell fate. Subsequent experiments validated several predictions generated by the simulations. Notably, we found that early cell cycle defects influence later maintenance of the progenitor cell population. This general modeling approach is potentially applicable to other stem cell systems. PMID:22147952

Setty, Yaki; Dalfó, Diana; Korta, Dorota Z; Hubbard, E Jane Albert; Kugler, Hillel

2012-01-01

144

A model of stem cell population dynamics: in silico analysis and in vivo validation

The proper renewal and maintenance of tissues by stem cell populations is simultaneously influenced by anatomical constraints, cell proliferation dynamics and cell fate specification. However, their relative influence is difficult to examine in vivo. To address this difficulty we built, as a test case, a cell-centered state-based computational model of key behaviors that govern germline development in C. elegans, and used it to drive simulations of cell population dynamics under a variety of perturbations. Our analysis provided unexpected possible explanations for laboratory observations, including certain ‘all-or-none’ phenotypes and complex differentiation patterns. The simulations also offered insights into niche-association dynamics and the interplay between cell cycle and cell fate. Subsequent experiments validated several predictions generated by the simulations. Notably, we found that early cell cycle defects influence later maintenance of the progenitor cell population. This general modeling approach is potentially applicable to other stem cell systems.

Setty, Yaki; Dalfo, Diana; Korta, Dorota Z.; Hubbard, E. Jane Albert; Kugler, Hillel

2012-01-01

145

A general method for modeling population dynamics and its applications.

Studying populations, be it a microbe colony or mankind, is important for understanding how complex systems evolve and exist. Such knowledge also often provides insights into evolution, history and different aspects of human life. By and large, populations' prosperity and decline is about transformation of certain resources into quantity and other characteristics of populations through growth, replication, expansion and acquisition of resources. We introduce a general model of population change, applicable to different types of populations, which interconnects numerous factors influencing population dynamics, such as nutrient influx and nutrient consumption, reproduction period, reproduction rate, etc. It is also possible to take into account specific growth features of individual organisms. We considered two recently discovered distinct growth scenarios: first, when organisms do not change their grown mass regardless of nutrients availability, and the second when organisms can reduce their grown mass by several times in a nutritionally poor environment. We found that nutrient supply and reproduction period are two major factors influencing the shape of population growth curves. There is also a difference in population dynamics between these two groups. Organisms belonging to the second group are significantly more adaptive to reduction of nutrients and far more resistant to extinction. Also, such organisms have substantially more frequent and lesser in amplitude fluctuations of population quantity for the same periodic nutrient supply (compared to the first group). Proposed model allows adequately describing virtually any possible growth scenario, including complex ones with periodic and irregular nutrient supply and other changing parameters, which present approaches cannot do. PMID:24057917

Shestopaloff, Yuri K

2013-12-01

146

NASA Astrophysics Data System (ADS)

We applied a hierarchical state space model to predict the abundance of Cx.pipiens (a West Nile Virus vector) in the Po River Delta Region, Northeastern Italy. The study area has large mosquito abundance, due to a favorable environment and climate as well as dense human population. Mosquito data were collected on a weekly basis at more than 20 sites from May to September in 2010 and 2011. Cx.pipiens was the dominant species in our samples, accounting for about 90% of the more than 300,000 total captures. The hydrological component of the model accounted for evapotranspiration, infiltration and deep percolation to infer, in a 0D context, the local dynamics of soil moisture as a direct exogenous forcing of mosquito dynamics. The population model had a Gompertz structure, which included exogenous meteorological forcings and delayed internal dynamics. The models were coupled within a hierarchical statistical structure to overcome the relatively short length of the samples by exploiting the large number of concurrent observations available. The results indicated that Cx.pipiens abundance had significant density dependence at 1 week lag, which approximately matched its development time from larvae to adult. Among the exogenous controls, temperature, daylight hours, and soil moisture explained most of the dynamics. Longer daylight hours and lower soil moisture values resulted in higher abundance. The negative correlation of soil moisture and mosquito population can be explained with the abundance of water in the region (e.g. due to irrigation) and the preference for eutrophic habitats by Cx.pipien. Variations among sites were explained by land use factors as represented by distance to the nearest rice field and NDVI values: the carrying capacity decreased with increased distance to the nearest rice filed, while the maximum growth rate was positively related with NDVI. The model shows a satisfactory performance in predicting (potentially one week in advance) mosquito abundance and particularly its peak timing and magnitude.

Jian, Y.; Silvestri, S.; Marani, M.; Saltarin, A.; Chillemi, G.

2012-12-01

147

Dynamical Interactions Between Human Populations and Landscapes in Barrier Island Environments

NASA Astrophysics Data System (ADS)

Although much research has focused on how humans affect landscapes or how landform processes affect humans, little attention has been paid to dynamical interactions between the two. Based on the hypothesis that landscape and human dynamics both self-organize into a temporal hierarchy of scale-separated behaviors, we model the evolution of a coupled human population and barrier island system. Barrier islands are represented as a series of alongshore nodes, with each node specifying the width, height, cross-shore position, and profile of the island and the beach width, dune position and dune height. These characteristics evolve according to rules governing sediment transport during acretionary phases, erosion from storms, dune growth and migration, tidal delta formation, overwash, inlet formation, alongshore sediment transport, and dune and backbarrier vegetation growth. At each of these nodes, human populations and their cultural accoutrements are represented by mean property value, fraction of land used for tourist accommodations and tourist population. The dynamics of these variables is determined by simulating the competition for economic resources amongst the local population and the desire of the tourist population for adequate recreational beaches. The human and barrier subsystems are coupled through beach replenishment and a dependence of tourist population on beach width. Model results fall into three general categories of dynamical behavior, as classified by the (linearized) time scale of recovery from perturbations for the uncoupled systems. When the time scale for barrier islands is much less than that of the human population, the long-time-scale evolution of the barrier island follows human dynamics. In the reverse case, the long-time-scale evolution of the human population follows barrier dynamics. When the time scales are similar, new long-time-scale, spatially varying behavior of the coupled system emerges. Implications for prediction and optimization strategies will be discussed.

McNamara, D. E.; Werner, B. T.

2003-12-01

148

Population Dynamics of Borrelia burgdorferi in Lyme Disease

Many chronic inflammatory diseases are known to be caused by persistent bacterial or viral infections. A well-studied example is the tick-borne infection by the gram-negative spirochaetes of the genus Borrelia in humans and other mammals, causing severe symptoms of chronic inflammation and subsequent tissue damage (Lyme Disease), particularly in large joints and the central nervous system, but also in the heart and other tissues of untreated patients. Although killed efficiently by human phagocytic cells in vitro, Borrelia exhibits a remarkably high infectivity in mice and men. In experimentally infected mice, the first immune response almost clears the infection. However, approximately 1 week post infection, the bacterial population recovers and reaches an even larger size before entering the chronic phase. We developed a mathematical model describing the bacterial growth and the immune response against Borrelia burgdorferi in the C3H mouse strain that has been established as an experimental model for Lyme disease. The peculiar dynamics of the infection exclude two possible mechanistic explanations for the regrowth of the almost cleared bacteria. Neither the hypothesis of bacterial dissemination to different tissues nor a limitation of phagocytic capacity were compatible with experiment. The mathematical model predicts that Borrelia recovers from the strong initial immune response by the regrowth of an immune-resistant sub-population of the bacteria. The chronic phase appears as an equilibration of bacterial growth and adaptive immunity. This result has major implications for the development of the chronic phase of Borrelia infections as well as on potential protective clinical interventions.

Binder, Sebastian C.; Telschow, Arndt; Meyer-Hermann, Michael

2012-01-01

149

Prediction of X-33 Engine Dynamic Environments

NASA Technical Reports Server (NTRS)

Rocket engines normally have two primary sources of dynamic excitation. The first source is the injector and the combustion chambers that generate wide band random vibration. The second source is the turbopumps, which produce lower levels of wide band random vibration as well as sinusoidal vibration at frequencies related to the rotating speed and multiples thereof. Additionally, the pressure fluctuations due to flow turbulence and acoustics represent secondary sources of excitation. During the development stage, in order to design/size the rocket engine components, the local dynamic environments as well as dynamic interface loads have to be defined.

Shi, John J.

1999-01-01

150

Accounting for Mating Pair Formation in Plasmid Population Dynamics

Plasmids are important vehicles for horizontal gene transfer and rapid adaptation in bacteria, including the spread of antibiotic resistance genes. Conjugative transfer of a plasmid from a plasmid-bearing to a plasmid-free bacterial cell requires contact and attachment of the cells followed by plasmid DNA transfer prior to detachment. We introduce a system of differential equations for plasmid transfer in well-mixed populations that accounts for attachment, DNA transfer, and detachment dynamics. These equations offer advantages over classical mass-action models that combine these three processes into a single “bulk” conjugation rate. By decomposing the process of plasmid transfer into its constituent parts, this new model provides a framework that facilitates meaningful comparisons of plasmid transfer rates in surface and liquid environments. The model also allows one to account for experimental and environmental effects such as mixing intensity. To test the adequacy of the model and further explore the effects of mixing on plasmid transfer, we performed batch culture experiments using three different plasmids and a range of different mixing intensities. The results show that plasmid transfer is optimized at low to moderate shaking speeds and that vigorous shaking negatively affects plasmid transfer. Using reasonable assumptions on attachment and detachment rates, the mathematical model predicts the same behavior.

Zhong, Xue; Krol, Jaroslaw E.; Top, Eva M.; Krone, Stephen M.

2009-01-01

151

Impact of transient climate change upon Grouse population dynamics in the Italian Alps

NASA Astrophysics Data System (ADS)

Understanding the effect of short to medium term weather condition, and of transient global warming upon wildlife species life history is essential to predict the demographic consequences therein, and possibly develop adaptation strategies, especially in game species, where hunting mortality may play an important role in population dynamics. We carried out a preliminary investigation of observed impact of weather variables upon population dynamics indexes of three alpine Grouse species (i.e. Rock Ptarmigan, Lagopus Mutus, Black Grouse, Tetrao Tetrix, Rock Partridge, Alectoris Graeca), nested within central Italian Alps, based upon 15 years (1995-2009) of available censuses data, provided by the Sondrio Province authority. We used a set of climate variables already highlighted within recent literature for carrying considerable bearing on Grouse population dynamics, including e.g. temperature at hatching time and during winter, snow cover at nesting, and precipitation during nursing period. We then developed models of Grouses' population dynamics by explicitly driving population change according to their dependence upon the significant weather variables and population density and we evaluated objective indexes to assess the so obtained predictive power. Eventually, we develop projection of future local climate, based upon locally derived trends, and upon projections from GCMs (A2 IPCC storyline) already validated for the area, to project forward in time (until 2100 or so) the significant climatic variables, which we then use to force population dynamics models of the target species. The projected patterns obtained through this exercise are discussed and compared against those expected under stationary climate conditions at present, and preliminary conclusions are drawn.

Pirovano, Andrea; Bocchiola, Daniele

2010-05-01

152

Cryptic Population Dynamics: Rapid Evolution Masks Trophic Interactions

Trophic relationships, such as those between predator and prey or between pathogen and host, are key interactions linking species in ecological food webs. The structure of these links and their strengths have major consequences for the dynamics and stability of food webs. The existence and strength of particular trophic links has often been assessed using observational data on changes in species abundance through time. Here we show that very strong links can be completely missed by these kinds of analyses when changes in population abundance are accompanied by contemporaneous rapid evolution in the prey or host species. Experimental observations, in rotifer-alga and phage-bacteria chemostats, show that the predator or pathogen can exhibit large-amplitude cycles while the abundance of the prey or host remains essentially constant. We know that the species are tightly linked in these experimental microcosms, but without this knowledge, we would infer from observed patterns in abundance that the species are weakly or not at all linked. Mathematical modeling shows that this kind of cryptic dynamics occurs when there is rapid prey or host evolution for traits conferring defense against attack, and the cost of defense (in terms of tradeoffs with other fitness components) is low. Several predictions of the theory that we developed to explain the rotifer-alga experiments are confirmed in the phage-bacteria experiments, where bacterial evolution could be tracked. Modeling suggests that rapid evolution may also confound experimental approaches to measuring interaction strength, but it identifies certain experimental designs as being more robust against potential confounding by rapid evolution.

Yoshida, Takehito; Ellner, Stephen P; Jones, Laura E; Bohannan, Brendan J. M; Lenski, Richard E; Hairston, Nelson G

2007-01-01

153

Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (??s) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on ?? s. The magnitude of variation in the proportion of gravid females and its effect on ??s was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on ??s was 4- 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life-history traits in the two ecotypes, which, in turn, affect population dynamics. M-slow populations have evolved life-history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long-term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life-history evolution. ?? 2011 by the Ecological Society of America.

Miller, D. A.; Clark, W. R.; Arnold, S. J.; Bronikowski, A. M.

2011-01-01

154

Real-Time Bioluminescent Tracking of Cellular Population Dynamics

Cellular population dynamics are routinely monitored across many diverse fields for a variety of purposes. In general, these dynamics are assayed either through the direct counting of cellular aliquots followed by extrapolation to the total population size, or through the monitoring of signal intensity from any number of externally stimulated reporter proteins. While both viable methods, here we describe a novel technique that allows for the automated, non-destructive tracking of cellular population dynamics in real-time. This method, which relies on the detection of a continuous bioluminescent signal produced through expression of the bacterial luciferase gene cassette, provides a low cost, low time-intensive means for generating additional data compared to alternative methods.

Close, Dan [University of Tennessee, Knoxville (UTK)] [University of Tennessee, Knoxville (UTK); Sayler, Gary Steven [ORNL] [ORNL; Xu, Tingting [ORNL] [ORNL; Ripp, Steven Anthony [ORNL] [ORNL

2014-01-01

155

Stochastic Population Dynamics of a Montane Ground-Dwelling Squirrel

Understanding the causes and consequences of population fluctuations is a central goal of ecology. We used demographic data from a long-term (1990–2008) study and matrix population models to investigate factors and processes influencing the dynamics and persistence of a golden-mantled ground squirrel (Callospermophilus lateralis) population, inhabiting a dynamic subalpine habitat in Colorado, USA. The overall deterministic population growth rate ? was 0.94±SE 0.05 but it varied widely over time, ranging from 0.45±0.09 in 2006 to 1.50±0.12 in 2003, and was below replacement (?<1) for 9 out of 18 years. The stochastic population growth rate ?s was 0.92, suggesting a declining population; however, the 95% CI on ?s included 1.0 (0.52–1.60). Stochastic elasticity analysis showed that survival of adult females, followed by survival of juvenile females and litter size, were potentially the most influential vital rates; analysis of life table response experiments revealed that the same three life history variables made the largest contributions to year-to year changes in ?. Population viability analysis revealed that, when the influences of density dependence and immigration were not considered, the population had a high (close to 1.0 in 50 years) probability of extinction. However, probability of extinction declined to as low as zero when density dependence and immigration were considered. Destabilizing effects of stochastic forces were counteracted by regulating effects of density dependence and rescue effects of immigration, which allowed our study population to bounce back from low densities and prevented extinction. These results suggest that dynamics and persistence of our study population are determined synergistically by density-dependence, stochastic forces, and immigration.

Hostetler, Jeffrey A.; Kneip, Eva; Van Vuren, Dirk H.; Oli, Madan K.

2012-01-01

156

Generating a reliable computer-simulated synthetic population is necessary for knowledge processing and decision-making analysis in agent-based systems in order to measure, interpret and describe each target area and the human activity patterns within it. In this paper, both synthetic reconstruction (SR) and combinatorial optimisation (CO) techniques are discussed for generating a reliable synthetic population for a certain geographic region (in Australia) using aggregated- and disaggregated-level information available for such an area. A CO algorithm using the quadratic function of population estimators is presented in this paper in order to generate a synthetic population while considering a two-fold nested structure for the individuals and households within the target areas. The baseline population in this study is generated from the confidentialised unit record files (CURFs) and 2006 Australian census tables. The dynamics of the created population is then projected over five years using a dynamic micro-simulation model for individual- and household-level demographic transitions. This projection is then compared with the 2011 Australian census. A prediction interval is provided for the population estimates obtained by the bootstrapping method, by which the variability structure of a predictor can be replicated in a bootstrap distribution.

Namazi-Rad, Mohammad-Reza; Mokhtarian, Payam; Perez, Pascal

2014-01-01

157

Generating a reliable computer-simulated synthetic population is necessary for knowledge processing and decision-making analysis in agent-based systems in order to measure, interpret and describe each target area and the human activity patterns within it. In this paper, both synthetic reconstruction (SR) and combinatorial optimisation (CO) techniques are discussed for generating a reliable synthetic population for a certain geographic region (in Australia) using aggregated- and disaggregated-level information available for such an area. A CO algorithm using the quadratic function of population estimators is presented in this paper in order to generate a synthetic population while considering a two-fold nested structure for the individuals and households within the target areas. The baseline population in this study is generated from the confidentialised unit record files (CURFs) and 2006 Australian census tables. The dynamics of the created population is then projected over five years using a dynamic micro-simulation model for individual- and household-level demographic transitions. This projection is then compared with the 2011 Australian census. A prediction interval is provided for the population estimates obtained by the bootstrapping method, by which the variability structure of a predictor can be replicated in a bootstrap distribution. PMID:24733522

Namazi-Rad, Mohammad-Reza; Mokhtarian, Payam; Perez, Pascal

2014-01-01

158

Evolutionary History and Population Dynamics of Hepatitis E Virus

Background Hepatitis E virus (HEV) is an enterically transmitted hepatropic virus. It segregates as four genotypes. All genotypes infect humans while only genotypes 3 and 4 also infect several animal species. It has been suggested that hepatitis E is zoonotic, but no study has analyzed the evolutionary history of HEV. We present here an analysis of the evolutionary history of HEV. Methods and Findings The times to the most recent common ancestors for all four genotypes of HEV were calculated using BEAST to conduct a Bayesian analysis of HEV. The population dynamics for genotypes 1, 3 and 4 were analyzed using skyline plots. Bayesian analysis showed that the most recent common ancestor for modern HEV existed between 536 and 1344 years ago. The progenitor of HEV appears to have given rise to anthropotropic and enzootic forms of HEV, which evolved into genotypes 1 and 2 and genotypes 3 and 4, respectively. Population dynamics suggest that genotypes 1, 3 and 4 experienced a population expansion during the 20th century. Genotype 1 has increased in infected population size ?30–35 years ago. Genotype 3 and 4 have experienced an increase in population size starting late in the 19th century until ca.1940-45, with genotype 3 having undergone additional rapid expansion until ca.1960. The effective population size for both genotype 3 and 4 rapidly declined to pre-expansion levels starting in ca.1990. Genotype 4 was further examined as Chinese and Japanese sequences, which exhibited different population dynamics, suggesting that this genotype experienced different evolutionary history in these two countries. Conclusions HEV appears to have evolved through a series of steps, in which the ancestors of HEV may have adapted to a succession of animal hosts leading to humans. Analysis of the population dynamics of HEV suggests a substantial temporal variation in the rate of transmission among HEV genotypes in different geographic regions late in the 20th Century.

Purdy, Michael A.; Khudyakov, Yury E.

2010-01-01

159

Population dynamics of animals in unpredictably-changing tropical environments

We studied population dynamics of a solitary phytophagous beetle,Epilachna viqintioctopunctata and a social stingless bee,Trigona minangkabau, in Sumatra, Indonesia for 5 years from 1981.\\u000a \\u000a Population increase ofEpilachna vigintioctopunctata was suppressed in months of normal rainfall (?300mm) but was released in the 1982–1983 El Nino-Southern. Oscillation when\\u000a rainfall dropped to 50% of the long-term average. Mechanisms might be direct; rainfall lowered

Tamiji Inoue; Koji Nakamura; Siti Salmah; Idrus Abbas

1993-01-01

160

Real-time prediction of neuronal population spiking activity using FPGA.

A field-programmable gate array (FPGA)-based hardware architecture is proposed and utilized for prediction of neuronal population firing activity. The hardware system adopts the multi-input multi-output (MIMO) generalized Laguerre-Volterra model (GLVM) structure to describe the nonlinear dynamic neural process of mammalian brain and can switch between the two important functions: estimation of GLVM coefficients and prediction of neuronal population spiking activity (model outputs). The model coefficients are first estimated using the in-sample training data; then the output is predicted using the out-of-sample testing data and the field estimated coefficients. Test results show that compared with previous software implementation of the generalized Laguerre-Volterra algorithm running on an Intel Core i7-2620M CPU, the FPGA-based hardware system can achieve up to 2.66×10(3) speedup in doing model parameters estimation and 698.84 speedup in doing model output prediction. The proposed hardware platform will facilitate research on the highly nonlinear neural process of the mammal brain, and the cognitive neural prosthesis design. PMID:23893208

Li, Will X Y; Cheung, Ray C C; Chan, Rosa H M; Song, Dong; Berger, Theodore W

2013-08-01

161

Parametric Prediction of the Transverse Dynamic Stability of Ships.

National Technical Information Service (NTIS)

There currently exists no direct method for predicting the righting energy of a ship based on key geometric hull properties. Consequently, naval architects traditionally select hull parameters based on other constraints and merely check the dynamic stabil...

J. W. Sebastian

1997-01-01

162

Phenotypic Variance Predicts Symbiont Population Densities in Corals: A Modeling Approach

Background We test whether the phenotypic variance of symbionts (Symbiodinium) in corals is closely related with the capacity of corals to acclimatize to increasing seawater temperatures. Moreover, we assess whether more specialist symbionts will increase within coral hosts under ocean warming. The present study is only applicable to those corals that naturally have the capacity to support more than one type of Symbiodinium within the lifetime of a colony; for example, Montastraea annularis and Montastraea faveolata. Methodology/Principal Findings The population dynamics of competing Symbiodinium symbiont populations were projected through time in coral hosts using a novel, discrete time optimal–resource model. Models were run for two Atlantic Ocean localities. Four symbiont populations, with different environmental optima and phenotypic variances, were modeled to grow, divide, and compete in the corals under seasonal fluctuations in solar insolation and seawater temperature. Elevated seawater temperatures were input into the model 1.5°C above the seasonal summer average, and the symbiont population response was observed for each location. The models showed dynamic fluctuations in Symbiodinium populations densities within corals. Population density predictions for Lee Stocking Island, the Bahamas, where temperatures were relatively homogenous throughout the year, showed a dominance of both type 2, with high phenotypic variance, and type 1, a high-temperature and high-insolation specialist. Whereas the densities of Symbiodinium types 3 and 4, a high-temperature, low-insolation specialist, and a high-temperature, low-insolation generalist, remained consistently low. Predictions for Key Largo, Florida, where environmental conditions were more seasonally variable, showed the coexistence of generalists (types 2 and 4) and low densities of specialists (types 1 and 3). When elevated temperatures were input into the model, population densities in corals at Lee Stocking Island showed an emergence of high-temperature specialists. However, even under high temperatures, corals in the Florida Keys were dominated by generalists. Conclusions/Significance Predictions at higher seawater temperatures showed endogenous shuffling and an emergence of the high-temperature Symbiodinium specialists, even though their phenotypic variance was low. The model shows that sustaining these “hidden” specialists becomes advantageous under thermal stress conditions, and shuffling symbionts may increase the corals' capacity to acclimatize but not adapt to climatechange–induced ocean warming.

van Woesik, Robert; Shiroma, Kazuyo; Koksal, Semen

2010-01-01

163

Brain mechanism of reward prediction under predictable and unpredictable environmental dynamics.

In learning goal-directed behaviors, an agent has to consider not only the reward given at each state but also the consequences of dynamic state transitions associated with action selection. To understand brain mechanisms for action learning under predictable and unpredictable environmental dynamics, we measured brain activities by functional magnetic resonance imaging (fMRI) during a Markov decision task with predictable and unpredictable state transitions. Whereas the striatum and orbitofrontal cortex (OFC) were significantly activated both under predictable and unpredictable state transition rules, the dorsolateral prefrontal cortex (DLPFC) was more strongly activated under predictable than under unpredictable state transition rules. We then modelled subjects' choice behaviours using a reinforcement learning model and a Bayesian estimation framework and found that the subjects took larger temporal discount factors under predictable state transition rules. Model-based analysis of fMRI data revealed different engagement of striatum in reward prediction under different state transition dynamics. The ventral striatum was involved in reward prediction under both unpredictable and predictable state transition rules, although the dorsal striatum was dominantly involved in reward prediction under predictable rules. These results suggest different learning systems in the cortico-striatum loops depending on the dynamics of the environment: the OFC-ventral striatum loop is involved in action learning based on the present state, while the DLPFC-dorsal striatum loop is involved in action learning based on predictable future states. PMID:16979871

Tanaka, Saori C; Samejima, Kazuyuki; Okada, Go; Ueda, Kazutaka; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

2006-10-01

164

Global quantitative predictions of complex laser dynamics

We demonstrate unprecedented agreement between a theoretical two-dimensional bifurcation diagram and the corresponding experimental stability map of an optically injected semiconductor laser over a large range of relevant injection parameter values. The bifurcation diagram encompasses both local and global bifurcations mapping out regions of regular, chaotic, and multistable behavior in considerable detail. This demonstrates the power of dynamical systems modeling

Sebastian Wieczorek; Thomas B. Simpson; Bernd Krauskopf; Daan Lenstra

2002-01-01

165

Predicting Tenure Dynamics: Models Help Manage Tenure System.

ERIC Educational Resources Information Center

Presents three different, complementary statistical models for predicting faculty tenure dynamics, using data from Worcester Polytechnic Institute (Massachusetts). The difference equation model exactly describes future behavior but requires complete specification. The Markov-chain model can predict the full life-cycle of tenure from initial age…

Strauss, Jon C.

1997-01-01

166

Predictions of a population of cataclysmic variables in globular clusters

NASA Technical Reports Server (NTRS)

We have studied the number of cataclysmic variables (CVs) that should be active in globular clusters during the present epoch as a result of binary formation via two-body tidal capture. We predict the orbital period and luminosity distributions of CVs in globular clusters. The results arebased on Monte Carlo simulations combined with evolution calculations appropriate to each system formed during the lifetime of two specific globular clusters, omega Cen and 47 Tuc. From our study of these two clusters, which represent the range of core densities and states of mass segregation that are likely to be interesting, we extrapolate our results to the Galactic globlular cluster system. Although there is at present little direct observational evidence of CVs in globular clusters, we find that there should be a large number of active systems. We predict that there should be more than approximately 100 CVs in both 47 Tuc and omega Cen and several thousand in the Galactic globular cluster system. These numbers are based on two-body processes alone and represent a lower bound on the number of systems that may have been formed as a result of stellar interaction within globular clusters. The relation between these calculations and the paucity of optically detected CVs in globular clusters is discussed. Should future observations fail to find convincing evidence of a substantial population of cluster CVs, then the two-body tidal capture scenario is likely to be seriously constrained. Of the CVs we espect in 47 Tuc and omega Cen, approximately 45 and 20, respectively, should have accretion luminosities above 10(exp 33) ergs/s. If one utilizes a relation for converting accretion luminosity to hard X-ray luminosity that is based on observations of Galactic plane CVs, even these sources will not exhibit X-ray luminosities above 10(exp 33) ergs/s. While we cannot account directly for the most luminous subset of the low-luminosity globular cluster X-ray sources without assuming an evolutionary pattern that is different from that of the majority of CVs in the disk, we are able to account for all of the observed lower luminosity subset of these sources, many of which have been recently discovered through ROSAT observations. In order for our predicted integrated cluster X-ray luminosities to be consistent with observational upper limits, the relation between accretion and X-ray luminosities should be something like that inferred from the Galactic plane population of CVs. Our calculations predict a large number of systems with L(sub acc) is less than 10(exp 32) ergs/s. Although our calculations imply that globular clusters should have an enhancement of CVs relative to the number thought to be present in the Galactic disk, this enhancement is at most roughly an order of magnitude, not comparable to the factor of approximately 100 for low-mass X-ray binaries (LMXBs).

Di Stefano, R.; Rappaport, S.

1994-01-01

167

Population Dynamics of the Black Tinder Fungus Beetle Bolitophagus reticulatus

LIK M. 2005. Population dynamics of the black tinder fungus beetle Bolitophagus reticulatus. Folia biol. (Kraków) 53 (Suppl.): 171-177. The aim of the study was to describe seasonal changes in numbers and settlement of basidiocarps of tinder fungus (Fomes fomentarius (L. ex Fr.) Kick) by the coleopteran Bolitophagus reticulatus L. in relation to the weight and the stage of decomposition

Monika Lik

2005-01-01

168

Distribution and population dynamics of Rhizobium sp. introduced into soil

In this thesis the population dynamics of bacteria introduced into soil was studied. In the introduction, the existence of microhabitats favourable for the survival of indigenous bacteria is discussed. Knowledge about the distribution of **introduced<\\/strong> bacteria over such microhabitats, however, is scarse. Nevertheless, it was hypothesized that upon introduction, bacteria reach other microsites in soil than bacteria which are already**

J. Postma

1989-01-01

169

Binary Populations and Stellar Dynamics in Young Clusters

NASA Astrophysics Data System (ADS)

We first summarize work that has been done on the effects of binaries on theoretical population synthesis of stars and stellar phenomena. Next, we highlight the influence of stellar dynamics in young clusters by discussing a few candidate UFOs (unconventionally formed objects) like intermediate mass black holes, ? Car, ? Pup, ?2 Velorum and WR 140.

Vanbeveren, D.; Belkus, H.; Van Bever, J.; Mennekens, N.

2008-06-01

170

Improved semiconductor-laser dynamics from induced population pulsation

This paper investigates theoretically the modification of dynamical properties in a semiconductor laser by a strong injected signal. It is found that enhanced relaxation oscillations are governed by the pulsations of the intracavity field and population at frequencies determined by the injected field and cavity resonances. Furthermore, the bandwidth enhancement is associated with the undamping of the injection-induced relaxation oscillation

Connie J. Chang-Hasnain; Lukas Chrostowski; Weng Wah Chow; Sebastian Maciej Wieczorek

2005-01-01

171

The role of resting cysts in Alexandrium minutum population dynamics

The role of resting cysts on the development of Alexandrium minutum blooms in a typical Mediterranean semi-enclosed water body (Arenys de Mar Harbor, NW Mediterranean) was studied by means of matrix and dynamic population models. We used a series of scenarios, constrained when possible by experimentally measured parameters to test whether excystment and encystment fluxes and changes in the dormancy

Marta Estrada; Jordi Solé; Sílvia Anglès; Esther Garcés

2010-01-01

172

Ecology and Population Dynamics of Colobus guereza in Ethiopia

The ecology of Colobus guereza in Ethiopia is described. Data on group size from a number of localities are given, and groups are typically found to be one-male groups of 5-8 animals. The dynamics of one population are discussed with particular reference to birth and death rates and immigration and emigration. Daily activity patterns and use of home ranges are

R. I. M. Dunbar; E. P. Dunbar

1974-01-01

173

Life history and population dynamics of Atriplex triangularis

Life history and population dynamics were examined for an annual halophyte, Atriplex triangularis Willd., in an inland salt marsh at Rittman, Ohio. The effect of salinity and precipitation on survival, growth, and reproduction of Atriplex triangularis under field conditions was determined. Early germination enhanced the possibility of survival and reproduction of this species. No distinct ecotypes were found, but various

M. A. Khan; I. A. Ungar

1986-01-01

174

Interactions between predation and resources shape zooplankton population dynamics.

