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Last update: November 12, 2013.

1

Modeling and prediction of cell population dynamics

Oscillatory yeast cell dynamics are observed in glucose-limited growth environments. Under such conditions, both glucose and the excreted product ethanol can serve as substrates for cell growth. The cell dynamics is described by a PDE (partial differential equation) system containing one PDE for the cell population and 8 ODEs for 8 substrates variations (extracellular glucose, extracellular ethanol, intracellular glucose, intracellular

Youngil Lima

2

Modeling and prediction of cell population dynamics

Oscillatory yeast cell dynamics are observed in glucose-limited growth environments. Under such conditions, both glucose and the excreted product ethanol can serve as substrates for cell growth. The cell dynamics is described by a PDE (partial differential equation) system containing one PDE for the cell population and 8 ODEs for 8 substrates variations (extracellular glucose, extracellular ethanol, intracellular glucose, intracellular

Youngil Lim

2005-01-01

3

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

4

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

5

Predicting shifts in dynamics of cannibalistic field populations using individual-based models.

The occurrence of qualitative shifts in population dynamical regimes has long been the focus of population biologists. Nonlinear ecological models predict that these shifts in dynamical regimes may occur as a result of parameter shifts, but unambiguous empirical evidence is largely restricted to laboratory populations. We used an individual-based modelling approach to predict dynamical shifts in field fish populations where the capacity to cannibalize differed between species. Model-generated individual growth trajectories that reflect different population dynamics were confronted with empirically observed growth trajectories, showing that our ordering and quantitative estimates of the different cannibalistic species in terms of life-history characteristics led to correct qualitative predictions of their dynamics.

Persson, Lennart; de Roos, Andre M; Bertolo, Andrea

2004-01-01

6

Hundreds of species are shifting their ranges in response to recent climate warming. To predict how continued climate warming will affect the potential, or “bioclimatic range,” of a skipper butterfly, we present a population?dynamic model of range shift in which population growth is a function of temperature. We estimate the parameters of this model using previously published data for Atalopedes campestris. Summer and winter temperatures affect population growth rate independently in this species and therefore interact as potential range?limiting factors. Our model predicts a two?phase response to climate change; one range?limiting factor gradually becomes dominant, even if warming occurs steadily along a thermally linear landscape. Whether the range shift accelerates or decelerates and whether the number of generations per year at the range edge increases or decreases depend on whether summer or winter warms faster. To estimate the uncertainty in our predictions of range shift, we use a parametric bootstrap of biological parameter values. Our results show that even modest amounts of data yield predictions with reasonably small confidence intervals, indicating that ecophysiological models can be useful in predicting range changes. Nevertheless, the confidence intervals are sensitive to regional differences in the underlying thermal landscape and the warming scenario. PMID:16685639

Crozier, Lisa; Dwyer, Greg

2006-06-01

7

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. PMID:23634763

Lebl, Karin; Brugger, Katharina; Rubel, Franz

2013-05-01

8

Behavioral ecology and population ecology are two separate branches of ecology; studies linking the effect of individual behavior and population dynamics are rare. This paper connects a stochastic optimal foraging model of insect predators with an age structured population model of its prey. I modeled syrphid larvae feeding on cereal aphids, an interaction critical to cereal crops in Germany. The

Brigitte Tenhumberg

9

ERIC Educational Resources Information Center

|Uses graphs to involve students in inquiry-based population investigations on the Wisconsin gray wolf. Requires students to predict future changes in the wolf population, carrying capacity, and deer population. (YDS)|

Bunton, Matt

2003-01-01

10

An age-classified projection matrix model has been developed to extrapolate the chronic (28-35d) demographic responses of Americamysis bahia (formerly Mysidopsis bahia) to population-level response. This study was conducted to evaluate the efficacy of this model for predicting t...

11

Wildlife-originated zoonotic diseases in general are a major contributor to emerging infectious diseases. Hantaviruses more specifically cause thousands of human disease cases annually worldwide, while understanding and predicting human hantavirus epidemics pose numerous unsolved challenges. Nephropathia epidemica (NE) is a human infection caused by Puumala virus, which is naturally carried and shed by bank voles (Myodes glareolus). The objective of this study was to develop a method that allows model-based predicting 3?months ahead of the occurrence of NE epidemics. Two data sets were utilized to develop and test the models. These data sets were concerned with NE cases in Finland and Belgium. In this study, we selected the most relevant inputs from all the available data for use in a dynamic linear regression (DLR) model. The number of NE cases in Finland were modelled using data from 1996 to 2008. The NE cases were predicted based on the time series data of average monthly air temperature (°C) and bank voles' trapping index using a DLR model. The bank voles' trapping index data were interpolated using a related dynamic harmonic regression model (DHR). Here, the DLR and DHR models used time-varying parameters. Both the DHR and DLR models were based on a unified state-space estimation framework. For the Belgium case, no time series of the bank voles' population dynamics were available. Several studies, however, have suggested that the population of bank voles is related to the variation in seed production of beech and oak trees in Northern Europe. Therefore, the NE occurrence pattern in Belgium was predicted based on a DLR model by using remotely sensed phenology parameters of broad-leaved forests, together with the oak and beech seed categories and average monthly air temperature (°C) using data from 2001 to 2009. Our results suggest that even without any knowledge about hantavirus dynamics in the host population, the time variation in NE outbreaks in Finland could be predicted 3?months ahead with a 34% mean relative prediction error (MRPE). This took into account solely the population dynamics of the carrier species (bank voles). The time series analysis also revealed that climate change, as represented by the vegetation index, changes in forest phenology derived from satellite images and directly measured air temperature, may affect the mechanics of NE transmission. NE outbreaks in Belgium were predicted 3?months ahead with a 40% MRPE, based only on the climatological and vegetation data, in this case, without any knowledge of the bank vole's population dynamics. In this research, we demonstrated that NE outbreaks can be predicted using climate and vegetation data or the bank vole's population dynamics, by using dynamic data-based models with time-varying parameters. Such a predictive modelling approach might be used as a step towards the development of new tools for the prevention of future NE outbreaks. PMID:23176630

Haredasht, S Amirpour; Taylor, C J; Maes, P; Verstraeten, W W; Clement, J; Barrios, M; Lagrou, K; Van Ranst, M; Coppin, P; Berckmans, D; Aerts, J-M

2012-11-26

12

Deer mice (Peromyscus maniculatus) are the main reservoir host for Sin Nombre virus, the primary etiologic agent of hantavirus pulmonary syndrome in North America. Sequential changes in weather and plant productivity (trophic cascades) have been noted as likely catalysts of deer mouse population irruptions, and monitoring and modeling of these phenomena may allow for development of early-warning systems for disease risk. Relationships among weather variables, satellite-derived vegetation productivity, and deer mouse populations were examined for a grassland site east of the Continental Divide and a sage-steppe site west of the Continental Divide in Montana, USA. We acquired monthly deer mouse population data for mid-1994 through 2007 from long-term study sites maintained for monitoring changes in hantavirus reservoir populations, and we compared these with monthly bioclimatology data from the same period and gross primary productivity data from the Moderate Resolution Imaging Spectroradiometer sensor for 2000-06. We used the Random Forests statistical learning technique to fit a series of predictive models based on temperature, precipitation, and vegetation productivity variables. Although we attempted several iterations of models, including incorporating lag effects and classifying rodent density by seasonal thresholds, our results showed no ability to predict rodent populations using vegetation productivity or weather data. We concluded that trophic cascade connections to rodent population levels may be weaker than originally supposed, may be specific to only certain climatic regions, or may not be detectable using remotely sensed vegetation productivity measures, although weather patterns and vegetation dynamics were positively correlated. PMID:22493110

Loehman, Rachel A; Elias, Joran; Douglass, Richard J; Kuenzi, Amy J; Mills, James N; Wagoner, Kent

2012-04-01

13

Human population dynamics revisited with the logistic model: How much can be modeled and predicted?

Decrease or growth of population comes from the interplay of death and birth (and locally, migration). We revive the logistic\\u000a model, which was tested and found wanting in early-20th-century studies of aggregate human populations, and apply it instead\\u000a to life expectancy (death) and fertility (birth), the key factors totaling population. For death, once an individual has legally\\u000a entered society, the

C. Marchetti; P. S. Meyer; J. H. Ausubel

2004-01-01

14

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

2011-05-13

15

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

16

Sensitivity analyses of population projection matrix (PPM) models are often used to identify life-history perturbations that will most influence a population's future dynamics. Sensitivities are linear extrapolations of the relationship between a population's growth rate and per- turbations to its demographic parameters. Their effectiveness depends on the validity of the assumption of linearity. Here we assess whether sensitivity analysis is

MAIREAD M. MACLEAN; DAVID J. CARSLAKE; MATTHEW R. EVANS; STUART TOWNLEY; DAVID J. HODGSON

2008-01-01

17

Prediction of Peromyscus maniculatus (deer mouse) population ...

Title: Prediction of Peromyscus maniculatus (deer mouse) population dynamics in Montana, USA, using satellite-driven vegetation productivity and weather data ... monitoring and modeling of these phenomena may allow for development of ...

18

Climate change could profoundly affect the status of agricultural insect pests. Several approaches have been used to predict how the temperature and precipitation changes could modify the abundances, distributions or status of insect pests. In this article it is demonstrated how the use of simple models, such as Ricker's classic equation, including a mechanistic representation of the influence of exogenous

S. A. Estay; M. Lima; F. A. Labra

2009-01-01

19

Sustainability of culture-driven population dynamics

We consider models of the interactions between human population dynamics and cultural evolution, asking whether they predict sustainable or unsustainable patterns of growth. Phenomenological models predict either unsustainable population growth or stabilization in the near future. The latter prediction, however, is based on extrapolation of current demographic trends and does not take into account causal processes of demographic and cultural

Stefano Ghirlanda; Magnus Enquist; Matjaž Perc

2010-01-01

20

Critical body residues (CBRs) are the measured tissue toxicant concentrations yielding a median dose-response on a dry-weight or lipid-normalized basis. They facilitate management decisions for species protection using tissue analysis. Population CBR is the mean dose yielding 50% population suppression and was predicted here in Amphiascus tenuiremis for fipronil sulfide (FS) using lifetables and the Leslie matrix. Microplate bioassays (ASTM E-2317-14) produced biomass sufficient for dry mass and lipid-normalized CBR estimates of reproduction (fertility) and population growth suppression. Significant FS toxic effects were delayed naupliar development (at ?0.10?µg?L(-1)), delayed copepodite development (at 0.85?µg?L(-1)), decreased reproductive success (at ? 0.39?µg?L(-1)), and decreased offspring production (at 0.85?µg?L(-1)). A reproductive median effective concentration (EC50) of 0.16?µg?L(-1) (95% CI: 0.12-0.21?µg?L(-1)) corresponded to an adult all-sex CBR and lipid-normalized CBR of 0.38?pg FS?·?µg(-1) dry weight (95% CI: 0.27-0.52?pg FS?·?µg(-1)) or 2.8?pg FS?·?µg(-1) lipid (95% CI: 2.2-3.6?pg FS?·?µg(-1)), respectively. Copepod log bioconcentration factor (BCF)?=?4.11?±?0.2. Leslie matrix projections regressed against internal dose predicted fewer than five gravid females in a population by the third generation at 0.39 and 0.85?µg FS?·?L(-1) (i.e., 9.6-10.2?µg FS?·?µg(-1) lipid), and 50% population suppression at a CBR of 1.6?pg FS?·?µg(-1) lipid. This more integrative population CBR as a management tool would fall 1.75 times below the CBR for the single most sensitive endpoint-fertility rate. PMID:22331616

Chandler, G Thomas; Ferguson, P Lee; Klauber, W W; Washburn, K M

2012-03-13

21

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

22

Dynamics of inhomogeneous populations and global demography models

The dynamic theory of inhomogeneous populations developed during the last decade predicts several essential new dynamic regimes applicable even to the well-known, simple population models. We show that, in an inhomogeneous population with a distributed reproduction coefficient, the entire initial distribution of the coefficient should be used to investigate real population dynamics. In the general case, neither the average rate

Georgy P. Karev

2005-01-01

23

Overcompensatory population dynamic responses to environmental stochasticity.

1. To quantify the interactions between density-dependent, population regulation and density-independent limitation, we studied the time-series dynamics of an experimental laboratory insect microcosm system in which both environmental noise and resource limitation were manipulated. 2. A hierarchical Bayesian state-space approach is presented through which it is feasible to capture all sources of uncertainty, including observation error to accurately quantify the density dependence operating on the dynamics. 3. The regulatory processes underpinning the dynamics of two different bruchid beetles (Callosobruchus maculatus and Callosobruchus chinensis) are principally determined by environmental conditions, with fluctuations in abundance explained in terms of changes in overcompensatory dynamics and stochastic processes. 4. A general, stochastic population model is developed to explore the link between abundance fluctuations and the interaction between density dependence and noise. Taking account of time-lags in population regulation can substantially increase predicted population fluctuations resulting from underlying noise processes. PMID:18647195

Bull, James C; Bonsall, Michael B

2008-07-17

24

Evolutionary dynamics of diploid populations

NASA Astrophysics Data System (ADS)

There has been much recent interest in constructing computer models of evolutionary dynamics. Typically these models focus on asexual population dynamics, which are appropriate for haploid organsims such as bacteria. Using a recently developed ``genome template'' model, we extend the algorithm to a sexual population of diploid organisms. We will present some early results showing the temporal evolution of mean fitness and genetic variation, and compare this to typical results from haploid populations.

Desimone, Ralph; Newman, Timothy

2003-10-01

25

Environmental colour affects aspects of single-species population dynamics.

Single-species populations of ciliates (Colpidium and Paramecium) experienced constant temperature or white or reddened temperature fluctuations in aquatic microcosms in order to test three hypotheses about how environmental colour influences population dynamics. (i) Models predict that the colour of population dynamics is tinged by the colour of the environmental variability. However, environmental colour had no effect on the colour of population dynamics. All population dynamics in this experiment were reddened, regardless of environmental colour. (ii) Models predict that populations will track reddened environmental variability more closely than white environmental variability and that populations with a higher intrinsic growth rate (r) will track environmental variability more closely than populations with a low r. The experimental populations behaved as predicted. (iii) Models predict that population variability is determined by interaction between r and the environmental variability. The experimental populations behaved as predicted. These results show that (i) reddened population dynamics may need no special explanation, such as reddened environments, spatial subdivision or interspecific interactions, and (ii) and (iii) that population dynamics are sensitive to environmental colour, in agreement with population models. Correct specification of the colour of the environmental variability in models is required for accurate predictions. Further work is needed to study the effects of environmental colour on communities and ecosystems. PMID:10819142

Petchey, O L

2000-04-22

26

Environmental colour affects aspects of single-species population dynamics.

Single-species populations of ciliates (Colpidium and Paramecium) experienced constant temperature or white or reddened temperature fluctuations in aquatic microcosms in order to test three hypotheses about how environmental colour influences population dynamics. (i) Models predict that the colour of population dynamics is tinged by the colour of the environmental variability. However, environmental colour had no effect on the colour of population dynamics. All population dynamics in this experiment were reddened, regardless of environmental colour. (ii) Models predict that populations will track reddened environmental variability more closely than white environmental variability and that populations with a higher intrinsic growth rate (r) will track environmental variability more closely than populations with a low r. The experimental populations behaved as predicted. (iii) Models predict that population variability is determined by interaction between r and the environmental variability. The experimental populations behaved as predicted. These results show that (i) reddened population dynamics may need no special explanation, such as reddened environments, spatial subdivision or interspecific interactions, and (ii) and (iii) that population dynamics are sensitive to environmental colour, in agreement with population models. Correct specification of the colour of the environmental variability in models is required for accurate predictions. Further work is needed to study the effects of environmental colour on communities and ecosystems.

Petchey, O L

2000-01-01

27

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

28

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.

Patra, Pintu; Klumpp, Stefan

2013-01-01

29

Population dynamic theory of size-dependent cannibalism

Cannibalism is characterized by four aspects: killing victims, gaining energy from victims, size-dependent interactions and intraspecific competition. In this review of mathematical models of cannibalistic populations, we relate the predicted population dynamic consequences of cannibalism to its four defining aspects. We distinguish five classes of effects of cannibalism: (i) regulation of population size; (ii) destabilization resulting in population cycles or

David Claessen; Roos de A. M; L. Persson

2004-01-01

30

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

31

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

32

Stochastic Gain in Population Dynamics

NASA Astrophysics Data System (ADS)

We introduce an extension of the usual replicator dynamics to adaptive learning rates. We show that a population with a dynamic learning rate can gain an increased average payoff in transient phases and can also exploit external noise, leading the system away from the Nash equilibrium, in a resonancelike fashion. The payoff versus noise curve resembles the signal to noise ratio curve in stochastic resonance. Seen in this broad context, we introduce another mechanism that exploits fluctuations in order to improve properties of the system. Such a mechanism could be of particular interest in economic systems.

Traulsen, Arne; Röhl, Torsten; Schuster, Heinz Georg

2004-07-01

33

Evolutionary dynamics on interdependent populations

NASA Astrophysics Data System (ADS)

Although several mechanisms can promote cooperative behavior, there is no general consensus about why cooperation survives when the most profitable action for an individual is to defect, especially when the population is well mixed. Here we show that when a replicator such as evolutionary game dynamics takes place on interdependent networks, cooperative behavior is fixed on the system. Remarkably, we analytically and numerically show that this is even the case for well-mixed populations. Our results open the path to mechanisms able to sustain cooperation and can provide hints for controlling its rise and fall in a variety of biological and social systems.

Gómez-Gardeńes, Jesús; Gracia-Lázaro, Carlos; Floría, Luis Mario; Moreno, Yamir

2012-11-01

34

Dynamics of inhomogeneous populations and global demography models

The dynamic theory of inhomogeneous populations developed during the last\\u000adecade predicts several essential new dynamic regimes applicable even to the\\u000awell-known, simple population models. We show that, in an inhomogeneous\\u000apopulation with a distributed reproduction coefficient, the entire initial\\u000adistribution of the coefficient should be used to investigate real population\\u000adynamics. In the general case, neither the average rate

Georgy P. Karev

2005-01-01

35

Bayesian Prediction and Population Size Assumptions.

National Technical Information Service (NTIS)

The distribution of the number of successes in a sample given the outcome of a previous sample is obtained by Bayesian methods. It is shown that the solution to the prediction problem is completely independent of population size. (Author)

T. L. Bratcher W. R. Schucany H. H. Hunt

1970-01-01

36

Phenotypic plasticity and population viability: the importance of environmental predictability

Phenotypic plasticity plays a key role in modulating how environmental variation influences population dynamics, but we have only rudimentary understanding of how plasticity interacts with the magnitude and predictability of environmental variation to affect population dynamics and persistence. We developed a stochastic individual-based model, in which phenotypes could respond to a temporally fluctuating environmental cue and fitness depended on the match between the phenotype and a randomly fluctuating trait optimum, to assess the absolute fitness and population dynamic consequences of plasticity under different levels of environmental stochasticity and cue reliability. When cue and optimum were tightly correlated, plasticity buffered absolute fitness from environmental variability, and population size remained high and relatively invariant. In contrast, when this correlation weakened and environmental variability was high, strong plasticity reduced population size, and populations with excessively strong plasticity had substantially greater extinction probability. Given that environments might become more variable and unpredictable in the future owing to anthropogenic influences, reaction norms that evolved under historic selective regimes could imperil populations in novel or changing environmental contexts. We suggest that demographic models (e.g. population viability analyses) would benefit from a more explicit consideration of how phenotypic plasticity influences population responses to environmental change.

Reed, Thomas E.; Waples, Robin S.; Schindler, Daniel E.; Hard, Jeffrey J.; Kinnison, Michael T.

2010-01-01

37

Phenotypic plasticity and population viability: the importance of environmental predictability.

Phenotypic plasticity plays a key role in modulating how environmental variation influences population dynamics, but we have only rudimentary understanding of how plasticity interacts with the magnitude and predictability of environmental variation to affect population dynamics and persistence. We developed a stochastic individual-based model, in which phenotypes could respond to a temporally fluctuating environmental cue and fitness depended on the match between the phenotype and a randomly fluctuating trait optimum, to assess the absolute fitness and population dynamic consequences of plasticity under different levels of environmental stochasticity and cue reliability. When cue and optimum were tightly correlated, plasticity buffered absolute fitness from environmental variability, and population size remained high and relatively invariant. In contrast, when this correlation weakened and environmental variability was high, strong plasticity reduced population size, and populations with excessively strong plasticity had substantially greater extinction probability. Given that environments might become more variable and unpredictable in the future owing to anthropogenic influences, reaction norms that evolved under historic selective regimes could imperil populations in novel or changing environmental contexts. We suggest that demographic models (e.g. population viability analyses) would benefit from a more explicit consideration of how phenotypic plasticity influences population responses to environmental change. PMID:20554553

Reed, Thomas E; Waples, Robin S; Schindler, Daniel E; Hard, Jeffrey J; Kinnison, Michael T

2010-06-16

38

Dynamic Branch Prediction Using Neural Networks

Dynamic branch prediction in high-performance processors is a specific instance of a general Time Series Prediction problem that occurs in many areas of science. In contrast, most branch prediction research focuses on Two-Level Adaptive Branch Prediction techniques, a very specific solution to the branch prediction problem. An alternative approach is to look to other application areas and fields for novel

Gordon B. Steven; Rubén Anguera; Colin Eganl; Fleur Steven; Lucian N. Vintan

2001-01-01

39

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

2011-04-18

40

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

41

Population Bottlenecks in Quasispecies Dynamics

The characteristics of natural populations result from different stochastic and deterministic processes that include reproduction with error, selection, and genetic drift. In particular, population fluctuations constitute a stochastic process that may play a very relevant role in shaping the structure of populations. For example, it is expected that small asexual populations will accumulate mutations at a higher rate than larger

C. Escarmís; E. Lázaro; S. Manrubia

42

THE RELATIVE IMPACT OF A SPRING HUNT ON SNOW GOOSE POPULATION DYNAMICS

Interest in the effect of spring hunting on goose population dynamics has arisen recently in two quite different contexts: measuring the impact of spring harvests by aboriginal hunters, and predicting the potential for using spring harvest to control populations. I developed a matrix-based population model to quantify the relative impact of spring versus autumn harvests on population dynamics of Lesser

Charles M. Francis

43

Population Dynamics under Parasitic Sex Ratio Distortion

We analyse the population dynamic effects of sex ratio distortion by vertically transmitted, feminizing parasites. We show that, for diploid hosts, sex ratio distortion may lead to extinction as males become too rare to maintain the host population through reproduction. Feminizers can magnify Allee effects, broadening the range of conditions leading to extinction of small populations. Depending on male mating

Melanie J. Hatcher; Dale E. Taneyhill; Alison M. Dunn; Chris Tofts

1999-01-01

44

Computational prediction of airfoil dynamic stall

The term dynamic stall refers to unsteady flow separation occurring on aerodynamic bodies, such as airfoils and wings, which execute an unsteady motion. The prediction of dynamic stall is important for flight vehicle, turbomachinery, and wind turbine applications. Due to the complicated flow physics of the dynamic stall phenomenon the industry has been forced to use empirical methods for its

John A. Ekaterinaris; Max F. Platzer

1998-01-01

45

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

46

Cyclic dynamics in simulated plant populations.

Despite the general interest in nonlinear dynamics in animal populations, plant populations are supposed to show a stable equilibrium that is attributed to fundamental differences compared with animals. Some studies find more complex dynamics, but empirical studies usually are too short and most modelling studies ignore important spatial aspects of local competition and establishment. Therefore, we used a spatially explicit individual-based model of a hypothetical, non-clonal perennial to explore which mechanisms might generate complex dynamics, i.e. cycles. The model is based on the field-of-neighbourhood approach that describes local competition and establishment in a phenomenological manner. We found cyclic population dynamics for a wide spectrum of model variants, provided that mortality is determined by local competition and recruitment is virtually completely suppressed within the zone of influence of established plants. This destabilizing effect of local processes within plant populations might have wide-ranging implications for the understanding of plant community dynamics and coexistence.