Identifying the relative importance of predation and resources in population dynamics has a long tradition in ecology, while interactions between them have been studied less intensively. In order to disentangle the effects of predation by juvenile fish, algal resource availability and their interactive effects on zooplankton population dynamics, we conducted an enclosure experiment where zooplankton were exposed to a gradient of predation of roach (Rutilus rutilus) at different algal concentrations. We show that zooplankton populations collapse under high predation pressure irrespective of resource availability, confirming that juvenile fish are able to severely reduce zooplankton prey when occurring in high densities. At lower predation pressure, however, the effect of predation depended on algal resource availability since high algal resource supply buffered against predation. Hence, we suggest that interactions between mass-hatching of fish, and the strong fluctuations in algal resources in spring have the potential to regulate zooplankton population dynamics. In a broader perspective, increasing spring temperatures due to global warming will most likely affect the timing of these processes and have consequences for the spring and summer zooplankton dynamics. PMID:21304980

Nicolle, Alice; Hansson, Lars-Anders; Brodersen, Jakob; Nilsson, P Anders; Brönmark, Christer

2011-01-01

175

Global Population Dynamics and Hot Spots of Response to Climate Change

NSDL National Science Digital Library

Understanding how biotic and abiotic factors influence the abundance and distribution of organisms has become more important with the growing awareness of the ecological consequences of climate change. In this article, we outline an approach that complements bioclimatic envelope modeling in quantifying the effects of climate change at the species level. The global population dynamics approach, which relies on distribution-wide, data-driven analyses of dynamics, goes beyond quantifying biotic interactions in population dynamics to identify hot spots of response to climate change. Such hot spots highlight populations or locations within speciesÃ¢ÂÂ distributions that are particularly sensitive to climate change, and identification of them should focus conservation and management efforts. An important result of the analyses highlighted here is pronounced variation at the species level in the strength and direction of population responses to warming. Although this variation complicates species-level predictions of responses to climate change, the global population dynamics approach may improve our understanding of the complex implications of climate change for species persistence or extinction.

Eric Post (Pennsylvania State University;)

2009-06-01

176

Uncovering epidemiological dynamics in heterogeneous host populations using phylogenetic methods

Host population structure has a major influence on epidemiological dynamics. However, in particular for sexually transmitted diseases, quantitative data on population contact structure are hard to obtain. Here, we introduce a new method that quantifies host population structure based on phylogenetic trees, which are obtained from pathogen genetic sequence data. Our method is based on a maximum-likelihood framework and uses a multi-type branching process, under which each host is assigned to a type (subpopulation). In a simulation study, we show that our method produces accurate parameter estimates for phylogenetic trees in which each tip is assigned to a type, as well for phylogenetic trees in which the type of the tip is unknown. We apply the method to a Latvian HIV-1 dataset, quantifying the impact of the intravenous drug user epidemic on the heterosexual epidemic (known tip states), and identifying superspreader dynamics within the men-having-sex-with-men epidemic (unknown tip states).

Stadler, Tanja; Bonhoeffer, Sebastian

2013-01-01

177

Uncovering epidemiological dynamics in heterogeneous host populations using phylogenetic methods.

Host population structure has a major influence on epidemiological dynamics. However, in particular for sexually transmitted diseases, quantitative data on population contact structure are hard to obtain. Here, we introduce a new method that quantifies host population structure based on phylogenetic trees, which are obtained from pathogen genetic sequence data. Our method is based on a maximum-likelihood framework and uses a multi-type branching process, under which each host is assigned to a type (subpopulation). In a simulation study, we show that our method produces accurate parameter estimates for phylogenetic trees in which each tip is assigned to a type, as well for phylogenetic trees in which the type of the tip is unknown. We apply the method to a Latvian HIV-1 dataset, quantifying the impact of the intravenous drug user epidemic on the heterosexual epidemic (known tip states), and identifying superspreader dynamics within the men-having-sex-with-men epidemic (unknown tip states). PMID:23382421

Stadler, Tanja; Bonhoeffer, Sebastian

2013-03-19

178

Reconsidering the Limits to World Population: Meta-analysis and Meta-prediction

NSDL National Science Digital Library

This peer-reviewed article from BioScience journal is on the topic of population growth. We performed a meta-analysis on the basis of 69 past studies that have assessed a limit to the world population. The estimates of this limit range from 0.5 billion to 1 1021 billion people. A meta-analysis allows us to see what overall picture emerges when different methods, limiting factors, levels of aggregation, and data are taken into account. Limiting factors for the world population include water availability, energy, carbon, forest products, nonrenewable resources, heat removal, photosynthetic capacity, and the availability of land for food production. Methods employed in the population studies include spatial extrapolation, modeling of multiple regions, temporal extrapolation, actual supply of a resource, hypothetical modeling, and dynamic systems modeling. Many studies rely on important assumptions about the level of technology, the energy intake per person, and the available arable land. The meta-analysis employs both descriptive statistics and regression analysis. We used the findings of these analyses to propose a number of meta-estimates of limits to world population. When taking all studies into account, the best point estimate is 7.7 billion people; the lower and upper bounds, given current technology, are 0.65 billion and 98 billion people, respectively. We offer a range of other conditional estimates as well. An important conclusion of this study is that recent predictions of stabilized world population levels for 2050 exceed several of our meta-estimates of a world population limit.

JEROEN C. J. M. VAN DEN BERGH and PIET RIETVELD (;)

2004-03-01

179

Modeling Tools Predict Flow in Fluid Dynamics

NASA Technical Reports Server (NTRS)

"Because rocket engines operate under extreme temperature and pressure, they present a unique challenge to designers who must test and simulate the technology. To this end, CRAFT Tech Inc., of Pipersville, Pennsylvania, won Small Business Innovation Research (SBIR) contracts from Marshall Space Flight Center to develop software to simulate cryogenic fluid flows and related phenomena. CRAFT Tech enhanced its CRUNCH CFD (computational fluid dynamics) software to simulate phenomena in various liquid propulsion components and systems. Today, both government and industry clients in the aerospace, utilities, and petrochemical industries use the software for analyzing existing systems as well as designing new ones."

2010-01-01

180

Parametric dynamic load prediction of a narrow gauge rocket sled

NASA Astrophysics Data System (ADS)

Dynamic load prediction of rocket sleds has been of interest to sled designers and analysts since the inception of the Holloman High Speed Test Track, (HHSTT). Dynamic loading along with thrust and aerodynamic loading is a primary contributor to sled design load cases. Dynamic loading comes directly from the rocket sled traversing the gap between the slipper and rail and the resulting sliding impacts. The current study investigates the prediction of narrow gauge sled dynamic loads by applying a systematic process of modeling validation, design parameter variation and dynamic load correlation. Numerical modeling was employed to simulate the Land Speed Record (LSR) test and the model data was validated by comparing it to the data taken from the sled during the LSR test. Modeling methods validated against the test data were applied to a reduced complexity narrow gauge sled representing a generic version of the LSR sled. Design parameters were identified that contributed to the generation of dynamic loading. The design parameters are: sled mass, slipper gap, vertical rail roughness, lateral rail roughness, vertical sled natural frequency, lateral sled natural frequency, torsional sled natural frequency, and sled velocity. Peak dynamic load results (from evaluating the reduced complexity model while varying the design parameter values over high, low, and typical ranges) were computed at the sled center of Gravity (CG). This peak dynamic loading, eta force, constituted the dynamic load prediction. The correlation of eta to its respective design parameters showed that a multivariate interpolation method was the most accurate method to relate eta force to its respective design parameters. The study revealed a heavy dependence of dynamic load on velocity, rail roughness, slipper gap, and translational sled natural frequencies. The study also showed a favorable comparison of eta force prediction over previously used methods at the HHSTT.

Furlow, John Scott

181

How population heterogeneity in susceptibility and infectivity influences epidemic dynamics.

An important concern in public health is what population group should be prioritised for vaccination. To this end, we present an epidemic model with arbitrary initial distributions for population susceptibility, and corresponding infectivity distributions. We consider four scenarios: first, a population with heterogeneous susceptibility with a uniform distribution, but homogeneous infectivity; second, a heterogeneously susceptible population with linear heterogeneous infectivity functions, where the most susceptible are either the most or least infectious; third, a bimodal distribution for susceptibility, with all combinations of infectivity functions; finally, we consider the effects of additional pre-epidemic immunity, ostensibly through vaccination, on the epidemic dynamics. For a seasonal influenza-like infectious disease, we find the smallest final size and overall number of deaths due to the epidemic to occur if the most susceptible are vaccinated, corresponding to targeting children. PMID:24444766

Hickson, R I; Roberts, M G

2014-06-01

182

Heterogeneous Structure of Stem Cells Dynamics: Statistical Models and Quantitative Predictions

Understanding stem cell (SC) population dynamics is essential for developing models that can be used in basic science and medicine, to aid in predicting cells fate. These models can be used as tools e.g. in studying patho-physiological events at the cellular and tissue level, predicting (mal)functions along the developmental course, and personalized regenerative medicine. Using time-lapsed imaging and statistical tools, we show that the dynamics of SC populations involve a heterogeneous structure consisting of multiple sub-population behaviors. Using non-Gaussian statistical approaches, we identify the co-existence of fast and slow dividing subpopulations, and quiescent cells, in stem cells from three species. The mathematical analysis also shows that, instead of developing independently, SCs exhibit a time-dependent fractal behavior as they interact with each other through molecular and tactile signals. These findings suggest that more sophisticated models of SC dynamics should view SC populations as a collective and avoid the simplifying homogeneity assumption by accounting for the presence of more than one dividing sub-population, and their multi-fractal characteristics.

Bogdan, Paul; Deasy, Bridget M.; Gharaibeh, Burhan; Roehrs, Timo; Marculescu, Radu

2014-01-01

183

Heterogeneous structure of stem cells dynamics: statistical models and quantitative predictions.

Understanding stem cell (SC) population dynamics is essential for developing models that can be used in basic science and medicine, to aid in predicting cells fate. These models can be used as tools e.g. in studying patho-physiological events at the cellular and tissue level, predicting (mal)functions along the developmental course, and personalized regenerative medicine. Using time-lapsed imaging and statistical tools, we show that the dynamics of SC populations involve a heterogeneous structure consisting of multiple sub-population behaviors. Using non-Gaussian statistical approaches, we identify the co-existence of fast and slow dividing subpopulations, and quiescent cells, in stem cells from three species. The mathematical analysis also shows that, instead of developing independently, SCs exhibit a time-dependent fractal behavior as they interact with each other through molecular and tactile signals. These findings suggest that more sophisticated models of SC dynamics should view SC populations as a collective and avoid the simplifying homogeneity assumption by accounting for the presence of more than one dividing sub-population, and their multi-fractal characteristics. PMID:24769917

Bogdan, Paul; Deasy, Bridget M; Gharaibeh, Burhan; Roehrs, Timo; Marculescu, Radu

2014-01-01

184

Heterogeneous Structure of Stem Cells Dynamics: Statistical Models and Quantitative Predictions

NASA Astrophysics Data System (ADS)

Understanding stem cell (SC) population dynamics is essential for developing models that can be used in basic science and medicine, to aid in predicting cells fate. These models can be used as tools e.g. in studying patho-physiological events at the cellular and tissue level, predicting (mal)functions along the developmental course, and personalized regenerative medicine. Using time-lapsed imaging and statistical tools, we show that the dynamics of SC populations involve a heterogeneous structure consisting of multiple sub-population behaviors. Using non-Gaussian statistical approaches, we identify the co-existence of fast and slow dividing subpopulations, and quiescent cells, in stem cells from three species. The mathematical analysis also shows that, instead of developing independently, SCs exhibit a time-dependent fractal behavior as they interact with each other through molecular and tactile signals. These findings suggest that more sophisticated models of SC dynamics should view SC populations as a collective and avoid the simplifying homogeneity assumption by accounting for the presence of more than one dividing sub-population, and their multi-fractal characteristics.

Bogdan, Paul; Deasy, Bridget M.; Gharaibeh, Burhan; Roehrs, Timo; Marculescu, Radu

2014-04-01

185

Predictive Performance of Current Risk Adjustment Systems: Application to Pediatric Populations.

National Technical Information Service (NTIS)

The objective of this study was to assess the predictive performance of current claims-based capitation adjustment methods for pediatric populations. These models were developed primarily for use in an adult or elderly population and have not been evaluat...

E. J. Fowler

1995-01-01

186

Cohort variation, climate effects and population dynamics in a short-lived lizard.

1. Demographic theory and empirical studies indicate that cohort variation in demographic traits has substantial effects on population dynamics of long-lived vertebrates but cohort effects have been poorly investigated in short-lived species. 2. Cohort effects were quantified in the common lizard (Zootoca vivipara Jacquin 1787), a short-lived ectothermic vertebrate, for body size, reproductive traits and age-specific survival with mark-recapture data collected from 1989 to 2005 in two wetlands. We assessed cohort variation and covariation in demographic traits, tested the immediate and delayed effects of climate conditions (temperature and rainfall), and predicted consequences for population growth. 3. Most demographic traits exhibited cohort variation, but this variation was stronger for juvenile growth and survival, sub-adult survival and breeding phenology than for other traits. 4. Cohort variation was partly explained by a web of immediate and delayed effects of climate conditions. Rainfall and temperature influenced distinct life-history traits and the periods of gestation and early juvenile life were critical stages for climate effects. 5. Cohort covariation between demographic traits was usually weak, apart from a negative correlation between juvenile and sub-adult body growth suggesting compensatory responses. An age-structured population model shows that cohort variation influences population growth mainly through direct numerical effects of survival variation early in life. 6. An understanding of cohort effects is necessary to predict critical life stages and climatic determinants of population dynamics, and therefore demographic responses to future climate warming. PMID:20649911

Le Galliard, Jean François; Marquis, Olivier; Massot, Manuel

2010-11-01

187

A comparison of six methods for stabilizing population dynamics.

Over the last two decades, several methods have been proposed for stabilizing the dynamics of biological populations. However, these methods have typically been evaluated using different population dynamics models and in the context of very different concepts of stability, which makes it difficult to compare their relative efficiencies. Moreover, since the dynamics of populations are dependent on the life-history of the species and its environment, it is conceivable that the stabilizing effects of control methods would also be affected by such factors, a complication that has typically not been investigated. In this study, we compare six different control methods with respect to their efficiency at inducing a common level of enhancement (defined as 50% increase) for two kinds of stability (constancy and persistence) under four different life-history/environment combinations. Since these methods have been analytically studied elsewhere, we concentrate on an intuitive understanding of realistic simulations incorporating noise, extinction probability and lattice effect. We show that for these six methods, even when the magnitude of stabilization attained is the same, other aspects of the dynamics like population size distribution can be very different. Consequently, correlated aspects of stability, like the amount of persistence for a given degree of constancy stability (and vice versa) or the corresponding effective population size (a measure of resistance to genetic drift) vary widely among the methods. Moreover, the number of organisms needed to be added or removed to attain similar levels of stabilization also varies for these methods, a fact that has economic implications. Finally, we compare the relative efficiencies of these methods through a composite index of various stability related measures. Our results suggest that Lower Limiter Control (LLC) seems to be the optimal method under most conditions, with the recently proposed Adaptive Limiter Control (ALC) being a close second. PMID:24801858

Tung, Sudipta; Mishra, Abhishek; Dey, Sutirth

2014-09-01

188

Coupling in goshawk and grouse population dynamics in Finland.

Different prey species can vary in their significance to a particular predator. In the simplest case, the total available density or biomass of a guild of several prey species might be most relevant to the predator, but behavioural and ecological traits of different prey species can alter the picture. We studied the population dynamics of a predator-prey setting in Finland by fitting first-order log-linear vector autoregressive models to long-term count data from active breeding sites of the northern goshawk (Accipiter gentilis; 1986-2009), and to three of its main prey species (1983-2010): hazel grouse (Bonasa bonasia), black grouse (Tetrao tetrix) and capercaillie (T. urogallus), which belong to the same forest grouse guild and show synchronous fluctuations. Our focus was on modelling the relative significance of prey species and estimating the tightness of predator-prey coupling in order to explain the observed population dynamics, simultaneously accounting for effects of density dependence, winter severity and spatial correlation. We established nine competing candidate models, where different combinations of grouse species affect goshawk dynamics with lags of 1-3 years. Effects of goshawk on grouse were investigated using one model for each grouse species. The most parsimonious model for goshawk indicated separate density effects of hazel grouse and black grouse, and different effects with lags of 1 and 3 years. Capercaillie showed no effects on goshawk populations, while the effect of goshawk on grouse was clearly negative only in capercaillie. Winter severity had significant adverse effects on goshawk and hazel grouse populations. In combination, large-scale goshawk-grouse population dynamics are coupled, but there are no clear mutual effects for any of the individual guild members. In a broader context, our study suggests that pooling data on closely related, synchronously fluctuating prey species can result in the loss of relevant information, rather than increased model parsimony. PMID:22961371

Tornberg, Risto; Lindén, Andreas; Byholm, Patrik; Ranta, Esa; Valkama, Jari; Helle, Pekka; Lindén, Harto

2013-04-01

189

Ecological change, range fluctuations and population dynamics during the Pleistocene.

Apart from the current human-induced climate change, the Holocene is notable for its stable climate. In contrast, the preceding age, the Pleistocene, was a time of intensive climatic fluctuations, with temperature changes of up to 15 degrees C occurring within a few decades. These climatic changes have substantially influenced both animal and plant populations. Until recently, the prevailing opinion about the effect of these climatic fluctuations on species in Europe was that populations survived glacial maxima in southern refugia and that populations died out outside these refugia. However, some of the latest studies of modern population genetics, the fossil record and especially ancient DNA reveal a more complex picture. There is now strong evidence for additional local northern refugia for a large number of species, including both plants and animals. Furthermore, population genetic analyses using ancient DNA have shown that genetic diversity and its geographical structure changed more often and in more unpredictable ways during the Pleistocene than had been inferred. Taken together, the Pleistocene is now seen as an extremely dynamic era, with rapid and large climatic fluctuations and correspondingly variable ecology. These changes were accompanied by similarly fast and sometimes dramatic changes in population size and extensive gene flow mediated by population movements. Thus, the Pleistocene is an excellent model case for the effects of rapid climate change, as we experience at the moment, on the ecology of plants and animals. PMID:19640497

Hofreiter, Michael; Stewart, John

2009-07-28

190

Prediction of breed composition in an admixed cattle population.

Swiss Fleckvieh was established in 1970 as a composite of Simmental (SI) and Red Holstein Friesian (RHF) cattle. Breed composition is currently reported based on pedigree information. Information on a large number of molecular markers potentially provides more accurate information. For the analysis, we used Illumina BovineSNP50 Genotyping Beadchip data for 90 pure SI, 100 pure RHF and 305 admixed bulls. The scope of the study was to compare the performance of hidden Markov models, as implemented in structure software, with methods conventionally used in genomic selection [BayesB, partial least squares regression (PLSR), least absolute shrinkage and selection operator (LASSO) variable selection)] for predicting breed composition. We checked the performance of algorithms for a set of 40 492 single nucleotide polymorphisms (SNPs), subsets of evenly distributed SNPs and subsets with different allele frequencies in the pure populations, using F(ST) as an indicator. Key results are correlations of admixture levels estimated with the various algorithms with admixture based on pedigree information. For the full set, PLSR, BayesB and structure performed in a very similar manner (correlations of 0.97), whereas the correlation of LASSO and pedigree admixture was lower (0.93). With decreasing number of SNPs, correlations decreased substantially only for 5% or 1% of all SNPs. With SNPs chosen according to F(ST) , results were similar to results obtained with the full set. Only when using 96 and 48 SNPs with the highest F(ST) , correlations dropped to 0.92 and 0.90 respectively. Reducing the number of pure animals in training sets to 50, 20 and 10 each did not cause a drop in the correlation with pedigree admixture. PMID:23061480

Frkonja, A; Gredler, B; Schnyder, U; Curik, I; Sölkner, J

2012-12-01

191

Dynamics of a combined medea-underdominant population transformation system

Background Transgenic constructs intended to be stably established at high frequencies in wild populations have been demonstrated to “drive” from low frequencies in experimental insect populations. Linking such population transformation constructs to genes which render them unable to transmit pathogens could eventually be used to stop the spread of vector-borne diseases like malaria and dengue. Results Generally, population transformation constructs with only a single transgenic drive mechanism have been envisioned. Using a theoretical modelling approach we describe the predicted properties of a construct combining autosomal Medea and underdominant population transformation systems. We show that when combined they can exhibit synergistic properties which in broad circumstances surpass those of the single systems. Conclusion With combined systems, intentional population transformation and its reversal can be achieved readily. Combined constructs also enhance the capacity to geographically restrict transgenic constructs to targeted populations. It is anticipated that these properties are likely to be of particular value in attracting regulatory approval and public acceptance of this novel technology.

2014-01-01

192

Global change requires plant ecologists to predict future states of biological diversity to aid the management of natural communities, thus introducing a number of significant challenges. One major challenge is considering how the many interacting features of biological systems, including ecophysiological processes, plant life histories, and species interactions, relate to performance in the face of a changing environment. We have employed a functional trait approach to understand the individual, population, and community dynamics of a model system of Sonoran Desert winter annual plants. We have used a comprehensive approach that connects physiological ecology and comparative biology to population and community dynamics, while emphasizing both ecological and evolutionary processes. This approach has led to a fairly robust understanding of past and contemporary dynamics in response to changes in climate. In this community, there is striking variation in physiological and demographic responses to both precipitation and temperature that is described by a trade-off between water-use efficiency (WUE) and relative growth rate (RGR). This community-wide trade-off predicts both the demographic and life history variation that contribute to species coexistence. Our framework has provided a mechanistic explanation to the recent warming, drying, and climate variability that has driven a surprising shift in these communities: cold-adapted species with more buffered population dynamics have increased in relative abundance. These types of comprehensive approaches that acknowledge the hierarchical nature of biology may be especially useful in aiding prediction. The emerging, novel and nonstationary climate constrains our use of simplistic statistical representations of past plant behavior in predicting the future, without understanding the mechanistic basis of change. PMID:23838034

Huxman, Travis E; Kimball, Sarah; Angert, Amy L; Gremer, Jennifer R; Barron-Gafford, Greg A; Venable, D Lawrence

2013-07-01

193

NASA Technical Reports Server (NTRS)

A procedure has been developed for predicting peak dynamic inlet distortion. This procedure combines Computational Fluid Dynamics (CFD) and distortion synthesis analysis to obtain a prediction of peak dynamic distortion intensity and the associated instantaneous total pressure pattern. A prediction of the steady state total pressure pattern at the Aerodynamic Interface Plane is first obtained using an appropriate CFD flow solver. A corresponding inlet turbulence pattern is obtained from the CFD solution via a correlation linking root mean square (RMS) inlet turbulence to a formulation of several CFD parameters representative of flow turbulence intensity. This correlation was derived using flight data obtained from the NASA High Alpha Research Vehicle flight test program and several CFD solutions at conditions matching the flight test data. A distortion synthesis analysis is then performed on the predicted steady state total pressure and RMS turbulence patterns to yield a predicted value of dynamic distortion intensity and the associated instantaneous total pressure pattern.

Norby, W. P.; Ladd, J. A.; Yuhas, A. J.

1996-01-01

194

Limits and Uses of Dynamical Predictions of Meteorological Drought

NASA Astrophysics Data System (ADS)

The overall technical capabilities now exist to make real time, seasonal drought forecasts on a near global scale, but how skillful are such predictions? In this talk the skill of seasonal drought indicator predictions based on a combination of real time observations and dynamical model seasonal forecasts is first evaluated over the US and Mexico. The relative contributions of predictive skill from sea surface temperatures and initialed land surface and atmospheric conditions is discussed relative to baseline predictability resulting from the inherent persistence of the indicators. Web-based tools which display such predictions are then briefly described. Finally, the challenges in using such predictions in decision-making settings is described. In many applications, more detailed or tailored information is desired. Examples of the latter are based on IRI-related projects on fire early warning in Kalimantan, food security outlooks in East Africa and research towards drought early warning in the agriculture sector in the Philippines and Sri Lanka.

Lyon, B.

2012-12-01

195

Biology as population dynamics: heuristics for transmission risk.

Population-type models, accounting for phenomena such as population lifetimes, mixing patterns, recruitment patterns, genetic evolution and environmental conditions, can be usefully applied to the biology of HIV infection and viral replication. A simple dynamic model can explore the effect of a vaccine-like stimulus on the mortality and infectiousness, which formally looks like fertility, of invading virions; the mortality of freshly infected cells; and the availability of target cells, all of which impact on the probability of infection. Variations on this model could capture the importance of the timing and duration of different key events in viral transmission, and hence be applied to questions of mucosal immunology. The dynamical insights and assumptions of such models are compatible with the continuum of between- and within-individual risks in sexual violence and may be helpful in making sense of the sparse data available on the association between HIV transmission and sexual violence. PMID:23194160

Keebler, Daniel; Walwyn, David; Welte, Alex

2013-02-01

196

Prediction-based Dynamic Energy Management in Wireless Sensor Networks

Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

Wang, Xue; Ma, Jun-Jie; Wang, Sheng; Bi, Dao-Wei

2007-01-01

197

Nonlinear dynamics and predictability in the atmospheric sciences

Systematic applications of nonlinear dynamics to studies of the atmosphere and climate are reviewed for the period 1987-1990. Problems discussed include paleoclimatic applications, low-frequency atmospheric variability, and interannual variability of the ocean-atmosphere system. Emphasis is placed on applications of the successive bifurcation approach and the ergodic theory of dynamical systems to understanding and prediction of intraseasonal, interannual, and Quaternary climate changes.

Ghil, M.; Kimoto, M.; Neelin, J.D. (USAF, Geophysics Laboratory, Hanscom AFB, MA (United States))

1991-01-01

198

Predicting catastrophes in nonlinear dynamical systems by compressive sensing

An extremely challenging problem of significant interest is to predict catastrophes in advance of their occurrences. We present a general approach to predicting catastrophes in nonlinear dynamical systems under the assumption that the system equations are completely unknown and only time series reflecting the evolution of the dynamical variables of the system are available. Our idea is to expand the vector field or map of the underlying system into a suitable function series and then to use the compressive-sensing technique to accurately estimate the various terms in the expansion. Examples using paradigmatic chaotic systems are provided to demonstrate our idea and potential challenges are discussed.

Wang, Wen-Xu; Yang, Rui; Lai, Ying-Cheng; Kovanis, Vassilios; Grebogi, Celso

2013-01-01

199

Development of paradigms for the dynamics of structured populations

This is a technical progress report on the dynamics of predator-prey systems in a patchy environment. A new phenomenon that might contribute to outbreaks in systems of discrete patches has been determined using a discrete time model with both spatial and age structure. A model for a single species in a patchy environment with migration, local population growth and disasters with in patches has been formulated and a brief description is included.

Not Available

1994-10-01

200

Urban Aerosols Harbor Diverse and Dynamic Bacterial Populations

Considering the importance of its potential implications for human health, agricultural productivity, and ecosystem stability, surprisingly little is known regarding the composition or dynamics of the atmosphere's microbial inhabitants. Using a custom high-density DNA microarray, we detected and monitored bacterial populations in two U.S. cities over 17 weeks. These urban aerosols contained at least 1,800 diverse bacterial types, a richness

Eoin L. Brodie; Todd Z. DeSantis; Jordan P. Moberg Parker; Ingrid X. Zubietta; Yvette M. Piceno; Gary L. Andersen

2007-01-01

201

Equilibrium solutions for microscopic stochastic systems in population dynamics.

The present paper deals with the problem of existence of equilibrium solutions of equations describing the general population dynamics at the microscopic level of modified Liouville equation (individually--based model) corresponding to a Markov jump process. We show the existence of factorized equilibrium solutions and discuss uniqueness. The conditions guaranteeing uniqueness or non-uniqueness are proposed under the assumption of periodic structures. PMID:23906149

Lachowicz, Miros?aw; Ryabukha, Tatiana

2013-06-01

202

Improved Semiconductor-Laser Dynamics From Induced Population Pulsation

This paper investigates theoretically the modification of dynamical properties in a semiconductor laser by a strong in- jected signal. It is found that enhanced relaxation oscillations are governed by the injection-induced intracavity-field and population pulsations at frequencies determined by the injected field and cavity resonances. Furthermore, the bandwidth enhancement is associated with the undamping of the injection-induced relaxation oscillation and

Sebastian Wieczorek; Weng W. Chow; Lukas Chrostowski; C. J. Chang-Hasnain

2006-01-01

203

Dynamic energy budget theory and population ecology: lessons from Daphnia.

Dynamic energy budget (DEB) theory offers a perspective on population ecology whose starting point is energy utilization by, and homeostasis within, individual organisms. It is natural to ask what it adds to the existing large body of individual-based ecological theory. We approach this question pragmatically--through detailed study of the individual physiology and population dynamics of the zooplankter Daphnia and its algal food. Standard DEB theory uses several state variables to characterize the state of an individual organism, thereby making the transition to population dynamics technically challenging, while ecologists demand maximally simple models that can be used in multi-scale modelling. We demonstrate that simpler representations of individual bioenergetics with a single state variable (size), and two life stages (juveniles and adults), contain sufficient detail on mass and energy budgets to yield good fits to data on growth, maturation and reproduction of individual Daphnia in response to food availability. The same simple representations of bioenergetics describe some features of Daphnia mortality, including enhanced mortality at low food that is not explicitly incorporated in the standard DEB model. Size-structured, population models incorporating this additional mortality component resolve some long-standing questions on stability and population cycles in Daphnia. We conclude that a bioenergetic model serving solely as a 'regression' connecting organismal performance to the history of its environment can rest on simpler representations than those of standard DEB. But there are associated costs with such pragmatism, notably loss of connection to theory describing interspecific variation in physiological rates. The latter is an important issue, as the type of detailed study reported here can only be performed for a handful of species. PMID:20921052

Nisbet, Roger M; McCauley, Edward; Johnson, Leah R

2010-11-12

204

Spatial scaling of avian population dynamics: population abundance, growth rate, and variability.

Synchrony in population fluctuations has been identified as an important component of population dynamics. In a previous study, we determined that local-scale (<15-km) spatial synchrony of bird populations in New England was correlated with synchronous fluctuations in lepidopteran larvae abundance and with the North Atlantic Oscillation. Here we address five questions that extend the scope of our earlier study using North American Breeding Bird Survey data. First, do bird populations in eastern North America exhibit spatial synchrony in abundances at scales beyond those we have documented previously? Second, does spatial synchrony depend on what population metric is analyzed (e.g., abundance, growth rate, or variability)? Third, is there geographic concordance in where species exhibit synchrony? Fourth, for those species that exhibit significant geographic concordance, are there landscape and habitat variables that contribute to the observed patterns? Fifth, is spatial synchrony affected by a species' life history traits? Significant spatial synchrony was common and its magnitude was dependent on the population metric analyzed. Twenty-four of 29 species examined exhibited significant synchrony in population abundance: mean local autocorrelation (rho)= 0.15; mean spatial extent (mean distance where rho=0) = 420.7 km. Five of the 29 species exhibited significant synchrony in annual population growth rate (mean local autocorrelation = 0.06, mean distance = 457.8 km). Ten of the 29 species exhibited significant synchrony in population abundance variability (mean local autocorrelation = 0.49, mean distance = 413.8 km). Analyses of landscape structure indicated that habitat variables were infrequent contributors to spatial synchrony. Likewise, we detected no effects of life history traits on synchrony in population abundance or growth rate. However, short-distance migrants exhibited more spatially extensive synchrony in population variability than either year-round residents or long-distance migrants. The dissimilarity of the spatial extent of synchrony across species suggests that most populations are not regulated at similar spatial scales. The spatial scale of the population synchrony patterns we describe is likely larger than the actual scale of population regulation, and in turn, the scale of population regulation is undoubtedly larger than the scale of individual ecological requirements. PMID:18027754

Jones, Jason; Doran, Patrick J; Holmes, Richard T

2007-10-01

205

VCGDB: a dynamic genome database of the Chinese population

Background The data released by the 1000 Genomes Project contain an increasing number of genome sequences from different nations and populations with a large number of genetic variations. As a result, the focus of human genome studies is changing from single and static to complex and dynamic. The currently available human reference genome (GRCh37) is based on sequencing data from 13 anonymous Caucasian volunteers, which might limit the scope of genomics, transcriptomics, epigenetics, and genome wide association studies. Description We used the massive amount of sequencing data published by the 1000 Genomes Project Consortium to construct the Virtual Chinese Genome Database (VCGDB), a dynamic genome database of the Chinese population based on the whole genome sequencing data of 194 individuals. VCGDB provides dynamic genomic information, which contains 35 million single nucleotide variations (SNVs), 0.5 million insertions/deletions (indels), and 29 million rare variations, together with genomic annotation information. VCGDB also provides a highly interactive user-friendly virtual Chinese genome browser (VCGBrowser) with functions like seamless zooming and real-time searching. In addition, we have established three population-specific consensus Chinese reference genomes that are compatible with mainstream alignment software. Conclusions VCGDB offers a feasible strategy for processing big data to keep pace with the biological data explosion by providing a robust resource for genomics studies; in particular, studies aimed at finding regions of the genome associated with diseases.

2014-01-01

206

Background Risk prediction models for hepatocellular carcinoma are available for individuals with chronic hepatitis B virus (HBV) and hepatitis C virus (HCV) infections who are at high risk but not for the general population with average or unknown risk. We developed five simple risk prediction models based on clinically available data from the general population. Methods A prospective cohort of 428 584 subjects from a private health screening firm in Taiwan was divided into two subgroups—one with known HCV test results (n = 130 533 subjects) and the other without (n = 298 051 subjects). A total of 1668 incident hepatocellular carcinomas occurred during an average follow-up of 8.5 years. Model inputs included age, sex, health history–related variables; HBV or HCV infection–related variables; serum levels of alanine transaminase (ALT), aspartate transaminase (AST), and alfa-fetoprotein (AFP), as well as other variables of routine blood panels for liver function. Cox proportional hazards regression method was used to identify risk predictors of hepatocellular carcinoma. Receiver operating characteristic curves were used to assess discriminatory accuracy of the models. Models were internally validated. All statistical tests were two-sided. Results Age, sex, health history, HBV and HCV status, and serum ALT, AST, AFP levels were statistically significant independent predictors of hepatocellular carcinoma risk (all P < .05). Use of serum transaminases only in a model showed a higher discrimination compared with HBV or HCV only (for transaminases, area under the curve [AUC] = 0.912, 95% confidence interval [CI] = 0.909 to 0.915; for HBV, AUC = 0.840, 95% CI = 0.833 to 0.848; and for HCV, AUC = 0.841, 95% CI = 0.834 to 0.847). Adding HBV and HCV data to the transaminase-only model improved the discrimination (AUC = 0.933, 95% CI = 0.929 to 0.949). Internal validation showed high discriminatory accuracy and calibration of these models. Conclusion Models with transaminase data were best able to predict hepatocellular carcinoma risk even among subjects with unknown or HBV- or HCV-negative infection status.

2012-01-01

207

A Novel Dynamic Update Framework for Epileptic Seizure Prediction

Epileptic seizure prediction is a difficult problem in clinical applications, and it has the potential to significantly improve the patients' daily lives whose seizures cannot be controlled by either drugs or surgery. However, most current studies of epileptic seizure prediction focus on high sensitivity and low false-positive rate only and lack the flexibility for a variety of epileptic seizures and patients' physical conditions. Therefore, a novel dynamic update framework for epileptic seizure prediction is proposed in this paper. In this framework, two basic sample pools are constructed and updated dynamically. Furthermore, the prediction model can be updated to be the most appropriate one for the prediction of seizures' arrival. Mahalanobis distance is introduced in this part to solve the problem of side information, measuring the distance between two data sets. In addition, a multichannel feature extraction method based on Hilbert-Huang transform and extreme learning machine is utilized to extract the features of a patient's preseizure state against the normal state. At last, a dynamic update epileptic seizure prediction system is built up. Simulations on Freiburg database show that the proposed system has a better performance than the one without update. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices.

Wang, Minghui; Hong, Xiaojun; Han, Jie

2014-01-01

208

A novel dynamic update framework for epileptic seizure prediction.

Epileptic seizure prediction is a difficult problem in clinical applications, and it has the potential to significantly improve the patients' daily lives whose seizures cannot be controlled by either drugs or surgery. However, most current studies of epileptic seizure prediction focus on high sensitivity and low false-positive rate only and lack the flexibility for a variety of epileptic seizures and patients' physical conditions. Therefore, a novel dynamic update framework for epileptic seizure prediction is proposed in this paper. In this framework, two basic sample pools are constructed and updated dynamically. Furthermore, the prediction model can be updated to be the most appropriate one for the prediction of seizures' arrival. Mahalanobis distance is introduced in this part to solve the problem of side information, measuring the distance between two data sets. In addition, a multichannel feature extraction method based on Hilbert-Huang transform and extreme learning machine is utilized to extract the features of a patient's preseizure state against the normal state. At last, a dynamic update epileptic seizure prediction system is built up. Simulations on Freiburg database show that the proposed system has a better performance than the one without update. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices. PMID:25050381

Han, Min; Ge, Sunan; Wang, Minghui; Hong, Xiaojun; Han, Jie

2014-01-01

209

Dynamic changes in fetal Leydig cell populations influence adult Leydig cell populations in mice

Testes contain two distinct Leydig cell populations during development: fetal and adult Leydig cells (FLCs and ALCs, respectively). ALCs are not derived from FLCs, and it is unknown whether these two populations share common progenitors. We discovered that hedgehog (Hh) signaling is responsible for transforming steroidogenic factor 1-positive (SF1+) progenitors into FLCs. However, not all SF1+ progenitors become FLCs, and some remain undifferentiated through fetal development. We therefore hypothesized that if FLCs and ALCs share SF1+ progenitors, increased Hh pathway activation in SF1+ progenitor cells could change the dynamics and distribution of SF1+ progenitors, FLCs, and ALCs. Using a genetic model involving constitutive activation of Hh pathway in SF1+ cells, we observed reduced numbers of SF1+ progenitor cells and increased FLCs. Conversely, increased Hh activation led to decreased ALC populations prepubertally, while adult ALC numbers were comparable to control testes. Hence, reduction in SF1+ progenitors temporarily affects ALC numbers, suggesting that SF1+ progenitors in fetal testes are a potential source of both FLCs and ALCs. Besides transient ALC defects, adult animals with Hh activation in SF1+ progenitors had reduced testicular weight, oligospermia, and decreased sperm mobility. These defects highlight the importance of properly regulated Hh signaling in Leydig cell development and testicular functions.—Barsoum, I. B., Kaur, J. Ge, R. S., Cooke, P. S., Yao, H. H.-C. Dynamic changes in fetal Leydig cell populations influence adult Leydig cell populations in mice.

Barsoum, Ivraym B.; Kaur, Jaspreet; Ge, Renshan S.; Cooke, Paul S.; Yao, Humphrey Hung-Chang

2013-01-01

210

Dynamic bifurcations for predictability of climate tipping events

NASA Astrophysics Data System (ADS)

Despite recent advances in understanding of the nonlinear processes responsible for changes in the climate system predicting the future abrupt climate changes remains an outstanding scientific challenge of special importance for the society. Better understanding of nonlinear mechanisms of tipping points is a major goal in treating this problem. Existed approaches to examine climatic tipping points allow identifying the climate-tipping events in the past but very limited to predict them in advance. Our recent theoretical findings suggest that for predicting tipping points it is crucial to distinguish which scenario of a bifurcation transition dominates: dynamic (predictable) or stochastic (unpredictable). In order to illustrate suggested approach we compare the features of dynamic and stochastic bifurcations in most common scenario of abrupt transition between two climate states. This scenario is associated with a saddle-node and a transcritical bifurcations. Such scenario has been used, in particularly, in the analysis of stability of the thermohaline circulation against freshwater flux, Indian summer monsoon against global change. We demonstrate the effect of the rate of change of the bifurcation parameter at dynamic bifurcation and noise effect at stochastic bifurcation transitions by theoretical estimates. We analyse pre-bifurcation noise-dependent and rate-dependent phenomena, and distinguish its roles as "precursors" of impending bifurcations for dynamic and stochastic transitions. We show that appropriate choice of "precursors" might lead to improving predictability of climate tipping points. Additionally, the evaluation of the role of dynamic and stochastic factors might be also useful for the assessment of the vulnerability of tipping elements to noise-induced changes. Finally, our preliminary investigations suggest that a hitherto neglected dynamic effect induced by such small parameter as rate of change of the bifurcation parameter may have had important influence on abrupt climate changes on the scale of the geological history of the Earth.

Surovyatkina, Elena; Kurths, Juergen

2014-05-01

211

Predictability in Nonlinear Dynamical Systems with Model Uncertainty

Nonlinear systems with model uncertainty are often described by stochastic differential equations. Some techniques from random dynamical systems are discussed. They are relevant to better understanding of solution processes of stochastic differential equations and thus may shed lights on predictability in nonlinear systems with model uncertainty.

Jinqiao Duan

2008-01-01

212

Prediction in dynamic models with time-dependent conditional variances

This paper considers forecasting the conditional mean and variance from a single-equation dynamic model with autocorrelated disturbances following an ARMA process, and innovations with time-dependent conditional heteroskedasticity as represented by a linear GARCH process. Expressions for the minimum MSE predictor and the conditional MSE are presented. We also derive the formula for all the theoretical moments of the prediction error

Richard T. Baillie; Tim Bollerslev

1992-01-01

213

Distributed Model Predictive Control for Dynamic Supply Chain Management

The purpose of this paper is to demonstrate the application of a recently developed theory for distributed nonlinear model predictive control (NMPC) to a promising and exciting future domain for NMPC: dy- namic management of supply chain networks. Recent work by the first author provides a distributed implementation of NMPC for application in large scale systems comprised of cooperative dynamic

William B. Dunbar; S. Desa

214

A predictive estimator of finite population mean using nonparametric regression

The paper considers the problem of estimating the population mean using auxiliary information. We propose a new model-based\\u000a estimator of the population mean, based on local polynomial regression. This estimator exhibits several attractive properties\\u000a under the model-based approach. The estimator is compared to a number of methods which have been proposed in the literature\\u000a via a simulation study based on

M. Rueda; I. R. Sánchez-Borrego

2009-01-01

215

NASA Technical Reports Server (NTRS)

Monte Carlo studies using population models intended to represent response surface applications are reported. Simulated experiments were generated by adding pseudo random normally distributed errors to population values to generate observations. Model equations were fitted to the observations and the decision procedure was used to delete terms. Comparison of values predicted by the reduced models with the true population values enabled the identification of deletion strategies that are approximately optimal for minimizing prediction errors.

Holms, A. G.

1974-01-01

216

Survival and Population Dynamics of the Marabou Stork in an Isolated Population, Swaziland

Investigating the ecology of long lived birds is particularly challenging owing to the time scales involved. Here an analysis is presented of a long term study of the survival and population dynamics of the marabou stork (Leptoptilos crumeniferus), a wide ranging scavenging bird from Sub-Saharan Africa. Using resightings data of tagged nestlings and free flying birds we show that the stork population can be divided into three general life stages with unique survival probabilities and fecundities. Fecundity of the storks is inversely related to rainfall during their breeding season. Corroborative evidence for a metapopulation structure is discussed highlighting the impact of the Swaziland birds on the ecology of the species in the broader region. The importance of tag loss or illegibility over time is highlighted. Clearly, any attempt at conserving a species will require a detailed understanding of its population structure, of the sort examined here.

Monadjem, Ara; Kane, Adam; Botha, Andre; Dalton, Desire; Kotze, Antoinette

2012-01-01

217

Studying physiology and pathophysiology over a broad population for long periods of time is difficult primarily because collecting human physiologic data can be intrusive, dangerous, and expensive. One solution is to use data that have been collected for a different purpose. Electronic health record (EHR) data promise to support the development and testing of mechanistic physiologic models on diverse populations and allow correlation with clinical outcomes, but limitations in the data have thus far thwarted such use. For example, using uncontrolled population-scale EHR data to verify the outcome of time dependent behavior of mechanistic, constructive models can be difficult because: (i) aggregation of the population can obscure or generate a signal, (ii) there is often no control population with a well understood health state, and (iii) diversity in how the population is measured can make the data difficult to fit into conventional analysis techniques. This paper shows that it is possible to use EHR data to test a physiological model for a population and over long time scales. Specifically, a methodology is developed and demonstrated for testing a mechanistic, time-dependent, physiological model of serum glucose dynamics with uncontrolled, population-scale, physiological patient data extracted from an EHR repository. It is shown that there is no observable daily variation the normalized mean glucose for any EHR subpopulations. In contrast, a derived value, daily variation in nonlinear correlation quantified by the time-delayed mutual information (TDMI), did reveal the intuitively expected diurnal variation in glucose levels amongst a random population of humans. Moreover, in a population of continuously (tube) fed patients, there was no observable TDMI-based diurnal signal. These TDMI-based signals, via a glucose insulin model, were then connected with human feeding patterns. In particular, a constructive physiological model was shown to correctly predict the difference between the general uncontrolled population and a subpopulation whose feeding was controlled.

Albers, D. J.; Hripcsak, George; Schmidt, Michael

2012-01-01

218

Assessing predictability of a hydrological stochastic-dynamical system

NASA Astrophysics Data System (ADS)

The water cycle includes the processes with different memory that creates potential for predictability of hydrological system based on separating its long and short memory components and conditioning long-term prediction on slower evolving components (similar to approaches in climate prediction). In the face of the Panta Rhei IAHS Decade questions, it is important to find a conceptual approach to classify hydrological system components with respect to their predictability, define predictable/unpredictable patterns, extend lead-time and improve reliability of hydrological predictions based on the predictable patterns. Representation of hydrological systems as the dynamical systems subjected to the effect of noise (stochastic-dynamical systems) provides possible tool for such conceptualization. A method has been proposed for assessing predictability of hydrological system caused by its sensitivity to both initial and boundary conditions. The predictability is defined through a procedure of convergence of pre-assigned probabilistic measure (e.g. variance) of the system state to stable value. The time interval of the convergence, that is the time interval during which the system losses memory about its initial state, defines limit of the system predictability. The proposed method was applied to assess predictability of soil moisture dynamics in the Nizhnedevitskaya experimental station (51.516N; 38.383E) located in the agricultural zone of the central European Russia. A stochastic-dynamical model combining a deterministic one-dimensional model of hydrothermal regime of soil with a stochastic model of meteorological inputs was developed. The deterministic model describes processes of coupled heat and moisture transfer through unfrozen/frozen soil and accounts for the influence of phase changes on water flow. The stochastic model produces time series of daily meteorological variables (precipitation, air temperature and humidity), whose statistical properties are similar to those of the corresponding series of the actual data measured at the station. Beginning from the initial conditions and being forced by Monte-Carlo generated synthetic meteorological series, the model simulated diverging trajectories of soil moisture characteristics (water content of soil column, moisture of different soil layers, etc.). Limit of predictability of the specific characteristic was determined through time of stabilization of variance of the characteristic between the trajectories, as they move away from the initial state. Numerical experiments were carried out with the stochastic-dynamical model to analyze sensitivity of the soil moisture predictability assessments to uncertainty in the initial conditions, to determine effects of the soil hydraulic properties and processes of soil freezing on the predictability. It was found, particularly, that soil water content predictability is sensitive to errors in the initial conditions and strongly depends on the hydraulic properties of soil under both unfrozen and frozen conditions. Even if the initial conditions are "well-established", the assessed predictability of water content of unfrozen soil does not exceed 30-40 days, while for frozen conditions it may be as long as 3-4 months. The latter creates opportunity for utilizing the autumn water content of soil as the predictor for spring snowmelt runoff in the region under consideration.

Gelfan, Alexander

2014-05-01

219

Macroscopic law of conservation revealed in the population dynamics of Toll-like receptor signaling

Stimulating the receptors of a single cell generates stochastic intracellular signaling. The fluctuating response has been attributed to the low abundance of signaling molecules and the spatio-temporal effects of diffusion and crowding. At population level, however, cells are able to execute well-defined deterministic biological processes such as growth, division, differentiation and immune response. These data reflect biology as a system possessing microscopic and macroscopic dynamics. This commentary discusses the average population response of the Toll-like receptor (TLR) 3 and 4 signaling. Without requiring detailed experimental data, linear response equations together with the fundamental law of information conservation have been used to decipher novel network features such as unknown intermediates, processes and cross-talk mechanisms. For single cell response, however, such simplicity seems far from reality. Thus, as observed in any other complex systems, biology can be considered to possess order and disorder, inheriting a mixture of predictable population level and unpredictable single cell outcomes.

2011-01-01

220

Plasmodium vivax Population Structure and Transmission Dynamics in Sabah Malaysia

Despite significant progress in the control of malaria in Malaysia, the complex transmission dynamics of P. vivax continue to challenge national efforts to achieve elimination. To assess the impact of ongoing interventions on P. vivax transmission dynamics in Sabah, we genotyped 9 short tandem repeat markers in a total of 97 isolates (8 recurrences) from across Sabah, with a focus on two districts, Kota Marudu (KM, n?=?24) and Kota Kinabalu (KK, n?=?21), over a 2 year period. STRUCTURE analysis on the Sabah-wide dataset demonstrated multiple sub-populations. Significant differentiation (FST ?=?0.243) was observed between KM and KK, located just 130 Km apart. Consistent with low endemic transmission, infection complexity was modest in both KM (mean MOI ?=?1.38) and KK (mean MOI ?=?1.19). However, population diversity remained moderate (HE ?=?0.583 in KM and HE ?=?0.667 in KK). Temporal trends revealed clonal expansions reflecting epidemic transmission dynamics. The haplotypes of these isolates declined in frequency over time, but persisted at low frequency throughout the study duration. A diverse array of low frequency isolates were detected in both KM and KK, some likely reflecting remnants of previous expansions. In accordance with clonal expansions, high levels of Linkage Disequilibrium (IAS >0.5 [P<0.0001] in KK and KM) declined sharply when identical haplotypes were represented once (IAS ?=?0.07 [P?=?0.0076] in KM, and IAS?=?-0.003 [P?=?0.606] in KK). All 8 recurrences, likely to be relapses, were homologous to the prior infection. These recurrences may promote the persistence of parasite lineages, sustaining local diversity. In summary, Sabah's shrinking P. vivax population appears to have rendered this low endemic setting vulnerable to epidemic expansions. Migration may play an important role in the introduction of new parasite strains leading to epidemic expansions, with important implications for malaria elimination.

Abdullah, Noor Rain; Barber, Bridget E.; William, Timothy; Norahmad, Nor Azrina; Satsu, Umi Rubiah; Muniandy, Prem Kumar; Ismail, Zakiah; Grigg, Matthew J.; Jelip, Jenarun; Piera, Kim; von Seidlein, Lorenz; Yeo, Tsin W.; Anstey, Nicholas M.; Price, Ric N.; Auburn, Sarah

2013-01-01

221

Background Nanoparticle-protein corona complex formation involves absorption of protein molecules onto nanoparticle surfaces in a physiological environment. Understanding the corona formation process is crucial in predicting nanoparticle behavior in biological systems, including applications of nanotoxicology and development of nano drug delivery platforms. Method This paper extends the modeling work in to derive a mathematical model describing the dynamics of nanoparticle corona complex formation from population balance equations. We apply nonlinear dynamics techniques to derive analytical results for the composition of nanoparticle-protein corona complex, and validate our results through numerical simulations. Results The model presented in this paper exhibits two phases of corona complex dynamics. In the first phase, proteins rapidly bind to the free surface of nanoparticles, leading to a metastable composition. During the second phase, continuous association and dissociation of protein molecules with nanoparticles slowly changes the composition of the corona complex. Given sufficient time, composition of the corona complex reaches an equilibrium state of stable composition. We find analytical approximate formulae for metastable and stable compositions of corona complex. Our formulae are very well-structured to clearly identify important parameters determining corona composition. Conclusion The dynamics of biocorona formation constitute vital aspect of interactions between nanoparticles and living organisms. Our results further understanding of these dynamics through quantitation of experimental conditions, modeling results for in vitro systems to better predict behavior for in vivo systems. One potential application would involve a single cell culture medium related to a complex protein medium, such as blood or tissue fluid.

Darabi Sahneh, Faryad; Scoglio, Caterina; Riviere, Jim

2013-01-01

222

Orbit determination and prediction study for Dynamic Explorer 2

NASA Technical Reports Server (NTRS)

Definitive orbit determination accuracy and orbit prediction accuracy for the Dynamic Explorer-2 (DE-2) are studied using the trajectory determination system for the period within six weeks of spacecraft reentry. Baseline accuracies using standard orbit determination models and methods are established. A promising general technique for improving the orbit determination accuracy of high drag orbits, estimation of random drag variations at perigee passages, is investigated. This technique improved the fit to the tracking data by a factor of five and improved the solution overlap consistency by a factor of two during a period in which the spacecraft perigee altitude was below 200 kilometers. The results of the DE-2 orbit predictions showed that improvement in short term prediction accuracy reduces to the problem of predicting future drag scale factors: the smoothness of the solar 10.7 centimeter flux density suggests that this may be feasible.

Smith, R. L.; Nakai, Y.; Doll, C. E.

1983-01-01

223

Dynamical systems modeling was used to analyze fluctuations in the pain prediction process of people with rheumatoid arthritis. 170 people diagnosed with rheumatoid arthritis completed 29 consecutive days of diaries. Difference scores between pain predictions and next-day pain experience ratings provided a time series of pain prediction accuracy. Pain prediction accuracy oscillated over time. The oscillation amplitude was larger at the start of the diary than at the end, which indicates damping toward more accurate predictions. State-level psychological characteristics moderated the damping pattern such that the oscillations for patients with lower negative affect and higher pain control damped more quickly than the oscillations for their counterparts. Those findings suggest that low negative affect and high pain control generally contributed to a more accurate pain prediction process in the chronically ill. Positive affect did not differentiate the damping pattern but, within each oscillation cycle, patients with higher positive affect spent more time making inaccurate predictions than their counterparts. The current analyses highlight the need to account for change in data through dynamical modeling, which cannot be fully observed through traditional statistical techniques.

Finan, Patrick H.; Hessler, Eric E.; Amazeen, Polemnia G.; Butner, Jonathan; Zautra, Alex J.; Tennen, Howard

2011-01-01

224

Evolutionary game dynamics in populations with different learners.

We study evolutionary game theory in a setting where individuals learn from each other. We extend the traditional approach by assuming that a population contains individuals with different learning abilities. In particular, we explore the situation where individuals have different search spaces, when attempting to learn the strategies of others. The search space of an individual specifies the set of strategies learnable by that individual. The search space is genetically given and does not change under social evolutionary dynamics. We introduce a general framework and study a specific example in the context of direct reciprocity. For this example, we obtain the counter intuitive result that cooperation can only evolve for intermediate benefit-to-cost ratios, while small and large benefit-to-cost ratios favor defection. Our paper is a step toward making a connection between computational learning theory and evolutionary game dynamics. PMID:22394652

Chatterjee, Krishnendu; Zufferey, Damien; Nowak, Martin A

2012-05-21

225

Population Dynamics and Range Expansion in Nine-Banded Armadillos

Understanding why certain species can successfully colonize new areas while others do not is a central question in ecology. The nine-banded armadillo (Dasypus novemcinctus) is a conspicuous example of a successful invader, having colonized much of the southern United States in the last 200 years. We used 15 years (1992–2006) of capture-mark-recapture data from a population of armadillos in northern Florida in order to estimate, and examine relationships among, various demographic parameters that may have contributed to this ongoing range expansion. Modeling across a range of values for ?, the probability of juveniles surviving in the population until first capture, we found that population growth rates varied from 0.80 for ??=?0.1, to 1.03 for ??=?1.0. Growth rates approached 1.0 only when ? ?0.80, a situation that might not occur commonly because of the high rate of disappearance of juveniles. Net reproductive rate increased linearly with ?, but life expectancy (estimated at 3 years) was independent of ?. We also found that growth rates were lower during a 3-year period of hardwood removal that removed preferred habitat than in the years preceding or following. Life-table response experiment (LTRE) analysis indicated the decrease in growth rate during logging was primarily due to changes in survival rates of adults. Likewise, elasticity analyses of both deterministic and stochastic population growth rates revealed that survival parameters were more influential on population growth than were those related to reproduction. Collectively, our results are consistent with recent theories regarding biological invasions which posit that populations no longer at the leading edge of range expansion do not exhibit strong positive growth rates, and that high reproductive output is less critical in predicting the likelihood of successful invasion than are life-history strategies that emphasize allocation of resources to future, as opposed to current, reproduction.

Loughry, William J.; Perez-Heydrich, Carolina; McDonough, Colleen M.; Oli, Madan K.

2013-01-01

226

Epoch Lifetimes in the Dynamics of a Competing Population

NASA Astrophysics Data System (ADS)

We propose a dynamical model of a competing population whose agents have a tendency to balance their decisions in time. The model is applicable to financial markets in which the agents trade with finite capital, or other multiagent systems such as routers in communication networks attempting to transmit multiclass traffic in a fair way. We find an oscillatory behavior due to the segregation of agents into two groups. Each group remains winning over epochs. The aggregation of smart agents is able to explain the lifetime distribution of epochs to 8 decades of probability. The existence of the super agents further refines the lifetime distribution of short epochs.

Yeung, C. H.; Ma, Y. P.; Wong, K. Y. Michael

227

Periodically varying externally imposed environmental effects on population dynamics

NASA Astrophysics Data System (ADS)

Effects of externally imposed periodic changes in the environment on population dynamics are studied with the help of a simple model. The environmental changes are represented by the temporal and spatial dependence of the competition terms in a standard equation of evolution. Possible applications of the analysis are on the one hand to bacteria in Petri dishes and on the other to rodents in the context of the spread of the Hantavirus epidemic. The analysis shows that spatiotemporal structures emerge, with interesting features which depend on the interplay of separately controllable aspects of the externally imposed environmental changes.

Ballard, M.; Kenkre, V. M.; Kuperman, M. N.

2004-09-01

228

Population dynamic of algae and bacteria in an oxidation channel.

A study on algae and bacteria population changes, as a function of time, was carried out in a pilot scale oxidation channel bioreactor using a carrousel system. Total Coliforms, Pseudomonas aeruginosa, and Streptococcus faecalis, the most common bacteria found in sewage, Scenedesmus obliquus and Chlorella vulgaris were the microalgae considered in this work. Physicochemical parameters such as COD, BOD, Chlorophyll a, nitrogen, and phosphorous compounds were studied and determined during the experiments. It was demonstrated that the level of wastewater contamination could be predicted based on the bacterial and algae composition. The relationships between the algae and bacteria population, and the variation of these microorganism populations as a measurement of the level of purification were established. The oxidation channel was able to remove a considerable amount of organic matter and pathogenic microorganisms in a relatively short time. The nitrification process could not be measured. The increase in the relative concentration of microalgae contributed toward improving the global efficiency of the system as well as reducing the pathogenic bacteria population. PMID:12716074

O'Farrill, N E; Travieso, L; Benítez, F; Bécares, E; Romo, S; Borja, R; Weiland, P; Sánchez, E

2003-04-01

229

Dispersal differences predict population genetic structure in Mormon crickets.

Research investigating the geographical context of speciation has primarily focused on abiotic factors such as the role of Pleistocene glacial cycles, or geotectonic events. Few study systems allow a direct comparison of how biological differences, such as dispersal behaviour, affect population genetic structure of organisms that were subdivided during the Pleistocene. Mormon crickets exist in solitary and gregarious 'phases', which broadly correspond with an east-west mtDNA division across the Rocky Mountains. Gregarious individuals form bands that can move up to 2 km daily. This study assessed whether population genetic structure results mainly from deep Pleistocene vicariance or if we can also detect more recent genetic patterns due to phase and dispersal differences superimposed on the older, deeper divisions. We found that separation in refugia was a more important influence on genetic divergence than phase, with the Rockies acting as a barrier that separated Mormon cricket populations into eastern and western refugia during Pleistocene glacial cycles. However, patterns of isolation by distance differ between eastern and western clades for both mitochondrial and nuclear DNA, with greater divergence within the eastern, solitary clade. An mtDNA haplotype mismatch distribution is compatible with historical population expansion in the western clade but not in the eastern clade. A persistent (and possibly sex-biased) difference in dispersal ability has most likely influenced the greater population genetic structure seen in the eastern clade, emphasizing the importance of the interaction of Quaternary climate fluctuations and geography with biotic factors in producing the patterns of genetic subdivision observed today. PMID:17498233

Bailey, Nathan W; Gwynne, Darryl T; Ritchie, Michael G

2007-05-01

230

Population dynamics in the presence of quasispecies effects and changing environments

NASA Astrophysics Data System (ADS)

This thesis explores how natural selection acts on organisms such as viruses that have either highly error-prone reproduction or face variable environmental conditions or both. By modeling population dynamics under these conditions, we gain a better understanding of the selective forces at work, both in our simulations and hopefully also in real organisms. With an understanding of the important factors in natural selection we can forecast not only the immediate fate of an existing population but also in what directions such a population might evolve in the future. We demonstrate that the concept of a quasispecies is relevant to evolution in a neutral fitness landscape. Motivated by RNA viruses such as HIV, we use RNA secondary structure as our model system and find that quasispecies effects arise both rapidly and in realistically small populations. We discover that the evolutionary effects of neutral drift, punctuated equilibrium and the selection for mutational robustness extend to the concept of a quasispecies. In our study of periodic environments, we consider the tradeoffs faced by quasispecies in adapting to environmental change. We develop an analytical model to predict whether evolution favors short-term or long-term adaptation and validate our model through simulation. Our results bear directly on the population dynamics of viruses such as West Nile that alternate between two host species. More generally, we discover that a selective pressure exists under these conditions to fuse or split genes with complementary environmental functions. Lastly, we study the general effects of frequency-dependent selection on two strains competing in a periodic environment. Under very general assumptions, we prove that stable coexistence rather than extinction is the likely outcome. The population dynamics of this system may be as simple as stable equilibrium or as complex as deterministic chaos.

Forster, Robert Burke

231

Individual-based approach to fish population dynamics: An overview

Individual-based simulation modeling tracks the attributes of individual fish through time and aggregates them to generate insights into population function. By seeking to understand how fish of differing phenotypes respond to variations in physicochemical and biological environments, analysts hope to improve predictions of population trends. A review of eight accompanying papers highlights the promise and current limitations of the individual-based approach. Among the challenges to be faced are accurately representing feeding encounter rates, extending models to account for spatial heterogeneity and transgenerational responses, dealing with practical limits to the amount of data on individuals that can be measured and managed, more fully conceptionalizing natural processes, and acquiring appropriate field data with which to formulate and test the models. 16 refs., 1 tab.