Bauer, Silke; Berger, Uta; Hildenbrandt, Hanno; Grimm, Volker

2002-01-01

47

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

48

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

2009-10-25

49

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

50

Concepts and tools for predictive modeling of microbial dynamics.

Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models. PMID:15453600

Bernaerts, Kristel; Dens, Els; Vereecken, Karen; Geeraerd, Annemie H; Standaert, Arnout R; Devlieghere, Frank; Debevere, Johan; Van Impe, Jan F

2004-09-01

51

Using stage-based system dynamics modeling for demographic management of captive populations

Management of captive populations relies on a complex synthesis of genetic and demographic analyses to guide populations toward sustainability. Demographic analyses of captive populations currently utilize age-based matrix projections to predict a population's trajectory. An alternate approach is to use a stage-based, system dynamics model for captive systems. Such models can more easily incorporate complex captive systems in which population

Lisa J. Faust; Steven D. Thompson; Joanne M. Earnhardt; Ellen Brown; Sadie Ryan; Michelle Sherman; Meghan Yurenka

2003-01-01

52

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

53

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

54

Relating individual behaviour to population dynamics

How do the behavioural interactions between individuals in an ecological system produce the global population dynamics of that system? We present a stochastic individual-based model of the reproductive cycle of the mite Varroa jacobsoni, a parasite of honeybees. The model has the interesting property in that its population level behaviour is approximated extremely accurately by the exponential logistic equation or

D. J. T. Sumpter; D. S. Broomhead

2001-01-01

55

Population Dynamic Consequences of Allee Effects

We take a well-known dynamic model of an isolated, unstructured population and modify this to include a factor that allows for a reduction in fitness due to declining population sizes, often termed an Allee effect. Analysis of the behaviour of this model is carried out on two fronts – determining the equilibrium values and examining the stability of these equilibria.

M. S. FOWLER; G. D. RUXTON

2002-01-01

56

Modeling the Population Dynamics of Pacific Yew.

National Technical Information Service (NTIS)

A study of Pacific yew (Taxus brevifolia Nutt.) population dynamics in the mountains of western Oregon and Washington was based on a combination of long-term population data and computer modeling. Rates of growth and mortality were low in mature and old-g...

R. T. Busing T. A. Spies

1995-01-01

57

Temporarily discontinuing the use of antibiotics has been proposed as a means to eliminate resistant bacteria by allowing sensitive clones to sweep through the population. In this study, we monitored a tetracycline-sensitive subpopulation that emerged during experimental evolution of E. coli K12 MG1655 carrying the multiresistance plasmid pB10 in the absence of antibiotics. The fraction of tetracycline- sensitive mutants increased

Leen De Gelder; Zaid Abdo; Paul Joyce; Larry J. Forney; Eva M. Top

2004-01-01

58

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

59

Neural population dynamics during reaching.

Most theories of motor cortex have assumed that neural activity represents movement parameters. This view derives from what is known about primary visual cortex, where neural activity represents patterns of light. Yet it is unclear how well the analogy between motor and visual cortex holds. Single-neuron responses in motor cortex are complex, and there is marked disagreement regarding which movement parameters are represented. A better analogy might be with other motor systems, where a common principle is rhythmic neural activity. Here we find that motor cortex responses during reaching contain a brief but strong oscillatory component, something quite unexpected for a non-periodic behaviour. Oscillation amplitude and phase followed naturally from the preparatory state, suggesting a mechanistic role for preparatory neural activity. These results demonstrate an unexpected yet surprisingly simple structure in the population response. This underlying structure explains many of the confusing features of individual neural responses. PMID:22722855

Churchland, Mark M; Cunningham, John P; Kaufman, Matthew T; Foster, Justin D; Nuyujukian, Paul; Ryu, Stephen I; Shenoy, Krishna V

2012-07-01

60

A cell population balance model describing positive feedback loop expression dynamics

Biological systems are inherently heterogeneous in the sense that cellular content is unevenly distributed amongst the cells of the population. In this work, we develop a cell population balance-modeling framework, which integrates biological detail at the single-cell level to accurately predict the dynamics of the distribution of cellular properties at the cell population level. The developed cell population balance model

Nikos V. Mantzaris

2005-01-01

61

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

2010-11-14

62

Predation, individual variability and vertebrate population dynamics

Both predation and individual variation in life history traits influence population dynamics. Recent results from laboratory\\u000a predator–prey systems suggest that differences between individuals can also influence predator–prey dynamics when different\\u000a genotypes experience different predation-associated mortalities. Despite the growing number of studies in this field, there\\u000a is no synthesis identifying the overall importance of the interactions between predation and individual heterogeneity

Nathalie Pettorelli; Tim Coulson; Sarah M. Durant; Jean-Michel Gaillard

63

Ecological processes can synchronize marine population dynamics over continental scales

Determining the relative importance of local and regional processes for the distribution of population abundance is a fundamental but contentious issue in ecology. In marine systems, classical theory holds that the influence of demographic processes and dispersal is confined to local populations whereas the environment controls regional patterns of abundance. Here, we use spatial synchrony to compare the distribution of population abundance of the dominant mussel Mytilus californianus observed along the West Coast of the United States to that predicted by dynamical models undergoing different dispersal and environmental treatments to infer the relative influence of local and regional processes. We reveal synchronized fluctuations in the abundance of mussel populations across a whole continent despite limited larval dispersal and strong environmental forcing. We show that dispersal among neighboring populations interacts with local demographic processes to generate characteristic patterns of spatial synchrony that can govern the dynamic distribution of mussel abundance over 1,800 km of coastline. Our study emphasizes the importance of dispersal and local dynamics for the distribution of abundance at the continental scale. It further highlights potential limits to the use of “climate envelope” models for predicting the response of large-scale ecosystems to global climate change.

Gouhier, Tarik C.; Guichard, Frederic; Menge, Bruce A.

2010-01-01

64

NASA Astrophysics Data System (ADS)

In evolutionary computing (EC), population size is one of the critical parameters that a researcher has to deal with. Hence, it was no surprise that the pioneers of EC, such as De Jong (1975) and Holland (1975), had already studied the population sizing from the very beginning of EC. What is perhaps surprising is that more than three decades later, we still largely depend on the experience or ad-hoc trial-and-error approach to set the population size. For example, in a recent monograph, Eiben and Smith (2003) indicated: "In almost all EC applications, the population size is constant and does not change during the evolutionary search." Despite enormous research on this issue in recent years, we still lack a well accepted theory for population sizing. In this paper, I propose to develop a population dynamics theory forEC with the inspiration from the population dynamics theory of biological populations in nature. Essentially, the EC population is considered as a dynamic system over time (generations) and space (search space or fitness landscape), similar to the spatial and temporal dynamics of biological populations in nature. With this conceptual mapping, I propose to 'transplant' the biological population dynamics theory to EC via three steps: (i) experimentally test the feasibility—whether or not emulating natural population dynamics improves the EC performance; (ii) comparatively study the underlying mechanisms—why there are improvements, primarily via statistical modeling analysis; (iii) conduct theoretical analysis with theoretical models such as percolation theory and extended evolutionary game theory that are generally applicable to both EC and natural populations. This article is a summary of a series of studies we have performed to achieve the general goal [27][30]-[32]. In the following, I start with an extremely brief introduction on the theory and models of natural population dynamics (Sections 1 & 2). In Sections 4 to 6, I briefly discuss three categories of population dynamics models: deterministic modeling with Logistic chaos map as an example, stochastic modeling with spatial distribution patterns as an example, as well as survival analysis and extended evolutionary game theory (EEGT) modeling. Sample experiment results with Genetic algorithms (GA) are presented to demonstrate the applications of these models. The proposed EC population dynamics approach also makes survival selection largely unnecessary or much simplified since the individuals are naturally selected (controlled) by the mathematical models for EC population dynamics.

Ma, Zhanshan (Sam)

65

Stochastic population dynamics: The Poisson approximation

NASA Astrophysics Data System (ADS)

We introduce an approximation to stochastic population dynamics based on almost independent Poisson processes whose parameters obey a set of coupled ordinary differential equations. The approximation applies to systems that evolve in terms of events such as death, birth, contagion, emission, absorption, etc., and we assume that the event-rates satisfy a generalized mass-action law. The dynamics of the populations is then the result of the projection from the space of events into the space of populations that determine the state of the system (phase space). The properties of the Poisson approximation are studied in detail. Especially, error bounds for the moment generating function and the generating function receive particular attention. The deterministic approximation for the population fractions and the Langevin-type approximation for the fluctuations around the mean value are recovered within the framework of the Poisson approximation as particular limit cases. However, the proposed framework allows to treat other limit cases and general situations with small populations that lie outside the scope of the standard approaches. The Poisson approximation can be viewed as a general (numerical) integration scheme for this family of problems in population dynamics.

Solari, Hernán G.; Natiello, Mario A.

2003-03-01

66

(Meta)population dynamics of infectious diseases

The metapopulation concept provides a very powerful tool for analysing the persistence of spatially-disaggregated populations, in terms of a balance between local extinction and colonization. Exactly the same approach has been developed by epidemiologists, in order to understand patterns of diseases persistence. There is great scope for further cross-fertilization between areas. Recent work on the spatitemporal dynamics of measles illustrates

Bryan Grenfell; John Harwood

1997-01-01

67

Dynamics of transitions in population interactions

A two-species model with transitions between population interactions is studied. Rich dynamics is observed as the number and quality of equilibria change when model parameters and functional responses vary. Existence and stability of equilibria and nonexistence of periodic solutions are established, existence of some bifurcation phenomena are analytically and numerically studied, explicit threshold values are computed to determine the kind

Teodoro Lara; Jorge Rebaza

68

Dynamics and Predictability of Hurricane Dolly (2008)

Through several cloud-resolving simulations with the Weather Research and Forecast (WRF-ARW) model, this study examines the dynamics and predictability of Hurricane Dolly (2008) with an emphasis on its initial development (around the time being declared as a tropical storm) and subsequent rapid intensification entering into the Gulf of Mexico. These WRF simulations include three that are directly initialized with the

J. Fang; F. Zhang; Y. Weng

2008-01-01

69

Predictive dynamic thermal management for multimedia applications

Dynamic Thermal Management (DTM) techniques have been proposed to save on thermal packaging and cooling costs for general-purpose processors. However, when invoked, these techniques result in a significant performance degradation. This paper concerns performance-effective DTM for multimedia applications. We make two contributions: (1) Current DTM algorithms are reactive in nature. We propose a predictive DTM algorithm targeted at multimedia applications,

Jayanth Srinivasan; Sarita V. Adve

2003-01-01

70

Dynamics of North American breeding bird populations

NASA Astrophysics Data System (ADS)

Population biologists have long been interested in the variability of natural populations. One approach to dealing with ecological complexity is to reduce the system to one or a few species, for which meaningful equations can be solved. Here we explore an alternative approach, by studying the statistical properties of a data set containing over 600 species, namely the North American breeding bird survey. The survey has recorded annual species abundances over a 31-year period along more than 3,000 observation routes. We now analyse the dynamics of population variability using this data set, and find scaling features in common with inanimate systems composed of strongly interacting subunits. Specifically, we find that the distribution of changes in population abundance over a one-year interval is remarkably symmetrical, with long tails extending over six orders of magnitude. The variance of the population over a time series increases as a power-law with increasing time lag, indicating long-range correlation in population size fluctuations. We also find that the distribution of species lifetimes (the time between colonization and local extinction) within local patches is a power-law with an exponential cutoff imposed by the finite length of the time series. Our results provide a quantitative basis for modelling the dynamics of large species assemblages.

Keitt, Timothy H.; Stanley, H. Eugene

1998-05-01

71

Dynamical Feedbacks between Population Growth and Sociopolitical Instability in Agrarian States

Most preindustrial states experienced recurrent waves of political collapse and internal warfare. One possible explanation of this pattern, the demographic-structural theory, suggests that population growth leads to state instability and breakdown, which in turn causes population decline. Mathematical models incorporating this mechanism predict sustained oscillations in demographic and political dynamics. Here I test these theoretical predictions with time-series data on

Peter Turchin

72

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

73

Model predictive dynamic control allocation with actuator dynamics

A model predictive, dynamic control allocation algorithm is developed in this paper for the inner loop of a re-entry vehicle guidance and control system. The purpose of the control allocation portion of the guidance and control architecture is to distribute control power among redundant control effectors to meet the desired control objectives under a set of constraints. Most existing algorithms

Yu Luo; A. Serrani; Stephen Yurkovich; David B. Doman; Michael W. Oppenheimer

2004-01-01

74

Application of optimal prediction to molecular dynamics

Optimal prediction is a general system reduction technique for large sets of differential equations. In this method, which was devised by Chorin, Hald, Kast, Kupferman, and Levy, a projection operator formalism is used to construct a smaller system of equations governing the dynamics of a subset of the original degrees of freedom. This reduced system consists of an effective Hamiltonian dynamics, augmented by an integral memory term and a random noise term. Molecular dynamics is a method for simulating large systems of interacting fluid particles. In this thesis, I construct a formalism for applying optimal prediction to molecular dynamics, producing reduced systems from which the properties of the original system can be recovered. These reduced systems require significantly less computational time than the original system. I initially consider first-order optimal prediction, in which the memory and noise terms are neglected. I construct a pair approximation to the renormalized potential, and ignore three-particle and higher interactions. This produces a reduced system that correctly reproduces static properties of the original system, such as energy and pressure, at low-to-moderate densities. However, it fails to capture dynamical quantities, such as autocorrelation functions. I next derive a short-memory approximation, in which the memory term is represented as a linear frictional force with configuration-dependent coefficients. This allows the use of a Fokker-Planck equation to show that, in this regime, the noise is {delta}-correlated in time. This linear friction model reproduces not only the static properties of the original system, but also the autocorrelation functions of dynamical variables.

Barber IV, John Letherman

2004-12-01

75

Predicting Spinor Condensate Dynamics from Simple Principles

NASA Astrophysics Data System (ADS)

We study the spin dynamics of quasi-one-dimensional F=1 condensates both at zero and finite temperatures for arbitrary initial spin configurations. The rich dynamical evolution exhibited by these nonlinear systems is explained by surprisingly simple principles: minimization of energy at zero temperature and maximization of entropy at high temperature. Our analytical results for the homogeneous case are corroborated by numerical simulations for confined condensates in a wide variety of initial conditions. These predictions compare qualitatively well with recent experimental observations and can, therefore, serve as a guidance for ongoing experiments.

Moreno-Cardoner, M.; Mur-Petit, J.; Guilleumas, M.; Polls, A.; Sanpera, A.; Lewenstein, M.

2007-07-01

76

Predicting Spinor Condensate Dynamics from Simple Principles

We study the spin dynamics of quasi-one-dimensional F=1 condensates both at zero and finite temperatures for arbitrary initial spin configurations. The rich dynamical evolution exhibited by these nonlinear systems is explained by surprisingly simple principles: minimization of energy at zero temperature and maximization of entropy at high temperature. Our analytical results for the homogeneous case are corroborated by numerical simulations for confined condensates in a wide variety of initial conditions. These predictions compare qualitatively well with recent experimental observations and can, therefore, serve as a guidance for ongoing experiments.

Moreno-Cardoner, M.; Guilleumas, M.; Polls, A. [Departament d'Estructura i Constituents de la Materia, Facultat de Fisica, Universitat de Barcelona, E-08028 Barcelona (Spain); Mur-Petit, J. [IFRAF and Laboratoire Aime Cotton, CNRS and Universite Paris-Sud, F-91405 Orsay (France); Sanpera, A. [ICREA and Grup de Fisica Teorica, Universitat Autonoma de Barcelona, E-08193 Bellaterra (Spain); Lewenstein, M. [ICREA and ICFO-Institut de Ciencies Fotoniques, E-08034 Barcelona (Spain)

2007-07-13

77

Predictive Dynamics of Human Pain Perception

While the static magnitude of thermal pain perception has been shown to follow a power-law function of the temperature, its dynamical features have been largely overlooked. Due to the slow temporal experience of pain, multiple studies now show that the time evolution of its magnitude can be captured with continuous online ratings. Here we use such ratings to model quantitatively the temporal dynamics of thermal pain perception. We show that a differential equation captures the details of the temporal evolution in pain ratings in individual subjects for different stimulus pattern complexities, and also demonstrates strong predictive power to infer pain ratings, including readouts based only on brain functional images.

Cecchi, Guillermo A.; Huang, Lejian; Hashmi, Javeria Ali; Baliki, Marwan; Centeno, Maria V.; Rish, Irina; Apkarian, A. Vania

2012-01-01

78

A combined computational fluid dynamics\\/population balance model (CFD-PBM) is developed for gas hydrate particle size prediction in turbulent pipeline flow. The model is based on a one-moment population balance technique, which is coupled with flow field parameters computed using commercial CFD software. The model is calibrated with a five-moment, off-line population balance model and validated with experimental data produced in

Boris V. Balakin; Alex C. Hoffmann; Pawel Kosinski; Vladimir A. Istomin; Evgeny M. Chuvilin

2010-01-01

79

Dynamics of selection in a heterogeneous population

The dynamics of the number of diploid individuals with possible n {ge} 2 alleles of a gene not located in a sex chromosome was studied in a heterogeneous isolated population. It was demonstrated that if only selection is accounted for, the number of individuals carrying alleles that do not a provide maximal selective advantage approaches zero as the time of observation increases, whereas the number of individuals with various genotypes, but with a maximal selective advantage, approaches nonzero stationary values depending on their initial numbers. It was established that under certain conditions and even if processes of death-reproduction are taken into account, the mechanism of selection may have a dominating effect on population dynamics.

Volkov, I.K.; Chebotarev, A.N. [Moscow Technical Univ. (Russian Federation)

1995-01-01

80

TIMBER HARVEST AND BLACK BEAR POPULATION DYNAMICS IN A SOUTHERN APPALACHIAN FOREST

Abstract: Habitat capability models are frequently used in long-term land management planning to evaluate the effects of management alternatives on wildlife populations. We believe that the relationships between timber harvest operations and black bear (Ursus americanus) population dynamics in the southern Appalachians make habitat capability models alone inadequate to predict long-term population response to timber harvest. An explicit consideration of

Allan J. Brody; Jeff N. Stone

81

Radiation Damage to a Dynamic Cell Population

Models for ionizing radiation damage to cells are surveyed. Examples are given for how radiation damage models can be combined with those standard cell population dynamics models which have, in the absence of radiation, a time development governed by a semi-group of non-negative operators. Such combined models are useful in analyzing observed radiation dose-rate effects: direct dose-rate effects when protracting

P. Hahnfeldt; R. K. Sachs

82

Predicting the Effects of Endocrine Disrupting Chemicals on Fish Populations

This study evaluates the applicability and sensitivity of fish population dynamics modeling in assessing the potential effects of individual chemicals on population sustainability and recovery. Fish reproductive health is an increasingly important issue for ecological risk assessment following international concern over endocrine disruption. Life-history data from natural brook trout and fathead minnow populations were combined with effects data from laboratory-based

A. R. Brown; A. M. Riddle; N. L. Cunningham; T. J. Kedwards; N. Shillabeer; T. H. Hutchinson

2003-01-01

83

Population dynamics of humans and other animals.

Human population dynamics, at least until the past century, have probably been governed by homeostasis and in this resembled those of other animals. Because human population homeostasis was probably substantially weaker than among large mammals, its operation has been less obvious. Nonetheless, the empirical evidence for advanced agriculturalists is compelling. Unlike animals, the human population has tended toward equilibria that have been tending upward at an accelerating rate. The acceleration might reflect long-run positive feedback between density and technological progress, as Boserup has suggested. Because homeostasis was weak, its role in shorter run historical explantation is limited; its force was gentle and easily overwhelmed by other particular influences. Malthusian oscillation, in the sense of distinctive medium-run dynamics arising from homeostasis, probably did not occur. And because homeostasis was weak, density dependence can in principle explain only a minute proportion of the annual variation in population growth rates. Yet homeostasis plays an essential role in demographic theory. Without it, we are incapable of explaining population size and change over time except by recounting a mindless chronology of events back to the beginning of humanity--whenever that was. Without it, we cannot explain the response of population growth to economic growth. Without it, we cannot explain recovery from catastrophe or the rapid natural increase in many frontier regions. Without it, we cannot properly analyze the influence of climatic variation and other partially density-independent factors. Our basic understanding of human history requires a grasp of what homeostasis can explain and what it cannot. A homeostatic approach to population dynamics also leads to questions about the roles of reproductive norms and institutions, not just whether they encourage high or low fertility, but whether they make natural increase responsive to resource abundance. And if they do, whether they strike the balance of population and the means of subsistence at a relatively prosperous or impoverished level. Such considerations may contribute to an understanding of broad preindustrial differences among the regions of the world in densities, average levels of vital rates, and living standards--which was very much how Malthus viewed the matter. Ordinary homeostatic tendencies essentially vanish in the course of economic development, and they were probably all but gone from much of Europe by the end of the 19th century.(ABSTRACT TRUNCATED AT 400 WORDS) PMID:3322884

Lee, R D

1987-11-01

84

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, ?, and provide a method for efficient numerical calculation.

Nowak, Martin A.

2009-01-01

85

ERIC Educational Resources Information Center

|Available on the University of Illinois PLATO IV Computer system, the Population Dynamic Group computer-aided instruction program for teaching population dynamics is described and explained. The computer-generated visual graphics enable fast and intuitive understanding of the dynamics of population and of the concepts and data of population. The…

Klaff, Vivian; Handler, Paul

86

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

87

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

88

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

89

Connecting phenological predictions with population growth rates ...

The model is parameterized and compared with 8 years of data from a recent outbreak in ... A model driven by observed south-side phloem temperatures and that ... is most predictive and generates realistic parameter values of mountain pine ...

90

Army Prisoner Population Prediction Study (AP3).

National Technical Information Service (NTIS)

The Army Prisoner Prediction Study (AP3) consists of the development of a methodology and associated model to provide the Army Correctional System proponent with an analytic managerial tool to assist in the management of the correctional system. The model...

R. M. Miller S. H. Miller

1983-01-01

91

Role of noise in population dynamics cycles

NASA Astrophysics Data System (ADS)

Noise is an intrinsic feature of population dynamics and plays a crucial role in oscillations called phase-forgetting quasicycles by converting damped into sustained oscillations. This function of noise becomes evident when considering Langevin equations whose deterministic part yields only damped oscillations. We formulate here a consistent and systematic approach to population dynamics, leading to a Fokker-Planck equation and the associate Langevin equations in accordance with this conceptual framework, founded on stochastic lattice-gas models that describe spatially structured predator-prey systems. Langevin equations in the population densities and predator-prey pair density are derived in two stages. First, a birth-and-death stochastic process in the space of prey and predator numbers and predator-prey pair number is obtained by a contraction method that reduces the degrees of freedom. Second, a van Kampen expansion in the inverse of system size is then performed to get the Fokker-Planck equation. We also study the time correlation function, the asymptotic behavior of which is used to characterize the transition from the cyclic coexistence of species to the ordinary coexistence.

Tomé, Tânia; de Oliveira, Mário J.

2009-06-01

92

Song Diversity Predicts the Viability of Fragmented Bird Populations

In the global scenario of increasing habitat fragmentation, finding appropriate indicators of population viability is a priority for conservation. We explored the potential of learned behaviours, specifically acoustic signals, to predict the persistence over time of fragmented bird populations. We found an association between male song diversity and the annual rate of population change, population productivity and population size, resulting in birds singing poor repertoires in populations more prone to extinction. This is the first demonstration that population viability can be predicted by a cultural trait (acquired via social learning). Our results emphasise that cultural attributes can reflect not only individual-level characteristics, but also the emergent population-level properties. This opens the way to the study of animal cultural diversity in the increasingly common human-altered landscapes.

Laiolo, Paola; Vogeli, Matthias; Serrano, David; Tella, Jose L.

2008-01-01

93

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

94

Predicting Agent Strategy Mix in Heterogeneous Populations

Prior research has identified agent behaviors or strate- gies that can develop and sustain mutually beneficial co- operative relationships with like-minded agents and can re - sist exploitation from selfish agents. Evolutionary tourna - ments with different strategies can model scenarios where agents periodically adopt strategies that are outperformi ng others in the population. However, such experiments can be computationally

Sabyasachi Saha; Sandip Sen

95

Dynamics of mutualist populations that are demographically open.

1. Few theoretical studies have examined the impact of immigration and emigration on mutualist population dynamics, but a recent empirical study (A.R. Thompson Oecologia, 143, 61-69) on mutualistic fish and shrimp showed that immigration can prevent population collapse, and that intraspecific competition for a mutualistic partner can curb population expansion. To understand in a theoretical context the implications of these results, and to assess their generality, we present a two-species model that accounts explicitly for immigration and emigration, as well as distinguishing the impacts of mutualism on birth rates, death rates and habitat acquisition. 2. The model confirms that immigration can stabilize mutualistic populations, and predicts that high immigration, along with enhanced reproduction and/or reduced mortality through mutualism, can cause population sizes to increase until habitat availability curbs further expansion. 3. We explore in detail the effects of different forms of habitat limitation on mutualistic populations. Habitat availability commonly limits the density of both populations if mutualists acquire shelter independently. If a mutualist depends on a partner for habitat, densities of that mutualist are capped by the amount of space provided by that partner. The density of the shelter-provider is limited by the environment. 4. If a mutualism solely augments reproduction, and most locally produced individuals leave the focal patch, then the mutualism will have a minimal effect on local dynamics. If the mutualism operates by reducing rates of death or enhancing habitat availability, and there is at least some immigration, then mutualism will affect local dynamics. This finding may be particularly relevant in marine systems, where there is high variability (among species and locations) in the extent to which progeny disperse from natal locations. 5. Overall, our results demonstrate that the consequences of immigration and emigration for the dynamics of mutualists depend strongly on which demographic rate is influenced by mutualism. 6. By relating our model to a variety of terrestrial and aquatic systems, we provide a general framework to guide future empirical studies of the dynamics of mutualistic populations. PMID:17032356

Thompson, Andrew R; Nisbet, Roger M; Schmitt, Russell J

2006-11-01

96

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

97

A population dynamics approach to biological aging

NASA Astrophysics Data System (ADS)

A dynamical model for aging in biological population is discussed where asexual reproduction is considered. The maximum life span is inherited from parent to offspring with some random mutations described by a transition matrix, and the fertile period begins at a defined age R. The intra species competition is modeled through a Verhulst-like factor. Discrete time evolution equations are iterated and the transient and asymptotic solutions are obtained. When only bad mutations are taken into account, the stationary solutions are obtained analytically. The results are applied to the Penna model.

de Almeida, R. M. C.

98

Predicting Protein Interactions by Brownian Dynamics Simulations

We present a newly adapted Brownian-Dynamics (BD)-based protein docking method for predicting native protein complexes. The approach includes global BD conformational sampling, compact complex selection, and local energy minimization. In order to reduce the computational costs for energy evaluations, a shell-based grid force field was developed to represent the receptor protein and solvation effects. The performance of this BD protein docking approach has been evaluated on a test set of 24 crystal protein complexes. Reproduction of experimental structures in the test set indicates the adequate conformational sampling and accurate scoring of this BD protein docking approach. Furthermore, we have developed an approach to account for the flexibility of proteins, which has been successfully applied to reproduce the experimental complex structure from the structure of two unbounded proteins. These results indicate that this adapted BD protein docking approach can be useful for the prediction of protein-protein interactions.

Meng, Xuan-Yu; Xu, Yu; Zhang, Hong-Xing; Mezei, Mihaly; Cui, Meng

2012-01-01

99

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

100

Building the bridge between animal movement and population dynamics

While the mechanistic links between animal movement and population dynamics are ecologically obvious, it is much less clear when knowledge of animal movement is a prerequisite for understanding and predicting population dynamics. GPS and other technologies enable detailed tracking of animal location concurrently with acquisition of landscape data and information on individual physiology. These tools can be used to refine our understanding of the mechanistic links between behaviour and individual condition through ‘spatially informed’ movement models where time allocation to different behaviours affects individual survival and reproduction. For some species, socially informed models that address the movements and average fitness of differently sized groups and how they are affected by fission–fusion processes at relevant temporal scales are required. Furthermore, as most animals revisit some places and avoid others based on their previous experiences, we foresee the incorporation of long-term memory and intention in movement models. The way animals move has important consequences for the degree of mixing that we expect to find both within a population and between individuals of different species. The mixing rate dictates the level of detail required by models to capture the influence of heterogeneity and the dynamics of intra- and interspecific interaction.

Morales, Juan M.; Moorcroft, Paul R.; Matthiopoulos, Jason; Frair, Jacqueline L.; Kie, John G.; Powell, Roger A.; Merrill, Evelyn H.; Haydon, Daniel T.

2010-01-01

101

Population viability analyses (PVA) are increasingly used in metapopulation conservation plans. Two major types of models are commonly used to assess vulnerability and to rank management options: population-based stochastic simulation models (PSM such as RAMAS or VORTEX) and stochastic patch occupancy models (SPOM). While the first set of models relies on explicit intrapatch dynamics and interpatch dispersal to predict population

Jérôme Pellet; Gérard Maze; Nicolas Perrin

2006-01-01

102

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

103

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

104

Population based reweighting of scaled molecular dynamics.

Molecular dynamics simulation using enhanced sampling methods is one of the powerful computational tools used to explore protein conformations and free energy landscapes. Enhanced sampling methods often employ either an increase in temperature or a flattening of the potential energy surface to rapidly sample phase space, and a corresponding reweighting algorithm is used to recover the Boltzmann statistics. However, potential energies of complex biomolecules usually involve large fluctuations on a magnitude of hundreds of kcal/mol despite minimal structural changes during simulation. This leads to noisy reweighting statistics and complicates the obtainment of accurate final results. To overcome this common issue in enhanced conformational sampling, we propose a scaled molecular dynamics method, which modifies the biomolecular potential energy surface and employs a reweighting scheme based on configurational populations. Statistical mechanical theory is applied to derive the reweighting formula, and the canonical ensemble of simulated structures is recovered accordingly. Test simulations on alanine dipeptide and the fast folding polypeptide Chignolin exhibit sufficiently enhanced conformational sampling and accurate recovery of free energy surfaces and thermodynamic properties. The results are comparable to long conventional molecular dynamics simulations and exhibit better recovery of canonical statistics over methods which employ a potential energy term in reweighting. PMID:23721224

Sinko, William; Miao, Yinglong; de Oliveira, César Augusto F; McCammon, J Andrew

2013-07-11

105

Population Based Reweighting of Scaled Molecular Dynamics

Molecular dynamics simulation using enhanced sampling methods is one of the powerful computational tools used to explore protein conformations and free energy landscapes. Enhanced sampling methods often employ either an increase in temperature or a flattening of the potential energy surface to rapidly sample phase space, and a corresponding reweighting algorithm is used to recover the Boltzmann statistics. However, potential energies of complex biomolecules usually involve large fluctuations on a magnitude of hundreds of kcal/mol despite minimal structural changes during simulation. This leads to noisy reweighting statistics and complicates the obtainment of accurate final results. To overcome this common issue in enhanced conformational sampling, we propose a scaled molecular dynamics method, which modifies the biomolecular potential energy surface and employs a reweighting scheme based on configurational populations. Statistical mechanical theory is applied to derive the reweighting formula, and the canonical ensemble of simulated structures is recovered accordingly. Test simulations on alanine dipeptide and the fast folding polypeptide Chignolin exhibit sufficiently enhanced conformational sampling and accurate recovery of free energy surfaces and thermodynamic properties. The results are comparable to long conventional molecular dynamics simulations and exhibit better recovery of canonical statistics over methods which employ a potential energy term in reweighting.

2013-01-01

106

The island syndrome and population dynamics of introduced rats.

The island syndrome predicts directional changes in the morphology and demography of insular vertebrates, due to changes in trophic complexity and migration rates caused by island size and isolation. However, the high rate of human-mediated species introductions to some islands also increases trophic complexity, and this will reduce the perceived insularity on any such island. We test four hypotheses on the role of increased trophic complexity on the island syndrome, using introduced black rats (Rattus rattus) on two isolated coral atolls in the Mozambique Channel. Europa Island has remained relatively pristine and insular, with few species introductions, whereas Juan de Nova Island has had many species introductions, including predators and competitors of rats, anthropogenically increasing its trophic complexity. In the most insular environments, the island syndrome is expected to generate increases in body size and densities of rodents but decreases in the rates of reproduction and population cycling. Morphology and reproduction were compared using linear regression and canonical discriminant analysis, while density and population cycling were compared using spatially explicit capture-recapture analysis. Results were compared to other insular black rat populations in the Mozambique Channel and were consistent with predictions from the island syndrome. The manifestation of an island syndrome in rodents depends upon the trophic composition of a community, and may not relate to island size alone when many species additions, such as invasions, have occurred. The differing patterns of rodent population dynamics on each island provide information for future rodent eradication operations. PMID:21643994

Russell, James C; Ringler, David; Trombini, Aurélien; Le Corre, Matthieu

2011-06-05

107

Individual-based modeling, population dynamics, and fisheries recruitment success

Prediction of recruitment success is a critical problem in fisheries research. From a theoretical perspective, the ability to predict the number and characteristics of reproducing survivors underlies the field of quantitative population dynamics. Form a practical perspective, rationale and efficient management of fisheries resources requires the ability to accurately forecast the effects of disturbances, both natural and anthropogenic in origin, on fish populations. The objective of this paper is to advocate individual- based modelling as an alternative to the more traditional approaches for predicting recruitment success. First, some reasons for the limited success to date in making long-term predictions of fisheries recruitment are summarized. The importance of information on individuals, rather than on the average individual, is then illustrated as the fallacy of the average'' using two sets of experimental data. The general ideas behind individual-based modelling, and four examples of individual-based models involving fish, are then briefly described. Finally, we make some concluding remarks. Two caveats are necessary. This paper is a summary of a workshop presentation; we therefore take many liberties and make gross generalizations throughout the paper. Also, although not explicitly stated, our discussion is based more on estuarine and marine, than on freshwater, fishes. 8 refs., 6 figs.

Rose, K.A.; DeAngelis, D.L.; Barnthouse, W.; Van Winkle, W.

1990-01-01

108

Analysis of urban - rural population dynamics for China

The multiregional demography approach is used in an analysis of the urban - rural population dynamics of China. Multiregional population-accounts and methods of estimation of demographic rates are developed on the basis of the multiregional population-accounts concept. An accounts-based urban - rural population projection model is established and used to project the population of China from 1988 to 2087.

J Shen

1991-01-01

109

Physical control of plankton population abundance and dynamics in intertidal rock pools

Little is known about the population structure and dynamics of plankton of intertidal rock pools. A numerical model was developed for rock pool plankton with growth limited by both tidal washout and the stress associated with adverse conditions in high-shore pools. This model predicts that a stress tolerant species will tend to have maximum population densities in high-shore pools and

M. P. Johnson

2000-01-01

110

Long-term dynamics of Typha populations

The zonation of Typha populations in an experimental pond in Michigan was re-examined 15 years after the original sampling to gain insight into the long-term dynamics. Current distributions of Typha populations were also examined in additional experimental ponds at the site that have been maintained for 23 years. The zonation between T. latifolia and T. angustifolia in the previously studied pond 15 years after the initial sampling revealed that the density and distribution of shoots had not changed significantly. Thus, it appears that previously reported results (based on 7- year old populations) have remained consistent over time. Additional insight into the interaction between these two taxa was sought by comparing mixed and monoculture stands in five experimental ponds that have remained undisturbed for their 23-year history. The maximum depth of T. latifolia, the shallow- water species, was not significantly reduced when growing in the presence of the more flood tolerant T. angustifolia. In contrast, the minimum depth of T. angustifolia was reduced from 0 to 37 cm when in the presence of T. latifolia. When total populations were compared between monoculture and mixed stands, the average density of T. angustifolia shoots was 59.4 percent lower in mixed stands while the density of T. latifolia was 32 percent lower, with T. angustifolia most affected at shallow depths (reduced by 92 percent) and T. latifolia most affected at the deepest depths (reduced by 60 percent). These long-term observations indicate that competitive displacement between Typha taxa has remained stable over time.

Grace, J. B.; Wetzel, R. G.

1998-01-01

111

Modeling the population dynamics of phytoplankton in lacustrine ecosystems

NASA Astrophysics Data System (ADS)

Phytoplankton are microscopic plants, diverse in shape, and form the basis of aquatic ecosystems. Through both photosynthesis and respiration, they produce organic compounds and contribute notably to the Earth's carbon cycle, which make the population dynamics of phytoplankton important in discussions on climate change. In this talk, we introduce a model that predicts the vertical distribution of phytoplankton in freshwater lakes. The growth of phytoplankton is intimately connected to nutrient and light availability. Quantifying the growth due to light availability requires quantifying the seasonal settling velocity of the particles. Careful consideration is paid to the interaction between the forces of buoyancy, gravity, and drag. To accurately formulate settling velocity, the low Reynolds nature of the system is exploited and added to an experimental, laboratory component. The laboratory research is guided by the use of a sedimentation tank and a collection of vertical cylinders that allow the characterization of particle separation and settling velocity for sparse phytoplankton populations of both spherical and slender shape.

Leiterman, Terry Jo

2011-11-01

112

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

113

Population and geographic range dynamics: implications for conservation planning

Continuing downward trends in the population sizes of many species, in the conservation status of threatened species, and in the quality, extent and connectedness of habitats are of increasing concern. Identifying the attributes of declining populations will help predict how biodiversity will be impacted and guide conservation actions. However, the drivers of biodiversity declines have changed over time and average trends in abundance or distributional change hide significant variation among species. While some populations are declining rapidly, the majority remain relatively stable and others are increasing. Here we dissect out some of the changing drivers of population and geographic range change, and identify biological and geographical correlates of winners and losers in two large datasets covering local population sizes of vertebrates since 1970 and the distributions of Galliform birds over the last two centuries. We find weak evidence for ecological and biological traits being predictors of local decline in range or abundance, but stronger evidence for the role of local anthropogenic threats and environmental change. An improved understanding of the dynamics of threat processes and how they may affect different species will help to guide better conservation planning in a continuously changing world.

Mace, Georgina M.; Collen, Ben; Fuller, Richard A.; Boakes, Elizabeth H.

2010-01-01

114

Nonlinear dynamical systems perspective on climate predictability

NASA Astrophysics Data System (ADS)

Nonlinear dynamical systems theory has inspired a new set of useful tools to be applied in climate studies. In this work we presented specific examples where information has been gained by the application of methods from nonlinear dynamical systems theory. The main goal is to understand the relative importance of stochastic forcing versus deterministic coupling within the context of Coupled General Circulation Models. This work address this important subject by approaching this goal through the development of a hierarchy of models with increasing complexity that we assert contain the essential dynamics of ENSO. We examined the effect of noise in a low order model and found that it is not restricted to blurring the attractor trajectories in phase space, but includes important changes in the dynamics of the system. The main results indicate that the presence of noise in a nonlinear system has two different effects. The presence of noise acts to increase the maximum Lyapunov exponent and can result in noise induced chaos if the system was originally stable. However, the same arguments are not valid if the original system is already in the chaotic regime, where the noise inclusion acts to decrease the maximum Lyapunov exponent, therefore increasing the system stability. The system of interest includes coupled ocean-atmosphere interactions and here we mimic this interaction by coupling two low order models with very different dominant time scales. These subsystems interact in a complex, nonlinear way and the behaviour of the whole system cannot be explained by a linear summation of dynamics of the system parts. We used information theory concepts to detect the influence of the slow system dynamics in synchronizing the fast system in coupled models. We introduced a fast-slow coupled system, where both the slowness of the ocean model and the intensity of the boundary forcing anomalies contribute to the asymmetry and phase locking of both subsystems. The mechanisms controlling the fast model spread were uncovered revealing uncertainty dynamics depending on the location of ensemble members in the model's phase space. As an intermediate step between low order models and CGCMs we study the effect of noise on an intermediate complexity model. The addition of gaussian noise to the Zebiak-Cane model in order to understand the effects of noise on its attractor led to a way of estimating the noise level based on the effects of noise on the correlation dimension curves. We investigate the intrinsic predictability of the coupled models used here, and the different time scales associated with fast and slow modes were detected using the Finite Size Lyapunov Exponents. We found new estimates for the prediction horizon of ENSO for the Zebiak-Cane model as well as for the NCAR CCSM3 model and observations. The whole analysis of observations and CCSM3 was possible after applying noise reduction techniques. We also improved our understanding of three different noise reduction techniques by comparing the Local Projective Noise Reduction, the Interactive Ensemble strategy, and a Random Interactive Ensemble applied to CCSM3. The main difference between these two noise reduction techniques is when the process is applied. The Local Projective Noise Reduction can be applied to both model and observations, and it is done a posteriori in phase space, therefore the trajectories to be adjusted already posses the physical mechanisms embedded in them. The Interactive Ensemble approach can only be applied to model simulations and has shown to be a very useful technique for noise reduction since its done a priori while the system evolves instead of a posteriori, besides the fact that it allows to retrieve the spatial distribution of the noise level in physical space.

Siqueira, Leo

115

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

116

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

117

Prediction of pancreatic necrosis by dynamic pancreatography.

Parenchymal necrosis has recently been recognized as the principal determinant of the incidence of secondary infection in acute pancreatitis. Because secondary infection of pancreatic necrosis accounts for more than 80% of all deaths from acute pancreatitis, a method for determining the presence or absence of parenchymal necrosis would offer considerable prognostic and therapeutic information. Thirty seven patients with unequivocal acute pancreatitis and five normal controls were prospectively studied with intravenous bolus, contrast-enhanced computed tomography (dynamic pancreatography). In the absence of pancreatic necrosis, there were no significant differences in parenchymal enhancement between any of the following patient groups: controls (5), uncomplicated pancreatitis (20), pancreatic abscess (7), or peripancreatic necrosis (4)(p less than 0.05). On the other hand, pancreatic parenchymal enhancement was significantly reduced or absent in all six patients with segmental or diffuse pancreatic necrosis (p less than 0.05). Postcontrast pancreatic parenchymal enhancement was also found to be inversely correlated with the number of Ranson signs (p less than 0.001). Dynamic pancreatography offers prognostic information and is a safe and reliable technique for predicting the presence or absence of pancreatic parenchymal necrosis. Images Figs. 1A and B. Figs. 3A and B. Figs. 4A and B. Fig. 5. Figs. 6A and B. Fig. 7.

Bradley, E L; Murphy, F; Ferguson, C

1989-01-01

118

Dynamic situation assessment and prediction (DSAP)

NASA Astrophysics Data System (ADS)

The face of war has changed. We no longer have the luxury of planning campaigns against a known enemy operating under a well-understood doctrine, using conventional weapons and rules of engagement; all in a well-charted region. Instead, today"s Air Force faces new, unforeseen enemies, asymmetric combat situations and unconventional warfare (Chem/Bio, co-location of military assets near civilian facilities, etc.). At the same time, the emergence of new Air Force doctrinal notions (e.g., Global Strike Task Force, Effects-Based Operations, the desire to minimize or eliminate any collateral damage, etc.)- while propounding the benefits that can be expected with the adoption of such concepts also impose many new technical and operational challenges. Furthermore, future mission/battle commanders will need to assimilate a tremendous glut of available information, and still be expected to make quick-response decisions and to quantify the effects of those decisions all in the face of uncertainty. All these factors translate to the need for dramatic improvements in the way we plan, rehearse, execute and dynamically assess the status of military campaigns. This paper addresses these crucial and revolutionary requirements through the pursuit of a new simulation paradigm that allows a user to perform real-time dynamic situation assessment and prediction.

Sisti, Alex F.

2003-09-01

119

Dynamics of a black bear population within a desert metapopulation

Understanding metapopulation dynamics in large carnivores with naturally fragmented populations is difficult because of the large temporal and spatial context of such dynamics. We coupled a long-term database of visitor sighting records with an intensive 3-year telemetry study to describe population dynamics of recolonization by black bears (Ursus americanus) of Big Bend National Park in Texas during 1988–2002. This population,

Eric C. Hellgren; David P. Onorato; J. Raymond Skiles

2005-01-01

120

Host-Driven Population Dynamics in an Herbivorous Insect

Understanding the nature and relative importance of endogenous (density-dependent) and exogenous (density-independent) effects on population dynamics remains a central problem in ecology. Evaluation of these forces has been constrained by the lack of long time series of population densities and largely limited to populations chosen for their unique dynamics (e.g., outbreak insects). Especially in herbivore populations, the relative contributions of

Tiina Ylioja; Heikki Roininen; Matthew P. Ayres; Matti Rousi; Peter W. Price

1999-01-01

121

Population Dynamics of Active and Total Ciliate Populations in Arable Soil Amended with Wheat

Soil protozoa are characterized by their ability to produce cysts, which allows them to survive unfavorable conditions (e.g., desiccation) for extended periods. Under favorable conditions, they may rapidly excyst and begin feeding, but even under optimal conditions, a large proportion of the population may be encysted. The factors governing the dynamics of active and encysted cells in the soil are not well understood. Our objective was to determine the dynamics of active and encysted populations of ciliates during the decomposition of freshly added organic material. We monitored, in soil microcosms, the active and total populations of ciliates, their potential prey (bacteria and small protozoa), their potential competitors (amoebae, flagellates, and nematodes), and their potential predators (nematodes). We sampled with short time intervals (2 to 6 days) and generated a data set, suitable for mathematical modeling. Following the addition of fresh organic material, bacterial numbers increased more than 1,400-fold. There was a temporary increase in the number of active ciliates, followed by a rapid decline, although the size of the bacterial prey populations remained high. During this initial burst of ciliate growth, the population of cystic ciliates increased 100-fold. We suggest that internal population regulation is the major factor governing ciliate encystment and that the rate of encystment depends on ciliate density. This model provides a quantitative explanation of ciliatostasis and can explain why protozoan growth in soil is less than that in aquatic systems. Internally governed encystment may be an essential adaptation to an unpredictable environment in which individual protozoa cannot predict when the soil will dry out and will survive desiccation only if they have encysted in time.

Ekelund, Flemming; Frederiksen, Helle B.; R?nn, Regin

2002-01-01

122

The effects of density-dependent dispersal on the spatiotemporal dynamics of cyclic populations

Density-dependent dispersal occurs throughout the animal kingdom, and has been shown to occur in some taxa whose populations exhibit multi-year population cycles. However, the importance of density-dependent dispersal for the spatiotemporal dynamics of cyclic populations is unknown. We investigated the potential effects of density-dependent dispersal on the properties of periodic travelling waves predicted by two coupled reaction–diffusion models: a commonly

Matthew J. Smith; Jonathan A. Sherratt; Xavier Lambin

2008-01-01

123

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. Habilidad de los Modelos Matriciales para Explicar el Pasado y Predecir el Futuro de las Poblaciones de Plantas. 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

2013-04-08

124

Monitoring the population dynamics of a biocontrol agent in soil is important for understanding, predicting and increasing its efficacy. In this study, the population dynamics and the efficacy of a promising biocontrol agent against nematode, the fungus Hirsutella rhossiliensis, were investigated in greenhouse experiments with quantitative real-time polymerase chain reaction (PCR) and bioassay. To explore the effects of the fungus

Limei Zhang; Ence Yang; Meichun Xiang; Xingzhong Liu; Senyu Chen

2008-01-01

125

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. Efectos de una Planta Invasora sobre las Dinámica Poblacional de Sapos. PMID:23692126

Greenberg, Daniel A; Green, David M

2013-05-21

126

Structural dynamics and ecology of flatfish populations

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,

Kevin M. Bailey

1997-01-01

127

Population dynamics of infectious diseases: A discrete time model

Mathematical models of infectious diseases can provide important insight into our understanding of epidemiological processes, the course of infection within a host, the transmission dynamics in a host population, and formulation or implementation of infection control programs. We present a framework for modeling the dynamics of infectious diseases in discrete time, based on the theory of matrix population models. The

Madan K. Oli; Meenakshi Venkataraman; Paul A. Klein; Lori D. Wendland; Mary B. Brown

2006-01-01

128

Cell Population Dynamics Modulate the Rates of Tissue Growth Processes

The development and testing of a discrete model describing the dynamic process of tissue growth in three-dimensional scaffolds is presented. The model considers populations of cells that execute persistent random walks on the computational grid, collide, and proliferate until they reach confluence. To isolate the effect of population dynamics on tissue growth, the model assumes that nutrient and growth factor

Gang Cheng; Belgacem B. Youssef; Pauline Markenscoff; Kyriacos Zygourakis

2006-01-01

129

Population Dynamics in Spatially Complex Environments: Theory and Data

Population dynamics and species interactions are spread out in space. This might seem like a trivial observation, but it has potentially important consequences. In particular, mathematical models show that the dynamics of populations can be altered fundamentally simply because organisms interact and disperse rather than being confined to one position for their entire lives. Models that deal with dispersal and

Peter Kareiva

1990-01-01

130

Microbial population dynamics by digital in-line holographic microscopy

Measurements of population dynamics are ubiquitous in experiments with microorganisms. Studies with microbes elucidating adaptation, selection, and competition rely on measurements of changing populations in time. Despite this importance, quantitative methods for measuring population dynamics microscopically, with high time resolution, across many replicates remain limited. Here we present a new noninvasive method to precisely measure microbial spatiotemporal population dynamics based on digital in-line holographic (DIH) microscopy. Our inexpensive, replicate DIH microscopes imaged hundreds of swimming algae in three dimensions within a volume of several microliters on a time scale of minutes over periods of weeks.