Van Winkle, W.; Rose, K.A. (Oak Ridge National Lab., TN (United States)); Chambers, R.C. (Huntsman Marine Science Centre, New Brunswick (Canada))

1993-05-01

232

Population dynamics of minimally cognitive individuals. Part 2: Dynamics of time-dependent knowledge

The dynamical principle for a population of interacting individuals with mutual pairwise knowledge, presented by the author in a previous paper for the case of constant knowledge, is extended to include the possibility that the knowledge is time-dependent. Several mechanisms are presented by which the mutual knowledge, represented by a matrix K, can be altered, leading to dynamical equations for K(t). The author presents various examples of the transient and long time asymptotic behavior of K(t) for populations of relatively isolated individuals interacting infrequently in local binary collisions. Among the effects observed in the numerical experiments are knowledge diffusion, learning transients, and fluctuating equilibria. This approach will be most appropriate to small populations of complex individuals such as simple animals, robots, computer networks, agent-mediated traffic, simple ecosystems, and games. Evidence of metastable states and intermittent switching leads them to envision a spectroscopy associated with such transitions that is independent of the specific physical individuals and the population. Such spectra may serve as good lumped descriptors of the collective emergent behavior of large classes of populations in which mutual knowledge is an important part of the dynamics.

Schmieder, R.W.

1995-07-01

233

A correction method suitable for dynamical seasonal prediction

NASA Astrophysics Data System (ADS)

Based on the hindcast results of summer rainfall anomalies over China for the period 1981-2000 by the Dynamical Climate Prediction System (IAP-DCP) developed by the Institute of Atmospheric Physics, a correction method that can account for the dependence of model's systematic biases on SST anomalies is proposed. It is shown that this correction method can improve the hindcast skill of the IAP-DCP for summer rainfall anomalies over China, especially in western China and southeast China, which may imply its potential application to real-time seasonal prediction.

Chen, H.; Lin, Z. H.

2006-05-01

234

Prediction of Muscle Performance During Dynamic Repetitive Exercise

NASA Technical Reports Server (NTRS)

A method for predicting human muscle performance was developed. Eight test subjects performed a repetitive dynamic exercise to failure using a Lordex spinal machine. Electromyography (EMG) data was collected from the erector spinae. Evaluation of the EMG data using a 5th order Autoregressive (AR) model and statistical regression analysis revealed that an AR parameter, the mean average magnitude of AR poles, can predict performance to failure as early as the second repetition of the exercise. Potential applications to the space program include evaluating on-orbit countermeasure effectiveness, maximizing post-flight recovery, and future real-time monitoring capability during Extravehicular Activity.

Byerly, D. L.; Byerly, K. A.; Sognier, M. A.; Squires, W. G.

2002-01-01

235

Dynamics of anticipatory mechanisms during predictive context processing

We employed an EEG paradigm manipulating predictive context to dissociate the neural dynamics of anticipatory mechanisms. Subjects either detected random targets or targets preceded by a predictive sequence of three distinct stimuli. The last stimulus in the 3-stimulus sequence (decisive stimulus) did not require any motor response but 100% predicted a subsequent target event. We show that predictive context optimizes target processing via the deployment of distinct anticipatory mechanisms at different times of the predictive sequence. Prior to the occurrence of the decisive stimulus, enhanced attentional preparation was manifested by reductions in the alpha oscillatory activities over visual cortices, resulting in facilitation of processing of the decisive stimulus. Conversely, the subsequent 100% predictable target event did not reveal deployment of attentional preparation in the visual cortices, but elicited enhanced motor preparation mechanisms, indexed by an increased contingent negative variation (CNV) and reduced mu oscillatory activities over motor cortices before movement onset. The present results provide evidence that anticipation operates via different attentional and motor preparation mechanisms by selectively pre-activating task-dependent brain areas as predictability gradually increases.

Bidet-Caulet, Aurelie; Barbe, Pierre-Guillaume; Roux, Sylvie; Viswanath, Humsini; Barthelemy, Catherine; Bruneau, Nicole; Knight, Robert T.; Bonnet-Brilhault, Frederique

2012-01-01

236

Impact of Simian Immunodeficiency Virus Infection on Chimpanzee Population Dynamics

Like human immunodeficiency virus type 1 (HIV-1), simian immunodeficiency virus of chimpanzees (SIVcpz) can cause CD4+ T cell loss and premature death. Here, we used molecular surveillance tools and mathematical modeling to estimate the impact of SIVcpz infection on chimpanzee population dynamics. Habituated (Mitumba and Kasekela) and non-habituated (Kalande) chimpanzees were studied in Gombe National Park, Tanzania. Ape population sizes were determined from demographic records (Mitumba and Kasekela) or individual sightings and genotyping (Kalande), while SIVcpz prevalence rates were monitored using non-invasive methods. Between 2002–2009, the Mitumba and Kasekela communities experienced mean annual growth rates of 1.9% and 2.4%, respectively, while Kalande chimpanzees suffered a significant decline, with a mean growth rate of ?6.5% to ?7.4%, depending on population estimates. A rapid decline in Kalande was first noted in the 1990s and originally attributed to poaching and reduced food sources. However, between 2002–2009, we found a mean SIVcpz prevalence in Kalande of 46.1%, which was almost four times higher than the prevalence in Mitumba (12.7%) and Kasekela (12.1%). To explore whether SIVcpz contributed to the Kalande decline, we used empirically determined SIVcpz transmission probabilities as well as chimpanzee mortality, mating and migration data to model the effect of viral pathogenicity on chimpanzee population growth. Deterministic calculations indicated that a prevalence of greater than 3.4% would result in negative growth and eventual population extinction, even using conservative mortality estimates. However, stochastic models revealed that in representative populations, SIVcpz, and not its host species, frequently went extinct. High SIVcpz transmission probability and excess mortality reduced population persistence, while intercommunity migration often rescued infected communities, even when immigrating females had a chance of being SIVcpz infected. Together, these results suggest that the decline of the Kalande community was caused, at least in part, by high levels of SIVcpz infection. However, population extinction is not an inevitable consequence of SIVcpz infection, but depends on additional variables, such as migration, that promote survival. These findings are consistent with the uneven distribution of SIVcpz throughout central Africa and explain how chimpanzees in Gombe and elsewhere can be at equipoise with this pathogen.

Rudicell, Rebecca S.; Holland Jones, James; Wroblewski, Emily E.; Learn, Gerald H.; Li, Yingying; Robertson, Joel D.; Greengrass, Elizabeth; Grossmann, Falk; Kamenya, Shadrack; Pintea, Lilian; Mjungu, Deus C.; Lonsdorf, Elizabeth V.; Mosser, Anna; Lehman, Clarence; Collins, D. Anthony; Keele, Brandon F.; Goodall, Jane; Hahn, Beatrice H.; Pusey, Anne E.; Wilson, Michael L.

2010-01-01

237

Population-Based Prediction Equations for Neurobehavioral Tests

Quantitative assessment of neurobehavioral function appraises brain injury from inhaled chemicals. Contemporary predicted values for tests useful in epidemiological studies have been developed with step-wise linear regression. In instances in which age and education do not match those of control groups, these equations assist in the interpretation of results of examinations of individual subjects and pilot studies. In this study,

Kaye H. Kilburn; John C. Thornton; Brad Hanscom

1998-01-01

238

Allele dynamics plots for the study of evolutionary dynamics in viral populations

Phylodynamic techniques combine epidemiological and genetic information to analyze the evolutionary and spatiotemporal dynamics of rapidly evolving pathogens, such as influenza A or human immunodeficiency viruses. We introduce ‘allele dynamics plots’ (AD plots) as a method for visualizing the evolutionary dynamics of a gene in a population. Using AD plots, we propose how to identify the alleles that are likely to be subject to directional selection. We analyze the method’s merits with a detailed study of the evolutionary dynamics of seasonal influenza A viruses. AD plots for the major surface protein of seasonal influenza A (H3N2) and the 2009 swine-origin influenza A (H1N1) viruses show the succession of substitutions that became fixed in the evolution of the two viral populations. They also allow the early identification of those viral strains that later rise to predominance, which is important for the problem of vaccine strain selection. In summary, we describe a technique that reveals the evolutionary dynamics of a rapidly evolving population and allows us to identify alleles and associated genetic changes that might be under directional selection. The method can be applied for the study of influenza A viruses and other rapidly evolving species or viruses.

Steinbruck, Lars; McHardy, Alice Carolyn

2011-01-01

239

Human mobility patterns predict divergent epidemic dynamics among cities.

The epidemic dynamics of infectious diseases vary among cities, but it is unclear how this is caused by patterns of infectious contact among individuals. Here, we ask whether systematic differences in human mobility patterns are sufficient to cause inter-city variation in epidemic dynamics for infectious diseases spread by casual contact between hosts. We analyse census data on the mobility patterns of every full-time worker in 48 Canadian cities, finding a power-law relationship between population size and the level of organization in mobility patterns, where in larger cities, a greater fraction of workers travel to work in a few focal locations. Similarly sized cities also vary in the level of organization in their mobility patterns, equivalent on average to the variation expected from a 2.64-fold change in population size. Systematic variation in mobility patterns is sufficient to cause significant differences among cities in infectious disease dynamics-even among cities of the same size-according to an individual-based model of airborne pathogen transmission parametrized with the mobility data. This suggests that differences among cities in host contact patterns are sufficient to drive differences in infectious disease dynamics and provides a framework for testing the effects of host mobility patterns in city-level disease data. PMID:23864593

Dalziel, Benjamin D; Pourbohloul, Babak; Ellner, Stephen P

2013-09-01

240

[Dynamic prediction and evaluation method of maize chilling damage].

In order to prevent and alleviate the chilling damage of maize, a dynamic prediction and evaluation method on its emergence and loss was developed by using an improved dynamic model of maize growth and dry matter accumulation, and new parameters and damage indices. The method followed the thermal constant theory and the principles of maize biology and ecology, utilized relative accumulated temperature as the leading factor of maize development stage prediction and damage discretion, and took dry matter shortage rate as the loss rate of the damage. The results of test and tryout showed that the method was objective and applicable, and suited for various places of Northeastern China through areal adjustment of parameters and indices. PMID:17209391

Ma, Shuqing; Liu, Yuying; Wang, Qi

2006-10-01

241

Low-dimensional modelling and prediction in fluid dynamics

NASA Technical Reports Server (NTRS)

Research into the development of a simplified, low-dimensional, state-variable model for a fluid dynamics system is discussed. The model would be capable of predicting the state of the system in as nearly real time as possible and would be suitable for implementation in a control loop. It is noted that state-variable modeling has an advantage for real-time health monitoring and control application over the Navier-Stokes equations since the latter require an enormous amount of real time. In this study, a dynamic procedure is developed for modeling and prediction using the CFD data generated for this model centerbody-combustor configuration. Some experiences with the NASA data available for the SSME are also reported. Application of this procedure to pressure and velocity measurements in an actual wind-tunnel experiment is described, and the applicability of the approach to health monitoring is considered.

Ghia, U.; Osswald, G. A.; Noll, C.

1990-01-01

242

Rational prediction with molecular dynamics for hit identification.

Although the motions of proteins are fundamental for their function, for pragmatic reasons, the consideration of protein elasticity has traditionally been neglected in drug discovery and design. This review details protein motion, its relevance to biomolecular interactions and how it can be sampled using molecular dynamics simulations. Within this context, two major areas of research in structure-based prediction that can benefit from considering protein flexibility, binding site detection and molecular docking, are discussed. Basic classification metrics and statistical analysis techniques, which can facilitate performance analysis, are also reviewed. With hardware and software advances, molecular dynamics in combination with traditional structure-based prediction methods can potentially reduce the time and costs involved in the hit identification pipeline. PMID:23110535

Nichols, Sara E; Swift, Robert V; Amaro, Rommie E

2012-01-01

243

Low-dimensional modelling and prediction in fluid dynamics

NASA Astrophysics Data System (ADS)

Research into the development of a simplified, low-dimensional, state-variable model for a fluid dynamics system is discussed. The model would be capable of predicting the state of the system in as nearly real time as possible and would be suitable for implementation in a control loop. It is noted that state-variable modeling has an advantage for real-time health monitoring and control application over the Navier-Stokes equations since the latter require an enormous amount of real time. In this study, a dynamic procedure is developed for modeling and prediction using the CFD data generated for this model centerbody-combustor configuration. Some experiences with the NASA data available for the SSME are also reported. Application of this procedure to pressure and velocity measurements in an actual wind-tunnel experiment is described, and the applicability of the approach to health monitoring is considered.

Ghia, U.; Osswald, G. A.; Noll, C.

244

A dynamic programming algorithm for RNA structure prediction including pseudoknots

We describe a dynamic programming algorithm for predicting optimal RNA secondary structure, including pseudoknots. The algorithm has a worst case complexity of ${\\\\cal O}(N^6)$ in time and ${\\\\cal O}(N^4)$ in storage. The description of the algorithm is complex, which led us to adopt a useful graphical representation (Feynman diagrams) borrowed from quantum field theory. We present an implementation of the

Elena Rivas; Sean R. Eddy

1998-01-01

245

Radon plays an important role for human exposure to natural sources of ionizing radiation. The aim of this article is to compare two approaches to estimate mean radon exposure in the Swiss population: model-based predictions at individual level and measurement-based predictions based on measurements aggregated at municipality level. A nationwide model was used to predict radon levels in each household and for each individual based on the corresponding tectonic unit, building age, building type, soil texture, degree of urbanization, and floor. Measurement-based predictions were carried out within a health impact assessment on residential radon and lung cancer. Mean measured radon levels were corrected for the average floor distribution and weighted with population size of each municipality. Model-based predictions yielded a mean radon exposure of the Swiss population of 84.1 Bq/m(3) . Measurement-based predictions yielded an average exposure of 78 Bq/m(3) . This study demonstrates that the model- and the measurement-based predictions provided similar results. The advantage of the measurement-based approach is its simplicity, which is sufficient for assessing exposure distribution in a population. The model-based approach allows predicting radon levels at specific sites, which is needed in an epidemiological study, and the results do not depend on how the measurement sites have been selected. PMID:23464847

Hauri, D D; Huss, A; Zimmermann, F; Kuehni, C E; Röösli, M

2013-10-01

246

A single climate driver has direct and indirect effects on insect population dynamics.

Weather drives population dynamics directly, through effects on vital rates, or indirectly, through effects on the population's competitors, predators or prey and thence on vital rates. Indirect effects may include non-additive interactions with density dependence. Detection of climate drivers is critical to predicting climate change effects, but identification of potential drivers may depend on knowing the underlying mechanisms. For the butterfly Speyeria mormonia, one climate driver, snow melt date, has multiple effects on population growth. Snow melt date in year t has density-dependent indirect effects. Through frost effects, early snow melt decreases floral resources, thence per-capita nectar availability, which determines fecundity in the lab. Snow melt date in year t?+?1 has density-independent direct effects. These effects explain 84% of the variation in population growth rate. One climate parameter thus has multiple effects on the dynamics of a species with non-overlapping generations, with one effect not detectable without understanding the underlying mechanism. PMID:22414183

Boggs, Carol L; Inouye, David W

2012-05-01

247

Two-Speed Gearbox Dynamic Simulation Predictions and Test Validation

NASA Technical Reports Server (NTRS)

Dynamic simulations and experimental validation tests were performed on a two-stage, two-speed gearbox as part of the drive system research activities of the NASA Fundamental Aeronautics Subsonics Rotary Wing Project. The gearbox was driven by two electromagnetic motors and had two electromagnetic, multi-disk clutches to control output speed. A dynamic model of the system was created which included a direct current electric motor with proportional-integral-derivative (PID) speed control, a two-speed gearbox with dual electromagnetically actuated clutches, and an eddy current dynamometer. A six degree-of-freedom model of the gearbox accounted for the system torsional dynamics and included gear, clutch, shaft, and load inertias as well as shaft flexibilities and a dry clutch stick-slip friction model. Experimental validation tests were performed on the gearbox in the NASA Glenn gear noise test facility. Gearbox output speed and torque as well as drive motor speed and current were compared to those from the analytical predictions. The experiments correlate very well with the predictions, thus validating the dynamic simulation methodologies.

Lewicki, David G.; DeSmidt, Hans; Smith, Edward C.; Bauman, Steven W.

2010-01-01

248

Constant immigration can stabilize population size fluctuations but its effects on extinction remain unexplored. We show that constant immigration significantly reduced extinction in fruitfly populations with relatively stable or unstable dynamics. In unstable populations with oscillations of amplitude around 1.5 times the mean population size, persistence and constancy were unrelated. Low immigration enhanced persistence without affecting constancy whereas high immigration increased constancy without enhancing persistence. In relatively stable populations with erratic fluctuations of amplitude close to the mean population size, both low and high immigration enhanced persistence. In these populations, the amplitude of fluctuations relative to mean population size went down due to immigration, and their dynamics were altered to low-period cycles. The effects of immigration on the population size distribution and intrinsic dynamics of stable versus unstable populations differed considerably, suggesting that the mechanisms by which immigration reduced extinction risk depended on underlying dynamics in complex ways.

Dey, Snigdhadip; Joshi, Amitabh

2013-01-01

249

Quantum dynamics and entanglement in coherent transport of atomic population

NASA Astrophysics Data System (ADS)

In this work we look at the quantum dynamics of the process known as either transport without transit, or coherent transfer of atomic population, of a Bose–Einstein condensate from one well of a lattice potential to another, non-adjacent well, without macroscopic occupation of the well between the two. This process has previously been analysed and in this work we extend those analyses by considering the effects of quantum statistics on the dynamics and entanglement properties of the condensate modes in the two relevant wells. In order to do this, we go beyond the mean-field analysis of the Gross–Pitaevskii type approach and utilize the phase-space stochastic methods so well known in quantum optics. In particular, we use the exact positive-P representation where it is suitable, and the approximate truncated Wigner representation otherwise. We find strong agreement between the results of these two methods, with the mean-field dynamics not depending on the initial quantum states of the trapped condensate. We find that the entanglement properties do depend strongly on the initial quantum states, with quantitatively different results found for coherent and Fock states. Comparison of the two methods gives us confidence that the truncated Wigner representation delivers accurate results for this system and is thus a useful method as the collisional nonlinearity increases and the positive-P results fail to converge.

Olsen, M. K.

2014-05-01

250

Predictability experiments using a low order empirically corrected dynamical model

NASA Technical Reports Server (NTRS)

It is generally accepted that day to day weather variations possess a finite range of predictability estimated to be approximately two weeks (e.g., Lorenz, 1965). However, considerable observational evidence points to the existence of a number of low frequency flow regimes which are potentially predictable beyond this limit. These include blocking events and teleconnection patterns such as those described in Wallace and Gutzler (1981). The problem of the predictability of such modes is addressed by employing a highly simplified dynamical model projected onto the modes of interest. These modes are computed from an empirical orthogonal function (EOF) analysis of 10-day averaged anomalies (deviations from the mean seasonal cycle) of the 500 mb stream function for the winters of 1967-76. The first three EOF's are associated with an index cycle and some of the teleconnection patterns. The fourth and ninth are related to North Pacific and North Atlantic blocking, respectively.

Schubert, S.

1984-01-01

251

Predictability of extreme seasonal precipitation using dynamical forecasting systems

NASA Astrophysics Data System (ADS)

While seasonal forecasts are often presented as anomaly sign or tercile probabilities,many users are more interested in the likelihood of an extreme season. The skill of Met Office dynamical ensemble forecast systems in predicting extremes has been assessed using the LEPS skill measure and compared with overall forecast skill. Assessments of retrospective forecast sets for each calendar month will be discussed. Extreme seasons here are defined as the wettest or driest 11% of seasons within a given climate period. Regional or global skill is measured by the number of model gridboxes within the selected region where the LEPS skill exceeds a given significance threshold, with thresholds evaluated using Monte Carlo experiments. Evidence of skill up to 6 months ahead will be shown for the Tropics, Europe and North America. The skill of predictions of extreme 3-month seasonal means has been found to be higher than the all-category skill of 3-month mean predictions in all these regions.

Colman, A. W.; Berrisford, P.; Davey, M. K.

2003-04-01

252

Macromolecular symmetric assembly prediction using swarm intelligence dynamic modeling.

Proteins often assemble in multimeric complexes to perform a specific biologic function. However, trapping these high-order conformations is difficult experimentally. Therefore, predicting how proteins assemble using in silico techniques can be of great help. The size of the associated conformational space and the fact that proteins are intrinsically flexible structures make this optimization problem extremely challenging. Nonetheless, known experimental spatial restraints can guide the search process, contributing to model biologically relevant states. We present here a swarm intelligence optimization protocol able to predict the arrangement of protein symmetric assemblies by exploiting a limited amount of experimental restraints and steric interactions. Importantly, within this scheme the native flexibility of each protein subunit is taken into account as extracted from molecular dynamics (MD) simulations. We show that this is a key ingredient for the prediction of biologically functional assemblies when, upon oligomerization, subunits explore activated states undergoing significant conformational changes. PMID:23810695

Degiacomi, Matteo T; Dal Peraro, Matteo

2013-07-01

253

Automated adaptive model inference to predict biological network dynamics

NASA Astrophysics Data System (ADS)

Dynamical models of cellular regulation often consist of large and intricate networks of interactions at the molecular scale. Since individual interaction parameters are usually difficult to measure, these parameters are often estimated implicitly, using statistical fits. This can lead to overfitting and degradation in the quality of models' predictions. Here we study phenomenological models that adapt their level of detail to the amount of available data, leading to accurate predictions even when microscopic details are not well understood. The model search is made computationally efficient by testing an ordered, nested set of models and by using a model class that can be solved using linear regression in log-space. We test the method on synthetic data and find that phenomenological models inferred this way often outperform detailed, ``correct'' molecular models in making predictions about responses of the system to signals yet unseen.

Daniels, Bryan; Nemenman, Ilya

2013-03-01

254

AN APPROACH TO PREDICT RISKS TO WILDLIFE POPULATIONS FROM MERCURY AND OTHER STRESSORS

255

Mysid Population Responses to Resource Limitation Differ from those Predicted by Cohort Studies

Effects of anthropogenic stressors on animal populations are often evaluated by assembling vital rate responses from isolated cohort studies into a single demographic model. However, models constructed from cohort studies are difficult to translate into ecological predictions be...

256

Predicting and understanding forest dynamics using a simple tractable model

The perfect-plasticity approximation (PPA) is an analytically tractable model of forest dynamics, defined in terms of parameters for individual trees, including allometry, growth, and mortality. We estimated these parameters for the eight most common species on each of four soil types in the US Lake states (Michigan, Wisconsin, and Minnesota) by using short-term (?15-year) inventory data from individual trees. We implemented 100-year PPA simulations given these parameters and compared these predictions to chronosequences of stand development. Predictions for the timing and magnitude of basal area dynamics and ecological succession on each soil were accurate, and predictions for the diameter distribution of 100-year-old stands were correct in form and slope. For a given species, the PPA provides analytical metrics for early-successional performance (H20, height of a 20-year-old open-grown tree) and late-successional performance (?*, equilibrium canopy height in monoculture). These metrics predicted which species were early or late successional on each soil type. Decomposing ?* showed that (i) succession is driven both by superior understory performance and superior canopy performance of late-successional species, and (ii) performance differences primarily reflect differences in mortality rather than growth. The predicted late-successional dominants matched chronosequences on xeromesic (Quercus rubra) and mesic (codominance by Acer rubrum and Acer saccharum) soil. On hydromesic and hydric soils, the literature reports that the current dominant species in old stands (Thuja occidentalis) is now failing to regenerate. Consistent with this, the PPA predicted that, on these soils, stands are now succeeding to dominance by other late-successional species (e.g., Fraxinus nigra, A. rubrum).

Purves, Drew W.; Lichstein, Jeremy W.; Strigul, Nikolay; Pacala, Stephen W.

2008-01-01

257

Bi-trophic food chain dynamics with multiple component populations.

Food web models describe the patterns of material and energy flow in communities. In classical food web models the state of each population is described by a single variable which represents, for instance, the biomass or the number of individuals that make up the population. However, in a number of models proposed recently in the literature the individual organisms consist of two components. In addition to the structural component there is an internal pool of nutrients, lipids or reserves. Consequently the population model for each trophic level is described by two state variables instead of one. As a result the classical predator-prey interaction formalisms have to be revised. In our model time budgets with actions as searching and handling provide the formulation of the functional response for both components. In the model, assimilation of the ingested two prey components is done in parallel and the extracted energy is added to a predators reserve pool. The reserves are used for vital processes; growth, reproduction and maintenance. We will explore the top-down modelling approach where the perspective is from the community. We will demonstrate that this approach facilitates a check on the balance equations for mass and energy at this level of organization. Here it will be shown that, if the individual is allowed to shrink when the energy reserves are in short to pay the maintenance costs, the growth process has to be 100% effective. This is unrealistic and some alternative model formulations are discussed. The long-term dynamics of a microbial food chain in the chemostat are studied using bifurcation analysis. The dilution rate and the concentration of nutrients in the reservoir are the bifurcation parameters. The studied microbial bi-trophic food chain with two-component populations shows chaotic behaviour. PMID:11276527

Kooi, B W; Hanegraaf, P P

2001-03-01

258

In most tissue engineering applications, understanding the factors affecting the growth dynamics of coculture systems is crucial for directing the population toward a desirable regenerative process. Yet, no comprehensive analysis method exists to quantify coculture population dynamics, let alone, a unifying model addressing the “environmental” factors influencing cell growth, all together. Here we suggest a modification of the Lotka-Volterra model to analyze the population dynamics of cocultured cells and predict their growth profiles for tissue engineering applications. This model, commonly used to describe the population dynamics of a prey and predator sharing a closed ecological niche, was found to fit our empirical data on cocultures of endothelial cells (ECs) and mesenchymal stem cells (MSCs) that have been widely investigated for their regenerative potential. Applying this model to cocultures of this sort allows us to quantify the effect that culturing conditions have on the way cell growth is affected by the same cells or by the other cells in the coculture. We found that in most cases, EC growth was inhibited by the same cells but promoted by MSCs. The principles resulting from this analysis can be used in various applications to guide the population toward a desired direction while shedding new light on the fundamental interactions between ECs and MSCs. Similar results were also demonstrated on complex substrates made from decellularized porcine cardiac extracellular matrix, where growth occurred only after coculturing ECs and MSCs together. Finally, this unique implementation of the Lotka-Volterra model may also be regarded as a roadmap for using such models with other potentially regenerative cocultures in various applications.

Wang, Yao; Bronshtein, Tomer; Sarig, Udi; Nguyen, Evelyne Bao-Vi; Boey, Freddy Yin Chiang; Venkatraman, Subbu S.

2013-01-01

259

In most tissue engineering applications, understanding the factors affecting the growth dynamics of coculture systems is crucial for directing the population toward a desirable regenerative process. Yet, no comprehensive analysis method exists to quantify coculture population dynamics, let alone, a unifying model addressing the "environmental" factors influencing cell growth, all together. Here we suggest a modification of the Lotka-Volterra model to analyze the population dynamics of cocultured cells and predict their growth profiles for tissue engineering applications. This model, commonly used to describe the population dynamics of a prey and predator sharing a closed ecological niche, was found to fit our empirical data on cocultures of endothelial cells (ECs) and mesenchymal stem cells (MSCs) that have been widely investigated for their regenerative potential. Applying this model to cocultures of this sort allows us to quantify the effect that culturing conditions have on the way cell growth is affected by the same cells or by the other cells in the coculture. We found that in most cases, EC growth was inhibited by the same cells but promoted by MSCs. The principles resulting from this analysis can be used in various applications to guide the population toward a desired direction while shedding new light on the fundamental interactions between ECs and MSCs. Similar results were also demonstrated on complex substrates made from decellularized porcine cardiac extracellular matrix, where growth occurred only after coculturing ECs and MSCs together. Finally, this unique implementation of the Lotka-Volterra model may also be regarded as a roadmap for using such models with other potentially regenerative cocultures in various applications. PMID:23216214

Wang, Yao; Bronshtein, Tomer; Sarig, Udi; Nguyen, Evelyne Bao-Vi; Boey, Freddy Yin Chiang; Venkatraman, Subbu S; Machluf, Marcelle

2013-05-01

260

Forced versus coupled dynamics in Earth system modelling and prediction

NASA Astrophysics Data System (ADS)

We compare coupled nonlinear climate models and their simplified forced counterparts with respect to predictability and phase space topology. Various types of uncertainty plague climate change simulation, which is, in turn, a crucial element of Earth System modelling. Since the currently preferred strategy for simulating the climate system, or the Earth System at large, is the coupling of sub-system modules (representing, e.g. atmosphere, oceans, global vegetation), this paper explicitly addresses the errors and indeterminacies generated by the coupling procedure. The focus is on a comparison of forced dynamics as opposed to fully, i.e. intrinsically, coupled dynamics. The former represents a particular type of simulation, where the time behaviour of one complex systems component is prescribed by data or some other external information source. Such a simplifying technique is often employed in Earth System models in order to save computing resources, in particular when massive model inter-comparisons need to be carried out. Our contribution to the debate is based on the investigation of two representative model examples, namely (i) a low-dimensional coupled atmosphere-ocean simulator, and (ii) a replica-like simulator embracing corresponding components.Whereas in general the forced version (ii) is able to mimic its fully coupled counterpart (i), we show in this paper that for a considerable fraction of parameter- and state-space, the two approaches qualitatively differ. Here we take up a phenomenon concerning the predictability of coupled versus forced models that was reported earlier in this journal: the observation that the time series of the forced version display artificial predictive skill. We present an explanation in terms of nonlinear dynamical theory. In particular we observe an intermittent version of artificial predictive skill, which we call on-off synchronization, and trace it back to the appearance of unstable periodic orbits. We also find it to be governed by a scaling law that allows us to estimate the probability of artificial predictive skill. In addition to artificial predictability we observe artificial bistability for the forced version, which has not been reported so far. The results suggest that bistability and intermittent predictability, when found in a forced model set-up, should always be cross-validated with alternative coupling designs before being taken for granted.

Knopf, B.; Held, H.; Schellnhuber, H. J.

2005-02-01

261

The Stochastic Human Exposure and Dose Simulation (SHEDS) models being developed by the US EPA/NERL use a probabilistic approach to predict population exposures to pollutants. The SHEDS model for particulate matter (SHEDS-PM) estimates the population distribution of PM exposure...

262

A series of experiments were performed to examine the population dynamics of the sugarbeet cyst nematode, Heterodera schachtii, and the nematophagus fungus Dactylella oviparasitica. After two nematode generations, the population densities of H. schachtii were measured in relation to various initial infestation densities of both D. oviparasitica and H. schachtii. In general, higher initial population densities of D. oviparasitica were associated with lower final population densities of H. schachtii. Regression models showed that the initial densities of D. oviparasitica were only significant when predicting the final densities of H. schachtii J2 and eggs as well as fungal egg parasitism, while the initial densities of J2 were significant for all final H. schachtii population density measurements. We also showed that the densities of H. schachtii-associated D. oviparasitica fluctuate greatly, with rRNA gene numbers going from zero in most field-soil-collected cysts to an average of 4.24 x 108 in mature females isolated directly from root surfaces. Finally, phylogenetic analysis of rRNA genes suggested that D. oviparasitica belongs to a clade of nematophagous fungi that includes Arkansas Fungus strain L (ARF-L) and that these fungi are widely distributed. We anticipate that these findings will provide foundational data facilitating the development of more effective decision models for sugar beet planting.

Yang, Jiue-in; Benecke, Scott; Jeske, Daniel R.; Rocha, Fernando S.; Smith Becker, Jennifer; Timper, Patricia; Ole Becker, J.