Frentz, Zak; Kuehn, Seppe; Hekstra, Doeke; Leibler, Stanislas

2010-01-01

131

Microbial population dynamics by digital in-line holographic microscopy

NASA Astrophysics Data System (ADS)

Measurements of population dynamics are ubiquitous in experiments with microorganisms. Studies with microbes elucidating adaptation, selection, and competition rely on measurements of changing populations in time. Despite this importance, quantitative methods for measuring population dynamics microscopically, with high time resolution, across many replicates remain limited. Here we present a new noninvasive method to precisely measure microbial spatiotemporal population dynamics based on digital in-line holographic (DIH) microscopy. Our inexpensive, replicate DIH microscopes imaged hundreds of swimming algae in three dimensions within a volume of several microliters on a time scale of minutes over periods of weeks.

Frentz, Zak; Kuehn, Seppe; Hekstra, Doeke; Leibler, Stanislas

2010-08-01

132

Background Size of the reference population and reliability of phenotypes are crucial factors influencing the reliability of genomic predictions. It is therefore useful to combine closely related populations. Increased accuracies of genomic predictions depend on the number of individuals added to the reference population, the reliability of their phenotypes, and the relatedness of the populations that are combined. Methods This paper assesses the increase in reliability achieved when combining four Holstein reference populations of 4000 bulls each, from European breeding organizations, i.e. UNCEIA (France), VikingGenetics (Denmark, Sweden, Finland), DHV-VIT (Germany) and CRV (The Netherlands, Flanders). Each partner validated its own bulls using their national reference data and the combined data, respectively. Results Combining the data significantly increased the reliability of genomic predictions for bulls in all four populations. Reliabilities increased by 10%, compared to reliabilities obtained with national reference populations alone, when they were averaged over countries and the traits evaluated. For different traits and countries, the increase in reliability ranged from 2% to 19%. Conclusions Genomic selection programs benefit greatly from combining data from several closely related populations into a single large reference population.

2011-01-01

133

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

134

Introducing Dynamic Analysis Using Malthus's Principle of Population.

ERIC Educational Resources Information Center

Declares the use of dynamic models is increasing in macroeconomics. Explains how to introduce dynamic models to students whose technical skills are modest or varied. Chooses Malthus's Principle of Population as a natural context for introducing dynamic analysis because it provides a method for reviewing the mathematical tools and theoretical…

Pingle, Mark

2003-01-01

135

Dynamic models of infectious diseases as regulators of population sizes

Five SIRS epidemiological models for populations of varying size are considered. The incidences of infection are given by mass action terms involving the number of infectives and either the number of susceptibles or the fraction of the population which is susceptible. When the population dynamics are immigration and deaths, thresholds are found which determine whether the disease dies out or

Jaime Mena-Lorcat; Herbert W. Hethcote

1992-01-01

136

Role of evolution by natural selection in population dynamics

Using a Monte Carlo approach we study the role of inheritance and natural selection in the dynamics of populations. We show that a population subject to inheritance has a much better chance of survival in a given condition than a population where new generations do not inherit genomes of their parents. The dependence of the survival chance on such factors

Michel Droz; Andrzej Pekalski

2004-01-01

137

Neutron Star Population Dynamics. I. Millisecond Pulsars

NASA Astrophysics Data System (ADS)

We study the field millisecond pulsar (MSP) population to infer its intrinsic distribution in spin period and luminosity and to determine its spatial distribution within the Galaxy. Our likelihood analysis on data from extant surveys (22 pulsars with periods less than 20 ms) accounts for the following important selection effects: (1) the survey sensitivity as a function of direction, spin period, and sky coverage; (2) interstellar scintillation, which modulates the pulsed flux and causes a net increase in search volume of ~30% and (3) errors in the pulsar distance scale. Adopting power-law models (with cutoffs) for the intrinsic distributions, the analysis yields a minimum-period cutoff Pmin > 0.65 ms (99% confidence), a period distribution proportional to P-2.0+/-0.33, and a pseudoluminosity distribution proportional to L^{-2.0+/-0.2}p (where Lp is the product of the flux density and the square of the distance, for Lp >= 1.1 mJy kpc2). We find that the column density of MSPs (uncorrected for beaming effects) is ~50^{+30}_{-20} kpc-2 in the vicinity of the solar system. For a Gaussian model, the z scale height is 0.65^{+0.16}_{-0.12} kpc, corresponding to the local number density 29^{+17}_{-11} kpc-3. (For an exponential model, the scale height becomes 0.50^{+0.19}_{-0.13} kpc, and the number density 44^{+25}_{-16} kpc-3.) Estimates of the total number of MSPs in the disk of the Galaxy and for the associated birthrate are given. The contribution of a diffuse halo-like component (tracing the Galactic spheroid, the halo, or the globular cluster density profile) to the local number density of MSPs is limited to <~1% of the midplane value. We consider a kinematic model for the MSP spatial distribution in which objects in the disk are kicked once at birth and then orbit in a smooth Galactic potential, becoming dynamically well-mixed. The analysis yields a column density 49^{+27}_{-17} kpc-2 (comparable to the above), a birth z kick velocity 52^{+17}_{-11} km s-1, and a three-dimensional velocity dispersion of ~84 km s-1. MSP velocities are smaller than those of young, long-period pulsars by about a factor of 5. The kinematic properties of the MSP population are discussed, including expected transverse motions, the occurrence of asymmetric drift, the shape of the velocity ellipsoid, and the z scale height at birth. If MSPs are long-lived, then a significant contribution to observed MSP z velocities is the result of diffusive processes that increase the scale height of old stellar populations; our best estimate of the one-dimensional velocity kick that is unique to MSP evolution is ~40 km s-1 if such diffusion is taken into account. The scale heights of millisecond pulsars and low-mass X-ray binaries are consistent, suggesting a common origin and that the primary channel for forming both classes of objects imparts only low velocities. Binaries involving a common envelope phase and a neutron star--forming supernova explosion can yield such objects, even with explosion asymmetries like those needed to provide the velocity distribution of isolated, nonspun-up radio pulsars. Future searches for MSPs may be optimized using the model results. As an example, we give the expected number of detectable MSPs per beam area and the volumes of the Galaxy sampled per beam area for a hypothetical Green Bank Telescope all sky survey. Estimates for the volume that must be surveyed to find a pulsar faster than 1.5 ms are given. We also briefly discuss how selection effects associated with fast binaries influence our results.

Cordes, J. M.; Chernoff, David F.

1997-06-01

138

Noise induced stabilization in population dynamics

NASA Astrophysics Data System (ADS)

We investigate a model where strong noise in a sub-population creates a metastable state in an otherwise unstable two-population system. The induced metastable state is vortex-like, and its persistence time grows exponentially with the noise strength. A variety of distinct scaling relations are observed depending on the relative strength of the sub-population noises.

Kamenev, Alex

2012-02-01

139

In the present study, a comprehensive population balance model is developed to predict the dynamic evolution of the particle size distribution in high hold-up (e.g., 40%) non-reactive liquid–liquid dispersions and reactive liquid(solid)–liquid suspension polymerization systems. Semiempirical and phenomenological expressions are employed to describe the breakage and coalescence rates of dispersed monomer droplets in terms of the type and concentration of

Costas Kotoulas; Costas Kiparissides

2006-01-01

140

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

2010-09-29

141

Multiple attractors, saddles, and population dynamics in periodic habitats

Mathematical models predict that a population which oscillates in the absence of time-dependent factors can develop multiple\\u000a attracting final states in the advent of periodic forcing. A periodically-forced, stage-structured mathematical model predicted\\u000a the transient and asymptotic behaviors of Tribolium (flour beetle) populations cultured in periodic habitats of fluctuating flour volume. Predictions included multiple (2-cycle)\\u000a attractors, resonance and attenuation phenomena, and

Shandelle M. Henson; R. F. Costantino; J. M. Cushing; Brian Dennis; Robert A. Desharnais

1999-01-01

142

Evolution of specialization under non-equilibrium population dynamics.

We analyze the evolution of specialization in resource utilization in a mechanistically underpinned discrete-time model using the adaptive dynamics approach. We assume two nutritionally equivalent resources that in the absence of consumers grow sigmoidally towards a resource-specific carrying capacity. The consumers use resources according to the law of mass-action with rates involving trade-off. The resulting discrete-time model for the consumer population has over-compensatory dynamics. We illuminate the way non-equilibrium population dynamics affect the evolutionary dynamics of the resource consumption rates, and show that evolution to the trimorphic coexistence of a generalist and two specialists is possible due to asynchronous non-equilibrium population dynamics of the specialists. In addition, various forms of cyclic evolutionary dynamics are possible. Furthermore, evolutionary suicide may occur even without Allee effects and demographic stochasticity. PMID:23306058

Nurmi, Tuomas; Parvinen, Kalle

2013-01-07

143

Population dynamics of Yellowstone grizzly bears

Data on the population of grizzly bears in the environs of Yellowstone National Park suggest that the population has not recovered from the reductions following closure of garbage dumps in 1970 and 1971, and may continue to decline. A computer simulation model indicates that the risk of extirpation over the next 30 yr is small, if the present population parameters continue to prevail. A review an further analysis of the available data brings out the importance of enhancing adult female survival if the population is to recover, and assesses various research needs. In particular, a reliable index of population trend is needed to augment available data on the population. 12 references, 9 figures, 6 tables.

Knight, R.R.; Eberhardt, L.L.

1985-04-01

144

Predictability of human EEG: a dynamical approach

The electroencephalogram recordings from human scalp are analysed in the framework of recent methods of nonlinear dynamics. Three stages of brain activity are considered: the alpha waves (eyes closed), the deep sleep (stage four) and the Creutzfeld-Jakob coma. Two dynamical parameters of the attractors are evaluated. These are the Lyapunov exponents, which measure the divergence or convergence of trajectories in

D. Gallez; A. Babloyantz

1991-01-01

145

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

146

On Population Structure and Marriage Dynamics

I develop an equilibrium, two-sided search model of marriage with endogenous population growth to study the interaction between fertility, the age structure of the population and the age at first marriage of men and women. Within a simple two-period overlapping generation model I show that, given an increase of the desired number of children, age at marriage is affected through

Eugenio P. Giolito

2010-01-01

147

Predictability of population displacement after the 2010 Haiti earthquake

Most severe disasters cause large population movements. These movements make it difficult for relief organizations to efficiently reach people in need. Understanding and predicting the locations of affected people during disasters is key to effective humanitarian relief operations and to long-term societal reconstruction. We collaborated with the largest mobile phone operator in Haiti (Digicel) and analyzed the movements of 1.9 million mobile phone users during the period from 42 d before, to 341 d after the devastating Haiti earthquake of January 12, 2010. Nineteen days after the earthquake, population movements had caused the population of the capital Port-au-Prince to decrease by an estimated 23%. Both the travel distances and size of people’s movement trajectories grew after the earthquake. These findings, in combination with the disorder that was present after the disaster, suggest that people’s movements would have become less predictable. Instead, the predictability of people’s trajectories remained high and even increased slightly during the three-month period after the earthquake. Moreover, the destinations of people who left the capital during the first three weeks after the earthquake was highly correlated with their mobility patterns during normal times, and specifically with the locations in which people had significant social bonds. For the people who left Port-au-Prince, the duration of their stay outside the city, as well as the time for their return, all followed a skewed, fat-tailed distribution. The findings suggest that population movements during disasters may be significantly more predictable than previously thought.

Lu, Xin; Bengtsson, Linus; Holme, Petter

2012-01-01

148

Predictability of population displacement after the 2010 Haiti earthquake.

Most severe disasters cause large population movements. These movements make it difficult for relief organizations to efficiently reach people in need. Understanding and predicting the locations of affected people during disasters is key to effective humanitarian relief operations and to long-term societal reconstruction. We collaborated with the largest mobile phone operator in Haiti (Digicel) and analyzed the movements of 1.9 million mobile phone users during the period from 42 d before, to 341 d after the devastating Haiti earthquake of January 12, 2010. Nineteen days after the earthquake, population movements had caused the population of the capital Port-au-Prince to decrease by an estimated 23%. Both the travel distances and size of people's movement trajectories grew after the earthquake. These findings, in combination with the disorder that was present after the disaster, suggest that people's movements would have become less predictable. Instead, the predictability of people's trajectories remained high and even increased slightly during the three-month period after the earthquake. Moreover, the destinations of people who left the capital during the first three weeks after the earthquake was highly correlated with their mobility patterns during normal times, and specifically with the locations in which people had significant social bonds. For the people who left Port-au-Prince, the duration of their stay outside the city, as well as the time for their return, all followed a skewed, fat-tailed distribution. The findings suggest that population movements during disasters may be significantly more predictable than previously thought. PMID:22711804

Lu, Xin; Bengtsson, Linus; Holme, Petter

2012-06-18

149

Prediction in Dynamic Environments via Identification of Critical Time Points

PRIDE (PRediction In Dynamic Environments) is a hierarchical multi-resolutional framework that incorporates multiple prediction algorithms to enable navigation of autonomous vehicles in real-life, on-road traffic situations. At the lower levels, we utilize estimation theoretic short-term (ST) predictions via an extended Kalman filter-based algorithm using sensor data to predict the future location of moving objects with an associated confidence measure. At

Z. Kootbally; R. Madhavan; C. Schlenoff

2006-01-01

150

Linking intraspecific variation in plant traits to ecosystem carbon uptake may allow us to better predict how shift in populations shape ecosystem function. We investigated whether plant populations of a dominant old-field plant species (Solidago altissima) differed in carbon dynamics and if variation in plant traits among genotypes and between populations predicted carbon dynamics. We established a common garden experiment with 35 genotypes from three populations of S. altissima from either Tennessee (southern populations) or Connecticut (northern populations) to ask whether: (1) southern and northern Solidago populations will differ in aboveground productivity, leaf area, flowering time and duration, and whole ecosystem carbon uptake, (2) intraspecific trait variation (growth and reproduction) will be related to intraspecific variation in gross ecosystem CO2 exchange (GEE) and net ecosystem CO2 exchange (NEE) within and between northern and southern populations. GEE and NEE were 4.8× and 2× greater in southern relative to northern populations. Moreover, southern populations produced 13× more aboveground biomass and 1.4× more inflorescence mass than did northern populations. Flowering dynamics (first- and last-day flowering and flowering duration) varied significantly among genotypes in both the southern and northern populations, but plant performance and ecosystem function did not. Both productivity and inflorescence mass predicted NEE and GEE between S. altissima southern and northern populations. Taken together, our data demonstrate that variation between S. altissima populations in performance and flowering traits are strong predictors of ecosystem function in a dominant old-field species and suggest that populations of the same species might differ substantially in their response to environmental perturbations.

Breza, Lauren C; Souza, Lara; Sanders, Nathan J; Classen, Aimee T

2012-01-01

151

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

152

Dynamic Targets for Stock Market Prediction

Features from the Saudi Stock Market (SSM) have been examined to attempt to predict the direction of daily price changes. Backpropagation neural network has been applied to predict the direction of price changes for the listed stocks in SSM. The price change in SSM ranges between -10% and 10%. The target has a representation of three classes 1, -1 and

Abdullah Al-Luhaib; Khaled Al-Ghoneim; Y. Al-Ohali

2007-01-01

153

Complex population dynamics and the coalescent under neutrality.

Estimates of the coalescent effective population size N(e) can be poorly correlated with the true population size. The relationship between N(e) and the population size is sensitive to the way in which birth and death rates vary over time. The problem of inference is exacerbated when the mechanisms underlying population dynamics are complex and depend on many parameters. In instances where nonparametric estimators of N(e) such as the skyline struggle to reproduce the correct demographic history, model-based estimators that can draw on prior information about population size and growth rates may be more efficient. A coalescent model is developed for a large class of populations such that the demographic history is described by a deterministic nonlinear dynamical system of arbitrary dimension. This class of demographic model differs from those typically used in population genetics. Birth and death rates are not fixed, and no assumptions are made regarding the fraction of the population sampled. Furthermore, the population may be structured in such a way that gene copies reproduce both within and across demes. For this large class of models, it is shown how to derive the rate of coalescence, as well as the likelihood of a gene genealogy with heterochronous sampling and labeled taxa, and how to simulate a coalescent tree conditional on a complex demographic history. This theoretical framework encapsulates many of the models used by ecologists and epidemiologists and should facilitate the integration of population genetics with the study of mathematical population dynamics. PMID:22042576

Volz, Erik M

2011-10-31

154

Complex Population Dynamics and the Coalescent Under Neutrality

Estimates of the coalescent effective population size Ne can be poorly correlated with the true population size. The relationship between Ne and the population size is sensitive to the way in which birth and death rates vary over time. The problem of inference is exacerbated when the mechanisms underlying population dynamics are complex and depend on many parameters. In instances where nonparametric estimators of Ne such as the skyline struggle to reproduce the correct demographic history, model-based estimators that can draw on prior information about population size and growth rates may be more efficient. A coalescent model is developed for a large class of populations such that the demographic history is described by a deterministic nonlinear dynamical system of arbitrary dimension. This class of demographic model differs from those typically used in population genetics. Birth and death rates are not fixed, and no assumptions are made regarding the fraction of the population sampled. Furthermore, the population may be structured in such a way that gene copies reproduce both within and across demes. For this large class of models, it is shown how to derive the rate of coalescence, as well as the likelihood of a gene genealogy with heterochronous sampling and labeled taxa, and how to simulate a coalescent tree conditional on a complex demographic history. This theoretical framework encapsulates many of the models used by ecologists and epidemiologists and should facilitate the integration of population genetics with the study of mathematical population dynamics.

Volz, Erik M.

2012-01-01

155

Mapping Genes that Predict Treatment Outcome in Admixed Populations

There is great interest in characterizing the genetic architecture underlying drug response. For many drugs, gene-based dosing models explain a considerable amount of the overall variation in treatment outcome. As such, prescription drug labels are increasingly being modified to contain pharmacogenetic information. Genetic data must, however, be interpreted within the context of relevant clinical covariates. Even the most predictive models improve with the addition of data related to biogeographical ancestry. The current review explores analytical strategies that leverage population structure to more fully characterize genetic determinants of outcome in large clinical practice-based cohorts. The success of this approach will depend upon several key factors: (1) the availability of outcome data from groups of admixed individuals (i.e., populations recombined over multiple generations), (2) a measurable difference in treatment outcome (i.e., efficacy and toxicity endpoints), and (3) a measurable difference in allele frequency between the ancestral populations.

Baye, Tesfaye M.; Wilke, Russell A.

2010-01-01

156

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

157

The Population of Helium-merger Progenitors: Observational Predictions

NASA Astrophysics Data System (ADS)

The helium-merger gamma-ray burst (GRB) progenitor is produced by the rapid accretion onto a compact remnant (neutron star or black hole) when it undergoes a common envelope inspiral with its companion's helium core. This merger phase produces a very distinct environment around these outbursts and recent observations suggest that, in some cases, we are detecting the signatures of the past merger in the GRB afterglow. These observations allow us, for the first time, to study the specific features of the helium-merger progenitor. In this paper, we couple population synthesis calculations to our current understanding of GRB engines and common envelope evolution to make observational predictions for the helium-merger GRB population. Many mergers do not produce GRB outbursts and we discuss the implications of these mergers with the broader population of astrophysical transients.

Fryer, Chris L.; Belczynski, Krzysztof; Berger, Edo; Thöne, Christina; Ellinger, Carola; Bulik, Tomasz

2013-02-01

158

PC BEEPOP - A PERSONAL COMPUTER HONEY BEE POPULATION DYNAMICS MODEL

PC BEEPOP is a computer model that simulates honey bee (Apis mellifera L.) colony population dynamics. he model consists of a system of interdependent elements, including colony condition, environmental variability, colony energetics, and contaminant exposure. t includes a mortal...

159

Predicting Random Effects with an Expanded Finite Population Mixed Model

Prediction of random effects is an important problem with expanding applications. In the simplest context, the problem corresponds to prediction of the latent value (the mean) of a realized cluster selected via two-stage sampling. Recently, Stanek and Singer (JASA, 2004) developed best linear unbiased predictors (BLUP) under a finite population mixed model that outperform BLUPs from mixed models and superpopulation models. Their setup, however, does not allow for unequally sized clusters. To overcome this drawback, we consider an expanded finite population mixed model based on a larger set of random variables that span a higher dimensional space than those typically applied to such problems. We show that BLUPs for linear combinations of the realized cluster means derived under such a model have considerably smaller mean squared error (MSE) than those obtained from mixed models, superpopulation models, and finite population mixed models. We motivate our general approach by an example developed for two-stage cluster sampling and show that it faithfully captures the stochastic aspects of sampling in the problem. We also consider simulation studies to illustrate the increased accuracy of the BLUP obtained under the expanded finite population mixed model.

Stanek, Edward J.; Singer, Julio M.

2008-01-01

160

Dynamics and Predictability of Hurricane Dolly (2008)

NASA Astrophysics Data System (ADS)

Through several cloud-resolving simulations with the Weather Research and Forecast (WRF-ARW) model, this study examines the dynamics and predictability of Hurricane Dolly (2008) with an emphasis on its initial development (around the time being declared as a tropical storm) and subsequent rapid intensification entering into the Gulf of Mexico. These WRF simulations include three that are directly initialized with the operational NCEP GFS analyses at 06, 12 and 18Z 20 July 2008, respectively (EXP06, EXP12, EXP18) and another the same as EXP06 except that the airborne Doppler velocity observations by a NOAA P3 aircraft during 12-15Z are assimilated with an ensemble-Kalman filter (ENKF06). Among the four experiments, only EXP06 fails to capture the rapid intensification and fails to develop the tropical storm into a mature hurricane. Preliminary comparison between the simulated fields of EXP06 and the GFS analysis at 12Z (e.g., IC of EXP12) indicates that large scale features favorable to the tropical cyclogenesis cannot be properly simulated in EXP06. The initial disturbance is rather weak positioned too far south-west that is far away from the primary convective. However, after the airborne radar data during 12-15Z are assimilated into the model, (from EXP06 into ENKF06), the ENKF06 simulation is greatly improved in that a well-organized warm-core vortex appears at the low level right after radar assimilation, which subsequently developed into a hurricane consistent with timing, track and intensity of observations. Interestingly, there are significant differences in the initial vortex position, structure and evolution among the three simulations (EXP12, EXP18, ENKF06) that all eventually develop a mature hurricane along the observed track (before landfall) with right timing after enters into the Gulf of Mexico. At 18Z 20 July, there is no apparent initial low-level cyclonic vortex in EXP12 and EXP18 (that is assimilated into ENKF06 due to radar observations). However, in both cases, a mesoscale vortex at the mid level apparently induced by the convection tends to induce a cyclonic circulation at the low level after several hours' adjustment which eventually leads to the development of the hurricane similar to that simulated in ENKF06 (and to observations). This result implies that, under favorable conditions for tropical development and rapid intensification, the exact route to tropical cyclogenesis, either top-down or bottom-up, may be of secondary importance. Nevertheless, prior to the rapid intensification, all three experiments produce abundant convection (VHTs) near the center of the TC circulation. As soon as one or a few VHTs appear right at the center of the low-level cyclonic circulation, rapid intensification of the tropical cyclone is followed. We are currently examining potential dominating factors in controlling the near- synchronous rapid development at similar location among the three simulations with significantly different initial circulations.