2012-01-01

263

A series of experiments were performed to examine the population dynamics of the sugarbeet cyst nematode, Heterodera schachtii, and the nematophagus fungus Dactylella oviparasitica. After two nematode generations, the population densities of H. schachtii were measured in relation to various initial infestation densities of both D. oviparasitica and H. schachtii. In general, higher initial population densities of D. oviparasitica were associated with lower final population densities of H. schachtii. Regression models showed that the initial densities of D. oviparasitica were only significant when predicting the final densities of H. schachtii J2 and eggs as well as fungal egg parasitism, while the initial densities of J2 were significant for all final H. schachtii population density measurements. We also showed that the densities of H. schachtii-associated D. oviparasitica fluctuate greatly, with rRNA gene numbers going from zero in most field-soil-collected cysts to an average of 4.24 x 10(8) in mature females isolated directly from root surfaces. Finally, phylogenetic analysis of rRNA genes suggested that D. oviparasitica belongs to a clade of nematophagous fungi that includes Arkansas Fungus strain L (ARF-L) and that these fungi are widely distributed. We anticipate that these findings will provide foundational data facilitating the development of more effective decision models for sugar beet planting. PMID:23481664

Yang, Jiue-In; Benecke, Scott; Jeske, Daniel R; Rocha, Fernando S; Smith Becker, Jennifer; Timper, Patricia; Ole Becker, J; Borneman, James

2012-09-01

264

Dynamics of population response to changes of motion direction in primary visual cortex

The visual system is thought to represent the direction of moving objects in the relative activity of large populations of cortical neurons that are broadly tuned to the direction of stimulus motion; but how changes in the direction of a moving stimulus are represented in the population response remains poorly understood. Here we take advantage of the orderly mapping of direction selectivity in ferret primary visual cortex (V1) to explore how abrupt changes in the direction of a moving stimulus are encoded in population activity using voltage-sensitive dye (VSD) imaging. For stimuli moving in a constant direction, the peak of the V1 population response accurately represented the direction of stimulus motion; but following abrupt changes in motion direction, the peak transiently departed from the direction of stimulus motion in a fashion that varied with the direction offset angle and was well predicted from the response to the component directions. We conclude that cortical dynamics and population coding mechanisms combine to place constraints on the accuracy with which abrupt changes in direction of motion can be represented by cortical circuits.

Wu, Wei; Tiesinga, Paul H.; Tucker, Thomas R.; Mitroff, Stephen R.; Fitzpatrick, David

2011-01-01

265

Predicting Cytotoxic T-cell Age from Multivariate Analysis of Static and Dynamic Biomarkers*

Adoptive T-cell transfer therapy relies upon in vitro expansion of autologous cytotoxic T cells that are capable of tumor recognition. The success of this cell-based therapy depends on the specificity and responsiveness of the T cell clones before transfer. During ex vivo expansion, CD8+ T cells present signs of replicative senescence and loss of function. The transfer of nonresponsive senescent T cells is a major bottleneck for the success of adoptive T-cell transfer therapy. Quantitative methods for assessing cellular age and responsiveness will facilitate the development of appropriate cell expansion and selection protocols. Although several biomarkers of lymphocyte senescence have been identified, these proteins in isolation are not sufficient to determine the age-dependent responsiveness of T cells. We have developed a multivariate model capable of extracting combinations of markers that are the most informative to predict cellular age. To acquire signaling information with high temporal resolution, we designed a microfluidic chip enabling parallel lysis and fixation of stimulated cell samples on-chip. The acquisition of 25 static biomarkers and 48 dynamic signaling measurements at different days in culture, integrating single-cell and population based information, allowed the multivariate regression model to accurately predict CD8+ T-cell age. From surface marker expression and early phosphorylation events following T-cell receptor stimulation, the model successfully predicts days in culture and number of population doublings with R2 = 0.91 and 0.98, respectively. Furthermore, we found that impairment of early signaling events following T cell receptor stimulation because of long term culture allows prediction of costimulatory molecules CD28 and CD27 expression levels and the number of population divisions in culture from a limited subset of signaling proteins. The multivariate analysis highlights the information content of both averaged biomarker values and heterogeneity metrics for prediction of cellular age within a T cell population.

Rivet, Catherine A.; Hill, Abby S.; Lu, Hang; Kemp, Melissa L.

2011-01-01

266

Urban aerosols harbor diverse and dynamic bacterial populations

Considering the importance of its potential implications for human health, agricultural productivity, and ecosystem stability, surprisingly little is known regarding the composition or dynamics of the atmosphere's microbial inhabitants. Using a custom high-density DNA microarray, we detected and monitored bacterial populations in two U.S. cities over 17 weeks. These urban aerosols contained at least 1,800 diverse bacterial types, a richness approaching that of some soil bacterial communities. We also reveal the consistent presence of bacterial families with pathogenic members including environmental relatives of select agents of bioterrorism significance. Finally, using multivariate regression techniques, we demonstrate that temporal and meteorological influences can be stronger factors than location in shaping the biological composition of the air we breathe.

Brodie, Eoin L.; DeSantis, Todd Z.; Parker, Jordan P. Moberg; Zubietta, Ingrid X.; Piceno, Yvette M.; Andersen, Gary L.

2007-01-01

267

BACKGROUND: Research on the evolution of reproductive isolation in African cichlid fishes has largely focussed on the role of male colours and female mate choice. Here, we tested predictions from the hypothesis that allopatric divergence in male colour is associated with corresponding divergence in preference. METHODS: We studied four populations of the Lake Malawi Pseudotropheus zebra complex. We predicted that

Jonatan Blais; Martin Plenderleith; Ciro Rico; Martin I Taylor; Ole Seehausen; Cock van Oosterhout; George F Turner

2009-01-01

268

Modeling community population dynamics with the open-source language R.

The ability to explain biological phenomena with mathematics and to generate predictions from mathematical models is critical for understanding and controlling natural systems. Concurrently, the rise in open-source software has greatly increased the ease at which researchers can implement their own mathematical models. With a reasonably sound understanding of mathematics and programming skills, a researcher can quickly and easily use such tools for their own work. The purpose of this chapter is to expose the reader to one such tool, the open-source programming language R, and to demonstrate its practical application to studying population dynamics. We use the Lotka-Volterra predator-prey dynamics as an example. PMID:24838889

Green, Robin; Shou, Wenying

2014-01-01

269

Predicting oscillatory dynamics in the movement of territorial animals

Understanding ecological processes relies upon the knowledge of the dynamics of each individual component. In the context of animal population ecology, the way animals move and interact is of fundamental importance in explaining a variety of observed patterns. Here, we present a theoretical investigation on the movement dynamics of interacting scent-marking animals. We study how the movement statistics of territorial animals is responsible for the appearance of damped oscillations in the mean square displacement (MSD) of the animals. This non-monotonicity is shown to depend on one dimensionless parameter, given by the ratio of the correlation distance between successive steps to the size of the territory. As that parameter increases, the time dependence of the animal's MSD displays a transition from monotonic, characteristic of Brownian walks, to non-monotonic, characteristic of highly correlated walks. The results presented here represent a novel way of determining the degree of persistence in animal movement processes within confined regions.

Giuggioli, L.; Potts, J. R.; Harris, S.

2012-01-01

270

Dynamic modeling of predictive uncertainty by regression on absolute errors

NASA Astrophysics Data System (ADS)

Uncertainty of hydrological forecasts represents valuable information for water managers and hydrologists. This explains the popularity of probabilistic models, which provide the entire distribution of the hydrological forecast. Nevertheless, many existing hydrological models are deterministic and provide point estimates of the variable of interest. Often, the model residual error is assumed to be homoscedastic; however, practical evidence shows that the hypothesis usually does not hold. In this paper we propose a simple and effective method to quantify predictive uncertainty of deterministic hydrological models affected by heteroscedastic residual errors. It considers the error variance as a hydrological process separate from that of the hydrological forecast and therefore predictable by an independent model. The variance model is built up using time series of model residuals, and under some conditions on the same residuals, it is applicable to any deterministic model. Tools for regression analysis applied to the time series of residual errors, or better their absolute values, combined with physical considerations of the hydrological features of the system can help to identify the most suitable input to the variance model and the most parsimonious model structure, including dynamic structure if needed. The approach has been called dynamic uncertainty modeling by regression on absolute errors and is demonstrated by application to two test cases, both affected by heteroscedasticity but with very different dynamics of uncertainty. Modeling results and comparison with other approaches, i.e., a constant, a cyclostationary, and a static model of the variance, confirm the validity of the proposed method.

Pianosi, F.; Raso, L.

2012-03-01

271

Connectionist Architectures for Time Series Prediction of Dynamical Systems

NASA Astrophysics Data System (ADS)

We investigate the effectiveness of connectionist networks for predicting the future continuation of temporal sequences. The problem of overfitting, particularly serious for short records of noisy data, is addressed by the method of weight-elimination: a term penalizing network complexity is added to the usual cost function in back-propagation. We describe the dynamics of the procedure and clarify the meaning of the parameters involved. From a Bayesian perspective, the complexity term can be usefully interpreted as an assumption about prior distribution of the weights. We analyze three time series. On the benchmark sunspot series, the networks outperform traditional statistical approaches. We show that the network performance does not deteriorate when there are more input units than needed. In the second example, the notoriously noisy foreign exchange rates series, we pick one weekday and one currency (DM vs. US). Given exchange rate information up to and including a Monday, the task is to predict the rate for the following Tuesday. Weight-elimination manages to extract a significant part of the dynamics and makes the solution interpretable. In the third example, the networks predict the resource utilization of a chaotic computational ecosystem for hundreds of steps forward in time.

Weigend, Andreas Sebastian

272

Prediction of muscle performance during dynamic repetitive movement

NASA Technical Reports Server (NTRS)

BACKGROUND: During long-duration spaceflight, astronauts experience progressive muscle atrophy and often perform strenuous extravehicular activities. Post-flight, there is a lengthy recovery period with an increased risk for injury. Currently, there is a critical need for an enabling tool to optimize muscle performance and to minimize the risk of injury to astronauts while on-orbit and during post-flight recovery. Consequently, these studies were performed to develop a method to address this need. METHODS: Eight test subjects performed a repetitive dynamic exercise to failure at 65% of their upper torso weight using a Lordex spinal machine. Surface electromyography (SEMG) data was collected from the erector spinae back muscle. The SEMG data was evaluated using a 5th order autoregressive (AR) model and linear regression analysis. RESULTS: The best predictor found was an AR parameter, the mean average magnitude of AR poles, with r = 0.75 and p = 0.03. This parameter can predict performance to failure as early as the second repetition of the exercise. CONCLUSION: A method for predicting human muscle performance early during dynamic repetitive exercise was developed. The capability to predict performance to failure has many potential applications to the space program including evaluating countermeasure effectiveness on-orbit, optimizing post-flight recovery, and potential future real-time monitoring capability during extravehicular activity.

Byerly, D. L.; Byerly, K. A.; Sognier, M. A.; Squires, W. G.

2003-01-01

273

Modelling lipid competition dynamics in heterogeneous protocell populations.

Recent experimental work in the field of synthetic protocell biology has shown that prebiotic vesicles are able to 'steal' lipids from each other. This phenomenon is driven purely by asymmetries in the physical state or composition of the vesicle membranes, and, when lipid resource is limited, translates directly into competition amongst the vesicles. Such a scenario is interesting from an origins of life perspective because a rudimentary form of cell-level selection emerges. To sharpen intuition about possible mechanisms underlying this behaviour, experimental work must be complemented with theoretical modelling. The aim of this paper is to provide a coarse-grain mathematical model of protocell lipid competition. Our model is capable of reproducing, often quantitatively, results from core experimental papers that reported distinct types vesicle competition. Additionally, we make some predictions untested in the lab, and develop a general numerical method for quickly solving the equilibrium point of a model vesicle population. PMID:25024020

Shirt-Ediss, Ben; Ruiz-Mirazo, Kepa; Mavelli, Fabio; Solé, Ricard V

2014-01-01

274

Modelling Lipid Competition Dynamics in Heterogeneous Protocell Populations

Recent experimental work in the field of synthetic protocell biology has shown that prebiotic vesicles are able to ‘steal’ lipids from each other. This phenomenon is driven purely by asymmetries in the physical state or composition of the vesicle membranes, and, when lipid resource is limited, translates directly into competition amongst the vesicles. Such a scenario is interesting from an origins of life perspective because a rudimentary form of cell-level selection emerges. To sharpen intuition about possible mechanisms underlying this behaviour, experimental work must be complemented with theoretical modelling. The aim of this paper is to provide a coarse-grain mathematical model of protocell lipid competition. Our model is capable of reproducing, often quantitatively, results from core experimental papers that reported distinct types vesicle competition. Additionally, we make some predictions untested in the lab, and develop a general numerical method for quickly solving the equilibrium point of a model vesicle population.

Shirt-Ediss, Ben; Ruiz-Mirazo, Kepa; Mavelli, Fabio; Sole, Ricard V.

2014-01-01

275

Zooplankton population dynamics in experimentally toxified pond ecosystems

To evaluate ecosystem response to and recovery from toxic contamination, we added phenolic compounds to a series of experimental ponds. Toxicants were added repeatedly in a temporally staggered sequence to evaluate the influence of seasonal factors and previous exposure history on the responses to toxicant stress. We hypothesized that seasonal changes in ecosystem structure, e.g. shifts in the relative importance of ''top-down'' and ''bottom-up'' controls on energy flow, would influence the system-level responses to the toxicant. Information from these experiments is being incorporated into models that predict ecological risk and system-level behavior under toxicant stress. Here we focus on the responses of zooplankton populations to toxicants, and factors which may affect the apparent severity of toxic effects. 9 refs., 4 figs.

Sierszen, M.E.; Boston, H.L.; Horn, M.J.

1989-01-01

276

Local Competition and Metapopulation Processes Drive Long-Term Seagrass-Epiphyte Population Dynamics

It is well known that ecological processes such as population regulation and natural enemy interactions potentially occur over a range of spatial scales, and there is a substantial body of literature developing theoretical understanding of the interplay between these processes. However, there are comparatively few studies quantifying the long-term effects of spatial scaling in natural ecosystems. A key challenge is that trophic complexity in real-world biological communities quickly obscures the signal from a focal process. Seagrass meadows provide an excellent opportunity in this respect: in many instances, seagrasses effectively form extensive natural monocultures, in which hypotheses about endogenous dynamics can be formulated and tested. We present amongst the longest unbroken, spatially explict time series of seagrass abundance published to date. Data include annual measures of shoot density, total above-ground abundance, and associated epiphyte cover from five Zostera marina meadows distributed around the Isles of Scilly, UK, from 1996 to 2011. We explore empirical patterns at the local and metapopulation scale using standard time series analysis and develop a simple population dynamic model, testing the hypothesis that both local and metapopulation scale feedback processes are important. We find little evidence of an interaction between scales in seagrass dynamics but that both scales contribute approximately equally to observed local epiphyte abundance. By quantifying the long-term dynamics of seagrass-epiphyte interactions we show how measures of density and extent are both important in establishing baseline information relevant to predicting responses to environmental change and developing management plans. We hope that this study complements existing mechanistic studies of physiology, genetics and productivity in seagrass, whilst highlighting the potential of seagrass as a model ecosystem. More generally, this study provides a rare opportunity to test some of the predictions of ecological theory in a natural ecosystem of global conservation and economic value.

Lobelle, Delphine; Kenyon, Emma J.; Cook, Kevan J.; Bull, James C.

2013-01-01

277

Modelling multi-pulse population dynamics from ultrafast spectroscopy.

Current advanced laser, optics and electronics technology allows sensitive recording of molecular dynamics, from single resonance to multi-colour and multi-pulse experiments. Extracting the occurring (bio-) physical relevant pathways via global analysis of experimental data requires a systematic investigation of connectivity schemes. Here we present a Matlab-based toolbox for this purpose. The toolbox has a graphical user interface which facilitates the application of different reaction models to the data to generate the coupled differential equations. Any time-dependent dataset can be analysed to extract time-independent correlations of the observables by using gradient or direct search methods. Specific capabilities (i.e. chirp and instrument response function) for the analysis of ultrafast pump-probe spectroscopic data are included. The inclusion of an extra pulse that interacts with a transient phase can help to disentangle complex interdependent pathways. The modelling of pathways is therefore extended by new theory (which is included in the toolbox) that describes the finite bleach (orientation) effect of single and multiple intense polarised femtosecond pulses on an ensemble of randomly oriented particles in the presence of population decay. For instance, the generally assumed flat-top multimode beam profile is adapted to a more realistic Gaussian shape, exposing the need for several corrections for accurate anisotropy measurements. In addition, the (selective) excitation (photoselection) and anisotropy of populations that interact with single or multiple intense polarised laser pulses is demonstrated as function of power density and beam profile. Using example values of real world experiments it is calculated to what extent this effectively orients the ensemble of particles. Finally, the implementation includes the interaction with multiple pulses in addition to depth averaging in optically dense samples. In summary, we show that mathematical modelling is essential to model and resolve the details of physical behaviour of populations in ultrafast spectroscopy such as pump-probe, pump-dump-probe and pump-repump-probe experiments. PMID:21445294

van Wilderen, Luuk J G W; Lincoln, Craig N; van Thor, Jasper J

2011-01-01

278

The role of resting cysts in Alexandrium minutum population dynamics

NASA Astrophysics Data System (ADS)

The role of resting cysts on the development of Alexandrium minutum blooms in a typical Mediterranean semi-enclosed water body (Arenys de Mar Harbor, NW Mediterranean) was studied by means of matrix and dynamic population models. We used a series of scenarios, constrained when possible by experimentally measured parameters to test whether excystment and encystment fluxes and changes in the dormancy period had a major effect on bloom intensity and duration. The results of the simulations highlighted the importance of knowing not only the magnitude and variability of growth and life-cycle transition rates, but also those of loss rates (both in the water column and in the sediment) due to physical or biological factors. Given the maximum encystment rates determined for A. minutum in the study area (0.01 d -1), this process contributed to reduce the peak concentrations of vegetative cells but did not have a dominant effect on bloom termination. Excystment fluxes could contribute to enhance population densities of vegetative cells during times or low or negative net growth rate and during the initial phases of a bloom, but once exponential growth had started, additional excystment had negligible effect on bloom magnitude. However, even if cysts did not contribute to larger blooms, they could represent a safety mechanism for reintroduction of the species when the vegetative cell population went extinct due to unfavorable environmental conditions. Increasing the dormancy time exposed newly formed cysts to a longer period of losses in the sediment that reduced the concentration of excystment-ready sediment cysts and decreased excystment fluxes. More complex models will be needed to explore the implications of different life-cycle strategies in a wider natural ecological context.

Estrada, Marta; Solé, Jordi; Anglès, Sílvia; Garcés, Esther

2010-02-01

279

Eukaryotic transcriptional dynamics: from single molecules to cell populations

Transcriptional regulation is achieved through combinatorial interactions between regulatory elements in the human genome and a vast range of factors that modulate the recruitment and activity of RNA polymerase. Experimental approaches for studying transcription in vivo now extend from single-molecule techniques to genome-wide measurements. Parallel to these developments is the need for testable quantitative and predictive models for understanding gene regulation. These conceptual models must also provide insight into the dynamics of transcription and the variability that is observed at the single-cell level. In this Review, we discuss recent results on transcriptional regulation and also the models those results engender. We show how a non-equilibrium description informs our view of transcription by explicitly considering time-and energy-dependence at the molecular level.

Coulon, Antoine; Chow, Carson C.; Singer, Robert H.; Larson, Daniel R.

2013-01-01

280

Understanding how climate change, exploitation and eutrophication will affect populations and ecosystems of the Baltic Sea can be facilitated with models which realistically combine these forcings into common frameworks. Here, we evaluate sensitivity of fish recruitment and population dynamics to past and future environmental forcings provided by three ocean-biogeochemical models of the Baltic Sea. Modeled temperature explained nearly as much variability in reproductive success of sprat (Sprattus sprattus; Clupeidae) as measured temperatures during 1973-2005, and both the spawner biomass and the temperature have influenced recruitment for at least 50 years. The three Baltic Sea models estimate relatively similar developments (increases) in biomass and fishery yield during twenty-first century climate change (ca. 28 % range among models). However, this uncertainty is exceeded by the one associated with the fish population model, and by the source of global climate data used by regional models. Knowledge of processes and biases could reduce these uncertainties. PMID:22926884

Mackenzie, Brian R; Meier, H E Markus; Lindegren, Martin; Neuenfeldt, Stefan; Eero, Margit; Blenckner, Thorsten; Tomczak, Maciej T; Niiranen, Susa

2012-09-01

281

NASA Astrophysics Data System (ADS)

In arid landscapes, desert shrubs individually and collectively modify how sediment is transported (e.g by wind, overland-flow, and rain-splash). Addressing how desert shrubs modify landscapes on geomorphic timescales therefore necessitates spanning multiple shrub lifetimes and accounting for how processes affecting shrub dynamics on these longer timescales (e.g. fire, grazing, drought, and climate change) may in turn impact sediment transport. To fulfill this need, we present a mechanistic model of the spatiotemporal dynamics of a desert-shrub population that uses a simple accounting framework and tracks individual shrubs as they enter, age, and exit the population (via recruitment, growth, and mortality). Our model is novel insomuch as it (1) features a strong biophysical foundation, (2) mimics well-documented aspects of how shrub populations respond to changes in precipitation, and (3) possesses the process granularity appropriate for use in geomorphic simulations. In a complimentary abstract (Fathel et al. 2014), we demonstrate the potential of this biological model by coupling it to a physical model of rain-splash sediment transport: We mechanistically reproduce the empirical observation that the erosion rate of a hillslope decreases as its vegetation coverage increases and we predict erosion rates under different climate-change scenarios.

Worman, Stacey; Furbish, David; Fathel, Siobhan

2014-05-01

282

Dynamical evolution and spatial mixing of multiple population globular clusters

NASA Astrophysics Data System (ADS)

Numerous spectroscopic and photometric observational studies have provided strong evidence for the widespread presence of multiple stellar populations in globular clusters. In this paper, we study the long-term dynamical evolution of multiple population clusters, focusing on the evolution of the spatial distributions of the first- (FG) and second-generation (SG) stars. In previous studies, we have suggested that SG stars formed from the ejecta of FG AGB stars are expected initially to be concentrated in the cluster inner regions. Here, by means of N-body simulations, we explore the time-scales and the dynamics of the spatial mixing of the FG and the SG populations and their dependence on the SG initial concentration. Our simulations show that, as the evolution proceeds, the radial profile of the SG/FG number ratio, NSG/NFG, is characterized by three regions: (1) a flat inner part; (2) a declining part in which FG stars are increasingly dominant and (3) an outer region where the NSG/NFG profile flattens again (the NSG/NFG profile may rise slightly again in the outermost cluster regions). Until mixing is complete and the NSG/NFG profile is flat over the entire cluster, the radial variation of NSG/NFG implies that the fraction of SG stars determined by observations covering a limited range of radial distances is not, in general, equal to the SG global fraction, (NSG/NFG)glob. The distance at which NSG/NFG equals (NSG/NFG)glob is approximately between 1 and 2 cluster half-mass radii. The time-scale for complete mixing depends on the SG initial concentration, but in all cases complete mixing is expected only for clusters in advanced evolutionary phases, having lost at least 60-70 per cent of their mass due to two-body relaxation (in addition to the early FG loss due to the cluster expansion triggered by SNII ejecta and gas expulsion).The results of our simulations suggest that in many Galactic globular clusters the SG should still be more spatially concentrated than the FG.

Vesperini, Enrico; McMillan, Stephen L. W.; D'Antona, Francesca; D'Ercole, Annibale

2013-03-01

283

Population dynamics of a meiotic/mitotic expansion model for the fragile X syndrome.

A model to explain the mutational process and population dynamics of the fragile X syndrome is presented. The mutational mechanism was assumed to be a multipathway, multistep process. Expansion of CGG repeats was based on an underlying biological process and was assumed to occur at two time points: meiosis and early embryonic development (mitosis). Meiotic expansion was assumed to occur equally in oogenesis and spermatogenesis, while mitotic expansion was restricted to somatic, or constitutional, alleles of maternal origin. Testable hypotheses were predicted by this meiotic/mitotic model. First, parental origin of mutation is predicted to be associated with the risk of a woman to have a full mutation child. Second, "contractions" seen in premutation male transmissions are predicted not to be true contractions in repeat size, but a consequence of the lack of mitotic expansion in paternally derived alleles. Third, a portion of full-mutation males should have full-mutation alleles in their sperm, due to the lack of complete selection against the full-mutation female. Fourth, a specific premutation-allele frequency distribution is predicted and differs from that based on models assuming only meiotic expansion. Last, it is predicted that approximately 65 generations are required to achieve equilibrium, but this depends greatly on the expansion probabilities.

Ashley, A E; Sherman, S L

1995-01-01

284

Identifying high performing hybrids is an essential part of every maize breeding program. Genomic prediction of maize hybrid performance allows to identify promising hybrids, when they themselves or other hybrids produced from their parents were not tested in field trials. Using simulations, we investigated the effects of marker density (10, 1, 0.3 marker per mega base pair, Mbp(-1)), convergent or divergent parental populations, number of parents tested in other combinations (2, 1, 0), genetic model (including population-specific and/or dominance marker effects or not), and estimation method (GBLUP or BayesB) on the prediction accuracy. We based our simulations on marker genotypes of Central European flint and dent inbred lines from an ongoing maize breeding program. To simulate convergent or divergent parent populations, we generated phenotypes by assigning QTL to markers with similar or very different allele frequencies in both pools, respectively. Prediction accuracies increased with marker density and number of parents tested and were higher under divergent compared with convergent parental populations. Modeling marker effects as population-specific slightly improved prediction accuracy under lower marker densities (1 and 0.3 Mbp(-1)). This indicated that modeling marker effects as population-specific will be most beneficial under low linkage disequilibrium. Incorporating dominance effects improved prediction accuracies considerably for convergent parent populations, where dominance results in major contributions of SCA effects to the genetic variance among inter-population hybrids. While the general trends regarding the effects of the aforementioned influence factors on prediction accuracy were similar for GBLUP and BayesB, the latter method produced significantly higher accuracies for models incorporating dominance. PMID:22733443

Technow, Frank; Riedelsheimer, Christian; Schrag, Tobias A; Melchinger, Albrecht E

2012-10-01

285

A dynamic model for predicting CANDU pressurizer performance

A digital computer approach for predicting the dynamic response of surge tanks is presented. The applications of different models are presented for analyzing the primary pressure transients of CANDU reactors. Conservation equations for deformable control volume have been employed to describe the flow inside both of the closed distinct regions (phases). In this model, the upper region can be either in the superheated state or two-phase saturated state. The lower region can be in the subcooled state or two-phase saturated state. Energy and mass transfer processes occurring inside the surge tanks have been investigated and determined under various operating conditions. These processes are spray condensation, wall condensation, vapor flashing, heat transfer at interface, and heat transfer from heaters. Numerical results showed that this model favorably predicted the pressurizer pressure when compared with those calculated by adiabatic and equilibrium models employed in the SOPHT code and with data obtained from the Gentilly-2 site and Bruce NGS-A.

Sami, S.M.

1986-01-01

286

Local predictability and information flow in complex dynamical systems

NASA Astrophysics Data System (ADS)

Predictability is by observation a local notion in complex dynamical systems. Its spatiotemporal structure implies a flow, or transfer in discrete cases, of information that redistributes the local predictability within the state space of concern. Information flow is a fundamental concept in general physics which has applications in a wide variety of disciplines such as neuroscience, material science, atmosphere-ocean science, and turbulence research, to name but a few. In this study, it is rigorously formulated with respect to relative entropy within the framework of a system with many components, each signifying a location or a structure. Given a component, the mechanism governing the evolution of its predictability can be classified into two groups, one due to the component itself, another due to a transfer of information from its peers. A measure of the transfer is rigorously derived, and an explicit expression obtained. This measure possesses a form reminiscent of that we have obtained before with respect to absolute entropy in [X.S. Liang and R. Kleeman, A rigorous formalism of information transfer between dynamical system components, Physica D 227 (2007) 173-182]; in particular, when the system is of dimensionality 2, there is no difference between the formalisms with respect to absolute entropy and relative entropy, except for a minus sign. Properties have been explored and discussed; particularly discussed is the property of asymmetry or causality, which states that information transfer from one component to another carries no hint about the transfer in the other direction, in contrast to the transfer of other quantities such as energy. This formalism has been applied to the study of the scale-scale interaction and information transfer between the first two modes of the truncated Burgers equation. It is found that all 12 transfers are essentially zero or negligible, save for a strong transfer between the sine components from the low-frequency mode to the high-frequency mode. That is to say, the predictability of the high-frequency mode is controlled by the knowledge of the low-frequency mode. This result, though from a highly idealized system, has interesting implications about the dynamical closure problem in turbulence research and atmosphere-ocean science, i.e., the subgrid processes may to some extent be parameterized by the large-scale dynamics. This study can be adopted to investigate the propagation of uncertainties in fluid flows, which has important applications in problems such as atmospheric observing platform design, and may be utilized to identify the route of information flowing within a complex network.

Liang, X. San

2013-04-01

287

Transmembrane topology and signal peptide prediction using dynamic bayesian networks.

Hidden Markov models (HMMs) have been successfully applied to the tasks of transmembrane protein topology prediction and signal peptide prediction. In this paper we expand upon this work by making use of the more powerful class of dynamic Bayesian networks (DBNs). Our model, Philius, is inspired by a previously published HMM, Phobius, and combines a signal peptide submodel with a transmembrane submodel. We introduce a two-stage DBN decoder that combines the power of posterior decoding with the grammar constraints of Viterbi-style decoding. Philius also provides protein type, segment, and topology confidence metrics to aid in the interpretation of the predictions. We report a relative improvement of 13% over Phobius in full-topology prediction accuracy on transmembrane proteins, and a sensitivity and specificity of 0.96 in detecting signal peptides. We also show that our confidence metrics correlate well with the observed precision. In addition, we have made predictions on all 6.3 million proteins in the Yeast Resource Center (YRC) database. This large-scale study provides an overall picture of the relative numbers of proteins that include a signal-peptide and/or one or more transmembrane segments as well as a valuable resource for the scientific community. All DBNs are implemented using the Graphical Models Toolkit. Source code for the models described here is available at http://noble.gs.washington.edu/proj/philius. A Philius Web server is available at http://www.yeastrc.org/philius, and the predictions on the YRC database are available at http://www.yeastrc.org/pdr. PMID:18989393

Reynolds, Sheila M; Käll, Lukas; Riffle, Michael E; Bilmes, Jeff A; Noble, William Stafford

2008-11-01

288

Dynamics of Populations of Planetary Systems (IAU C197)

NASA Astrophysics Data System (ADS)

1. Resonances and stability of extra-solar planetary systems C. Beaugé, N. Callegari, S. Ferraz-Mello and T. A. Michtchenko; 2. Formation, migration, and stability of extrasolar planetary systems Fred C. Adams; 3. Dynamical evolution of extrasolar planetary systems Ji-Lin Zhou and Yi-Sui Sun; 4. Dynamics of planetesimals: the role of two-body relaxation Eiichiro Kokubo; 5. Fitting orbits Andrzej J. Maciejewski, Krzysztof Gozdziewski and Szymon Kozlowski; 6. The secular planetary three body problem revisited Jacques Henrard and Anne-Sophie Libert; 7. Dynamics of extrasolar systems at the 5/2 resonance: application to 47 UMa Dionyssia Psychoyos and John D. Hadjidemetriou; 8. Our solar system as model for exosolar planetary systems Rudolf Dvorak, Áron Süli and Florian Freistetter; 9. Planetary motion in double stars: the influence of the secondary Elke Pilat-Lohinger; 10. Planetary orbits in double stars: influence of the binary's orbital eccentricity Daniel Benest and Robert Gonczi; 11. Astrometric observations of 51 Peg and Gliese 623 at Pulkovo observatory with 65 cm refractor N. A. Shakht; 12. Observations of 61 Cyg at Pulkovo Denis L. Gorshanov, N. A. Shakht, A. A. Kisselev and E. V. Poliakow; 13. Formation of the solar system by instability Evgeny Griv and Michael Gedalin; 14. Behaviour of a two-planetary system on a cosmogonic time-scale Konstantin V. Kholshevnikov and Eduard D. Kuznetsov; 15. Boundaries of the habitable zone: unifying dynamics, astrophysics, and astrobiology Milan M. Cirkovic; 16. Asteroid proper elements: recent computational progress Fernando Roig and Cristian Beaugé; 17. Asteroid family classification from very large catalogues Anne Lemaitre; 18. Non-gravitational perturbations and evolution of the asteroid main belt David Vokrouhlicky, M. Broz and W. F. Bottke, D. Nesvorny and A. Morbidelli; 19. Diffusion in the asteroid belt Harry Varvoglis; 20. Accurate model for the Yarkovsky effect David Capek and David Vokrouhlicky; 21. The population of asteroids in the 2:1 mean motion resonance with Jupiter revised Miroslav Broz, D. Vokrouhlicky, F. Roig, D. Nesvorny, W. F. Bottke and A. Morbidelli; 22. On the reliability of computation of maximum Lyapunov Characteristic Exponents for asteroids Zoran Knezevic and Slobodan Ninkovic; 23. Nekhoroshev stability estimates for different models of the Trojan asteroids Christos Efthymiopoulos; 24. The role of the resonant 'stickiness' in the dynamical evolution of Jupiter family comets A. Alvarez-Canda and F. Roig; 25. Regimes of stability and scaling relations for the removal time in the asteroid belt: a simple kinetic model and numerical tests Mihailo Cubrovic; 26. Virtual asteroids and virtual impactors Andrea Milani; 27. Asteroid population models Alessandro Morbidelli; 28. Linking Very Large Telescope asteroid observations M. Granvik, K. Muinonen, J. Virtanen, M. Delbó, L. Saba, G. De Sanctis, R. Morbidelli, A. Cellino and E. Tedesco; 29. Collision orbits and phase transition for 2004 AS1 at discovery Jenni Virtanen, K. Muinonen, M. Granvik and T. Laakso; 30. The size of collision solutions in orbital elements space G. B. Valsecchi, A. Rossi, A. Milani and S. R. Chesley; 31. Very short arc orbit determination: the case of asteroid 2004 FU162 Steven R. Chesley; 32. Nonlinear impact monitoring: 2-dimensional sampling Giacomo Tommei; 33. Searching for gravity assisted trajectories to accessible near-Earth asteroids Stefan Berinde; 34. KLENOT - Near Earth and other unusual objects observations Michal Kocer, Jana Tichá and M. Tichy; 35. Transport of comets to the Inner Solar System Hans Rickman; 36. Nongravitational Accelerations on Comets Steven R. Chesley and Donald K. Yeomans; 37. Interaction of planetesimals with the giant planets and the shaping of the trans-Neptunian belt Harold F. Levison and Alessandro Morbidelli; 38. Transport of comets to the outer p

Knezevic, Zoran; Milani, Andrea

2005-05-01

289

Comparative Population Dynamics of Two Closely Related Species Differing in Ploidy Level

Background Many studies compare the population dynamics of single species within multiple habitat types, while much less is known about the differences in population dynamics in closely related species in the same habitat. Additionally, comparisons of the effect of habitat types and species are largely missing. Methodology and Principal Findings We estimated the importance of the habitat type and species for population dynamics of plants. Specifically, we compared the dynamics of two closely related species, the allotetraploid species Anthericum liliago and the diploid species Anthericum ramosum, occurring in the same habitat type. We also compared the dynamics of A. ramosum in two contrasting habitats. We examined three populations per species and habitat type. The results showed that single life history traits as well as the mean population dynamics of A. liliago and A. ramosum from the same habitat type were more similar than the population dynamics of A. ramosum from the two contrasting habitats. Conclusions Our findings suggest that when transferring knowledge regarding population dynamics between populations, we need to take habitat conditions into account, as these conditions appear to be more important than the species involved (ploidy level). However, the two species differ significantly in their overall population growth rates, indicating that the ploidy level has an effect on species performance. In contrast to what has been suggested by previous studies, we observed a higher population growth rate in the diploid species. This is in agreement with the wider range of habitats occupied by the diploid species.

Cerna, Lucie; Munzbergova, Zuzana

2013-01-01

290

Background The present study aimed to develop an artificial neural network (ANN) based prediction model for cardiovascular autonomic (CA) dysfunction in the general population. Methods We analyzed a previous dataset based on a population sample consisted of 2,092 individuals aged 30–80 years. The prediction models were derived from an exploratory set using ANN analysis. Performances of these prediction models were evaluated in the validation set. Results Univariate analysis indicated that 14 risk factors showed statistically significant association with CA dysfunction (P?prediction model developed using ANN analysis. The mean sensitivity, specificity, positive and negative predictive values were similar in the prediction models was 0.751, 0.665, 0.330 and 0.924, respectively. All HL statistics were less than 15.0. Conclusion ANN is an effective tool for developing prediction models with high value for predicting CA dysfunction among the general population.

2013-01-01

291

PCI-SS: MISO dynamic nonlinear protein secondary structure prediction

Background Since the function of a protein is largely dictated by its three dimensional configuration, determining a protein's structure is of fundamental importance to biology. Here we report on a novel approach to determining the one dimensional secondary structure of proteins (distinguishing ?-helices, ?-strands, and non-regular structures) from primary sequence data which makes use of Parallel Cascade Identification (PCI), a powerful technique from the field of nonlinear system identification. Results Using PSI-BLAST divergent evolutionary profiles as input data, dynamic nonlinear systems are built through a black-box approach to model the process of protein folding. Genetic algorithms (GAs) are applied in order to optimize the architectural parameters of the PCI models. The three-state prediction problem is broken down into a combination of three binary sub-problems and protein structure classifiers are built using 2 layers of PCI classifiers. Careful construction of the optimization, training, and test datasets ensures that no homology exists between any training and testing data. A detailed comparison between PCI and 9 contemporary methods is provided over a set of 125 new protein chains guaranteed to be dissimilar to all training data. Unlike other secondary structure prediction methods, here a web service is developed to provide both human- and machine-readable interfaces to PCI-based protein secondary structure prediction. This server, called PCI-SS, is available at . In addition to a dynamic PHP-generated web interface for humans, a Simple Object Access Protocol (SOAP) interface is added to permit invocation of the PCI-SS service remotely. This machine-readable interface facilitates incorporation of PCI-SS into multi-faceted systems biology analysis pipelines requiring protein secondary structure information, and greatly simplifies high-throughput analyses. XML is used to represent the input protein sequence data and also to encode the resulting structure prediction in a machine-readable format. To our knowledge, this represents the only publicly available SOAP-interface for a protein secondary structure prediction service with published WSDL interface definition. Conclusion Relative to the 9 contemporary methods included in the comparison cascaded PCI classifiers perform well, however PCI finds greatest application as a consensus classifier. When PCI is used to combine a sequence-to-structure PCI-based classifier with the current leading ANN-based method, PSIPRED, the overall error rate (Q3) is maintained while the rate of occurrence of a particularly detrimental error is reduced by up to 25%. This improvement in BAD score, combined with the machine-readable SOAP web service interface makes PCI-SS particularly useful for inclusion in a tertiary structure prediction pipeline.

Green, James R; Korenberg, Michael J; Aboul-Magd, Mohammed O

2009-01-01

292

Most of previous empirical studies with genome-wide prediction were focused on within-environment prediction based on a single-environment (SE) model. In this study, we evaluated accuracy improvements of across-environment prediction by using genetic and residual covariance across correlated environments. Predictions with a multienvironment (ME) model were evaluated for two corn polygenic leaf structure traits, leaf length and leaf width, based on within-population (WP) and across-population (AP) experiments using a large maize nested association mapping data set consisting of 25 populations of recombinant inbred-lines. To make our study more applicable to plant breeding, two cross-validation schemes were used by evaluating accuracies of (CV1) predicting unobserved phenotypes of untested lines and (CV2) predicting unobserved phenotypes of lines that have been evaluated in some environments but not others. We concluded that (1) genome-wide prediction provided greater prediction accuracies than traditional quantitative trait loci-based prediction in both WP and AP and provided more advantages over quantitative trait loci -based prediction for WP than for AP. (2) Prediction accuracy with ME was significantly greater than that attained by SE in CV1 and CV2, and gains with ME over SE were greater in CV2 than in CV1. These gains were also greater in WP than in AP in both CV1 and CV2. (3) Gains with ME over SE attributed to genetic correlation between environments, with little effect from residual correlation. Impacts of marker density on predictions also were investigated in this study.

Guo, Zhigang; Tucker, Dominic M.; Wang, Daolong; Basten, Christopher J.; Ersoz, Elhan; Briggs, William H.; Lu, Jianwei; Li, Min; Gay, Gilles

2013-01-01

293

White sturgeons Acipenser transmontanus were sampled in three lower Columbia River reservoirs from 1987 to 1991 to describe population dynamics, the ability of these stocks to sustain harvest, and differences among reservoir and unimpounded populations. Significant differences were observed among reservoirs in white sturgeon abundance, biomass, size composition, sex ratio, size of females at maturity, growth rate, condition factor, and rate of exploitation. No differences among reservoirs were detected in fecundity, natural mortality rate, or longevity, in part because of sampling difficulties. Recruitment rates and densities in reservoirs were inversely correlated with growth rate, condition factor, and size of females at maturity. Differences in population dynamics resulted in substantial differences in sustainable yields. Maximum yields per recruit were predicted at annual exploitation rates between 5 and 15%. Most characteristics of reservoir populations were less than or equal to optima reported for the unimpounded lower river; as a result, yield per recruit, reproductive potential per recruit, and the number of recruits were less in reservoirs than in the unimpounded river. Comparisons with pristine standing stocks suggest that the unimpounded river may approximate preimpoundment conditions for white sturgeon. We conclude that potential yield from impounded populations has been reduced by dam construction, which restricts populations to river segments that may not include conditions optimal for all life stages. Alternatives for enchancement of reservoir populations might include improved passage at dams, increased spring flow to improve spawning success, transplants from productive populations, hatchery supplementation, and more intensive harvest management. 54 refs., 7 figs., 7 tabs.

Beamesderfer, R.C.P.; Rien, T.A.; Nigro, A.A. [Oregon Department of Fish and Wildlife, Clackamas, OR (United States)

1995-11-01

294

Although molecular chaperones are essential components of protein homeostatic machinery, their mechanism of action and impact on adaptation and evolutionary dynamics remain controversial. Here we developed a physics-based ab initio multi-scale model of a living cell for population dynamics simulations to elucidate the effect of chaperones on adaptive evolution. The 6-loci genomes of model cells encode model proteins, whose folding and interactions in cellular milieu can be evaluated exactly from their genome sequences. A genotype-phenotype relationship that is based on a simple yet non-trivially postulated protein-protein interaction (PPI) network determines the cell division rate. Model proteins can exist in native and molten globule states and participate in functional and all possible promiscuous non-functional PPIs. We find that an active chaperone mechanism, whereby chaperones directly catalyze protein folding, has a significant impact on the cellular fitness and the rate of evolutionary dynamics, while passive chaperones, which just maintain misfolded proteins in soluble complexes have a negligible effect on the fitness. We find that by partially releasing the constraint on protein stability, active chaperones promote a deeper exploration of sequence space to strengthen functional PPIs, and diminish the non-functional PPIs. A key experimentally testable prediction emerging from our analysis is that down-regulation of chaperones that catalyze protein folding significantly slows down the adaptation dynamics.

Cetinbas, Murat; Shakhnovich, Eugene I.

2013-01-01

295

Understanding how genetic variation is generated and maintained in natural populations, and how this process unfolds in a changing environment, remains a central issue in biological research. In this work, we analysed patterns of genetic diversity from several populations of three cichlid species from Lake Tanganyika in parallel, using the mitochondrial DNA control region. We sampled populations inhabiting the littoral rocky habitats in both very deep and very shallow areas of the lake. We hypothesized that the former would constitute relatively older, more stable and genetically more diverse populations, because they should have been less severely affected by the well-documented episodes of dramatic water-level fluctuations. In agreement with our predictions, populations of all three species sampled in very shallow shorelines showed traces of stronger population growth than populations of the same species inhabiting deep shorelines. However, contrary to our working hypothesis, we found a significant trend towards increased genetic diversity in the younger, demographically less stable populations inhabiting shallow areas, in comparison with the older and more stable populations inhabiting the deep shorelines. We interpret this finding as the result of the establishment of metapopulation dynamics in the former shorelines, by the frequent perturbation and reshuffling of individuals between populations due to the lake-level fluctuations. The repeated succession of periods of allopatric separation and secondary contact is likely to have further increased the rapid pace of speciation in lacustrine cichlids. PMID:23837841

Nevado, B; Mautner, S; Sturmbauer, C; Verheyen, E

2013-08-01

296

Understanding how genetic variation is generated and maintained in natural populations, and how this process unfolds in a changing environment, remains a central issue in biological research. In this work, we analysed patterns of genetic diversity from several populations of three cichlid species from Lake Tanganyika in parallel, using the mitochondrial DNA control region. We sampled populations inhabiting the littoral rocky habitats in both very deep and very shallow areas of the lake. We hypothesized that the former would constitute relatively older, more stable and genetically more diverse populations, because they should have been less severely affected by the well-documented episodes of dramatic water-level fluctuations. In agreement with our predictions, populations of all three species sampled in very shallow shorelines showed traces of stronger population growth than populations of the same species inhabiting deep shorelines. However, contrary to our working hypothesis, we found a significant trend towards increased genetic diversity in the younger, demographically less stable populations inhabiting shallow areas, in comparison with the older and more stable populations inhabiting the deep shorelines. We interpret this finding as the result of the establishment of metapopulation dynamics in the former shorelines, by the frequent perturbation and reshuffling of individuals between populations due to the lake-level fluctuations. The repeated succession of periods of allopatric separation and secondary contact is likely to have further increased the rapid pace of speciation in lacustrine cichlids.

Nevado, B; Mautner, S; Sturmbauer, C; Verheyen, E

2013-01-01

297

Satellite Microwave Remote Sensing for Environmental Modeling of Mosquito Population Dynamics

Environmental variability has important influences on mosquito life cycles and understanding the spatial and temporal patterns of mosquito populations is critical for mosquito control and vector-borne disease prevention. Meteorological data used for model-based predictions of mosquito abundance and life cycle dynamics are typically acquired from ground-based weather stations; however, data availability and completeness are often limited by sparse networks and resource availability. In contrast, environmental measurements from satellite remote sensing are more spatially continuous and can be retrieved automatically. This study compared environmental measurements from the NASA Advanced Microwave Scanning Radiometer on EOS (AMSR-E) and in situ weather station data to examine their ability to predict the abundance of two important mosquito species (Aedes vexans and Culex tarsalis) in Sioux Falls, South Dakota, USA from 2005 to 2010. The AMSR-E land parameters included daily surface water inundation fraction, surface air temperature, soil moisture, and microwave vegetation opacity. The AMSR-E derived models had better fits and higher forecasting accuracy than models based on weather station data despite the relatively coarse (25-km) spatial resolution of the satellite data. In the AMSR-E models, air temperature and surface water fraction were the best predictors of Aedes vexans, whereas air temperature and vegetation opacity were the best predictors of Cx. tarsalis abundance. The models were used to extrapolate spatial, seasonal, and interannual patterns of climatic suitability for mosquitoes across eastern South Dakota. Our findings demonstrate that environmental metrics derived from satellite passive microwave radiometry are suitable for predicting mosquito population dynamics and can potentially improve the effectiveness of mosquito-borne disease early warning systems.

Chuang, Ting-Wu; Henebry, Geoffrey M.; Kimball, John S.; VanRoekel-Patton, Denise L.; Hildreth, Michael B.; Wimberly, Michael C.

2012-01-01

298

Temporal dynamics of emotional responding: amygdala recovery predicts emotional traits.

An individual's affective style is influenced by many things, including the manner in which an individual responds to an emotional challenge. Emotional response is composed of a number of factors, two of which are the initial reactivity to an emotional stimulus and the subsequent recovery once the stimulus terminates or ceases to be relevant. However, most neuroimaging studies examining emotional processing in humans focus on the magnitude of initial reactivity to a stimulus rather than the prolonged response. In this study, we use functional magnetic resonance imaging to study the time course of amygdala activity in healthy adults in response to presentation of negative images. We split the amygdala time course into an initial reactivity period and a recovery period beginning after the offset of the stimulus. We find that initial reactivity in the amygdala does not predict trait measures of affective style. Conversely, amygdala recovery shows predictive power such that slower amygdala recovery from negative images predicts greater trait neuroticism, in addition to lower levels of likability of a set of social stimuli (neutral faces). These data underscore the importance of taking into account temporal dynamics when studying affective processing using neuroimaging. PMID:23160815

Schuyler, Brianna S; Kral, Tammi R A; Jacquart, Jolene; Burghy, Cory A; Weng, Helen Y; Perlman, David M; Bachhuber, David R W; Rosenkranz, Melissa A; Maccoon, Donal G; van Reekum, Carien M; Lutz, Antoine; Davidson, Richard J

2014-02-01

299

We study the time dependent interaction between hydrogeological and exposure parameters in daily dose predictions due to exposure of humans to groundwater contamination. Dose predictions are treated stochastically to account for an incomplete hydrogeological and geochemical field characterization, and an incomplete knowledge of the physiological response. We used a nested Monte Carlo framework to account for uncertainty and variability arising from both hydrogeological and exposure variables. Our interest is in the temporal dynamics of the total dose and their effects on parametric uncertainty reduction. We illustrate the approach to a HCH (lindane) pollution problem at the Ebro River, Spain. The temporal distribution of lindane in the river water can have a strong impact in the evaluation of risk. The total dose displays a non-linear effect on different population cohorts, indicating the need to account for population variability. We then expand the concept of Comparative Information Yield Curves developed earlier (see de Barros et al. [29]) to evaluate parametric uncertainty reduction under temporally variable exposure dose. Results show that the importance of parametric uncertainty reduction varies according to the temporal dynamics of the lindane plume. The approach could be used for any chemical to aid decision makers to better allocate resources towards reducing uncertainty. PMID:24011618

Kumar, Vikas; de Barros, Felipe P J; Schuhmacher, Marta; Fernàndez-Garcia, Daniel; Sanchez-Vila, Xavier

2013-12-15

300

Multiprocess dynamic modeling of tumor evolution with bayesian tumor-specific predictions.

We propose a sequential probabilistic mixture model for individualized tumor growth forecasting. In contrast to conventional deterministic methods for estimation and prediction of tumor evolution, we utilize all available tumor-specific observations up to the present time to approximate the unknown multi-scale process of tumor growth over time, in a stochastic context. The suggested mixture model uses prior information obtained from the general population and becomes more individualized as more observations from the tumor are sequentially taken into account. Inference can be carried out using the full, possibly multimodal, posterior, and predictive distributions instead of point estimates. In our simulation study we illustrate the superiority of the suggested multi-process dynamic linear model compared to the single process alternative. The validation of our approach was performed with experimental data from mice. The methodology suggested in the present study may provide a starting point for personalized adaptive treatment strategies. PMID:24488234

Achilleos, Achilleas; Loizides, Charalambos; Hadjiandreou, Marios; Stylianopoulos, Triantafyllos; Mitsis, Georgios D

2014-05-01

301

Using glucose time series data from a well measured population drawn from an electronic health record (EHR) repository, the variation in predictability of glucose values quantified by the time-delayed mutual information (TDMI) was explained using a mechanistic endocrine model and manual and automated review of written patient records. The results suggest that predictability of glucose varies with health state where the relationship (e.g., linear or inverse) depends on the source of the acuity. It was found that on a fine scale in parameter variation, the less insulin required to process glucose, a condition that correlates with good health, the more predictable glucose values were. Nevertheless, the most powerful effect on predictability in the EHR subpopulation was the presence or absence of variation in health state, specifically, in- and out-of-control glucose versus in-control glucose. Both of these results are clinically and scientifically relevant because the magnitude of glucose is the most commonly used indicator of health as opposed to glucose dynamics, thus providing for a connection between a mechanistic endocrine model and direct insight to human health via clinically collected data.

Albers, D. J.; Elhadad, Noemie; Tabak, E.; Perotte, A.; Hripcsak, George

2014-01-01

302

Using glucose time series data from a well measured population drawn from an electronic health record (EHR) repository, the variation in predictability of glucose values quantified by the time-delayed mutual information (TDMI) was explained using a mechanistic endocrine model and manual and automated review of written patient records. The results suggest that predictability of glucose varies with health state where the relationship (e.g., linear or inverse) depends on the source of the acuity. It was found that on a fine scale in parameter variation, the less insulin required to process glucose, a condition that correlates with good health, the more predictable glucose values were. Nevertheless, the most powerful effect on predictability in the EHR subpopulation was the presence or absence of variation in health state, specifically, in- and out-of-control glucose versus in-control glucose. Both of these results are clinically and scientifically relevant because the magnitude of glucose is the most commonly used indicator of health as opposed to glucose dynamics, thus providing for a connection between a mechanistic endocrine model and direct insight to human health via clinically collected data. PMID:24933368

Albers, D J; Elhadad, Noémie; Tabak, E; Perotte, A; Hripcsak, George

2014-01-01

303

Genomic selection using dense markers covering the whole genome is a tool for the genetic improvement of livestock and is revolutionizing the breeding system in dairy cattle. Progeny-tested bulls have been used to form reference populations in almost all countries where genomic selection has been implemented. In this study, the accuracy of genomic prediction when cows are used to form the reference population was investigated. The reference population consisted of 3,087 cows. All individuals were genotyped with Illumina BovineSNP50. After genotype imputation and editing, 48,676 single nucleotide polymorphisms were available for analysis. Two methods, genomic BLUP (GBLUP) and BayesB, were used to render genomic estimated breeding values (GEBV) for 5 milk production traits. Accuracies of GEBV were assessed in 3 ways: r(GEBV,EBV) (the correlation between GEBV and conventional EBV) in 67 progeny-tested bulls, rGEBV,EBV from a 5-fold cross validation in the 3,087 cow reference population, and the theoretical accuracy (for GBLUP) calculated in the same way as for conventional BLUP. The results showed that using GBLUP, the r(GEBV,EBV) and theoretical accuracy of genomic prediction in Chinese Holstein ranged from 0.59 to 0.76 and 0.70 to 0.80, respectively, which was 0.13 to 0.30 and 0.23 to 0.33 higher than the accuracies of conventional pedigree index, respectively. The results indicate that, as an alternative, genomic selection using cows in the reference population is feasible. PMID:23746588

Ding, X; Zhang, Z; Li, X; Wang, S; Wu, X; Sun, D; Yu, Y; Liu, J; Wang, Y; Zhang, Y; Zhang, S; Zhang, Y; Zhang, Q

2013-08-01

304

Summary Objective: By using a population pharmacokinetic analysis method, we predicted the efficacy of Ceftriaxone (CTRX) based on\\u000a the pharmacokinetics of CTRX in Japanese adults and the sensitivity of infective organisms to CTRX in 2004. In addition, we\\u000a clarified the difference in efficacy between once-a-day administration and twice-a-day administration. Methods: The population\\u000a pharmacokinetic analysis was based on the serum concentrations of

SATOFUMI IIDAI; Haruki Kinoshita; Takehiko Kawanishi; Masahiro Hayashi

2009-01-01

305

Prediction of additive and dominance effects in selected or unselected populations with inbreeding

A genetic model with either 64 or 1,600 unlinked biallelic loci and complete dominance was used to study prediction of additive and dominance effects in selected or unselected populations with inbreeding. For each locus the initial frequency of the favourable allele was 0.2, 0.5, or 0.8 in different alternatives, while the initial narrow-sense heritability was fixed at 0.30. A population

I. J. M. de Boer; J. A. M. Arendonk

1992-01-01

306

The Population and Evolutionary Dynamics of Phage and Bacteria with CRISPR-Mediated Immunity

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), together with associated genes (cas), form the CRISPR–cas adaptive immune system, which can provide resistance to viruses and plasmids in bacteria and archaea. Here, we use mathematical models, population dynamic experiments, and DNA sequence analyses to investigate the host–phage interactions in a model CRISPR–cas system, Streptococcus thermophilus DGCC7710 and its virulent phage 2972. At the molecular level, the bacteriophage-immune mutant bacteria (BIMs) and CRISPR–escape mutant phage (CEMs) obtained in this study are consistent with those anticipated from an iterative model of this adaptive immune system: resistance by the addition of novel spacers and phage evasion of resistance by mutation in matching sequences or flanking motifs. While CRISPR BIMs were readily isolated and CEMs generated at high rates (frequencies in excess of 10?6), our population studies indicate that there is more to the dynamics of phage–host interactions and the establishment of a BIM–CEM arms race than predicted from existing assumptions about phage infection and CRISPR–cas immunity. Among the unanticipated observations are: (i) the invasion of phage into populations of BIMs resistant by the acquisition of one (but not two) spacers, (ii) the survival of sensitive bacteria despite the presence of high densities of phage, and (iii) the maintenance of phage-limited communities due to the failure of even two-spacer BIMs to become established in populations with wild-type bacteria and phage. We attribute (i) to incomplete resistance of single-spacer BIMs. Based on the results of additional modeling and experiments, we postulate that (ii) and (iii) can be attributed to the phage infection-associated production of enzymes or other compounds that induce phenotypic phage resistance in sensitive bacteria and kill resistant BIMs. We present evidence in support of these hypotheses and discuss the implications of these results for the ecology and (co)evolution of bacteria and phage.

Levin, Bruce R.; Moineau, Sylvain; Bushman, Mary; Barrangou, Rodolphe

2013-01-01

307

On the dynamics and predictability of moist turbulence

NASA Astrophysics Data System (ADS)

In this thesis I present a simple, computationally-inexpensive moist turbulence model in order to study the differences between moist and dry turbulence. The model is validated by comparing a moist-bubble simulation with ones presented in Grabowski and Clark (1993) using a more-sophisticated model. We show that the outputs compare well and that our model can easily be extended to higher resolutions due to its simplified equations and uncomplicated implementation. Measurements of liquid water content spectra from the 3843 validation run are shown having shallow slopes, implying that moist processes require high resolution. Consideration is also given to the issue of Gibb's oscillations near sharp gradients, such as at a cloud boundary. It is shown that, due to our high resolutions, the dynamics of our model are not seriously affected if corrections are not made to address them. The model is used to study the small-scale predictability and dynamics of moist and dry shallow convective turbulence. Although moist flows are less predictable than their associated dry flows, we can account for the differences via a simple scaling. Using large-scale (the root-mean-squared vorticity) and small-scale (the dissipation wavenumber, kd) measures, we can reconcile classical predictability statistics from both wet and dry runs, with different lapse rates and relative humidities. Finally, I present a more thorough investigation of the dynamical differences between wet and dry convective turbulence, and then consider the very small-scale (? ? 10 m) variability of liquid water content and compare our high-resolution simulation results to existing in situ cumulus-cloud observations. We find that there is a small decrease in the spatial intermittency of vorticity in wet runs relative to dry ones. This is consistent with the idea that evaporation of the liquid water in the clouds reduces the instabilities that would lead to the most intense vortices. At the same time, the liquid water content spectra show that in these areas of intense mixing and cloud decay, the characteristic scale of variability is shifted to smaller scales compared to a passive scalar. Further integrations in which the convective forcing is removed show that as the amount of liquid water decreases through evaporation, there is delayed decay of the smallest scales of the cloud. These findings may explain the small-scale shallow liquid water content spectra from cumulus-cloud fly-through measurements reported in Davis et al. (1999).

Spyksma, Kyle

308

A model describing the population dynamics of Sitobion avenae and Coccinella septempunctata

A model that described the summer population dynamics of the cereal aphid Sitobion avenae (Carter et al., 1982) was modified and extended to include the population dynamics of the aphidophagous predator Coccinella septempunctata. New equations were formulated to describe the dependence of aphid development and reproduction on temperature. The predation interaction between the aphid and coccinellid was formulated with a

D. J. Skirvin; J. N. Perry; R. Harrington

1997-01-01

309

Accuracy of genotypic value predictions for marker-based selection in biparental plant populations.

The availability of cheap and abundant molecular markers has led to plant-breeding methods that rely on the prediction of genotypic value from marker data, but published information is lacking on the accuracy of genotypic value predictions with empirical data in plants. Our objectives were to (1) determine the accuracy of genotypic value predictions from multiple linear regression (MLR) and genomewide selection via best linear unbiased prediction (BLUP) in biparental plant populations; (2) assess the accuracy of predictions for different numbers of markers (N(M)) and progenies (N(P)) used in estimation; and (3) determine if an empirical Bayes approach for modeling of the variances of individual markers and of epistatic effects leads to more accurate predictions in empirical data. We divided each of four maize (Zea mays L.) datasets, one Arabidopsis dataset, and two barley (Hordeum vulgare L.) datasets into an estimation set, where marker effects were calculated, and a test set, where genotypic values were predicted based on markers. Predictions were more accurate with BLUP than with MLR. Predictions became more accurate as N(P) and N(M) increased, until sufficient genome coverage was reached. Modeling marker variances with the empirical Bayes method sometimes led to slightly better predictions, but the accuracy with different variants of the empirical Bayes method was often inconsistent. In nearly all cases, the accuracy with BLUP was not significantly different from the highest accuracy across all methods. Accounting for epistasis in the empirical Bayes procedure led to poorer predictions. We concluded that among the methods considered, the quick and simple BLUP approach is the method of choice for predicting genotypic value in biparental plant populations. PMID:19841887

Lorenzana, Robenzon E; Bernardo, Rex

2009-12-01

310

The prevalence and impact of bacteriophages in the ecology of bacterial communities coupled with their ability to control pathogens turn essential to understand and predict the dynamics between phage and bacteria populations. To achieve this knowledge it is essential to develop mathematical models able to explain and simulate the population dynamics of phage and bacteria. We have developed an unstructured mathematical model using delay-differential equations to predict the interactions between a broad-host-range Salmonella phage and its pathogenic host. The model takes into consideration the main biological parameters that rule phage-bacteria interactions likewise the adsorption rate, latent period, burst size, bacterial growth rate, and substrate uptake rate, among others. The experimental validation of the model was performed with data from phage-interaction studies in a 5 L bioreactor. The key and innovative aspect of the model was the introduction of variations in the latent period and adsorption rate values that are considered as constants in previous developed models. By modelling the latent period as a normal distribution of values and the adsorption rate as a function of the bacterial growth rate it was possible to accurately predict the behaviour of the phage-bacteria population. The model was shown to predict simulated data with a good agreement with the experimental observations and explains how a lytic phage and its host bacteria are able to coexist.

Santos, Silvio B.; Carvalho, Carla; Azeredo, Joana; Ferreira, Eugenio C.