Fang, J.; Zhang, F.; Weng, Y.

2008-12-01

161

Can neural responses of a small group of individuals predict the behavior of large-scale populations? In this investigation, brain activations were recorded while smokers viewed three different television campaigns promoting the National Cancer Institute's telephone hotline to help smokers quit (1-800-QUIT-NOW). The smokers also provided self-report predictions of the campaigns' relative effectiveness. Population measures of the success of each campaign were computed by comparing call volume to 1-800-QUIT-NOW in the month before and the month after the launch of each campaign. This approach allowed us to directly compare the predictive value of self-reports with neural predictors of message effectiveness. Neural activity in a medial prefrontal region of interest, previously associated with individual behavior change, predicted the population response, whereas self-report judgments did not. This finding suggests a novel way of connecting neural signals to population responses that has not been previously demonstrated and provides information that may be difficult to obtain otherwise. PMID:22510393

Falk, Emily B; Berkman, Elliot T; Lieberman, Matthew D

2012-04-17

162

Can neural responses of a small group of individuals predict the behavior of large-scale populations? In this investigation, brain activations were recorded while smokers viewed three different television campaigns promoting the National Cancer Institute’s telephone hotline to help smokers quit (1-800-QUIT-NOW). The smokers also provided self-report predictions of the campaigns’ relative effectiveness. Population measures of the success of each campaign were computed by comparing call volume to 1-800-QUIT-NOW in the month before and the month after the launch of each campaign. This approach allowed us to directly compare the predictive value of self-reports with neural predictors of message effectiveness. Neural activity in a medial prefrontal region of interest, previously associated with individual behavior change, predicted the population response, whereas self-report judgments did not. This finding suggests a novel way of connecting neural signals to population responses that has not been previously demonstrated and provides information that may be difficult to obtain otherwise.

Falk, Emily B.; Berkman, Elliot T.; Lieberman, Matthew D.

2013-01-01

163

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 Me˙er; Michael C. Scholl; Ryan Johnson; Shannon O'Brien; Herman Oosthuizen; Stephan Swanson; Deon Kotze; Michael Paterson

2005-01-01

164

Microbial population dynamics on seeds during drum and steeping priming

In the UK, seeds are primed commercially via drum or steeping priming processes to improve seed germination and seedling establishment but the microbial population dynamics occurring during these processes are unknown. Consequently, changes in culturable bacterial and fungal populations that occurred during laboratory and commercial scale drum priming of carrot, leek and parsnip seed and during laboratory scale and commercial

B. Wright; H. Rowse; J. M. Whipps

2003-01-01

165

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

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

2010-01-01

166

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...

167

Understanding the processes generating fluctuations of natural populations lies at the very heart of academic ecology. It is also very important for applications such as fisheries management and pest control. We are interested in the effect of harvesting on population fluctuations and for that purpose we develop and analyze an age-structured model where recruitment is a stochastic process and the adult segment of the population is harvested. When a constant annual harvest is taken the coefficient of variation of the adult population increases for most parameter values due to the age truncation effect, i.e. an increased variability in a juvenescent population due to the removal of older individuals. However, if a constant proportion of the adults is harvested the age truncation effect is sometimes counteracted by a stabilizing dynamic effect of harvesting. Depending on parameter values mirroring different life histories, proportional harvest can either increase or decrease the relative fluctuations of an exploited population. When there is a demographic Allee effect the ratio of juveniles to adults may actually decrease with harvesting. We conclude that, depending on life history and harvest strategy, harvesting can either reinforce or dampen population fluctuations due to the relative importance of stabilizing dynamic effects and the age truncation effect. The strength of the latter is highly dependent on the fished population's endogenous, age-structured dynamics. More specifically, we predict that populations with strong and positively autocorrelated dynamics will show stronger age truncation effect, a testable prediction that offers a simple rule-of-thumb assessment of a population's vulnerability to exploitation. PMID:22227065

Wikström, Anders; Ripa, Jörgen; Jonzén, Niclas

2011-12-27

168

Knee Joint Dynamics Predict Patellar Tendinitis in Elite Volleyball Players

We quantified the lower extremity dynamics developed during the volleyball spike and block jumps to find out if predictive relations exist between jump dynamics and patellar tendinitis. Lower extremity movement biome chanics were analyzed for 10 members of the 1994 Canadian Men's National Volleyball Team (all right- handed hitters). Based on physical examination, 3 of the 10 players had patellar

David P. Richards; Stanley V. Ajemian; J. Preston Wiley; Ronald F. Zernicke

1996-01-01

169

Guarded execution and branch prediction in dynamic ILP processors

We evaluate the effects of guarded (or conditional, or predicated) execution on the performance of an instruction level parallel processor employing dynamic branch prediction. First, we assess the utility of guarded execution, both qualitatively and quantitatively, using a variety of application programs. Our assessment shows that guarded execution significantly increases the opportunities, for both compiler and dynamic hardware, to extract

Dionisios N. Pnevmatikatos; Gurindar S. Sohi

1994-01-01

170

Necessary and sufficient conditions for the occurrence of generalized synchronization of unidirectionally coupled dynamical systems are given in terms of asymptotic stability. The relation between generalized synchronization, predictability, and equivalence of dynamical systems is discussed. All theoretical results are illustrated by analytical and numerical examples. In particular, the existence of generalized synchronization in the case of parameter mismatch between coupled

L. Kocarev; U. Parlitz

1996-01-01

171

Prediction and analysis of human motion dynamics performing various tasks

Several digital human softwares have shown the capabilities of simulating simple reach motions. However, predicting the dynamic effects on human motion due to different task loads is still immature. This paper presents an optimisation-based algorithm for simulating the dynamic motion of a digital human. The hypothesis is that human performance measures such as the total energy consumption governs human motion;

Joo H. Kim; Karim Abdel Malek; Jingzhou Yang; R. Timothy Marler

2006-01-01

172

Generalized modeling of ecological population dynamics

Over the past years several authors have used the approach of generalized modeling to study the dynamics of food chains and food webs. Generalized models come close to the efficiency of random matrix models, while being as directly interpretable as conventional differential-equation-based models. Here we present a pedagogical introduction to the approach of generalized modeling. This introduction places more emphasis

Justin D. Yeakel; Dirk Stiefs; Mark Novak; Thilo Gross

2010-01-01

173

Modeling population dynamics and conservation of arapaima in the Amazon

To promote understanding of fish population dynamics in tropical river-floodplains, we have synthesized existing information\\u000a by developing a largely empirical population model for arapaima (Arapaima sp.). Arapaima are characterized by very large bodies, relatively late sexual maturity, small clutches, and large parental\\u000a investment per offspring, and their populations are overexploited and even declining due to overfishing. We used unparalleled\\u000a time

L. CastelloD; D. J. Stewart; C. C. Arantes

174

Population dynamics with or without evolution: a physicist's approach

NASA Astrophysics Data System (ADS)

Modeling the dynamics of interacting species (or populations) is a long standing problem in sciences which, in the recent years, has attracted a lot of physicists working in statistical physics. The similarities and differences between models of dynamics of population and usual statistical mechanics problems on a lattice are discussed. First the question of the appropriate level of description (ordinary differential equations, reaction-diffusion equations, patches models or individual-based models for extended systems) is considered. Second, the role of the internal degrees of freedom associated to the phenotype of the individuals on the dynamics is discussed.

Droz, Michel; Pe?alski, Andrzej

2004-05-01

175

The population dynamics of the enchytraeid Cognettia sphagnetorum originating from an unmanaged forest (FP), a clear-cut area (CCP) or a plot treated with birch ash (APP) and the effects of population origin on labile C and N dynamics were investigated. Twenty individuals of C. sphagnetorum were introduced in microcosms containing humus from the unmanaged forest devoid of enchytraeids and amended

Jouni K. Nieminen; Jari Haimi

2010-01-01

176

Dynamic knee loads during gait predict proximal tibial bone distribution

This study tested the validity of the prediction of dynamic knee loads based on gait measurements. The relationship between the predicted loads at the knee and the distribution of bone between the medial and lateral sides of the tibia was examined. The motion and external forces and moments at the knee were measured during gait and a statically determinate muscle

Debra E. Hurwitz; Dale R. Sumner; Thomas P. Andriacchi; David A. Sugar

1998-01-01

177

Noise-Induced Stabilization in Population Dynamics

NASA Astrophysics Data System (ADS)

We investigate a model in which strong noise in a subpopulation creates a metastable state in an otherwise unstable two-population system. The induced metastable state is vortexlike, and its persistence time grows exponentially with the noise strength. A variety of distinct scaling relations are observed depending on the relative strength of the subpopulation noises.

Parker, Matthew; Kamenev, Alex; Meerson, Baruch

2011-10-01

178

Generalized modeling of ecological population dynamics

Over the past 7 years, several authors have used the approach of generalized modeling to study the dynamics of food chains\\u000a and food webs. Generalized models come close to the efficiency of random matrix models, while being as directly interpretable\\u000a as conventional differential-equation-based models. Here, we present a pedagogical introduction to the approach of generalized\\u000a modeling. This introduction places more emphasis

Justin D. Yeakel; Dirk Stiefs; Mark Novak; Thilo Gross

2011-01-01

179

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

180

Dynamics of single-species population growth: stability or chaos

We have examined stability at the carrying capacity for 25 genetically different populations of Drosophila melanogaster. In spite of their genetic heterogeneity, 20 of the populations yield stable equilibria and none have eigenvalues significantly greater than one. Computer simulations demonstrate how selection at the individual level may account for population stability (and, hence, that group selection is not necessary for the evolution of stability). Recent theoretical studies on density-dependent selection in random environments provide predictions consistent with our empirical findings.

Mueller, L.D.; Ayala, F.J.

1981-01-01

181

QT Interval Prolongation Predicts Cardiovascular Mortality inan Apparently Healthy Population

Background. Inmyocardial infarction patients, heart rate-adjusted QT interval (QT), an electrocardiographic indicator ofsympathetic balance, isprognostic forsurvival. Methods andResults. Ina 28-year follow-up, theassociation betweenQT,andall-cause, cardiovascular, andischemic heartdisease mortality was studied ina population of3,091 apparently healthy Dutchcivil servants andtheir spouses,aged40-65 years,whoparticipated ina medical examination during 1953-1954. Moderate (QTc, 420-440 msec)andextensive (QTc, more than440msec)QTcprolongations significantly predict all-cause mortality during thefirst 15yearsamong men (adjusted

Evert G. Schouten; Jacqueline M. Dekker; Peter Meppelink; Frans J. Kok

2010-01-01

182

Predicting urinary tract infections in a urogynecology population.

A retrospective chart review was performed on all new patients presenting to a urogynecology clinic. Urine dipsticks, symptoms, and cultures were evaluated to identify urinary tract infections. The most sensitive result was for the combination of nitrites or leukocytes (59%) without significant change in specificity (95%) for either result individually. The addition of the statistically significant symptoms did not improve the outcome. Based on these findings, it was determined that no combination of dipstick and/or symptoms adequately predicted an infection to the point that a recommendation to dispense with the need for a culture in this urogynecology population could be made. PMID:18335699

Kuklinski, Deborah; Koduri, Sumana

2008-02-01

183

Improving structure-based function prediction using molecular dynamics

Summary The number of molecules with solved three-dimensional structure but unknown function is increasing rapidly. Particularly problematic are novel folds with little detectable similarity to molecules of known function. Experimental assays can determine the functions of such molecules, but are time-consuming and expensive. Computational approaches can identify potential functional sites; however, these approaches generally rely on single static structures and do not use information about dynamics. In fact, structural dynamics can enhance function prediction: we coupled molecular dynamics simulations with structure-based function prediction algorithms that identify Ca2+ binding sites. When applied to 11 challenging proteins, both methods showed substantial improvement in performance, revealing 22 more sites in one case and 12 more in the other, with a modest increase in apparent false positives. Thus, we show that treating molecules as dynamic entities improves the performance of structure-based function prediction methods.

Glazer, Dariya S.; Radmer, Randall J.; Altman, Russ B.

2009-01-01

184

Bidirectional Dynamics for Protein Secondary Structure Prediction

Connectionist models for learning in sequential domains are typically dynamical systems that use hidden states to store contextual\\u000a information. In principle, these models can adapt to variable time lags and perform complex sequential mappings. In spite\\u000a of several successful applications (mostly based on hidden Markov models), the general class of sequence learning problems\\u000a is still far from being satisfactorily solved.

Pierre Baldi; Sřren Brunak; Paolo Frasconi; Gianluca Pollastri; Giovanni Soda

185

Correlations and population dynamics in cortical networks.

The function of cortical networks depends on the collective interplay between neurons and neuronal populations, which is reflected in the correlation of signals that can be recorded at different levels. To correctly interpret these observations it is important to understand the origin of neuronal correlations. Here we study how cells in large recurrent networks of excitatory and inhibitory neurons interact and how the associated correlations affect stationary states of idle network activity. We demonstrate that the structure of the connectivity matrix of such networks induces considerable correlations between synaptic currents as well as between subthreshold membrane potentials, provided Dale's principle is respected. If, in contrast, synaptic weights are randomly distributed, input correlations can vanish, even for densely connected networks. Although correlations are strongly attenuated when proceeding from membrane potentials to action potentials (spikes), the resulting weak correlations in the spike output can cause substantial fluctuations in the population activity, even in highly diluted networks. We show that simple mean-field models that take the structure of the coupling matrix into account can adequately describe the power spectra of the population activity. The consequences of Dale's principle on correlations and rate fluctuations are discussed in the light of recent experimental findings. PMID:18439141

Kriener, Birgit; Tetzlaff, Tom; Aertsen, Ad; Diesmann, Markus; Rotter, Stefan

2008-09-01

186

Quantifying the dynamics of the early stages in the life cycle of mangroves is essential to predict the distribution, species composition and structure of mangrove forests, and their maintenance and recovery from perturbations. The growth and population dynamics of two stands of the mangrove Kandelia candel in Halong Bay (Viet Nam) were examined for 1 year. Growth was highly seasonal,

Hoang Thi Ha; Carlos M. Duarte; Nguyen Hoang Tri; Jorge Terrados; Jens Borum

2003-01-01

187

Life span correlates with population dynamics in perennial herbaceous plants.

Survival and fecundity are basic components of demography and therefore have a strong influence on population dynamics. These two key parameters and their relationship are crucial to understand the evolution of life histories. It remains, however, to be empirically established how life span, fecundity, and population dynamics are linked in different organism groups. We conducted a comparative study based on demographic data sets of 55 populations of 23 perennial herbs for which structured demographic models and among-year natural variation in demographic attributes were available. Life span (from 4 to 128 yr old), estimated by using an algorithm, was inversely correlated with the deviance of the population growth rate from equilibrium as well as with among-year population fluctuations. Temporal variability was greater for short-lived species than for the long-lived ones because fecundity was more variable than survival and relatively more important for population dynamics for the short-lived species. The relationship between life span and population stability suggests that selection for longevity may have played an important role in the life history evolution of plants because of its ability to buffer temporal fluctuations in population size. PMID:21632350

García, María B; Picó, F Xavier; Ehrlén, Johan

2008-02-01

188

NASA Astrophysics Data System (ADS)

The galactic field's late-type stellar single and binary populations are calculated on the observationally well-constrained supposition that all stars form as binaries with invariant properties in discrete star formation events. A recently developed tool (Marks, Kroupa & Oh) is used to evolve the binary star distributions in star clusters for a few million years until an equilibrium situation is achieved which has a particular mixture of single and binary stars. On cluster dissolution the population enters the galactic field with these characteristics. The different contributions of single stars and binaries from individual star clusters, which are selected from a power-law-embedded star cluster mass function, are then added up. This gives rise to integrated galactic field binary distribution functions (IGBDFs), resembling a galactic field's stellar content (dynamical population synthesis). It is found that the binary proportion in the galactic field of a galaxy is larger the lower the minimum cluster mass, Mecl, min, the lower the star formation rate, SFR, the steeper the embedded star cluster mass function (described by index ?) and the larger the typical size of forming star clusters in the considered galaxy. In particular, period, mass ratio and eccentricity IGBDFs for the Milky Way (MW) are modelled using Mecl, min= 5 M?, SFR = 3 M? yr-1 and ?= 2 which are justified by observations. For rh? 0.1-0.3 pc, the half-mass radius of an embedded cluster, the aforementioned theoretical IGBDFs agree with independently observed distributions, suggesting that the individual discrete star formation events in the MW generally formed compact star clusters. Of all late-type binaries, 50 per cent stem from Mecl? 300 M? clusters, while 50 per cent of all single stars were born in Mecl? 104 M? clusters. Comparison of the G-dwarf and M-dwarf binary populations indicates that the stars are formed in mass-segregated clusters. In particular, it is pointed out that although in the present model all M-dwarfs are born in binary systems, in the MW's Galactic field the majority ends up being single stars. This work predicts that today's binary frequency in elliptical galaxies is lower than that in spiral and dwarf galaxies. The period and mass-ratio distributions in these galaxies are explicitly predicted.

Marks, Michael; Kroupa, Pavel

2011-11-01

189

Dynamical recurrent neural networks towards prediction and modeling of dynamical systems

This paper addresses the use of dynamical recurrent neural networks (DRNN) for time series prediction and modeling of small dynamical systems. Since the recurrent synapses are represented by finite impulse response (FIR) filters, DRNN are state-based connectionist models in which all hidden units act as state variables of a dynamical system. The model is trained with temporal recurrent backprop (TRBP),

Alex Aussem

1999-01-01

190

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

191

Population dynamical parameters of Trichuris trichiura infections in children were estimated from longitudinal intensity and prevalence data from a population (n = 23) in a children's home in Jamaica. The theoretical predictions of a deterministic model incorporating these parameters were approximated to observed horizontal-age prevalence data from a naturally infected population (n = 203) of children in a St. Lucian village, and a rough estimate of the basic reproductive rate (Ro = 8-10) of T. trichiura obtained. The findings suggest that T. trichiura populations are intrinsically more difficult to control by traditional mass-treatment chemotherapy (eradication requires greater than 91% of the population to be treated every 6 months for greater than 5 years) than are populations of Ascaris, but may be more susceptible to selective chemotherapy programmes which aim to treat only the most heavily infected individuals. PMID:3832488

Bundy, D A; Thompson, D E; Cooper, E S; Golden, M H; Anderson, R M

1985-01-01

192

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

193

Unstable dynamics and population limitation in mountain hares.

The regular large-scale population fluctuations that characterize many species of northern vertebrates have fascinated ecologists since the time of Charles Elton. There is still, however, no clear consensus on what drives these fluctuations. Throughout their circumpolar distribution, mountain hares Lepus timidus show regular and at times dramatic changes in density. There are distinct differences in the nature, amplitude and periodicity of these fluctuations between regions and the reasons for these population fluctuations and the geographic differences remain largely unknown. In this review we synthesize knowledge on the factors that limit or regulate mountain hare populations across their range in an attempt to identify the drivers of unstable dynamics. Current knowledge of mountain hare population dynamics indicates that trophic interactions--either predator-prey or host-parasite--appear to be the major factor limiting populations and these interactions may contribute to the observed unstable dynamics. There is correlative and experimental evidence that some mountain hare populations in Fennoscandia are limited by predation and that predation may link hare and grouse cycles to microtine cycles. Predation is unlikely to be important in mountain hare populations in Scotland as most hares occur on sporting estates where predators are controlled, but this hypothesis remains to be experimentally tested. There is, however, emerging experimental evidence that some Scottish mountain hare populations are limited by parasites and that host-parasite interactions contribute to unstable dynamics. By contrast, there is little evidence from Fennoscandia that parasitism is of any importance to mountain hare population dynamics, although disease may cause periodic declines. Although severe weather and food limitation may interact to cause periodic high winter mortality there is little evidence that food availability limits mountain hare populations. There is a paucity of information concerning the factors limiting or regulating mountain hare populations in the Alps of Central Europe or in the tundra and taiga belts of Russia. Future research on mountain hare population dynamics should focus on the interactions between predation, parasitism and nutrition with stochastic factors such as climate and anthropogenic management including harvesting. PMID:17944616

Newey, Scott; Dahl, Fredrik; Willebrand, Tomas; Thirgood, Simon

2007-11-01

194

2 ABSTRACf Laboratory studies have been previously used to examine fundamental aspects of fish population dynamics and may be explicitly structured to examine the stock-recruitment relation. Previousstudies have shown that cycling of population numbers occurs in refuge-free environments, but provision of refuge areas allows maintenance of stable population numbers. Results of these studies may be adequately explained by simple stock-recruitment

DAVID G. HANKIN

195

Food web theory predicts that the loss of large carnivores may contribute to elevated predation rates and, hence, declining prey populations, through the process of mesopredator release. However, opportunities to test predictions of the mesopredator release hypothesis are rare, and the extent to which changes in predation rates influence prey population dynamics may not be clear due to a lack of demographic information on the prey population of interest. We utilized spatial and seasonal heterogeneity in wolf distribution and abundance to evaluate whether mesopredator release of coyotes (Canis latrans), resulting from the extirpation of wolves (Canis lupus) throughout much of the United States, contributes to high rates of neonatal mortality in ungulates. To test this hypothesis, we contrasted causes of mortality and survival rates of pronghorn (Antilocapra americana) neonates captured at wolf-free and wolf-abundant sites in western Wyoming, USA, between 2002 and 2004. We then used these data to parameterize stochastic population models to heuristically assess the impact of wolves on pronghorn population dynamics due to changes in neonatal survival. Coyote predation was the primary cause of mortality at all sites, but mortality due to coyotes was 34% lower in areas utilized by wolves (P < 0.001). Based on simulation modeling, the realized population growth rate was 0.92 based on fawn survival in the absence of wolves, and 1.06 at sites utilized by wolves. Thus, wolf restoration is predicted to shift the trajectory of the pronghorn population from a declining to an increasing trend. Our results suggest that reintroductions of large carnivores may influence biodiversity through effects on prey populations mediated by mesopredator suppression. In addition, our approach, which combines empirical data on the population of interest with information from other data sources, demonstrates the utility of using simulation modeling to more fully evaluate ecological theories by moving beyond estimating changes in vital rates to analyses of population-level impacts. PMID:18488620

Berger, Kim Murray; Conner, Mary M

2008-04-01

196

Nonstationary modeling of neural population dynamics.

A stochastic state point-process adaptive filter was used to track the temporal evolution of several simulated nonlinear dynamical systems. The estimated Laguerre coefficients and Laguerre poles were used to reconstruct the feedforward and feedback kernels in the system. Simulations showed that the proposed method could track the actual underlying changes of nonlinear kernels using spike input and spike output information alone. The estimated models also converge quickly to the actual models after abrupt step changes in kernels. The proposed method can be used to track the functional input-output properties of neural systems as a result of learning, changes in context, aging or other factors in the natural flow of behavioral events. PMID:19963837

Chan, Rosa H M; Song, Dong; Berger, Theodore W

2009-01-01

197

Cardiovascular risk prediction tools for populations in Asia

Background Cardiovascular risk equations are traditionally derived from the Framingham Study. The accuracy of this approach in Asian populations, where resources for risk factor measurement may be limited, is unclear. Objective To compare “low?information” equations (derived using only age, systolic blood pressure, total cholesterol and smoking status) derived from the Framingham Study with those derived from the Asian cohorts, on the accuracy of cardiovascular risk prediction. Design Separate equations to predict the 8?year risk of a cardiovascular event were derived from Asian and Framingham cohorts. The performance of these equations, and a subsequently “recalibrated” Framingham equation, were evaluated among participants from independent Chinese cohorts. Setting Six cohort studies from Japan, Korea and Singapore (Asian cohorts); six cohort studies from China; the Framingham Study from the US. Participants 172?077 participants from the Asian cohorts; 25?682 participants from Chinese cohorts and 6053 participants from the Framingham Study. Main results In the Chinese cohorts, 542 cardiovascular events occurred during 8?years of follow?up. Both the Asian cohorts and the Framingham equations discriminated cardiovascular risk well in the Chinese cohorts; the area under the receiver–operator characteristic curve was at least 0.75 for men and women. However, the Framingham risk equation systematically overestimated risk in the Chinese cohorts by an average of 276% among men and 102% among women. The corresponding average overestimation using the Asian cohorts equation was 11% and 10%, respectively. Recalibrating the Framingham risk equation using cardiovascular disease incidence from the non?Chinese Asian cohorts led to an overestimation of risk by an average of 4% in women and underestimation of risk by an average of 2% in men. Interpretation A low?information Framingham cardiovascular risk prediction tool, which, when recalibrated with contemporary data, is likely to estimate future cardiovascular risk with similar accuracy in Asian populations as tools developed from data on local cohorts.

Collaboration, Asia Pacific Cohort Studies

2007-01-01

198

NASA Astrophysics Data System (ADS)

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 implies generalized synchrony. Numerical examples studied include three classes of unidirectionally coupled systems: systems with identical parameters, nonidentical parameters, and stochastic driving of a nonlinear system. This technique is then applied to the activity of motoneurons within a spinal cord motoneuron pool. The interrelationships examined include single neuron unit firing, the total number of neurons discharging at one time as measured by the integrated monosynaptic reflex, and intracellular measurements of integrated excitatory postsynaptic potentials (EPSP's). Dynamical interdependence, perhaps generalized synchrony, was identified in this neuronal network between simultaneous single unit firings, between units and the population, and between units and intracellular EPSP's.

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

1996-12-01

199

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. PMID:24166372

Close, Dan; Xu, Tingting; Ripp, Steven; Sayler, Gary

2014-01-01

200

NASA Astrophysics Data System (ADS)

A model of clustering dynamics is proposed for a population of spatially distributed active rotators. A transition from excitable to oscillatory dynamics is induced by the increase of the local density of active rotators. It is interpreted as dynamical quorum sensing. In the oscillation regime, phase waves propagate without decay, which generates an effectively long-range interaction in the clustering dynamics. The clustering process becomes facilitated and only one dominant cluster appears rapidly as a result of the dynamical quorum sensing. An exact localized solution is found to a simplified model equation, and the competitive dynamics between two localized states is studied numerically.

Sakaguchi, Hidetsugu; Maeyama, Satomi

2013-02-01

201

Dynamic Predictions of Semi-Arid Land Cover Change

NASA Astrophysics Data System (ADS)

Savannas make up about 18% of the global landmass and contain about 22% of the world's population (Falkenmark and Rockstrom, 2008). They are unique ecosystems in that they consist of both grass and trees. Depending on the land use, amount of precipitation, herbivory, and fire frequency, either trees or grasses can be more prevalent than the other (Sankaran et al., 2005). Savannas in sub-Saharan Africa are usually considered water-limited ecosystems due to the seasonal rainfall. It has been shown that the vegetation responds on a short timescale to the rainfall (Scanlon et al, 2002). Therefore, savannas are foreseen as vulnerable ecosystems to future changes in the land use and climate change (Sankaran et al, 2005). The goal of this research is to quantify the vulnerability of this ecosystem by projecting future changes in the savanna structure due to land use and climate change through the use of a dynamic vegetation model. This research will provide a better understanding of the relationship between precipitation and vegetation in savannas through the use of a Vegetation Dynamics Model developed to predict surface water fluxes and vegetation dynamics in water-limited ecosystems (Williams and Albertson, 2005). In this project, it will be used to model leaf area index (LAI) for point locations within sub-Saharan Africa between Kenya and Botswana with a range of annual rainfall and savanna type. With this model, future projections are developed for what can be anticipated in the future for the savanna structure based on three climate change scenarios; (1) decreased depth, (2) decreased frequency, and (3) decreased wet season length. The effect of the climate change scenarios on the plant water stress and plant water uptake will be analyzed in order to understand the dynamic effects of precipitation on vegetation. Therefore, this will allow conclusions to be drawn about how mean precipitation and a changing climate effect the sensitivity of savanna vegetation. It is hypothesized that the combined effects of climate change and land use lead to a destabilization of the grass-tree state and an increased tendency toward a state of desertification. If desertification is considered to be irreversible degradation, it can be detrimental not only to plant-life but also to the livelihood of those whom consider the savanna their home. Because a large population lives in savanna ecosystems, it is important to study them to hopefully be able to make changes now before conditions become irreversible. Resources: Falkenmark, M., and Rockstrom, Johan (2008). "Building Resilience to Drought in Desertification-Prone Savannas in Sub-Saharan Africa: The Water Perspective." Natural Resources Forum 32: 93-102. Sankaran, M., Hanan, Niall P., Scholes, Robert J., Ratnman, Jayashree, Augustine, David J. , et al (2005). "Determinants of Woody Cover in African Savannas." Nature 438(8): 846-849. Scanlon, T., J.D. Albertson, K.K. Caylor, & C.A.Willaims (2002). "Determining Land Surface Fractional Cover from NDVI and Rainfall Time Series for a Savanna Ecosystem." Remote Sensing of Environment. 82:376-388. Williams, C., and Albertson, J. (2005). "Contrasting Short- and Long-Timescale Effects of Vegetation Dynamics on Water and Carbon Fluxes in Water-Limited Ecosystems." Water Resources Research. 41: 1-13

Foster-Wittig, T. A.

2011-12-01

202

Pair approximations of takeover dynamics in regular population structures.

In complex adaptive systems, the topological properties of the interaction network are strong governing influences on the rate of flow of information throughout the system. For example, in epidemiological models, the structure of the underlying contact network has a pronounced impact on the rate of spread of infectious disease throughout a population. Similarly, in evolutionary systems, the topology of potential mating interactions (i.e., population structure) affects the rate of flow of genetic information and therefore affects selective pressure. One commonly employed method for quantifying selective pressure in evolutionary algorithms is through the analysis of the dynamics with which a single favorable mutation spreads throughout the population (a.k.a. takeover time analysis). While models of takeover dynamics have been previously derived for several specific regular population structures, these models lack generality. In contrast, so-called pair approximations have been touted as a general technique for rapidly approximating the flow of information in spatially structured populations with a constant (or nearly constant) degree of nodal connectivities, such as in epidemiological and ecological studies. In this work, we reformulate takeover time analysis in terms of the well-known Susceptible-Infectious-Susceptible model of disease spread and adapt the pair approximation for takeover dynamics. Our results show that the pair approximation, as originally formulated, is insufficient for approximating pre-equilibrium dynamics, since it does not properly account for the interaction between the size and shape of the local neighborhood and the population size. After parameterizing the pair approximation to account for these influences, we demonstrate that the resulting pair approximation can serve as a general and rapid approximator for takeover dynamics on a variety of spatially-explicit regular interaction topologies with varying population sizes and varying uptake and reversion probabilities. Strengths, limitations, and potential applications of the pair approximation to evolutionary computation are discussed. PMID:19413488

Payne, Joshua L; Eppstein, Margaret J

2009-01-01

203

Contrasting dynamics of a mutator allele in asexual populations of differing size

Mutators have been shown to hitchhike in asexual populations when the anticipated beneficial mutation supply rate of the mutator subpopulation, NUb (for subpopulation of size N and beneficial mutation rate Ub) exceeds that of the wild-type subpopulation. Here, we examine the effect of total population size on mutator dynamics in asexual experimental populations of Saccharomyces cerevisiae. Although mutators quickly hitchhike to fixation in smaller populations, mutator fixation requires more and more time as population size increases; this observed delay in mutator hitchhiking is consistent with the expected effect of clonal interference. Interestingly, despite their higher beneficial mutation supply rate, mutators are supplanted by the wild type in very large populations. We postulate that this striking reversal in mutator dynamics is caused by an interaction between clonal interference, the fitness cost of the mutator allele, and infrequent large-effect beneficial mutations in our experimental populations. Our work thus identifies a potential set of circumstances under which mutator hitchhiking can be inhibited in natural asexual populations, despite recent theoretical predictions that such populations should have a net tendency to evolve ever-higher genomic mutation rates.

Raynes, Yevgeniy; Gazzara, Matthew R.; Sniegowski, Paul D.

2012-01-01

204

The evolutionary dynamics of spite in finite populations.

Spite, the shady relative of altruism, involves paying a fitness cost to inflict a cost on some recipient. Here, we investigate a density dependent dynamic model for the evolution of spite in populations of changing size. We extend the model by introducing a dynamic carrying capacity. Our analysis shows that it is possible for unconditionally spiteful behavior to evolve without population structure in any finite population. In some circumstances spiteful behavior can contribute to its own stability by limiting population growth. We use the model to show that there are differences between spite and altruism, and to refine Hamilton's original argument about the insignificance of spite in the wild. We also discuss the importance of fixing the measure of fitness to classify behaviors as selfish or spiteful. PMID:23461321

Smead, Rory; Forber, Patrick

2012-11-16

205

Beneficial mutations and the dynamics of adaptation in asexual populations.

We discuss the dynamics of adaptive evolution in asexual (clonal) populations. The classical 'periodic selection' model of clonal evolution assumed that beneficial mutations are very rare and therefore substitute unfettered into populations as occasional, isolated events. Newer models allow for the possibility that beneficial mutations are sufficiently common to coexist and compete for fixation within populations. Experimental evolution studies in microbes provide empirical support for stochastic models in which both selection and mutation are strong effects and clones compete for fixation; however, the relative importance of competition among clones bearing mutations of different selective effects versus competition among clones bearing multiple mutations remains unresolved. We provide some new theoretical results, moreover, suggesting that population dynamics consistent with the periodic selection model can arise even in a deterministic model that can accommodate a very high beneficial mutation rate. PMID:20308101

Sniegowski, Paul D; Gerrish, Philip J

2010-04-27

206

An empirical quantitative framework for the seasonal population dynamics of the tick Ixodes ricinus.

The wide geographic and climatic range of the tick Ixodes ricinus, and the consequent marked variation in its seasonal population dynamics, have a direct impact on the transmission dynamics of the many pathogens vectored by this tick species. We use long-term observations on the seasonal abundance and fat contents (a marker of physiological ageing) of ticks, and contemporaneous microclimate at three field sites in the UK, to establish a simple quantitative framework for the phenology (i.e. seasonal cycle of development) of I. ricinus as a foundation for a generic population model. An hour-degree tick inter-stadial development model, driven by soil temperature and including diapause, predicts the recruitment (i.e. emergence from the previous stage) of a single cohort of each stage of ticks each year in the autumn. The timing of predicted emergence coincides exactly with the new appearance of high-fat nymphs and adults in the autumn. Thereafter, fat contents declined steadily until unfed ticks with very low energy reserves disappeared from the questing population within about 1 year from their recruitment. Very few newly emerged ticks were counted on the vegetation in the autumn, but they appeared in increasing numbers through the following spring. Larger ticks became active and subsequently left the questing population before smaller ones. Questing tick population dynamics are determined by seasonal patterns of tick behaviour, host-contact rates and mortality rates, superimposed on a basal phenology that is much less complex than has hitherto been portrayed. PMID:12076627

Randolph, Sarah E; Green, R M; Hoodless, A N; Peacey, M F

2002-07-01

207

On the Population Dynamics of the Malaria Vector

A deterministic differential equation model for the population dynamics of the human malaria vector is derived and studied.\\u000a Conditions for the existence and stability of a non-zero steady state vector population density are derived. These reveal\\u000a that a threshold parameter, the vectorial basic reproduction number, exist and the vector can established itself in the community\\u000a if and only if this

Gideon A. Ngwa; Abdus Salam

2006-01-01

208

Seasonal growth rate and population dynamics of a freshwater sponge

Five sites of various water depths on four transects were sampled on a seasonal basis to determine Ephydatia fluviatilis population dynamics. The temporal occurrence of life cycle events was influenced by factors (e.g. water temperature) that varied with water depth. The shallow-water (1.5 m deep) portion of the population. Sexual reproduction occurred in the spring. Seasonal growth rates were determined

Russell B. Raderl; Robert N. Winget

1985-01-01

209

Interannual dynamics of aerial and arboreal green spruce aphid populations

Partial defoliation of spruce by the green spruce aphid Elatobium abietinum (Walker) is a recurrent event in European and, increasingly, North American forests. The patterns of insect abundance on\\u000a trees have never been satisfactorily described by a numerical model despite considerable knowledge of endogenous and exogenous\\u000a factors in the population dynamics of the species. Long-term field population estimates of the

Keith Richard Day; Matthew P. Ayres; Richard Harrington; Neil A. C. Kidd

2010-01-01

210

Human population as a dynamic factor in environmental degradation

The environmental consequences of increasing human population size are dynamic and nonlinear, not passive and linear. The\\u000a role of feedbacks, thresholds, and synergies in the interaction of population size and the environment are reviewed here,\\u000a with examples drawn from climate change, acid deposition, land use, soil degradation, and other global and regional environmental\\u000a issues. The widely-assumed notion that environmental degradation

John Harte

2007-01-01

211

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

212

Temporal Dynamics and Linkage Disequilibrium in Natural Caenorhabditis elegans Populations

Caenorhabditis elegans is a major laboratory model system yet a newcomer to the field of population genetics, and relatively little is known of its biology in the wild. Recent studies of natural populations at a single time point revealed strong spatial population structure and suggested that these populations may be very dynamic. We have therefore studied several natural C. elegans populations over time and genotyped them at polymorphic microsatellite loci. While some populations appear to be genetically stable over the course of observation, others seem to go extinct, with full replacement of multilocus genotypes upon regrowth. The frequency of heterozygotes indicates that outcrossing occurs at a mean frequency of 1.7% and is variable between populations. However, in genetically stable populations, linkage disequilibrium between different chromosomes can be maintained over several years at a level much higher than expected from the heterozygote frequency. C. elegans seems to follow metapopulation dynamics, and the maintenance of linkage disequilibrium despite a low yet significant level of outcrossing suggests that selection may act against the progeny of outcrossings.

Barriere, Antoine; Felix, Marie-Anne

2007-01-01

213

Density-dependent dispersal and spatial population dynamics

The synchronization of the dynamics of spatially subdivided populations is of both fundamental and applied interest in population biology. Based on theoretical studies, dispersal movements have been inferred to be one of the most general causes of population synchrony, yet no empirical study has mapped distance-dependent estimates of movement rates on the actual pattern of synchrony in species that are known to exhibit population synchrony. Northern vole and lemming species are particularly well-known for their spatially synchronized population dynamics. Here, we use results from an experimental study to demonstrate that tundra vole dispersal movements did not act to synchronize population dynamics in fragmented habitats. In contrast to the constant dispersal rate assumed in earlier theoretical studies, the tundra vole, and many other species, exhibit negative density-dependent dispersal. Simulations of a simple mathematical model, parametrized on the basis of our experimental data, verify the empirical results, namely that the observed negative density-dependent dispersal did not have a significant synchronizing effect.

Ims, Rolf A; Andreassen, Harry P

2005-01-01

214

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

215

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

216

Predicting NCLEX-RN success in a diverse student population.

Many schools of nursing have implemented standardized testing using platforms such as those developed by Assessment Technologies Institute (ATI) to better prepare students for success on the National Council Licensure Examination for Registered Nurses® (NCLEX-RN). This study extends and replicates the research on standardized testing to predict first-time pass success in a diverse student population and across two prelicensure program types. The final sample consisted of 589 students who graduated between 2003 and 2009. Demographic data, as well as academic performance and scores on the ATI RN Comprehensive Predictor, were analyzed. The findings in this study indicate that scores on the ATI RN Comprehensive Predictor were positively, significantly associated with first-time pass success. Students in jeopardy of failing the NCLEX-RN on their first attempt can be identified prior to graduation and remediation efforts can be strengthened to improve their success. PMID:21366169

Alameida, Marshall D; Prive, Alice; Davis, Harvey C; Landry, Lynette; Renwanz-Boyle, Andrea; Dunham, Michelle

2011-02-28

217

A new approach to quantify predictability: Nonlinear error growth dynamics

NASA Astrophysics Data System (ADS)

Measuring quantitatively the predictability of chaotic systems is of practical significance but very complex. In this study, a new theory of nonlinear error growth dynamics and a new concept, the nonlinear local Lyapunov exponent (NLLE), from the theory are introduced to quantify the predictability of chaotic systems. The NLLE, which is a nonlinear generalization to the existing local or finite-time Lyapunov exponents, can characterize the growth rate of initial errors of nonlinear dynamical models without linearizing the governing equations. A saturation theorem of the ensemble mean relative growth of initial error (RGIE) for the chaotic dynamical systems is obtained and the predictability limit can be defined as the time when the RGIE reaches its saturation level. Therefore, quantitative research on the predictability limits of chaotic systems could be really performed based on the new approach. The new approach is employed to quantify the predictability limits of the atmosphere and ocean on various scales and their spatial-temporal structure. Besides, the new theory could also be applied to estimate the predictability of forecast models.

Li, J.; Ding, R.

2009-04-01

218

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 speciesĂ˘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

219

In the attempt to use results from small-scale studies to make large-scale predictions, it is critical that we take into account\\u000a the greater spatial heterogeneity encountered at larger spatial scales. An important component of this heterogeneity is variation\\u000a in plant quality, which can have a profound influence on herbivore population dynamics. This influence is particularly relevant\\u000a when we consider that

Sandra E. Helms; Mark D. Hunter

2005-01-01

220

Simulation model of Rhyzopertha dominica population dynamics in concrete grain bins

Rhyzopertha dominica is one of the most damaging insect pests in grain elevators and causes millions of dollars worth of stored grain losses annually in the USA. A simulation model was developed for predicting R. dominica population dynamics in concrete grain bins. The model used a two-dimensional representation of a cylindrical concrete bin (33m tall×6.4m wide), and used hourly weather

Paul W. Flinn; David W. Hagstrum; Carl Reed; Thomas W. Phillips

2004-01-01

221

Fitness versus longevity in age-structured population dynamics.

We examine the dynamics of an age-structured population model in which the life expectancy of an offspring may be mutated with respect to that of the parent. While the total population of the system always reaches a steady state, the fitness and age characteristics exhibit counter-intuitive behavior as a function of the mutational bias. By analytical and numerical study of the underlying rate equations, we show that if deleterious mutations are favored, the average fitness of the population reaches a steady state, while the average population age is a decreasing function of the average fitness. When advantageous mutations are favored, the average population fitness grows linearly with time t, while the average age is independent of the average fitness. For no mutational bias, the average fitness grows as t2/3. PMID:11984646

Hwang, W; Krapivsky, P L; Redner, S

2002-04-01

222

Toward linking ocean models to fish population dynamics

We discuss Lehodey et al.’s (2009) approach to linking ocean models to population dynamics of large marine predators, consider its benefits and limitations, and outline alternative approaches. We advocate a middle ground between Lehodey et al.’s pragmatic, phenomenological approach and the detailed mechanistic approach common to most individual based models. These models should capture the essence of critical processes controlling

Lawrence J. Buckley; Lauren B. Buckley

2010-01-01

223

STOCHASTIC WEALTH DYNAMICS AND RISK MANAGEMENT AMONG A POOR POPULATION

The literature on economic growth and development has focused considerable attention on questions of risk management and the possibility of multiple equilibria associated with poverty traps. We use herd history data collected among pastoralists in southern Ethiopia to study stochastic wealth dynamics among a very poor population. These data yield several novel findings. Although covariate rainfall shocks plainly matter, household-specific

Travis J. Lybbert; Christopher B. Barrett; Solomon Desta; D. Layne Coppock

2002-01-01

224

COMPARISON OF SAMPLING TECHNIQUES USED IN STUDYING LEPIDOPTERA POPULATION DYNAMICS

Four methods (light traps, foliage samples, canvas bands, and gypsy moth egg mass surveys) that are used to study the population dynamics of foliage-feeding Lepidoptera were compared for 10 species, including gypsy moth, Lymantria dispar L. Samples were collected weekly at 12 sit...

225

A new technique for dynamic size populations in genetic programming

New techniques for dynamically changing the size of populations during the execution of genetic programming systems are proposed. Two models are presented, allowing to add and suppress individuals on the basis of some particular events occurring during the evolution. These models allow to find solutions of better quality, to save considerable amounts of computational effort and to find optimal solutions

Marco Tomassini; L. Vanneschi; J. Cuendet; F. Fernandez

2004-01-01

226

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

227

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

228

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.

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

2011-01-01

229

Bayesian Coalescent Inference of Past Population Dynamics from Molecular Sequences

Weintroduce the Bayesian skyline plot,anew method for estimating past population dynamics throughtime from asample of molecular sequences without dependence on a prespecified parametric model of demographic history. We describe a Markov chain Monte Carlo sampling procedure that efficiently samples a variant of the generalized skyline plot, given sequence data, and combines these plots to generate a posterior distribution of effective

A. J. Drummond; A. Rambaut; B. Shapiro; O. G. Pybus

2005-01-01

230

Evolution of complex dynamics in spatially structured populations

Dynamics of populations depend on demographic parameters which may change during evolution. In simple ecological models given by one-dimensional difference equations, the evolution of demographic parameters generally leads to equilibrium population dynamics. Here we show that this is not true in spatially structured ecological models. Using a multi-patch metapopulation model, we study the evolutionary dynamics of phenotypes that differ both in their response to local crowding, i.e. in their competitive behaviour within a habitat, and in their rate of dispersal between habitats. Our simulation results show that evolution can favour phenotypes that have the intrinsic potential for very complex dynamics provided that the environment is spatially structured and temporally variable. These phenotypes owe their evolutionary persistence to their large dispersal rates. They typically coexist with phenotypes that have low dispersal rates and that exhibit equilibrium dynamics when alone. This coexistence is brought about through the phenomenon of evolutionary branching, during which an initially uniform population splits into the two phenotypic classes.

Johst, K.; Doebeli, M.; Brandl, R.

1999-01-01

231

Predictable Threads for Dynamic, Hard Real-Time Environments

Abstract Next-generationhard real-time systemswill require new,flexible functionality and guaranteed, predictable performance. This paper describes the UMass Spring threads package, designed specifically for multiprocessing in dynamic, hard real-time envi- ronments.,This package,is unique,because,of its support,for new,thread semantics for real-time processing.,Predictable creation and execution of threads,is achieved because of an underlying predictable kernel, the UMass Spring kernel. Design de- cisions and lessons learned,while

Marty Humphrey; John A. Stankovic

1999-01-01

232

Population dynamics and mutualism: functional responses of benefits and costs.

We develop an approach for studying population dynamics resulting from mutualism by employing functional responses based on density-dependent benefits and costs. These functional responses express how the population growth rate of a mutualist is modified by the density of its partner. We present several possible dependencies of gross benefits and costs, and hence net effects, to a mutualist as functions of the density of its partner. Net effects to mutualists are likely a monotonically saturating or unimodal function of the density of their partner. We show that fundamental differences in the growth, limitation, and dynamics of a population can occur when net effects to that population change linearly, unimodally, or in a saturating fashion. We use the mutualism between senita cactus and its pollinating seed-eating moth as an example to show the influence of different benefit and cost functional responses on population dynamics and stability of mutualisms. We investigated two mechanisms that may alter this mutualism's functional responses: distribution of eggs among flowers and fruit abortion. Differences in how benefits and costs vary with density can alter the stability of this mutualism. In particular, fruit abortion may allow for a stable equilibrium where none could otherwise exist. PMID:18707376

Holland, J Nathaniel; Deangelis, Donald L; Bronstein, Judith L

2002-03-01

233

Evolutionary dynamics of group interactions on structured populations: a review.