2014-01-01

311

The prevalence and impact of bacteriophages in the ecology of bacterial communities coupled with their ability to control pathogens turn essential to understand and predict the dynamics between phage and bacteria populations. To achieve this knowledge it is essential to develop mathematical models able to explain and simulate the population dynamics of phage and bacteria. We have developed an unstructured mathematical model using delay-differential equations to predict the interactions between a broad-host-range Salmonella phage and its pathogenic host. The model takes into consideration the main biological parameters that rule phage-bacteria interactions likewise the adsorption rate, latent period, burst size, bacterial growth rate, and substrate uptake rate, among others. The experimental validation of the model was performed with data from phage-interaction studies in a 5 L bioreactor. The key and innovative aspect of the model was the introduction of variations in the latent period and adsorption rate values that are considered as constants in previous developed models. By modelling the latent period as a normal distribution of values and the adsorption rate as a function of the bacterial growth rate it was possible to accurately predict the behaviour of the phage-bacteria population. The model was shown to predict simulated data with a good agreement with the experimental observations and explains how a lytic phage and its host bacteria are able to coexist. PMID:25051248

Santos, Sílvio B; Carvalho, Carla; Azeredo, Joana; Ferreira, Eugénio C

2014-01-01

312

The influence of spatio-temporal resource fluctuations on insular rat population dynamics

Local spatio-temporal resource variations can strongly influence the population dynamics of small mammals. This is particularly true on islands which are bottom-up driven systems, lacking higher order predators and with high variability in resource subsidies. The influence of resource fluctuations on animal survival may be mediated by individual movement among habitat patches, but simultaneously analysing survival, resource availability and habitat selection requires sophisticated analytical methods. We use a Bayesian multi-state capture–recapture model to estimate survival and movement probabilities of non-native black rats (Rattus rattus) across three habitats seasonally varying in resource availability. We find that survival varies most strongly with temporal rainfall patterns, overwhelming minor spatial variation among habitats. Surprisingly for a generalist forager, movement between habitats was rare, suggesting individuals do not opportunistically respond to spatial resource subsidy variations. Climate is probably the main driver of rodent population dynamics on islands, and even substantial habitat and seasonal spatial subsidies are overwhelmed in magnitude by predictable annual patterns in resource pulses. Marked variation in survival and capture has important implications for the timing of rat control.

Russell, James C.; Ruffino, Lise

2012-01-01

313

Discrete molecular dynamics can predict helical prestructured motifs in disordered proteins.

Intrinsically disordered proteins (IDPs) lack a stable tertiary structure, but their short binding regions termed Pre-Structured Motifs (PreSMo) can form transient secondary structure elements in solution. Although disordered proteins are crucial in many biological processes and designing strategies to modulate their function is highly important, both experimental and computational tools to describe their conformational ensembles and the initial steps of folding are sparse. Here we report that discrete molecular dynamics (DMD) simulations combined with replica exchange (RX) method efficiently samples the conformational space and detects regions populating ?-helical conformational states in disordered protein regions. While the available computational methods predict secondary structural propensities in IDPs based on the observation of protein-protein interactions, our ab initio method rests on physical principles of protein folding and dynamics. We show that RX-DMD predicts ?-PreSMos with high confidence confirmed by comparison to experimental NMR data. Moreover, the method also can dissect ?-PreSMos in close vicinity to each other and indicate helix stability. Importantly, simulations with disordered regions forming helices in X-ray structures of complexes indicate that a preformed helix is frequently the binding element itself, while in other cases it may have a role in initiating the binding process. Our results indicate that RX-DMD provides a breakthrough in the structural and dynamical characterization of disordered proteins by generating the structural ensembles of IDPs even when experimental data are not available. PMID:24763499

Szöll?si, Dániel; Horváth, Tamás; Han, Kyou-Hoon; Dokholyan, Nikolay V; Tompa, Péter; Kalmár, Lajos; Heged?s, Tamás

2014-01-01

314

Discrete Molecular Dynamics Can Predict Helical Prestructured Motifs in Disordered Proteins

Intrinsically disordered proteins (IDPs) lack a stable tertiary structure, but their short binding regions termed Pre-Structured Motifs (PreSMo) can form transient secondary structure elements in solution. Although disordered proteins are crucial in many biological processes and designing strategies to modulate their function is highly important, both experimental and computational tools to describe their conformational ensembles and the initial steps of folding are sparse. Here we report that discrete molecular dynamics (DMD) simulations combined with replica exchange (RX) method efficiently samples the conformational space and detects regions populating ?-helical conformational states in disordered protein regions. While the available computational methods predict secondary structural propensities in IDPs based on the observation of protein-protein interactions, our ab initio method rests on physical principles of protein folding and dynamics. We show that RX-DMD predicts ?-PreSMos with high confidence confirmed by comparison to experimental NMR data. Moreover, the method also can dissect ?-PreSMos in close vicinity to each other and indicate helix stability. Importantly, simulations with disordered regions forming helices in X-ray structures of complexes indicate that a preformed helix is frequently the binding element itself, while in other cases it may have a role in initiating the binding process. Our results indicate that RX-DMD provides a breakthrough in the structural and dynamical characterization of disordered proteins by generating the structural ensembles of IDPs even when experimental data are not available.

Han, Kyou-Hoon; Dokholyan, Nikolay V.; Tompa, Peter; Kalmar, Lajos; Hegedus, Tamas

2014-01-01

315

Predicting large area surface reconstructions using molecular dynamics methods.

In this paper we discuss a new simulation method that can be used to predict preferred surface reconstructions of model systems by Molecular Dynamics (MD). The method overcomes the limitations imposed by periodic boundary conditions for finite boundary MD simulations which can normally prevent reconstructions. By simulating only the reconstructed surface layer and by removing the periodic boundary effects and the free energy barriers to reconstruction, the method allows surfaces to reconstruct to a preferred structure. We test the method on three types of surfaces: (i) the Au(100) and Pt(100) hexagonally reconstructed surface, (ii) the Au(111) herringbone surfaces, and (iii) the triangularly reconstructed Ag surface layer on a Pt(111) substrate and find the method readily finds lower surface energy reconstructions as preferred by the potential. PMID:24511962

Grochola, Gregory; Snook, Ian K; Russo, Salvy P

2014-02-01

316

Methods for evaluating the predictive accuracy of structural dynamic models

NASA Technical Reports Server (NTRS)

Uncertainty of frequency response using the fuzzy set method and on-orbit response prediction using laboratory test data to refine an analytical model are emphasized with respect to large space structures. Two aspects of the fuzzy set approach were investigated relative to its application to large structural dynamics problems: (1) minimizing the number of parameters involved in computing possible intervals; and (2) the treatment of extrema which may occur in the parameter space enclosed by all possible combinations of the important parameters of the model. Extensive printer graphics were added to the SSID code to help facilitate model verification, and an application of this code to the LaRC Ten Bay Truss is included in the appendix to illustrate this graphics capability.

Hasselman, T. K.; Chrostowski, Jon D.

1990-01-01

317

Nonlinear Dynamic Inversion Baseline Control Law: Architecture and Performance Predictions

NASA Technical Reports Server (NTRS)

A model reference dynamic inversion control law has been developed to provide a baseline control law for research into adaptive elements and other advanced flight control law components. This controller has been implemented and tested in a hardware-in-the-loop simulation; the simulation results show excellent handling qualities throughout the limited flight envelope. A simple angular momentum formulation was chosen because it can be included in the stability proofs for many basic adaptive theories, such as model reference adaptive control. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as basic as possible to simplify the addition of the adaptive elements. Those design choices are explained, along with their predicted impact on the handling qualities.

Miller, Christopher J.

2011-01-01

318

Predicting large area surface reconstructions using molecular dynamics methods

NASA Astrophysics Data System (ADS)

In this paper we discuss a new simulation method that can be used to predict preferred surface reconstructions of model systems by Molecular Dynamics (MD). The method overcomes the limitations imposed by periodic boundary conditions for finite boundary MD simulations which can normally prevent reconstructions. By simulating only the reconstructed surface layer and by removing the periodic boundary effects and the free energy barriers to reconstruction, the method allows surfaces to reconstruct to a preferred structure. We test the method on three types of surfaces: (i) the Au(100) and Pt(100) hexagonally reconstructed surface, (ii) the Au(111) herringbone surfaces, and (iii) the triangularly reconstructed Ag surface layer on a Pt(111) substrate and find the method readily finds lower surface energy reconstructions as preferred by the potential.

Grochola, Gregory; Snook, Ian K.; Russo, Salvy P.

2014-02-01

319

In order to improve the prediction accuracy of current existing model, the financial crisis prediction dynamic model is proposed. By means of the data streams processing method, the sliding window technology is used for real-time updated samples in this paper, and then the optimal features of samples are selected by Mahalanobis-Taguchi System. The financial crisis prediction dynamic model is built

Jianzhong Shi; Longsheng Cheng

2011-01-01

320

The applied research of Kalman in the dynamic travel time prediction

The dynamic travel time prediction is important contents of The intelligent Transportation System. Dynamic travel time is updating the travel time by the prediction model on the same path or segment of the journey. Different forecasting models are corresponded to different methods, and different methods are corresponded to different prediction accuracy. Contrast to the existing methods, such as historical trends

Huifeng Ji; Aigong Xu; Xin Sui; Lanyong Li

2010-01-01

321

Predicting the performance of large scale plants can be difficult due to model uncertainties etc, meaning that one can be almost certain that the prediction will diverge from the plant performance with time. In this paper output multiplicative uncertainty models are used as dynamical models of the prediction error. These proposed dynamical uncertainty models results in an upper and lower

P. F. Odgaard; J. Stoustrup; B. Mataji

322

Utility of Microcosm Studies for Predicting Phylloplane Bacterium Population Sizes in the Field

Population sizes of two ice nucleation-active strains of Pseudomonas syringae were compared on leaves in controlled environments and in the field to determine the ability of microcosm studies to predict plant habitat preferences in the field. The P. syringae strains investigated were the parental strains of recombinant deletion mutant strains deficient in ice nucleation activity that had been field tested for their ability to control plant frost injury. The population size of the P. syringae strains was measured after inoculation at three field locations on up to 40 of the same plant species that were studied in the growth chamber. There was seldom a significant relationship between the mean population size of a given P. syringae strain incubated under either wet or dry conditions in microcosms and the mean population size which could be recovered from the same species when inoculated in the field. Specifically, on some plant species, the population size recovered from leaves in the field was substantially greater than from that species in a controlled environment, while for other plant species field populations were significantly smaller than those observed under controlled conditions. Population sizes of inoculated P. syringae strains, however, were frequently highly positively correlated with the indigenous bacterial population size on the same plant species in the field, suggesting that the ability of a particular plant species to support introduced bacterial strains is correlated with its ability to support large bacterial populations or that indigenous bacteria enhance the survival of introduced strains. Microcosm studies therefore seem most effective at assessing possible differences between parental and recombinant strains under a given environmental regime but are limited in their ability to predict the specific population sizes or plant habitat preferences of bacteria on leaves under field conditions.

Kinkel, L. L.; Wilson, M.; Lindow, S. E.

1996-01-01

323

The investigation of individual heterogeneity in vital rates has recently received growing attention among population ecologists. Individual heterogeneity in wild animal populations has been accounted for and quantified by including individually varying effects in models for mark–recapture data, but the real need for underlying individual effects to account for observed levels of individual variation has recently been questioned by the work of Tuljapurkar et al. (Ecology Letters, 12, 93, 2009) on dynamic heterogeneity. Model-selection approaches based on information criteria or Bayes factors have been used to address this question. Here, we suggest that, in addition to model-selection, model-checking methods can provide additional important insights to tackle this issue, as they allow one to evaluate a model's misfit in terms of ecologically meaningful measures. Specifically, we propose the use of posterior predictive checks to explicitly assess discrepancies between a model and the data, and we explain how to incorporate model checking into the inferential process used to assess the practical implications of ignoring individual heterogeneity. Posterior predictive checking is a straightforward and flexible approach for performing model checks in a Bayesian framework that is based on comparisons of observed data to model-generated replications of the data, where parameter uncertainty is incorporated through use of the posterior distribution. If discrepancy measures are chosen carefully and are relevant to the scientific context, posterior predictive checks can provide important information allowing for more efficient model refinement. We illustrate this approach using analyses of vital rates with long-term mark–recapture data for Weddell seals and emphasize its utility for identifying shortfalls or successes of a model at representing a biological process or pattern of interest. We show how posterior predictive checks can be used to strengthen inferences in ecological studies. We demonstrate the application of this method on analyses dealing with the question of individual reproductive heterogeneity in a population of Antarctic pinnipeds.

Chambert, Thierry; Rotella, Jay J; Higgs, Megan D

2014-01-01

324

The investigation of individual heterogeneity in vital rates has recently received growing attention among population ecologists. Individual heterogeneity in wild animal populations has been accounted for and quantified by including individually varying effects in models for mark-recapture data, but the real need for underlying individual effects to account for observed levels of individual variation has recently been questioned by the work of Tuljapurkar et al. (Ecology Letters, 12, 93, 2009) on dynamic heterogeneity. Model-selection approaches based on information criteria or Bayes factors have been used to address this question. Here, we suggest that, in addition to model-selection, model-checking methods can provide additional important insights to tackle this issue, as they allow one to evaluate a model's misfit in terms of ecologically meaningful measures. Specifically, we propose the use of posterior predictive checks to explicitly assess discrepancies between a model and the data, and we explain how to incorporate model checking into the inferential process used to assess the practical implications of ignoring individual heterogeneity. Posterior predictive checking is a straightforward and flexible approach for performing model checks in a Bayesian framework that is based on comparisons of observed data to model-generated replications of the data, where parameter uncertainty is incorporated through use of the posterior distribution. If discrepancy measures are chosen carefully and are relevant to the scientific context, posterior predictive checks can provide important information allowing for more efficient model refinement. We illustrate this approach using analyses of vital rates with long-term mark-recapture data for Weddell seals and emphasize its utility for identifying shortfalls or successes of a model at representing a biological process or pattern of interest. We show how posterior predictive checks can be used to strengthen inferences in ecological studies. We demonstrate the application of this method on analyses dealing with the question of individual reproductive heterogeneity in a population of Antarctic pinnipeds. PMID:24834335

Chambert, Thierry; Rotella, Jay J; Higgs, Megan D

2014-04-01

325

Multi-population genomic prediction using a multi-task Bayesian learning model

Background Genomic prediction in multiple populations can be viewed as a multi-task learning problem where tasks are to derive prediction equations for each population and multi-task learning property can be improved by sharing information across populations. The goal of this study was to develop a multi-task Bayesian learning model for multi-population genomic prediction with a strategy to effectively share information across populations. Simulation studies and real data from Holstein and Ayrshire dairy breeds with phenotypes on five milk production traits were used to evaluate the proposed multi-task Bayesian learning model and compare with a single-task model and a simple data pooling method. Results A multi-task Bayesian learning model was proposed for multi-population genomic prediction. Information was shared across populations through a common set of latent indicator variables while SNP effects were allowed to vary in different populations. Both simulation studies and real data analysis showed the effectiveness of the multi-task model in improving genomic prediction accuracy for the smaller Ayshire breed. Simulation studies suggested that the multi-task model was most effective when the number of QTL was small (n?=?20), with an increase of accuracy by up to 0.09 when QTL effects were lowly correlated between two populations (??=?0.2), and up to 0.16 when QTL effects were highly correlated (??=?0.8). When QTL genotypes were included for training and validation, the improvements were 0.16 and 0.22, respectively, for scenarios of the low and high correlation of QTL effects between two populations. When the number of QTL was large (n?=?200), improvement was small with a maximum of 0.02 when QTL genotypes were not included for genomic prediction. Reduction in accuracy was observed for the simple pooling method when the number of QTL was small and correlation of QTL effects between the two populations was low. For the real data, the multi-task model achieved an increase of accuracy between 0 and 0.07 in the Ayrshire validation set when 28,206 SNPs were used, while the simple data pooling method resulted in a reduction of accuracy for all traits except for protein percentage. When 246,668 SNPs were used, the accuracy achieved from the multi-task model increased by 0 to 0.03, while using the pooling method resulted in a reduction of accuracy by 0.01 to 0.09. In the Holstein population, the three methods had similar performance. Conclusions Results in this study suggest that the proposed multi-task Bayesian learning model for multi-population genomic prediction is effective and has the potential to improve the accuracy of genomic prediction.

2014-01-01

326

Frontal oscillatory dynamics predict feedback learning and action adjustment.

Frontal oscillatory dynamics in the theta (4-8 Hz) and beta (20-30 Hz) frequency bands have been implicated in cognitive control processes. Here we investigated the changes in coordinated activity within and between frontal brain areas during feedback-based response learning. In a time estimation task, participants learned to press a button after specific, randomly selected time intervals (300-2000 msec) using the feedback after each button press (correct, too fast, too slow). Consistent with previous findings, theta-band activity over medial frontal scalp sites (presumably reflecting medial frontal cortex activity) was stronger after negative feedback, whereas beta-band activity was stronger after positive feedback. Theta-band power predicted learning only after negative feedback, and beta-band power predicted learning after positive and negative feedback. Furthermore, negative feedback increased theta-band intersite phase synchrony (a millisecond resolution measure of functional connectivity) among right lateral prefrontal, medial frontal, and sensorimotor sites. These results demonstrate the importance of frontal theta- and beta-band oscillations and intersite communication in the realization of reinforcement learning. PMID:21812570

van de Vijver, Irene; Ridderinkhof, K Richard; Cohen, Michael X

2011-12-01

327

Population Dynamics of a Spin1 Bose Gas at Finite Temperatures

We study population dynamics of a trapped spin-1 Bose gas above the Bose-Einstein transition temperature. Starting from the\\u000a semiclassical kinetic equation for a spin-1 gas, we derive coupled rate equations for the populations of internal states.\\u000a Solving the rate equations, we study the dynamical evolution of spin populations. We also estimate the characteristic timescale\\u000a in which the system reaches equilibrium.

Yuki Endo; Tetsuro Nikuni

2010-01-01

328

Quantifying Salmonella population dynamics in water and biofilms.

Members of the bacterial genus Salmonella are recognized worldwide as major zoonotic pathogens often found to persist in non-enteric environments including heterogeneous aquatic biofilms. In this study, Salmonella isolates that had been detected repeatedly over time in aquatic biofilms at different sites in Spring Lake, San Marcos, Texas, were identified as serovars Give, Thompson, Newport and -:z10:z39. Pathogenicity results from feeding studies with the nematode Caenorhabditis elegans as host confirmed that these strains were pathogenic, with Salmonella-fed C. elegans dying faster (mean survival time between 3 and 4 days) than controls, i.e., Escherichia coli-fed C. elegans (mean survival time of 9.5 days). Cells of these isolates inoculated into water at a density of up to 10(6)?ml(-1) water declined numerically by 3 orders of magnitude within 2 days, reaching the detection limit of our quantitative polymerase chain reaction (qPCR)-based quantification technique (i.e., 10(3) cells ml(-1)). Similar patterns were obtained for cells in heterogeneous aquatic biofilms developed on tiles and originally free of Salmonella that were kept in the inoculated water. Cell numbers increased during the first days to more than 10(7) cells cm(-2), and then declined over time. Ten-fold higher cell numbers of Salmonella inoculated into water or into biofilm resulted in similar patterns of population dynamics, though cells in biofilms remained detectable with numbers around 10(4) cells cm(-2) after 4 weeks. Independent of detectability by qPCR, samples of all treatments harbored viable salmonellae that resembled the inoculated isolates after 4 weeks of incubation. These results demonstrate that pathogenic salmonellae were isolated from heterogeneous aquatic biofilms and that they could persist and stay viable in such biofilms in high numbers for some time. PMID:22890729

Sha, Qiong; Vattem, Dhiraj A; Forstner, Michael R J; Hahn, Dittmar

2013-01-01

329

This study investigated correlations among climatic variability, population age structure, and seedling survival of a dominant Sonoran Desert tree, Cercidium microphyllum (foothill paloverde), at Tucson, Arizona, USA. A major goal was to determine whether wet years promote seedling establishment and thereby determine population structure. Plant age was estimated from basal circumference for a sample of 980 living and dead trees in twelve 0.5-ha plots. Ages ranged from 1 to 181 years. Age frequency distribution showed that the population is in decline. Most (51.2%) of the 814 living trees were 40-80 years old; only 6.5% were younger than 20 years. The average age of the 166 dead trees was 78 years. Fifty-nine percent of dead trees were aged 60-100 years. Survival of newly emerged seedlings was monitored for 7 years in a 557-m2 permanent plot. Mean survival in the 1st year of life was 1.7%. Only 2 of 1,008 seedlings lived longer than 1 year. Length of survival was not correlated with rainfall. Residual regeneration, an index of the difference between predicted and observed cohort size, showed that regeneration was high during the first half of the twentieth century and poor after the mid-1950s. Trends in regeneration did not reflect interannual variation in seasonal temperature or rain before 1950, that is, in the years before urban warming. Taken together, the seedling study and the regeneration analysis suggest that local population dynamics reflect biotic factors to such an extent that population age structure might not always be a reliable clue to past climatic influences.

Bowers, J. E.; Turner, R. M.

2002-01-01

330

High population variability and source-sink dynamics in a solitary bee species.

Although solitary bees are considered to play key roles in ecosystem functions, surprisingly few studies have explored their population dynamics. We investigated the population dynamics of a rare, declining, solitary bee (Andrena humilis) in a landscape of 80 km2 in southern Sweden from 2003 to 2011. Only one population was persistent throughout all years studied; most likely this population supplied the surrounding landscape with 11 smaller, temporary local populations. Despite stable pollen availability, the size of the persistent population fluctuated dramatically in a two-year cycle over the nine years, with 490-1230 nests in odd-numbered years and 21-48 nests in even-numbered years. These fluctuations were not significantly related to climatic variables or pollen availability. Nineteen colonization and 14 extinction events were recorded. Occupancy decreased with distance from the persistent population and increased with increasing resource (pollen) availability. There were significant positive correlations between the size of the persistent population and patch occupancy and colonization. Colonizations were generally more common in patches closer to the persistent population, whereas extinctions were independent of distance from the persistent population. Our results highlight the complex population dynamics that exist for this solitary bee species, which could be due to source-sink dynamics, a prolonged diapause, or can represent a bet-hedging strategy to avoid natural enemies and survive in small habitat patches. If large fluctuations in solitary bee populations prove to be widespread, it will have important implications for interpreting ecological relationships, bee conservation, and pollination. PMID:23923503

Franzén, Markus; Nilsson, Sven G

2013-06-01

331

The evolution of population dynamics in a stochastic environment is analysed under a general form of density-dependence with genetic variation in r and K, the intrinsic rate of increase and carrying capacity in the average environment, and in se 2 , the environmental variance of population growth rate. The continuous-time model assumes a large population size and a stationary distribution

Russell Lande; Steinar Engen; B.-E. Saether

2009-01-01

332

Weed populations and crop rotations : Exploring dynamics of a structured periodic system

The periodic growing of a certain set of crops in a prescribed order, called a crop rotation, is considered to be an important tool for managing weed populations. Nevertheless, the effects of crop rotations on weed population dynamics are not well understood. Explanations for rotation effects on weed populations usually invoke the diversity of environments caused by different crops that

Shana K. Mertens; Frank van den Bosch

2002-01-01

333

The Dynamics of Nestedness Predicts the Evolution of Industrial Ecosystems

In economic systems, the mix of products that countries make or export has been shown to be a strong leading indicator of economic growth. Hence, methods to characterize and predict the structure of the network connecting countries to the products that they export are relevant for understanding the dynamics of economic development. Here we study the presence and absence of industries in international and domestic economies and show that these networks are significantly nested. This means that the less filled rows and columns of these networks' adjacency matrices tend to be subsets of the fuller rows and columns. Moreover, we show that their nestedness remains constant over time and that it is sustained by both, a bias for industries that deviate from the networks' nestedness to disappear, and a bias for the industries that are missing according to nestedness to appear. This makes the appearance and disappearance of individual industries in each location predictable. We interpret the high level of nestedness observed in these networks in the context of the neutral model of development introduced by Hidalgo and Hausmann (2009). We show that the model can reproduce the high level of nestedness observed in these networks only when we assume a high level of heterogeneity in the distribution of capabilities available in countries and required by products. In the context of the neutral model, this implies that the high level of nestedness observed in these economic networks emerges as a combination of both, the complementarity of inputs and heterogeneity in the number of capabilities available in countries and required by products. The stability of nestedness in industrial ecosystems, and the predictability implied by it, demonstrates the importance of the study of network properties in the evolution of economic networks.

Bustos, Sebastian; Gomez, Charles; Hausmann, Ricardo; Hidalgo, Cesar A.

2012-01-01

334

Understanding the role of interactions between intrinsic feedback loops and external climatic forces is one of the central challenges within the field of population ecology. For rodent dynamics, the seasonal structure of the environment necessitates changes between two stages: reproductive and non-reproductive. Nevertheless, the interactions between seasonality, climate, density dependence and predators have been generally ignored. We demonstrate that direct climate effects, the nonlinear effect of predators and the nonlinear first-order feedback embedded in a seasonal structure are key elements underlying the large and irregular fluctuations in population numbers exhibited by a small rodent in a semi-arid region of central Chile. We found that factors influencing population growth rates clearly differ between breeding and non-breeding seasons. In addition, we detected nonlinear density dependencies as well as nonlinear and differential effects of generalist and specialist predators. Recent climatic changes may account for dramatic perturbations of the rodent's population dynamics. Changes in the predator guild induced by climate are likely to result, through the food web, in a large impact on small rodent demography and population dynamics. Assuming such interactions to be typical of ecological systems, we conclude that appropriate predictions of the ecological consequences of climate change will depend on having an in-depth understanding of the community-weather system.

Lima, Mauricio; Stenseth, Nils Chr; Jaksic, Fabian M

2002-01-01

335

Many biologists use population models that are spatial, stochastic and individual based. Analytical methods that describe the behaviour of these models approximately are attracting increasing interest as an alternative to expensive computer simulation. The methods can be employed for both prediction and fitting models to data. Recent work has extended existing (mean field) methods with the aim of accounting for

J. A. N. Filipe; M. M. Maule

2003-01-01

336

The US EPA National Exposure Research Laboratory (NERL) is currently developing an integrated human exposure source-to-dose modeling system (HES2D). This modeling system will incorporate models that use a probabilistic approach to predict population exposures to environmental ...

337

Background Culicoides imicola KIEFFER, 1913 (Diptera: Ceratopogonidae) is the principal vector of Bluetongue disease in the Mediterranean basin, Africa and Asia. Previous studies have identified a range of eco-climatic variables associated with the distribution of C. imicola, and these relationships have been used to predict the large-scale distribution of the vector. However, these studies are not temporally-explicit and can not be used to predict the seasonality in C. imicola abundances. Between 2001 and 2006, longitudinal entomological surveillance was carried out throughout Italy, and provided a comprehensive spatio-temporal dataset of C. imicola catches in Onderstepoort-type black-light traps, in particular in Sardinia where the species is considered endemic. Methods We built a dynamic model that allows describing the effect of eco-climatic indicators on the monthly abundances of C. imicola in Sardinia. Model precision and accuracy were evaluated according to the influence of process and observation errors. Results A first-order autoregressive cofactor, a digital elevation model and MODIS Land Surface Temperature (LST)/or temperatures acquired from weather stations explained ~77% of the variability encountered in the samplings carried out in 9 sites during 6?years. Incorporating Normalized Difference Vegetation Index (NDVI) or rainfall did not increase the model's predictive capacity. On average, dynamics simulations showed good accuracy (predicted vs. observed r corr?=?0.9). Although the model did not always reproduce the absolute levels of monthly abundances peaks, it succeeded in reproducing the seasonality in population level and allowed identifying the periods of low abundances and with no apparent activity. On that basis, we mapped C. imicola monthly distribution over the entire Sardinian region. Conclusions This study demonstrated prospects for modelling data arising from Culicoides longitudinal entomological surveillance. The framework explicitly incorporates the influence of eco-climatic factors on population growth rates and accounts for observation and process errors. Upon validation, such a model could be used to predict monthly population abundances on the basis of environmental conditions, and hence can potentially reduce the amount of entomological surveillance.

2012-01-01

338

Synfire waves are propagating spike packets in synfire chains, which are feedforward chains embedded in random networks. Although synfire waves have proved to be effective quantification for network activity with clear relations to network structure, their utilities are largely limited to feedforward networks with low background activity. To overcome these shortcomings, we describe a novel generalisation of synfire waves, and define ‘synconset wave’ as a cascade of first spikes within a synchronisation event. Synconset waves would occur in ‘synconset chains’, which are feedforward chains embedded in possibly heavily recurrent networks with heavy background activity. We probed the utility of synconset waves using simulation of single compartment neuron network models with biophysically realistic conductances, and demonstrated that the spread of synconset waves directly follows from the network connectivity matrix and is modulated by top-down inputs and the resultant oscillations. Such synconset profiles lend intuitive insights into network organisation in terms of connection probabilities between various network regions rather than an adjacency matrix. To test this intuition, we develop a Bayesian likelihood function that quantifies the probability that an observed synfire wave was caused by a given network. Further, we demonstrate it's utility in the inverse problem of identifying the network that caused a given synfire wave. This method was effective even in highly subsampled networks where only a small subset of neurons were accessible, thus showing it's utility in experimental estimation of connectomes in real neuronal-networks. Together, we propose synconset chains/waves as an effective framework for understanding the impact of network structure on function, and as a step towards developing physiology-driven network identification methods. Finally, as synconset chains extend the utilities of synfire chains to arbitrary networks, we suggest utilities of our framework to several aspects of network physiology including cell assemblies, population codes, and oscillatory synchrony.

Raghavan, Mohan; Amrutur, Bharadwaj; Narayanan, Rishikesh; Sikdar, Sujit Kumar

2013-01-01

339

Synfire waves are propagating spike packets in synfire chains, which are feedforward chains embedded in random networks. Although synfire waves have proved to be effective quantification for network activity with clear relations to network structure, their utilities are largely limited to feedforward networks with low background activity. To overcome these shortcomings, we describe a novel generalisation of synfire waves, and define 'synconset wave' as a cascade of first spikes within a synchronisation event. Synconset waves would occur in 'synconset chains', which are feedforward chains embedded in possibly heavily recurrent networks with heavy background activity. We probed the utility of synconset waves using simulation of single compartment neuron network models with biophysically realistic conductances, and demonstrated that the spread of synconset waves directly follows from the network connectivity matrix and is modulated by top-down inputs and the resultant oscillations. Such synconset profiles lend intuitive insights into network organisation in terms of connection probabilities between various network regions rather than an adjacency matrix. To test this intuition, we develop a Bayesian likelihood function that quantifies the probability that an observed synfire wave was caused by a given network. Further, we demonstrate it's utility in the inverse problem of identifying the network that caused a given synfire wave. This method was effective even in highly subsampled networks where only a small subset of neurons were accessible, thus showing it's utility in experimental estimation of connectomes in real neuronal-networks. Together, we propose synconset chains/waves as an effective framework for understanding the impact of network structure on function, and as a step towards developing physiology-driven network identification methods. Finally, as synconset chains extend the utilities of synfire chains to arbitrary networks, we suggest utilities of our framework to several aspects of network physiology including cell assemblies, population codes, and oscillatory synchrony. PMID:24116018

Raghavan, Mohan; Amrutur, Bharadwaj; Narayanan, Rishikesh; Sikdar, Sujit Kumar

2013-01-01

340

Population dynamics of the estuarine isopod Sphaeroma rugicauda

NASA Astrophysics Data System (ADS)

Population density, spatial distribution, size distribution, sex ratio and fecundity were studied in a population over a three-year period. Young are produced in the summer, overwinter, reproduce and then die. Population densities decrease due to mortality from March to June and increase due to natality from July to September. Climate has a significant effect on population density. An abnormally warm summer (1976) led to earlier breeding, reduced fecundity, faster growth and higher mortality of juveniles. This led to fewer, larger, breeding adults in 1977. Two years which were climatically similar showed similar population trends. Egg and offspring number were positively correlated with female size but differed between years. Brood pouch mortality was estimated at 17%. Marked changes in population sex ratio were shown to be artefacts due to differences in swimming activity of the sexes.