Interactions among living organisms, from bacteria colonies to human societies, are inherently more complex than interactions among particles and non-living matter. Group interactions are a particularly important and widespread class, representative of which is the public goods game. In addition, methods of statistical physics have proved valuable for studying pattern formation, equilibrium selection and self-organization in evolutionary games. Here, we review recent advances in the study of evolutionary dynamics of group interactions on top of structured populations, including lattices, complex networks and coevolutionary models. We also compare these results with those obtained on well-mixed populations. The review particularly highlights that the study of the dynamics of group interactions, like several other important equilibrium and non-equilibrium dynamical processes in biological, economical and social sciences, benefits from the synergy between statistical physics, network science and evolutionary game theory. PMID:23303223

Perc, Matjaz; Gómez-Gardeńes, Jesús; Szolnoki, Attila; Floría, Luis M; Moreno, Yamir

2013-01-09

234

Using stochastic population process models to predict the impact of climate change

NASA Astrophysics Data System (ADS)

More than ten years ago a paper was published in which stochastic population process models were fitted to time series of two marine polychaete species in the western Wadden Sea, The Netherlands (Van der Meer et al., 2000). For the predator species, model fits pointed to a strong effect of average sea surface winter temperature on the population dynamics, and one-year ahead model forecasts correlated well with true observations (r = 0.90). During the last decade a pronounced warming of the area occurred. Average winter temperature increased with 0.9 °C. Here we show that despite the high goodness-of-fit whilst using the original dataset, predictive capability of the models for the recent warm period was poor.

van der Meer, Jaap; Beukema, J. J.; Dekker, Rob

2013-09-01

235

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

236

Individual predictions of eye-movements with dynamic scenes

We present a model that predicts saccadic eye-movements and can be tuned to a particular human observer who is viewing a dynamic sequence of images. Our work is motivated by applications that involve gaze-contingent interactive displays on which information is displayed as a function of gaze direction. The approach therefore differs from standard approaches in two ways: (1) we deal

Erhardt Barth; Jan Drewes; Thomas Martinetz

2003-01-01

237

Information Flow Prediction by Modeling Dynamic Probabilistic Social Network

In this paper, we propose a novel Behavioral Information Flow (BIF) model which can be used to predict how information is propagated through a complex social network. We consider both the dynamic and probabilistic characteristics of human behavior in receiving and redirecting information. Information can be duplicated without any distortion and send to as many people as the user has

Ching-Yung Lin

2006-01-01

238

The influence of context-dependent maternal effects on population dynamics: an experimental test

Parental effects arise when either the maternal or paternal phenotype influences the phenotypes of subsequent generations. Simple analytical models assume maternal effects are a mechanism creating delayed density dependence. Such models predict that maternal effects can very easily lead to population cycles. Despite this, unambiguous maternal-effect mediated cycles have not been demonstrated in any system. Additionally, much evidence has arisen to invalidate the underlying assumption that there is a simple positive correlation between maternal performance and offspring performance. A key issue in understanding how maternal effects may affect population dynamics is determining how the expression of parental effects changes in different environments. In this study, we tested the hypothesis that maternal effects influence population dynamics in a context-dependent way. Populations of the soil mite, Sancassania berlesei, were set up at high density (500 eggs) or low density (50 eggs), with eggs that were either laid by young mothers or old mothers (a previously documented maternal effect in this system). The influence of maternal age on both population and egg and body-size dynamics was only observed in the populations initiated under low density rather than high density. This difference was attributable to the context-dependence of maternal effects at the individual level. In low-density (high food) conditions, maternal effects have an impact on offspring reproductive performance, creating an impact on the population growth rate. In high density (low food), maternal effects impact more on juvenile survival (not adult size or reproduction), creating a smaller impact on the population growth rate. This context dependence of effects at the population level means that, in fluctuating populations, maternal effects cause intermittent delayed density dependence that does not lead to persistent cycles.

Plaistow, S.J.; Benton, T.G.

2009-01-01

239

Background The evolutionary success of Wolbachia bacteria, infections of which are widespread in invertebrates, is largely attributed to an ability to manipulate host reproduction without imposing substantial fitness costs. Here, we describe a stage-structured model with deterministic immature lifestages and a stochastic adult female lifestage. Simulations were conducted to better understand Wolbachia invasions into uninfected host populations. The model includes conventional Wolbachia parameters (the level of cytoplasmic incompatibility, maternal inheritance, the relative fecundity of infected females, and the initial Wolbachia infection frequency) and a new parameter termed relative larval viability (RLV), which is the survival of infected larvae relative to uninfected larvae. Results The results predict the RLV parameter to be the most important determinant for Wolbachia invasion and establishment. Specifically, the fitness of infected immature hosts must be close to equal to that of uninfected hosts before population replacement can occur. Furthermore, minute decreases in RLV inhibit the invasion of Wolbachia despite high levels of cytoplasmic incompatibility, maternal inheritance, and low adult fitness costs. Conclusions The model described here takes a novel approach to understanding the spread of Wolbachia through a population with explicit dynamics. By combining a stochastic female adult lifestage and deterministic immature/adult male lifestages, the model predicts that even those Wolbachia infections that cause minor decreases in immature survival are unlikely to invade and spread within the host population. The results are discussed in relation to recent theoretical and empirical studies of natural population replacement events and proposed applied research, which would use Wolbachia as a tool to manipulate insect populations.

2011-01-01

240

Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids

Inactivation of ?-lactam antibiotics by resistant bacteria is a ‘cooperative' behavior that may allow sensitive bacteria to survive antibiotic treatment. However, the factors that determine the fraction of resistant cells in the bacterial population remain unclear, indicating a fundamental gap in our understanding of how antibiotic resistance evolves. Here, we experimentally track the spread of a plasmid that encodes a ?-lactamase enzyme through the bacterial population. We find that independent of the initial fraction of resistant cells, the population settles to an equilibrium fraction proportional to the antibiotic concentration divided by the cell density. A simple model explains this behavior, successfully predicting a data collapse over two orders of magnitude in antibiotic concentration. This model also successfully predicts that adding a commonly used ?-lactamase inhibitor will lead to the spread of resistance, highlighting the need to incorporate social dynamics into the study of antibiotic resistance.

Yurtsev, Eugene A; Chao, Hui Xiao; Datta, Manoshi S; Artemova, Tatiana; Gore, Jeff

2013-01-01

241

The bay of Izmir, which is the biggest harbor on the Aegean Sea, is of upmost economical importance for Izmir, the third largest city in Turkey. Most of the studies carried out focused on the effects of intensive industrial activity and agricultural production on the bay pollution within the region. These studies, most of the time, are limited to monitoring the level of pollution. However, it is believed that these studies should be supported with models and statistical analysis techniques, as the models, especially the prediction ones, provide an important approach to assessing risk and assessment. In this study, neural network analysis was used to construct prediction models for nanoplankton population change with nutrients and other environmentally important parameters. The results indicated that, using data over a 52 week period, it is possible to predict nanoplankton population dynamics and dissolved oxygen change for the future. PMID:19513447

Sunlu, F S; Demir, I; Onkal Engin, G; Buyukisik, B; Sunlu, U; Koray, T; Kukrer, S

2009-04-21

242

Population dynamics and climate change: what are the links?

Climate change has been described as the biggest global health threat of the 21(st) century. World population is projected to reach 9.1 billion by 2050, with most of this growth in developing countries. While the principal cause of climate change is high consumption in the developed countries, its impact will be greatest on people in the developing world. Climate change and population can be linked through adaptation (reducing vulnerability to the adverse effects of climate change) and, more controversially, through mitigation (reducing the greenhouse gases that cause climate change). The contribution of low-income, high-fertility countries to global carbon emissions has been negligible to date, but is increasing with the economic development that they need to reduce poverty. Rapid population growth endangers human development, provision of basic services and poverty eradication and weakens the capacity of poor communities to adapt to climate change. Significant mass migration is likely to occur in response to climate change and should be regarded as a legitimate response to the effects of climate change. Linking population dynamics with climate change is a sensitive issue, but family planning programmes that respect and protect human rights can bring a remarkable range of benefits. Population dynamics have not been integrated systematically into climate change science. The contribution of population growth, migration, urbanization, ageing and household composition to mitigation and adaptation programmes needs urgent investigation. PMID:20501867

Stephenson, Judith; Newman, Karen; Mayhew, Susannah

2010-06-01

243

Combined analytical and experimental approaches to dynamic component stress prediction

NASA Astrophysics Data System (ADS)

In modern times, the ability to investigate the aeroelastic behavior of dynamic components on rotorcraft has become essential for the prediction of their useful fatigue life. At the same time, the aeroelastic modeling of a rotorcraft is particularly complex and costly. Inaccuracies in numerical predictions are mostly due to imprecisions in the structural modeling, to the presence of structural degradation or to the limited information on aerodynamic loads. The integration of experimental measurements on dynamic components such as rotor blades has the potential to improve fatigue estimation, augment the knowledge of the dynamic behavior and inform numerical models. The objective of this research is the development of a combined numerical and experimental approach, named Confluence Algorithm, that accurately predicts the response of dynamic components with a limited set of experimental data. The integration of experimental measurements into a numerical algorithm enables the continuous and accurate tracking of the dynamic strain and stress fields. The Confluence Algorithm systematically updates the numerical model of the external loads, and mass and stiffness distributions to improve the representation and extrapolation of the experimental data, and to extract information on the response of the system at non-measured locations. The capabilities of this algorithm are first verified in a numerical framework and with well-controlled lab experiments. Numerical results from a comprehensive UH-60A multibody model are then compared with available experimental data. These analyses demonstrate that the integration of the Confluence Algorithm improves the accuracy of the numerical prediction of the dynamic response of systems characterized by a periodic behavior, even in presence of non-linearities. The algorithm enables the use of simplified models that are corrected through experimental data to achieve accurate tracking of the system.

Chierichetti, Maria

244

Noise-Driven Stem Cell and Progenitor Population Dynamics

Background The balance between maintenance of the stem cell state and terminal differentiation is influenced by the cellular environment. The switching between these states has long been understood as a transition between attractor states of a molecular network. Herein, stochastic fluctuations are either suppressed or can trigger the transition, but they do not actually determine the attractor states. Methodology/Principal Findings We present a novel mathematical concept in which stem cell and progenitor population dynamics are described as a probabilistic process that arises from cell proliferation and small fluctuations in the state of differentiation. These state fluctuations reflect random transitions between different activation patterns of the underlying regulatory network. Importantly, the associated noise amplitudes are state-dependent and set by the environment. Their variability determines the attractor states, and thus actually governs population dynamics. This model quantitatively reproduces the observed dynamics of differentiation and dedifferentiation in promyelocytic precursor cells. Conclusions/Significance Consequently, state-specific noise modulation by external signals can be instrumental in controlling stem cell and progenitor population dynamics. We propose follow-up experiments for quantifying the imprinting influence of the environment on cellular noise regulation.

Hoffmann, Martin; Chang, Hannah H.; Huang, Sui; Ingber, Donald E.; Loeffler, Markus; Galle, Joerg

2008-01-01

245

Cooperative breeding is a system in which certain individuals facilitate the production of offspring by others. The ecological constraints hypothesis states that ecological conditions deter individuals from breeding independently, and so individuals breed cooperatively to make the best of a bad situation. Current theoretical support for the ecological constraints hypothesis is lacking. We formulate a mathematical model that emphasizes the underlying ecology of cooperative breeders. Our goal is to derive theoretical support for the ecological constraints hypothesis using an ecological model of population dynamics. We consider a population composed of two kinds of individuals, nonbreeders (auxiliaries) and breeders. We suppose that help provided by an auxiliary increases breeder fecundity, but reduces the probability with which the auxiliary becomes a breeder. Our main result is a condition that guarantees success of auxiliary help. We predict that increasing the cost of dispersal promotes helping, in agreement with verbal theory. We also predict that increasing breeder mortality can either hinder helping (at high population densities), or promote it (at low population densities). We conclude that ecological constraints can exert influence over the evolution of auxiliary help when population dynamics are considered; moreover, that influence need not coincide with direct fitness benefits as previously found. PMID:24152004

McLeod, David V; Wild, Geoff

2013-07-10

246

Stochastic dynamic population model for northern corn rootworm (Coleoptera: Chrysomelidae).

A stochastic dynamic population model for the complete life cycle of northern corn rootworm, Diabrotica barberi Smith & Lawrence, is described. Adult population dynamics from emergence to oviposition are based on a published single-season model for which temperature-dependent development and age-dependent advancement determine adult population dynamics and oviposition. Randomly generated daily temperatures make this model component stochastic. Stochastic hatch is 50+/-8%. A stochastic nonlinear density-dependent larval survival model is estimated using field data from artificial infestation experiments. A regional model of corn phenology is estimated to incorporate the effect of dispersal on adult mortality. Random daily weather is generated using parameters for Brookings, SD. Model performance is evaluated with deterministic simulations, which show that the population converges to zero unless adult mortality is reduced by the availability of corn pollen from the regional model of corn phenology. Stochastic model performance is evaluated with stochastic daily weather, egg hatch, and larval survival in various combinations. Sensitivity analysis is conducted to evaluate model responsiveness to each parameter. Model results are generally consistent with published data. PMID:11425012

Mitchell, P D; Riedell, W E

2001-06-01

247

Population rate dynamics and multineuron firing patterns in sensory cortex

Cortical circuits encode sensory stimuli through the firing of neuronal ensembles, and also produce spontaneous population patterns in the absence of sensory drive. This population activity is often characterized experimentally by the distribution of multineuron “words” (binary firing vectors), and a match between spontaneous and evoked word distributions has been suggested to reflect learning of a probabilistic model of the sensory world. We analyzed multineuron word distributions in sensory cortex of anesthetized rats and cats, and found that they are dominated by fluctuations in population firing rate rather than precise interactions between individual units. Furthermore, cortical word distributions change when brain state shifts, and similar behavior is seen in simulated networks with fixed, random connectivity. Our results suggest that similarity or dissimilarity in multineuron word distributions could primarily reflect similarity or dissimilarity in population firing rate dynamics, and not necessarily the precise interactions between neurons that would indicate learning of sensory features.

Okun, Michael; Yger, Pierre; Marguet, Stephan; Gerard-Mercier, Florian; Benucci, Andrea; Katzner, Steffen; Busse, Laura; Carandini, Matteo; Harris, Kenneth D.

2012-01-01

248

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

2012-09-11

249

Computational Methods for Predicting Sites of Functionally Important Dynamics

Understanding and controlling biological function of proteins at the atomic level is of great importance; allosteric mechanisms provide such an interface. Experimental and computational methods have been developed to search for residue mutations that produce changes in function by altering sites of correlated motion. These methods are often observational in that altered motions are achieved by random sampling without revealing the underlying mechanism(s). We present two deterministic methods founded on structure-function relationships that predict dynamic control sites (i.e. locations that experience correlated motions as a result of altered dynamics). The first method (“static”) is based on a single structure conformation (e.g. the wild type (WT)) and utilizes a graph description of atomic connectivity. The local atomic interactions are used to compute the propagation of contact paths. This description of structure connectivity reveals flexible locations that are susceptible to altered dynamics. The second method (“dynamic”) is a comparative analysis between the normal modes of a WT structure and a mutant structure. A mapping function is defined that quantifies the significance of the motions in one structure projected onto the motions of the other. Each mode is considered up- or down-regulated according to its change in relative significance. This description of altered dynamics is the basis for a motion correlation analysis, from which the dynamic control sites are readily identified. The methods are theoretically derived and applied using the canonical system dihydrofolate reductase (DHFR). Both methods demonstrate a very high predictive value (p < 0.005) in identifying known dynamic control sites. The dynamic method also produces a new hypothesis regarding the mechanism by which the DHFR mutant achieves hyperactivity. These tools are suitable for allosteric investigations and may greatly enhance the speed and effectiveness of other computational and experimental methods.

Schuyler, Adam D.; Carlson, Heather A.; Feldman, Eva L.

2009-01-01

250

Between July 1978 and March 1980, the distribution, population dynamics and secondary production of Caulleriella caputesocis St. Joseph, 1864, in Southampton Water, South England, were investigated. The distribution of the polychaete was related to amount of silt and copper-content of the sediment, the highest densities occurring in sediment containing 60 to 100% silt and less than 50 ppm copper. Breeding

J. A. Oyenekan

1987-01-01

251

How Predation and Landscape Fragmentation Affect Vole Population Dynamics

Background Microtine species in Fennoscandia display a distinct north-south gradient from regular cycles to stable populations. The gradient has often been attributed to changes in the interactions between microtines and their predators. Although the spatial structure of the environment is known to influence predator-prey dynamics of a wide range of species, it has scarcely been considered in relation to the Fennoscandian gradient. Furthermore, the length of microtine breeding season also displays a north-south gradient. However, little consideration has been given to its role in shaping or generating population cycles. Because these factors covary along the gradient it is difficult to distinguish their effects experimentally in the field. The distinction is here attempted using realistic agent-based modelling. Methodology/Principal Findings By using a spatially explicit computer simulation model based on behavioural and ecological data from the field vole (Microtus agrestis), we generated a number of repeated time series of vole densities whose mean population size and amplitude were measured. Subsequently, these time series were subjected to statistical autoregressive modelling, to investigate the effects on vole population dynamics of making predators more specialised, of altering the breeding season, and increasing the level of habitat fragmentation. We found that fragmentation as well as the presence of specialist predators are necessary for the occurrence of population cycles. Habitat fragmentation and predator assembly jointly determined cycle length and amplitude. Length of vole breeding season had little impact on the oscillations. Significance There is good agreement between our results and the experimental work from Fennoscandia, but our results allow distinction of causation that is hard to unravel in field experiments. We hope our results will help understand the reasons for cycle gradients observed in other areas. Our results clearly demonstrate the importance of landscape fragmentation for population cycling and we recommend that the degree of fragmentation be more fully considered in future analyses of vole dynamics.

Dalkvist, Trine; Sibly, Richard M.; Topping, Chris J.

2011-01-01

252

Dynamics of fisheries that affect the population growth rate coefficient

NASA Astrophysics Data System (ADS)

Conventional surplus production models indicate that destruction of fish populations by overfishing is difficult, if not impossible, but catastrophic declines in abundance of exploited populations are common. Surplus production models also do not predict large continuing fluctuations in yield, but large fluctuations in yield are common. Conventional surplus production models assume that fisheries do not impact the population's capacity to increase, but changes in age structure or a decrease in age-specific fecundity resulting from fishing can decrease the coefficient of increase. A surplus production model is developed in which fishing reduces the capacity of a population to increase; the model is applied to describe the fluctuations observed in yield of lake herring ( Coregonus artedii) from the upper Great Lakes. The fisheries of the Great Lakes were decimated by the combined effects of heavy fishing and a changing environment. For some species, yield increased to high levels and then the fisheries collapsed; for other species, yield and effort fluctuated greatly.

Jensen, A. L.

1984-03-01

253

Structural Drift: The Population Dynamics of Sequential Learning

We introduce a theory of sequential causal inference in which learners in a chain estimate a structural model from their upstream “teacher” and then pass samples from the model to their downstream “student”. It extends the population dynamics of genetic drift, recasting Kimura's selectively neutral theory as a special case of a generalized drift process using structured populations with memory. We examine the diffusion and fixation properties of several drift processes and propose applications to learning, inference, and evolution. We also demonstrate how the organization of drift process space controls fidelity, facilitates innovations, and leads to information loss in sequential learning with and without memory.

Crutchfield, James P.; Whalen, Sean

2012-01-01

254

Evolutionary dynamics of a multigroup fluctuating-population system

NASA Astrophysics Data System (ADS)

We studied the evolutionary dynamics of a population undergoing asexual reproduction in a flat-fitness landscape. The quantity of interest is the distribution of the overlap function q which is a measure of the similarity in the genome structure between two individuals. We obtain analytical expressions for ,

Bhatia, D. P.; Arora, D.; Prasad, M. A.

1993-03-01

255

Single-crossover dynamics: finite versus infinite populations.

Populations evolving under the joint influence of recombination and resampling (traditionally known as genetic drift) are investigated. First, we summarize and adapt a deterministic approach, as valid for infinite populations, which assumes continuous time and single crossover events. The corresponding nonlinear system of differential equations permits a closed solution, both in terms of the type frequencies and via linkage disequilibria of all orders. To include stochastic effects, we then consider the corresponding finite-population model, the Moran model with single crossovers, and examine it both analytically and by means of simulations. Particular emphasis is on the connection with the deterministic solution. If there is only recombination and every pair of recombined offspring replaces their pair of parents (i.e., there is no resampling), then the expected type frequencies in the finite population, of arbitrary size, equal the type frequencies in the infinite population. If resampling is included, the stochastic process converges, in the infinite-population limit, to the deterministic dynamics, which turns out to be a good approximation already for populations of moderate size. PMID:17957409

Baake, Ellen; Herms, Inke

2007-10-24

256

Integrating population dynamics into mapping human exposure to seismic hazard

NASA Astrophysics Data System (ADS)

Disaster risk is not fully characterized without taking into account vulnerability and population exposure. Assessment of earthquake risk in urban areas would benefit from considering the variation of population distribution at more detailed spatial and temporal scales, and from a more explicit integration of this improved demographic data with existing seismic hazard maps. In the present work, "intelligent" dasymetric mapping is used to model population dynamics at high spatial resolution in order to benefit the analysis of spatio-temporal exposure to earthquake hazard in a metropolitan area. These night- and daytime-specific population densities are then classified and combined with seismic intensity levels to derive new spatially-explicit four-class-composite maps of human exposure. The presented approach enables a more thorough assessment of population exposure to earthquake hazard. Results show that there are significantly more people potentially at risk in the daytime period, demonstrating the shifting nature of population exposure in the daily cycle and the need to move beyond conventional residence-based demographic data sources to improve risk analyses. The proposed fine-scale maps of human exposure to seismic intensity are mainly aimed at benefiting visualization and communication of earthquake risk, but can be valuable in all phases of the disaster management process where knowledge of population densities is relevant for decision-making.

Freire, S.; Aubrecht, C.

2012-11-01

257

Analysis of urban-rural population dynamics for China.