Heath, David J.; Khazaeli, Aziz A.

1985-01-01

341

Eco-evolutionary dynamics: disentangling phenotypic, environmental and population fluctuations

Decomposing variation in population growth into contributions from both ecological and evolutionary processes is of fundamental concern, particularly in a world characterized by rapid responses to anthropogenic threats. Although the impact of ecological change on evolutionary response has long been acknowledged, the converse has predominantly been neglected, especially empirically. By applying a recently published conceptual framework, we assess and contrast the relative importance of phenotypic and environmental variability on annual population growth in five ungulate populations. In four of the five populations, the contribution of phenotypic variability was greater than the contribution of environmental variability, although not significantly so. The similarity in the contributions of environment and phenotype suggests that neither is worthy of neglect. Population growth is a consequence of multiple processes, which strengthens arguments advocating integrated approaches to assess how populations respond to their environments.

Ezard, Thomas H.G.; Cote, Steeve D.; Pelletier, Fanie

2009-01-01

342

Genomic predictions based on a joint reference population for the Nordic Red cattle breeds.

The main aim of this study was to compare accuracies of imputation and genomic predictions based on single and joint reference populations for Norwegian Red (NRF) and a composite breed (DFS) consisting of Danish Red, Finnish Ayrshire, and Swedish Red. The single nucleotide polymorphism (SNP) data for NRF consisted of 2 data sets: one including 25,000 markers (NRF25K) and the other including 50,000 markers (NRF50K). The NRF25K data set had 2,572 bulls, and the NRF50K data set had 1,128 bulls. Four hundred forty-two bulls were genotyped in both data sets (double-genotyped bulls). The DFS data set (DSF50K) included 50,000 markers of 13,472 individuals, of which around 4,700 were progeny-tested bulls. The NRF25K data set was imputed to 50,000 density using the software Beagle. The average error rate for the imputation of NRF25K decreased slightly from 0.023 to 0.021, and the correlation between observed and imputed genotypes changed from 0.935 to 0.936 when comparing the NRF50K reference and the NRF50K-DFS50K joint reference imputations. A genomic BLUP (GBLUP) model and a Bayesian 4-component mixture model were used to predict genomic breeding values for the NRF and DFS bulls based on the single and joint NRF and DFS reference populations. In the multiple population predictions, accuracies of genomic breeding values increased for the 3 production traits (milk, fat, and protein yields) for both NRF and DFS. Accuracies increased by 6 and 1.3 percentage points, on average, for the NRF and DFS bulls, respectively, using the GBLUP model, and by 9.3 and 1.3 percentage points, on average, using the Bayesian 4-component mixture model. However, accuracies for health or reproduction traits did not increase from the multiple population predictions. Among the 3 DFS populations, Swedish Red gained most in accuracies from the multiple population predictions, presumably because Swedish Red has a closer genetic relationship with NRF than Danish Red and Finnish Ayrshire. The Bayesian 4-component mixture model performed better than the GBLUP model for most production traits for both NRF and DFS, whereas no advantage was found for health or reproduction traits. In general, combining NRF and DFS reference populations was useful in genomic predictions for both the NRF and DFS bulls. PMID:24792791

Zhou, L; Heringstad, B; Su, G; Guldbrandtsen, B; Meuwissen, T H E; Svendsen, M; Grove, H; Nielsen, U S; Lund, M S

2014-07-01

343

Intraspecific Competition and Population Dynamics of Aedes aegypti

NASA Astrophysics Data System (ADS)

We report computational simulations for the evolution of the population of the dengue vector, Aedes aegypti mosquitoes. The results suggest that controlling the mosquito population, on the basis of intraspecific competition at the larval stage, can be an efficient mechanism for controlling the spread of the epidemic. The results also show the presence of a kind of genetic evolution in vector population, which results mainly in increasing the average lifespan of individuals in adulthood.

Paixão, C. A.; Charret, I. C.; Lima, R. R.

2012-04-01

344

Dynamic prediction of traffic volume through Kalman filtering theory

Two models employing Kalman filtering theory are proposed for predicting short-term traffic volume. Prediction parameters are improved using the most recent prediction error and better volume prediction on a link is achieved by taking into account data from a number of links. Based on data collected from a street network in Nagoya City, average prediction error is found to be

Iwao Okutani; Yorgos J. Stephanedes

1984-01-01

345

Modelling for prediction of global deforestation based on the growth of human population

NASA Astrophysics Data System (ADS)

Deforestation due to ever-increasing activities of the growing human population has been an issue of major concern for the global environment. It has been especially serious in the last several decades in the developing countries. A population-deforestation model has been developed by the authors to relate the population density with the cumulative forest loss, which is defined and computed as the total forest loss until 1990 since prior to human civilisation. NOAA-AVHRR-based land cover map and the FAO forest statistics have been used for 1990 land cover. A simulated land cover map, based on climatic data, is used for computing the natural land cover before the human impacts. With the 1990 land cover map as base and using the projected population growth, predictions are then made for deforestation until 2025 and 2050 in both spatial and statistical forms.

Pahari, Krishna; Murai, Shunji

346

Modeling the population dynamics of Gulf Coast sandhill cranes

The Midcontinental population of sandhill cranes (Grus canadensis) has a large geographic range, contains nearly 500,000 birds, and is hunted in much of its range. The population includes three subspecies; the numbers of two of these are uncertain, and they should be afforded protection from hunting that would be detrimental to their population. The two subspecies of concern tend to concentrate in the eastern part of the Great Plains during fall and spring and to winter along the Gulf Coast in Texas. This paper uses the limited information available about the Gulf Coast subpopulation in a model. We included in the model five input parameters: population size, annual survival rate in absence of hunting, the number of birds taken by hunters, the extent of additivity of hunting mortality, and recruitment rate, measured as the fraction of juveniles in the winter population. Using three widely ranging estimates of each parameter, we examined the general behavior of the simulated population. Realistic population projections occurred with medium (60,000) or large (166,000) population sizes, low (2000) or moderate (4000) harvests, and recruitment rates of 0.07 and 0.11. All values of survival in the absence of hunting and additivity of hunting yielded some realistic projections. Results of modelling suggest that the variables warranting closer monitoring are population size and recruitment rate.

Johnson, D.H; Kendall, W. L.

1997-01-01

347

Population genetic dynamics in the French Guiana region.

Three sets of genetic markers (blood group plus protein polymorphisms, mitochondrial DNA, and Y-chromosome) were compared in four French Guiana and one Brazilian Amerindian populations. Spearman's rank correlation coefficient between five gene diversity statistics and historical or present-day population sizes showed significant values, indicating loss of diversity due to population bottlenecks. The three sets of markers furnished distinct admixture estimates, and the blood group plus protein polymorphisms could have overestimated the European contribution to their gene pool. Correspondence analysis distinguished the coastal from the interior populations, possibly reflecting past migration events. PMID:18942716

Mazières, Stéphane; Sevin, André; Callegari-Jacques, Sidia M; Crubézy, Eric; Larrouy, Georges; Dugoujon, Jean-Michel; Salzano, Francisco M

2009-01-01

348

Population dynamics of pond zooplankton, I. Diaptomus pallidus Herrick

The simultaneous and lag relationships between 27 environmental variables and seven population components of a perennial calanoid copepod were examined by simple and partial correlations and stepwise regression. The analyses consistently explained more than 70% of the variation of a population component. The multiple correlation coefficient (R) usually was highest in no lag or in 3-week or 4-week lag except for clutch size in which R was highest in 1-week lag. Population control, egg-bearing, and clutch size were affected primarily by environmental components categorized as weather; food apparently was relatively minor in affecting population control or reproduction. ?? 1973 Dr. W. Junk B.V. Publishers.

Armitage, K. B.; Saxena, B.; Angino, E. E.

1973-01-01

349

ERIC Educational Resources Information Center

Predicting student academic performance has long been an important research topic in many academic disciplines. The present study is the first study that develops and compares four types of mathematical models to predict student academic performance in engineering dynamics--a high-enrollment, high-impact, and core course that many engineering…

Huang, Shaobo; Fang, Ning

2013-01-01

350

A unique population of muskellunge Esox masquinongy inhabits Shoepack Lake in Voyageurs National Park, Minnesota. Little is known about its status, dynamics, and angler exploitation, and there is concern for the long-term viability of this population. We used intensive sampling and mark-recapture methods to quantify abundance, survival, growth, condition, age at maturity and fecundity and angler surveys to quantify angler pressure, catch rates, and exploitation. During our study, heavy rain washed out a dam constructed by beavers Castor canadensis which regulates the water level at the lake outlet, resulting in a nearly 50% reduction in surface area. We estimated a population size of 1,120 adult fish at the beginning of the study. No immediate reduction in population size was detected in response to the loss of lake area, although there was a gradual, but significant, decline in population size over the 2-year study. Adults grew less than 50 mm per year, and relative weight (W r) averaged roughly 80. Anglers were successful in catching, on average, two fish during a full day of angling, but harvest was negligible. Shoepack Lake muskellunge exhibit much slower growth rates and lower condition, but much higher densities and angler catch per unit effort (CPUE), than other muskellunge populations. The unique nature, limited distribution, and location of this population in a national park require special consideration for management. The results of this study provide the basis for assessing the long-term viability of the Shoepack Lake muskellunge population through simulations of long-term population dynamics and genetically effective population size. ?? Copyright by the American Fisheries Society 2007.

Frohnauer, N. K.; Pierce, C. L.; Kallemeyn, L. W.

2007-01-01

351

A method to characterize dynamical interdependence among nonlinear systems is derived based on mutual nonlinear prediction. Systems with nonlinear correlation will show mutual nonlinear prediction when standard analysis with linear cross correlation might fail. Mutual nonlinear prediction also provides information on the directionality of the coupling between systems. Furthermore, the existence of bidirectional mutual nonlinear prediction in unidirectionally coupled systems

Steven J. Schiff; Paul So; Taeun Chang; Robert E. Burke; Tim Sauer

1996-01-01

352

Population structure in the native range predicts the spread of introduced marine species

Forecasting invasion success remains a fundamental challenge in invasion biology. The effort to identify universal characteristics that predict which species become invasive has faltered in part because of the diversity of taxa and systems considered. Here, we use an alternative approach focused on the spread stage of invasions. FST, a measure of alternative fixation of alleles, is a common proxy for realized dispersal among natural populations, summarizing the combined influences of life history, behaviour, habitat requirements, population size, history and ecology. We test the hypothesis that population structure in the native range (FST) is negatively correlated with the geographical extent of spread of marine species in an introduced range. An analysis of the available data (29 species, nine phyla) revealed a significant negative correlation (R2 = 0.245–0.464) between FST and the extent of spread of non-native species. Mode FST among pairwise comparisons between populations in the native range demonstrated the highest predictive power (R2 = 0.464, p < 0.001). There was significant improvement when marker type was considered, with mtDNA datasets providing the strongest relationship (n = 21, R2 = 0.333–0.516). This study shows that FST can be used to make qualitative predictions concerning the geographical extent to which a non-native marine species will spread once established in a new area.

Gaither, Michelle R.; Bowen, Brian W.; Toonen, Robert J.

2013-01-01

353

Montane refugia predict population genetic structure in the Large-blotched Ensatina salamander.

Understanding the biotic consequences of Pleistocene range shifts and fragmentation remains a fundamental goal in historical biogeography and evolutionary biology. Here, we combine species distribution models (SDM) from the present and two late Quaternary time periods with multilocus genetic data (mitochondrial DNA and microsatellites) to evaluate the effect of climate-induced habitat shifts on population genetic structure in the Large-blotched Ensatina (Ensatina eschscholtzii klauberi), a plethodontid salamander endemic to middle and high-elevation conifer forest in the Transverse and Peninsular Ranges of southern California and northern Baja California. A composite SDM representing the range through time predicts two disjunct refugia, one in southern California encompassing the core of the species range and the other in the Sierra San Pedro Mártir of northern Baja California at the southern limit of the species range. Based on our spatial model, we would expect a pattern of high connectivity among populations within the northern refugium and, conversely, a pattern of isolation due to long-term persistence of the Sierra San Pedro Mártir population. Our genetic results are consistent with these predictions based on the hypothetical refugia in that (i) historical measures of population connectivity among stable areas are correlated with gene flow estimates; and (ii) there is strong geographical structure between separate refugia. These results provide evidence for the role of recent climatic change in shaping patterns of population persistence and connectivity within the Transverse and Peninsular Ranges, an evolutionary hotspot. PMID:23379992

Devitt, Thomas J; Devitt, Susan E Cameron; Hollingsworth, Bradford D; McGuire, Jimmy A; Moritz, Craig

2013-03-01

354

Impact of model error structure on predictability of linear stochastic dynamics

NASA Astrophysics Data System (ADS)

A system is predictable on those times-scales where prediction errors do not exceed climate variability. Predictability, therefore, depends on both the physical system and on the prediction system. Here, we consider the predictability of physical systems described by linear stochastic dynamics and prediction systems with perfect initial conditions and temporally uncorrelated model error. We investigate the impact of model error structure on global measures of predictability. Decomposing the model error in the normal modes of the dynamics, we find that predictability is independent of model error spectrum when model error is uncorrelated in normal-mode space. Predictability is increased when model error is correlated in normal-mode space. Therefore normal-mode analysis gives lower bounds for predictability. These results are illustrated in some theoretical examples that identify factors leading to enhanced predictability.

Tippett, M. K.; Chang, P.

2001-12-01

355

Long-term model predictive control of gene expression at the population and single-cell levels

Gene expression plays a central role in the orchestration of cellular processes. The use of inducible promoters to change the expression level of a gene from its physiological level has significantly contributed to the understanding of the functioning of regulatory networks. However, from a quantitative point of view, their use is limited to short-term, population-scale studies to average out cell-to-cell variability and gene expression noise and limit the nonpredictable effects of internal feedback loops that may antagonize the inducer action. Here, we show that, by implementing an external feedback loop, one can tightly control the expression of a gene over many cell generations with quantitative accuracy. To reach this goal, we developed a platform for real-time, closed-loop control of gene expression in yeast that integrates microscopy for monitoring gene expression at the cell level, microfluidics to manipulate the cells’ environment, and original software for automated imaging, quantification, and model predictive control. By using an endogenous osmostress responsive promoter and playing with the osmolarity of the cells environment, we show that long-term control can, indeed, be achieved for both time-constant and time-varying target profiles at the population and even the single-cell levels. Importantly, we provide evidence that real-time control can dynamically limit the effects of gene expression stochasticity. We anticipate that our method will be useful to quantitatively probe the dynamic properties of cellular processes and drive complex, synthetically engineered networks.

Uhlendorf, Jannis; Miermont, Agnes; Delaveau, Thierry; Charvin, Gilles; Fages, Francois; Bottani, Samuel; Batt, Gregory; Hersen, Pascal

2012-01-01

356

Predicting Thymine Dimerization Yields from Molecular Dynamics Simulations

It was recently shown that thymine dimers in the all-thymine oligonucleotide (dT)18 are fully formed in <1 ps after ultraviolet excitation. The speed and low quantum yield of this reaction suggest that only a small fraction of the conformers of this structurally disordered oligonucleotide are in a position to react at the instant of photon absorption. In this work, we explore the hypothesis that conventional molecular dynamics simulations can be used to predict the yield of cyclobutane pyrimidine dimers in DNA. Conformations obtained from simulations of thymidylyl-(3?-5?)-thymidine in various cosolvents were classified as dimerizable or nondimerizable depending on the distance between the C5-C6 double bonds of the adjacent thymine bases and the torsion angle between them. The quantum yield of cyclobutane pyrimidine dimer formation was calculated as the number of dimerizable conformations divided by the total number of conformations. The experimental quantum yields measured in the different solvents were satisfactorily reproduced using physically reasonable values for the two parameters. The mean dimerizable structure computed by averaging all of the dimerizable cis-syn conformations is structurally similar to the actual cis-syn dimer. Compared to the canonical B-form TT step, the most important structural property of a dimerizable conformation is its reduced helical twist angle of 22°.

Law, Yu Kay; Azadi, Javad; Crespo-Hernandez, Carlos E.; Olmon, Eric; Kohler, Bern

2008-01-01

357

Geographical gradients in the population dynamics of North American prairie ducks.

1. Geographic gradients in population dynamics may occur because of spatial variation in resources that affect the deterministic components of the dynamics (i.e. carrying capacity, the specific growth rate at small densities or the strength of density regulation) or because of spatial variation in the effects of environmental stochasticity. To evaluate these, we used a hierarchical Bayesian approach to estimate parameters characterizing deterministic components and stochastic influences on population dynamics of eight species of ducks (mallard, northern pintail, blue-winged teal, gadwall, northern shoveler, American wigeon, canvasback and redhead (Anas platyrhynchos, A. acuta, A. discors, A. strepera, A. clypeata, A. americana, Aythya valisineria and Ay. americana, respectively) breeding in the North American prairies, and then tested whether these parameters varied latitudinally. 2. We also examined the influence of temporal variation in the availability of wetlands, spring temperature and winter precipitation on population dynamics to determine whether geographical gradients in population dynamics were related to large-scale variation in environmental effects. Population variability, as measured by the variance of the population fluctuations around the carrying capacity K, decreased with latitude for all species except canvasback. This decrease in population variability was caused by a combination of latitudinal gradients in the strength of density dependence, carrying capacity and process variance, for which details varied by species. 3. The effects of environmental covariates on population dynamics also varied latitudinally, particularly for mallard, northern pintail and northern shoveler. However, the proportion of the process variance explained by environmental covariates, with the exception of mallard, tended to be small. 4. Thus, geographical gradients in population dynamics of prairie ducks resulted from latitudinal gradients in both deterministic and stochastic components, and were likely influenced by spatial differences in the distribution of wetland types and shapes, agricultural practices and dispersal processes. 5. These results suggest that future management of these species could be improved by implementing harvest models that account explicitly for spatial variation in density effects and environmental stochasticity on population abundance. PMID:18631261

Saether, Bernt-Erik; Lillegård, Magnar; Grøtan, Vidar; Drever, Mark C; Engen, Steinar; Nudds, Thomas D; Podruzny, Kevin M

2008-09-01

358

Purpose To develop a predictive pharmacokinetic model for propofol that could inform development of a dosing strategy for the obese\\u000a population.\\u000a \\u000a \\u000a \\u000a Methods A prior model that included a nonlinear relationship between clearance (CL) and Total Body Weight (TBW) was re-parameterized\\u000a with a linear relationship between CL and Lean Body Weight (LBW). The predictive performance of both models was compared and\\u000a the LBW

Sarah C. McLeay; Glynn A. Morrish; Carl M. Kirkpatrick; Bruce Green

2009-01-01

359

Stochastic modeling of aphid population growth with nonlinear, power-law dynamics.

This paper develops a deterministic and a stochastic population size model based on power-law kinetics for the black-margined pecan aphid. The deterministic model in current use incorporates cumulative-size dependency, but its solution is symmetric. The analogous stochastic model incorporates the prolific reproductive capacity of the aphid. These models are generalized in this paper to include a delayed feedback mechanism for aphid death. Whereas the per capita aphid death rate in the current model is proportional to cumulative size, delayed feedback is implemented by assuming that the per capita rate is proportional to some power of cumulative size, leading to so-called power-law dynamics. The solution to the resulting differential equations model is a left-skewed abundance curve. Such skewness is characteristic of observed aphid data, and the generalized model fits data well. The assumed stochastic model is solved using Kolmogrov equations, and differential equations are given for low order cumulants. Moment closure approximations, which are simple to apply, are shown to give accurate predictions of the two endpoints of practical interest, namely (1) a point estimate of peak aphid count and (2) an interval estimate of final cumulative aphid count. The new models should be widely applicable to other aphid species, as they are based on three fundamental properties of aphid population biology. PMID:17306309

Matis, James H; Kiffe, Thomas R; Matis, Timothy I; Stevenson, Douglass E

2007-08-01

360

It is increasingly clear that bacteria manage to evade killing by antibiotics and antimicrobials in a variety of ways, including mutation, phenotypic variations, and formation of biofilms. With recent advances in understanding the dynamics of the tolerance mechanisms, there have been subsequent advances in understanding how to manipulate the bacterial environments to eradicate the bacteria. This study focuses on using mathematical techniques to find the optimal disinfection strategy to eliminate the bacteria while managing the load of antibiotic that is applied. In this model, the bacterial population is separated into those that are tolerant to the antibiotic and those that are susceptible to disinfection. There are transitions between the two populations whose rates depend on the chemical environment. Our results extend previous mathematical studies to include more realistic methods of applying the disinfectant. The goal is to provide experimentally testable predictions that have been lacking in previous mathematical studies. In particular, we provide the optimal disinfection protocol under a variety of assumptions within the model that can be used to validate or invalidate our simplifying assumptions and the experimental hypotheses that we used to develop the model. We find that constant dosing is not the optimal method for disinfection. Rather, cycling between application and withdrawal of the antibiotic yields the fastest killing of the bacteria.

Brown, Jason; Darres, Kyle; Petty, Katherine

2012-01-01

361

Disentangling the demographic processes that determine the genetic structure of a given species is a fundamental question in conservation and management. In the present study, the population structure of the European eel was examined with a multidisciplinary approach combining the fields of molecular genetics and population dynamics modelling. First, we analyzed a total of 346 adult specimens of known age collected in three separate sample sites using a large panel of 22 EST-linked microsatellite loci. Second, we developed a European eel-specific model to unravel the demographic mechanisms that can produce the level of genetic differentiation estimated by molecular markers. This is the first study that reveals a pattern of genetic patchiness in maturing adults of the European eel. A highly significant genetic differentiation was observed among samples that did not follow an Isolation-by-Distance or Isolation-by-Time pattern. The observation of genetic patchiness in adults is likely to result from a limited parental contribution to each spawning event as suggested by our modelling approach. The value of genetic differentiation found is predicted by the model when reproduction occurs in a limited number of spawning events isolated from each other in time or space, with an average of 130-375 breeders in each spawning event. Unpredictability in spawning success may have important consequences for the life-history evolution of the European eel, including a bet-hedging strategy (distributing reproductive efforts over time) which could in turn guarantee successful reproduction of some adults. PMID:21129491

Pujolar, José Martin; Bevacqua, Daniele; Andrello, Marco; Capoccioni, Fabrizio; Ciccotti, Eleonora; De Leo, Giulio A; Zane, Lorenzo

2011-02-01

362

An illusion predicted by V1 population activity implicates cortical topography in shape perception

Mammalian primary visual cortex (V1) is topographically organized such that the pattern of neural activation in V1 reflects the location and spatial extent of visual elements in the retinal image, but it is unclear whether this organization contributes to visual perception. We combined computational modeling, voltage-sensitive dye imaging (VSDI) in behaving monkeys, and behavioral measurements in humans, to investigate whether the large-scale topography of V1 population responses influences shape judgments. Specifically, we used a computational model to design visual stimuli that have the same physical shape, but are predicted to elicit variable V1 response spread. We confirmed these predictions with VSDI. Finally, we designed a behavioral task in which human observers judged the shapes of these stimuli, and found that their judgments were systematically distorted by the spread of V1 activity. This novel illusion suggests that the topographic pattern of neural population responses in visual cortex contributes to visual perception.

Michel, Melchi M.; Chen, Yuzhi; Geisler, Wilson S.; Seidemann, Eyal

2013-01-01

363

Characterizing cumulative impacts using a brook trout population dynamics model

An individuals-based modelling framework is used to characterize the nature of exploitation and toxaphene stressors acting simultaneously on a population of brook trout (Salvelinus fontinalis) in terms of age 0 + and adult abundance, survivorship and population size-structure. A no-stressor control case was estimated against which exploitation-only, toxaphene-only and cumulative exploitation and toxaphene stressor cases were compared to determine the

M. Power

1996-01-01

364

Taylor's law (TL) asserts that the variance of the density (individuals per area or volume) of a set of comparable populations is a power-law function of the mean density of those populations. Despite the empirical confirmation of TL in hundreds of species, there is little consensus about why TL is so widely observed and how its estimated parameters should be interpreted. Here, we report that the Lewontin–Cohen (henceforth LC) model of stochastic population dynamics, which has been widely discussed and applied, leads to a spatial TL in the limit of large time and provides an explicit, exact interpretation of its parameters. The exponent of TL exceeds 2 if and only if the LC model is supercritical (growing on average), equals 2 if and only if the LC model is deterministic, and is less than 2 if and only if the LC model is subcritical (declining on average). TL and the LC model describe the spatial variability and the temporal dynamics of populations of trees on long-term plots censused over 75 years at the Black Rock Forest, Cornwall, NY, USA.

Cohen, Joel E.; Xu, Meng; Schuster, William S. F.

2013-01-01

365

Summary 1. Our understanding of the interplay between density dependence, climatic perturbations, and conservation practices on the dynamics of small populations is still limited. This can result in uninformed strategies that put endangered populations at risk. Moreover, the data available for a large number of populations in such circumstances are sparse and mined with missing data. Under the current climate

Fernando Colchero; Rodrigo A. Medellin; James S. Clark; Raymond Lee; Gabriel G. Katul

2009-01-01

366

In this study we investigated the population dynamics of Chrysomya albiceps (Wiedemann) with laboratory experiments, employing survival analysis and stage structure mathematical models, emphasizing survival among life stages. The study also assessed the theoretical influence of density dependence and cannibalism during immature stages, on the population dynamics of the species. The survival curves were similar, indicating that populations of C. albiceps exhibit the same pattern of survival among life stages. A strong nonlinear trend was observed, suggesting density dependence, acting during the first life stages of C. albiceps. The time-series simulations produced chaotic oscillations for all life stages, and the cannibalism did not produce qualitative changes in the dynamic behavior. The bifurcation analysis shows that for low values for survival, the population reaches a stable equilibrium, but the cannibalism results in chaotic oscillations practically over all the parametric space. The implications of the patterns of dynamic behavior observed are discussed. PMID:21584398

Rosa, G S; Costa, M I S; Corrente, J E; Silveira, L V A; Godoy, W A C

2011-01-01

367

Escalator Boxcar Train: Basic Theory and an Application to Daphnia Population Dynamics.

National Technical Information Service (NTIS)

The various discrete and continuous time models for the dynamics of physiologically structured populations are put into a contextual framework to elucidate the relations between them. The authors introduce the basic concepts and discuss in detail the assu...

A. M. de Roos O. Diekmann J. A. J. Metz

1988-01-01

368

Variation in food resource availability can have profound effects on habitat selection and dynamics of populations. Previous studies reported higher food resource availability and fruit removal in treefall gaps than in the understorey. Therefore, gaps have been considered 'keystone habitat' for Neotropical frugivore birds. Here we test if this prediction would also hold for terrestrial small mammals. In the Amazon, we quantified food resource availability in eleven treefall gaps and paired understorey habitats and used feeding experiments to test if two common terrestrial rodents (Oryzomys megacephalus and Proechimys spp.) would perceive differences between habitats. We live-trapped small mammals in eleven gaps and understorey sites for two years, and compared abundance, fitness components (survival and per capita recruitment) and dispersal of these two rodent species across gaps and understorey and seasons (rainy and dry). Our data indicated no differences in resource availability and consumption rate between habitats. Treefall gaps may represent a sink habitat for Oryzomys where individuals had lower fitness, apparently because of habitat-specific ant predation on early life stages, than in the understorey, the source habitat. Conversely, gaps may be source habitat for Proechimys where individuals had higher fitness, than in the understorey, the sink habitat. Our results suggest the presence of source-sink dynamics in a tropical gap-understorey landscape, where two rodent species perceive habitats differently. This may be a mechanism for their coexistence in a heterogeneous and species-diverse system.

Beck H.; Gaines M. S.; Hines J. E.; Nichols J. D.

2004-01-01

369

An Approach to Predict Risks to Wildlife Populations from Mercury and Other Stressors

Ecological risk assessments for mercury (Hg) require measured and modeled information on exposure and effects. While most of this special issue focuses on the former, i.e., distribution and fate of Hg within aquatic food webs, this paper describes an approach to predict the effects of dietary methylmercury (CH3Hg) on populations of piscivorous birds. To demonstrate this approach, the U.S. Environmental

Diane Nacci; Marguerite Pelletier; Jim Lake; Rick Bennett; John Nichols; Romona Haebler; Jason Grear; Anne Kuhn; Jane Copeland; Matthew Nicholson; Steven Walters; WAYNE R. MUNNS JR

2005-01-01

370

Synchrony's double edge: transient dynamics and the Allee effect in stage structured populations.

In populations subject to positive density dependence, individuals can increase their fitness by synchronizing the timing of key life history events. However, phenological synchrony represents a perturbation from a population's stable stage structure and the ensuing transient dynamics create troughs of low abundance that can promote extinction. Using an ecophysiological model of a mass-attacking pest insect, we show that the effect of synchrony on local population persistence depends on population size and adult lifespan. Results are consistent with a strong empirical pattern of increased extinction risk with decreasing initial population size. Mortality factors such as predation on adults can also affect transient dynamics. Throughout the species range, the seasonal niche for persistence increases with the asynchrony of oviposition. Exposure to the Allee effect after establishment may be most likely at northern range limits, where cold winters tend to synchronize spring colonization, suggesting a role for transient dynamics in the determination of species distributions. PMID:17542935

Friedenberg, Nicholas A; Powell, James A; Ayres, Matthew P

2007-07-01

371

A direct approach to control short term population dynamics in time series studies

Background: Short term population dynamics is an important issue in several epidemiological studies. Usually, calendar time or dummy variables are used to control indirectly for this confounding. This study tested a direct method. Methods: The study compared as proxy variables of population dynamics the summer 2003 data of cooking gas consumptions, solid urban waste production, and television access for the municipality of Bologna (Italy). Results: Solid urban waste production and television access data showed similar trends. Considerably different were the >65 year olds estimates with respect to total population based on television access. Conclusions: Television access data are probably the best indicator in the estimates of population dynamics in large or densely populated areas, especially because of the possibility of stratifications with respect to age.

Zauli, S; Scotto, F.; Lauriola, P.

2005-01-01

372

Effective population size and evolutionary dynamics in outbred laboratory populations of Drosophila.

Census population size, sex-ratio and female reproductive success were monitored in 10 laboratory populations of Drosophila melanogaster selected for different ages of reproduction. With this demographic information, we estimated eigenvalue, variance and probability of allele loss effective population sizes. We conclude that estimates of effective size based on genefrequency change at a few loci are biased downwards. We analysed the relative roles of selection and genetic drift in maintaining genetic variation in laboratory populations of Drosophila. We suggest that rare, favourable genetic variants in our laboratory populations have a high chance of being lost if their fitness effect is weak, e.g. 1% or less. However, if the fitness effect of this variation is 10% or greater, these rare variants are likely to increase to high frequency. The demographic information developed in this study suggests that some of our laboratory populations harbour more genetic variation than expected. One explanation for this finding is that part of the genetic variation in these outbred laboratory Drosophila populations may be maintained by some form of balancing selection. We suggest that, unlike bacteria, medium-term adaptation of laboratory populations of fruit flies is not primarily driven by new mutations, but rather by changes in the frequency of preexisting alleles. PMID:24371158

Mueller, Laurence D; Joshi, Amitabh; Santos, Marta; Rose, Michael R

2013-12-01

373

This paper introduces a real-time reliability prediction method for a dynamic system which suffers from a hidden degradation process. The hidden degradation process is firstly identified by use of particle filtering based on measurable outputs of the considered dynamic system. Then the system's reliability is predicted according to the model of the degradation path. We analyze the identification algorithm mathematically,

Zhengguo Xu; Yindong Ji; Donghua Zhou