The population dynamics of China are presented in a multiregional demographic model using regional estimates or mortality and migration based on the 1% population sample survey in 1987. An open ended population account is generated for period cohort a, gender g of region i (urban) and j (rural) using population, birth, death, and migration. Demographic rates and equations for flows of nonsurviving migrants of period cohort a of gender g are estimated using the forward demographic rate definition. Out-migration rates for period cohort a of gender g are defined by migration flow divided by the initial population. The death rate for period cohort A1 and A are estimated using a single region method. Death and migration rates are simultaneously estimated with an iterative procedure. The population accounts estimates and demographic rates are provided for the period ending 1986-87 for male births, males in period cohorts 10 and 20, female births, and females in period cohorts 10 and 20. The urban and rural population projection model is based on the population accounts concept and assumes fixed rates of mortality, migration, and normal fertility for the base year 1987. The results of this projection are a population of 1090 million that will grow to 1304 million in 2000, 1720 million in 2050, and 1791 million in 2087. Urban population will expand from 44.2% in 1988 to 46.6% in 2000, and 54.7% in 2087. The labor population of males 18-65 years and females 18-60 years will increase from 58.8% in 1988 to 59.7% in 2000 and decline to 58.4% by 2087. The old age population of males 65 years and females 60 years will increase from 6.5% in 1988 to 7.9% in 2000, and 16.3% in 2087. The mean age increased from 28.3 years in 1988 to 37 in 2087. Urban population may be underprojected; migration problems are recognized. Fertility also is likely to decline. An alternative projection (B) is given to account for the U-shape distribution and urban fertility of 1.8 in 2000, increasing to and stabilizing at 2.2 in 2020, such that population estimates for 2000 are 1291 and 1524 for 2087 with a peak in 2048 of 1573. A faster fertility decline is also used to generate projection C. The author's projections A, B, and C, which are based on more recent data and a more realistic model, are than the "objective projection" and than the "warning projection" generated by China's Population Census Office based on 1982 census data. PMID:12343497

Shen, J

1991-12-01

258

Artificial nest experiments (ANEs) are widely used to obtain proxies of natural nest predation for testing a variety of hypotheses, from those dealing with variation in life-history strategies to those assessing the effects of habitat fragmentation on the persistence of bird populations. However, their applicability to real-world scenarios has been criticized owing to the many potential biases in comparing predation rates of artificial and natural nests. Here, we aimed to test the validity of estimates of ANEs using a novel approach. We related predation rates on artificial nests to population viability analyses in a songbird metapopulation as a way of predicting the real impact of predation events on the local populations studied. Predation intensity on artificial nests was negatively related to the species' annual population growth rate in small local populations, whereas the viability of large local populations did not seem to be influenced, even by high nest predation rates. The potential of extrapolation from ANEs to real-world scenarios is discussed, as these results suggest that artificial nest predation estimates may predict demographic processes in small structured populations. PMID:21493624

Vögeli, Matthias; Laiolo, Paola; Serrano, David; Tella, José L

2011-04-14

259

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

260

The dynamics of hierarchical age-structured populations

An age-structured population is considered in which the birth and death rates of an individual of age a is a function of the density of individuals older and\\/or younger than a. An existence\\/uniqueness theorem is proved for the McKendrick equation that governs the dynamics of the age distribution function. This proof shows how a decoupled ordinary differential equation for the

J. M. Cushing

1994-01-01

261

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

262

Population Dynamics of Earthworms in Organic Farming Systems

\\u000a Earthworm population dynamics and diversity were evaluated in long-term farming systems experiments at the West Virginia University\\u000a Organic Research Farm from 2000 to 2007. Farming systems included vegetable and field crop rotations, with versus without\\u000a annual compost amendments. Field crop rotations with livestock included 3 years of clover grassland. Earthworms were monitored\\u000a by hand-sorting soil samples. Aporrectodea caliginosa and Lumbricus

James B. Kotcon

263

Interacting trophic forcing and the population dynamics of herring.

Small pelagic fish occupy a central position in marine ecosystems worldwide, largely by determining the energy transfer from lower trophic levels to predators at the top of the food web, including humans. Population dynamics of small pelagic fish may therefore be regulated neither strictly bottom-up nor top-down, but rather through multiple external and internal drivers. While in many studies single drivers have been identified, potential synergies of multiple factors, as well as their relative importance in regulating population dynamics of small pelagic fish, is a largely unresolved issue. Using a statistical, age-structured modeling approach, we demonstrate the relative importance and influence of bottom-up (e.g., climate, zooplankton availability) and top-down (i.e., fishing and predation) factors on the population dynamics of Bothnian Sea herring (Clupea harengus) throughout its life cycle. Our results indicate significant bottom-up effects of zooplankton and interspecific competition from sprat (Sprattus sprattus), particularly on younger age classes of herring. Although top-down forcing through fishing and predation by grey seals (Halichoerus grypus) and Atlantic cod (Gadus morhua) also was evident, these factors were less important than resource availability and interspecific competition. Understanding key ecological processes and interactions is fundamental to ecosystem-based management practices necessary to promote sustainable exploitation of small pelagic fish. PMID:21870614

Lindegren, Martin; Ostman, Orjan; Gĺrdmark, Anna

2011-07-01

264

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.

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

2010-01-01

265

Dynamic noise, chaos and parameter estimation in population biology.

We revisit the parameter estimation framework for population biological dynamical systems, and apply it to calibrate various models in epidemiology with empirical time series, namely influenza and dengue fever. When it comes to more complex models such as multi-strain dynamics to describe the virus-host interaction in dengue fever, even the most recently developed parameter estimation techniques, such as maximum likelihood iterated filtering, reach their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and the deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors. PMID:23565331

Stollenwerk, N; Aguiar, M; Ballesteros, S; Boto, J; Kooi, B; Mateus, L

2012-02-01

266

A Dose-Structured Population Dynamics Model for Outmigrant Salmon

NASA Astrophysics Data System (ADS)

The response of fish populations to differing levels of exposure to stressor chemical is commonly characterized using canonical dose-response models that are calibrated in laboratory (e.g., toxicological) studies. Use of such information in the study of migrating populations is difficult because dose received in the environment can vary greatly within a population due to the heterogeneity of the mixing between population members and stressor chemicals. Thus direct use of dose-response models is often predicated on assumptions of complete mixing in the environment. To relax this assumption it is required to devise an approach that keeps track of dose as a distributed quantity over a population. Here such a method is described that uses an added dimension of exposure-time to keep track of the mixing time, or dose, between outmigrant Fall Chinook Salmon and stressor organic contaminants. A mathematical model for the fish population dynamics is developed in the form of a first-order partial differential equation in multiple structural dimensions of dose, size, and age, in addition to space and time. A method-of-characteristics solution to the model under some simplifying conditions is presented and described. The results shed light on the nature of the distribution of outmigrant salmon over structural variables on arrival at the ocean.

Ginn, T. R.; Loge, F. J.

2004-12-01

267

Spatiotemporal dynamics of Puumala hantavirus in suburban reservoir rodent populations.

The transmission of pathogens to susceptible hosts is dependent on the vector population dynamics. In Europe, bank voles (Myodes glareolus) carry Puumala hantavirus, which causes nephropathia epidemica (NE) in humans. Fluctuations in bank vole populations and epidemics in humans are correlated but the main factors influencing this relationship remain unclear. In Belgium, more NE cases are reported in spring than in autumn. There is also a higher incidence of human infections during years of large vole populations. This study aimed to better understand the link between virus prevalence in the vector, vole demography, habitat quality, and human infections. Three rodent populations in different habitats bordering Brussels city, Belgium, were studied for two years. The seroprevalence in voles was influenced first by season (higher in spring), then by vole density, vole weight (a proxy for age), and capture site but not by year or sex. Moreover, voles with large maximal distance between two captures had a high probability for Puumala seropositivity. Additionally, the local vole density showed similar temporal variations as the number of NE cases in Belgium. These results showed that, while season was the main factor influencing vole seroprevalence, it was not sufficient to explain human risks. Indeed, vole density and weight, as well as the local habitat, were essential to understanding the interactions in these host-pathogen dynamics. This can, in turn, be of importance for assessing the human risks. PMID:23181849

Dobly, Alexandre; Yzoard, Chloé; Cochez, Christel; Ducoffre, Genevičve; Aerts, Marc; Roels, Stefan; Heyman, Paul

2012-12-01

268

Neural population modes capture biologically realistic large scale network dynamics.

Large scale brain networks are understood nowadays to underlie the emergence of cognitive functions, though the detailed mechanisms are hitherto unknown. The challenges in the study of large scale brain networks are amongst others their high dimensionality requiring significant computational efforts, the complex connectivity across brain areas and the associated transmission delays, as well as the stochastic nature of neuronal processes. To decrease the computational effort, neurons are clustered into neural masses, which then are approximated by reduced descriptions of population dynamics. Here, we implement a neural population mode approach (Assisi et al. in Phys. Rev. Lett. 94(1):018106, 2005; Stefanescu and Jirsa in PLoS Comput. Biol. 4(11):e1000219, 2008), which parsimoniously captures various types of population behavior. We numerically demonstrate that the reduced population mode system favorably captures the high-dimensional dynamics of neuron networks with an architecture involving homogeneous local connectivity and a large-scale, fiber-like connection with time delay. PMID:20821061

Jirsa, Viktor K; Stefanescu, Roxana A

2010-09-04

269

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

2012-03-23

270

Pattern formation and coexistence domains for a nonlocal population dynamics

NASA Astrophysics Data System (ADS)

In this Rapid Communication we propose a most general equation to study pattern formation for one-species populations and their limit domains in systems of length L. To accomplish this, we include nonlocality in the growth and competition terms, where the integral kernels now depend on characteristic length parameters ? and ?. Therefore, we derived a parameter space (?,?) where it is possible to analyze a coexistence curve ?*=?*(?) that delimits domains for the existence (or absence) of pattern formation in population dynamics systems. We show that this curve is analogous to the coexistence curve in classical thermodynamics and critical phenomena physics. We have successfully compared this model with experimental data for diffusion of Escherichia coli populations.

da Cunha, Jefferson A. R.; Penna, André L. A.; Oliveira, Fernando A.

2011-01-01

271

Dynamic transmission, host quality, and population structure in a multihost parasite of bumblebees.

The evolutionary ecology of multihost parasites is predicted to depend upon patterns of host quality and the dynamics of transmission networks. Depending upon the differences in host quality and transmission asymmetries, as well as the balance between intra- and interspecific transmission, the evolution of specialist or generalist strategies is predicted. Using a trypanosome parasite of bumblebees, we ask how host quality and transmission networks relate to parasite population structure across host species, and thus the potential for the evolution of specialist strains adapted to different host species. Host species differed in quality, with parasite growth varying across host species. Highly asymmetric transmission networks, together with differences in host quality, likely explain local population structure of the parasite across host species. However, parasite population structure across years was highly dynamic, with parasite populations varying significantly from one year to the next within individual species at a given site. This suggests that, while host quality and transmission may provide the opportunity for short-term host specialization by the parasite, repeated bottlenecking of the parasite, in combination with its own reproductive biology, overrides these smaller scale effects, resulting in the evolution of a generalist parasite. PMID:23025597

Ruiz-González, Mario X; Bryden, John; Moret, Yannick; Reber-Funk, Christine; Schmid-Hempel, Paul; Brown, Mark J F

2012-05-02

272

Dynamic modeling of vehicle populations: An engineering approach for emissions calculations

A model initially developed for forecasts of air pollutant emissions from motor vehicles is presented, with special emphasis on its vehicle dynamics module. Vehicle density forecasts are performed separately for passenger cars, trucks, buses, and motorcycles. Combined with estimates of vehicle usage parameters they are used to predict the total traffic volume up to the year 2010. The internal turnover of the vehicle fleet is simulated with a modified Weibull function, and the technology substitution process is determined nonanalytically. Although more refined approaches have been developed for the prediction of the dynamic behavior of car populations, the one presented here has been designed in such a way that it can be applied to countries where detailed information is lacking or too difficult to find, and even nonexperts can implement it reasonably well. 17 refs., 3 tabs., 4 figs.

Zachariadis, T.; Samaras, Z. [Aristotle Univ. of Thessaloniki (Greece); Zierock, K.H. [European Commission, Berlin (Germany)

1995-10-01

273

Uncertainty estimation and prediction for interdisciplinary ocean dynamics

Scientific computations for the quantification, estimation and prediction of uncertainties for ocean dynamics are developed and exemplified. Primary characteristics of ocean data, models and uncertainties are reviewed and quantitative data assimilation concepts defined. Challenges involved in realistic data-driven simulations of uncertainties for four-dimensional interdisciplinary ocean processes are emphasized. Equations governing uncertainties in the Bayesian probabilistic sense are summarized. Stochastic forcing formulations are introduced and a new stochastic-deterministic ocean model is presented. The computational methodology and numerical system, Error Subspace Statistical Estimation, that is used for the efficient estimation and prediction of oceanic uncertainties based on these equations is then outlined. Capabilities of the ESSE system are illustrated in three data-assimilative applications: estimation of uncertainties for physical-biogeochemical fields, transfers of ocean physics uncertainties to acoustics, and real-time stochastic ensemble predictions with assimilation of a wide range of data types. Relationships with other modern uncertainty quantification schemes and promising research directions are discussed.

Lermusiaux, Pierre F.J. [Harvard University, Division of Engineering and Applied Sciences, Pierce Hall G2A, 29 Oxford Street, Cambridge, MA 02318 (United States)]. E-mail: pierrel@pacific.harvard.edu

2006-09-01

274

Secondary seed dispersal is an important plant-animal interaction, which is central to understanding plant population and community dynamics. Very little information is still available on the effects of dispersal on plant demography and, particularly, for ant-seed dispersal interactions. As many other interactions, seed dispersal by animals involves costs (seed predation) and benefits (seed dispersal), the balance of which determines the outcome of the interaction. Separate quantification of each of them is essential in order to understand the effects of this interaction. To address this issue, we have successfully separated and analyzed the costs and benefits of seed dispersal by seed-harvesting ants on the plant population dynamics of three shrub species with different traits. To that aim a stochastic, spatially-explicit individually-based simulation model has been implemented based on actual data sets. The results from our simulation model agree with theoretical models of plant response dependent on seed dispersal, for one plant species, and ant-mediated seed predation, for another one. In these cases, model predictions were close to the observed values at field. Nonetheless, these ecological processes did not affect in anyway a third species, for which the model predictions were far from the observed values. This indicates that the balance between costs and benefits associated to secondary seed dispersal is clearly related to specific traits. This study is one of the first works that analyze tradeoffs of secondary seed dispersal on plant population dynamics, by disentangling the effects of related costs and benefits. We suggest analyzing the effects of interactions on population dynamics as opposed to merely analyzing the partners and their interaction strength. PMID:22880125

Arnan, Xavier; Molowny-Horas, Roberto; Rodrigo, Anselm; Retana, Javier

2012-08-07

275

Fish farms, parasites, and predators: implications for salmon population dynamics.

For some salmon populations, the individual and population effects of sea lice (Lepeophtheirus salmonis) transmission from sea cage salmon farms is probably mediated by predation, which is a primary natural source of mortality of juvenile salmon. We examined how sea lice infestation affects predation risk and mortality of juvenile pink (Oncorhynchus gorbuscha) and chum (O. keta) salmon, and developed a mathematical model to assess the implications for population dynamics and conservation. A risk-taking experiment indicated that infected juvenile pink salmon accept a higher predation risk in order to obtain foraging opportunities. In a schooling experiment with juvenile chum salmon, infected individuals had increased nearest-neighbor distances and occupied peripheral positions in the school. Prey selection experiments with cutthroat trout (O. clarkii) predators indicated that infection reduces the ability of juvenile pink salmon to evade a predatory strike. Group predation experiments with coho salmon (O. kisutch) feeding on juvenile pink or chum salmon indicated that predators selectively consume infected prey. The experimental results indicate that lice may increase the rate of prey capture but not the handling time of a predator. Based on this result, we developed a mathematical model of sea lice and salmon population dynamics in which parasitism affects the attack rate in a type II functional response. Analysis of the model indicates that: (1) the estimated mortality of wild juvenile salmon due to sea lice infestation is probably higher than previously thought; (2) predation can cause a simultaneous decline in sea louse abundance on wild fish and salmon productivity that could mislead managers and regulators; and (3) compensatory mortality occurs in the saturation region of the type II functional response where prey are abundant because predators increase mortality of parasites but not overall predation rates. These findings indicate that predation is an important component of salmon-louse dynamics and has implications for estimating mortality, reducing infection, and developing conservation policy. PMID:21639053

Krkosek, Martin; Connors, Brendan M; Ford, Helen; Peacock, Stephanie; Mages, Paul; Ford, Jennifer S; Morton, Alexandra; Volpe, John P; Hilborn, Ray; Dill, Lawrence M; Lewis, Mark A

2011-04-01

276

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

277

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

278

Microbial population dynamics of kimchi, a fermented cabbage product.

Lactic acid bacteria are known to perform significant roles in the fermentation of kimchi, a fermented cabbage product. However, the microbial population dynamics inherent to kimchi fermentation remain to be clearly elucidated. In this study, we have characterized the microbial dynamics via the identification of a total of 970 bacterial isolates, representing 15 species of the genera Lactobacillus, Leuconostoc, and Weissella, all of which were primarily identified by PCR-based restriction enzyme analysis. These population dynamics appear to be influenced markedly by fermentation temperature. Distinct biphasic microbial growth was observed with preliminary 2-day incubation at 15 degrees C, conducted before main fermentation at -1 degrees C. Leuconostoc citreum, as well as Leuconostoc gasicomitatum, predominated during the first growth phase, whereas Weissella koreensis predominated during the second phase. By way of contrast, with preliminary 4-day incubation at 10 degrees C, only W. koreensis grew rapidly from the beginning of the process. Therefore, our findings suggest that a short incubation at 15 degrees C enhances the growth of the less psychrophilic Leuconostoc species, including Lc. citreum, thus delaying the growth of the predominant W. koreensis, which is a more adaptive species at -1 degrees C. PMID:16553862

Cho, Jinhee; Lee, Dongyun; Yang, Changnam; Jeon, Jongin; Kim, Jeongho; Han, Hongui

2006-04-01

279

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

280

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

281

Evolution of the Known Centaurs Population - Dynamical and Thermal Pathways

NASA Astrophysics Data System (ADS)

The structural and thermal evolution of small Solar system bodies may be strongly dependent on their dynamical history and environment. Objects on planet-crossing orbits are prone to gravitational perturbations that de-stabilize their orbits. Such are the Centaurs, which are the transient population, between the relatively stable trans-Neptunian objects (TNOs) and the short-lived Jupiter family Comets (JFCs). This may indicate that these objects experience intermediate levels of internal processing, at different periods of their lives. Examining the evolution of several these Centaur objects, both in orbital and physical parameters, can help categorize the different states and origin and evolution scenarios in the outer Solar system. Determining the dynamical evolution of each object is achieved through statistical analysis of the results of multiple N-body integrations. This is achieved by using many clones of specific objects, with known orbital elements. Statistics of large clone samples of specific objects yield valuable information about their current states and future fates. Specifically, and with greater importance to thermal evolution, we focus on the dynamical lifetimes, survivability and mean orbital elements. The latter are considered during the relatively stable and non-diffusive phase of orbital evolution. Profiles of temperature, structure and composition are calculated utilizing our robust thermal evolution code several specific objects, which represent slightly varying dynamical groups, and for different orbits of the same object, which represent specific orbital evolution pathways. This has an influence on the internal stratified structure, through an adapting thermal response of the nucleus.

Sarid, Gal

2010-10-01

282

A Stochastic Super-Exponential Growth Model for Population Dynamics

NASA Astrophysics Data System (ADS)

A super-exponential growth model with environmental noise has been studied analytically. Super-exponential growth rate is a property of dynamical systems exhibiting endogenous nonlinear positive feedback, i.e., of self-reinforcing systems. Environmental noise acts on the growth rate multiplicatively and is assumed to be Gaussian white noise in the Stratonovich interpretation. An analysis of the stochastic super-exponential growth model with derivations of exact analytical formulae for the conditional probability density and the mean value of the population abundance are presented. Interpretations and various applications of the results are discussed.

Avila, P.; Rekker, A.

2010-11-01

283

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

284

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. PMID:22262814

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

2012-01-19

285

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. PMID:21193537

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

2010-12-30

286

Melting of genomic DNA: Predictive modeling by nonlinear lattice dynamics

NASA Astrophysics Data System (ADS)

The melting behavior of long, heterogeneous DNA chains is examined within the framework of the nonlinear lattice dynamics based Peyrard-Bishop-Dauxois (PBD) model. Data for the pBR322 plasmid and the complete T7 phage have been used to obtain model fits and determine parameter dependence on salt content. Melting curves predicted for the complete fd phage and the Y1 and Y2 fragments of the ?X174 phage without any adjustable parameters are in good agreement with experiment. The calculated probabilities for single base-pair opening are consistent with values obtained from imino proton exchange experiments.

Theodorakopoulos, Nikos

2010-08-01

287

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

288

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

289

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. PMID:20886099

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

2010-09-23

290

Fast stochastic algorithm for simulating evolutionary population dynamics

Motivation: Many important aspects of evolutionary dynamics can only be addressed through simulations. However, accurate simulations of realistically large populations over long periods of time needed for evolution to proceed are computationally expensive. Mutants can be present in very small numbers and yet (if they are more fit than others) be the key part of the evolutionary process. This leads to significant stochasticity that needs to be accounted for. Different evolutionary events occur at very different time scales: mutations are typically much rarer than reproduction and deaths. Results: We introduce a new exact algorithm for fast fully stochastic simulations of evolutionary dynamics that include birth, death and mutation events. It produces a significant speedup compared to direct stochastic simulations in a typical case when the population size is large and the mutation rates are much smaller than birth and death rates. The algorithm performance is illustrated by several examples that include evolution on a smooth and rugged fitness landscape. We also show how this algorithm can be adapted for approximate simulations of more complex evolutionary problems and illustrate it by simulations of a stochastic competitive growth model. Contact: ltsimring@ucsd.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Mather, William H.; Hasty, Jeff; Tsimring, Lev S.

2012-01-01

291

The model of fungal population dynamics affected by nystatin

NASA Astrophysics Data System (ADS)

Fungal diseases are acute problems of the up-to-day medicine. Significant increase of resistance of microorganisms to the medically used antibiotics and a lack of new effective drugs follows in a growth of dosage of existing chemicals to solve the problem. Quite often such approach results in side effects on humans. Detailed study of fungi-antibiotic dynamics can identify new mechanisms and bring new ideas to overcome the microbial resistance with a lower dosage of antibiotics. In this study, the dynamics of the microbial population under antibiotic treatment was investigated. The effects of nystatin on the population of Saccharomyces cerevisiae yeasts were used as a model system. Nystatin effects were investigated both in liquid and solid media by viability tests. Dependence of nystatin action on osmotic gradient was evaluated in NaCl solutions. Influences of glucose and yeast extract were additionally analyzed. A "stepwise" pattern of the cell death caused by nystatin was the most intriguing. This pattern manifested in periodical changes of the stages of cell death against stages of resistance to the antibiotic. The mathematical model was proposed to describe cell-antibiotic interactions and nystatin viability effects in the liquid medium. The model implies that antibiotic ability to cause a cells death is significantly affected by the intracellular compounds, which came out of cells after their osmotic barriers were damaged

Voychuk, Sergei I.; Gromozova, Elena N.; Sadovskiy, Mikhail G.

292

Folding and binding cascades: dynamic landscapes and population shifts.

Whereas previously we have successfully utilized the folding funnels concept to rationalize binding mechanisms (Ma B, Kumar S, Tsai CJ, Nussinov R, 1999, Protein Eng 12:713-720) and to describe binding (Tsai CJ, Kumar S, Ma B, Nussinov R, 1999, Protein Sci 8:1181-1190), here we further extend the concept of folding funnels, illustrating its utility in explaining enzyme pathways, multimolecular associations, and allostery. This extension is based on the recognition that funnels are not stationary; rather, they are dynamic, depending on the physical or binding conditions (Tsai CJ, Ma B, Nussinov R, 1999, Proc Natl Acad Sci USA 96:9970-9972). Different binding states change the surrounding environment of proteins. The changed environment is in turn expressed in shifted energy landscapes, with different shapes and distributions of populations of conformers. Hence, the function of a protein and its properties are not only decided by the static folded three-dimensional structure; they are determined by the distribution of its conformational substates, and in particular, by the redistributions of the populations under different environments. That is, protein function derives from its dynamic energy landscape, caused by changes in its surroundings.

Kumar, S.; Ma, B.; Tsai, C. J.; Sinha, N.; Nussinov, R.

2000-01-01

293

Naled is a commonly used insecticide for controlling populations of the oriental fruit fly, Bactrocera dorsalis (Hendel), in Taiwan and other countries. B. dorsalis has developed resistance to the insecticide, and the resistance management is an important issue. Ecological effects (e.g., fitness costs) of the resistance, when fully understood, can be used for the resistance management. This study examined the effects of the insecticide resistance on important life history traits (i.e., survival rates, stage durations, and fecundity) of the oriental fruit fly by comparing the traits of insecticide resistant individuals and susceptible individuals. Population dynamical properties were also examined using a stage-structured matrix model that was parameterized with the empirical data. The results revealed that susceptible individuals had shorter stage durations (e.g., grew faster) and reproduced more than resistant individuals. The average longevity of sexually mature susceptible adults was longer than that of sexually mature resistant adults. The matrix population model predicted that a population of the susceptible individuals would grow faster than a population of the resistant individuals in the absence of the insecticide. The sensitivity analysis of the model suggests that the sexually immature adult stage is a good candidate for controlling B. dorsalis populations. PMID:22299368

Fang, Chi-Chun; Okuyama, Toshinori; Wu, Wen-Jer; Feng, Hai-Tung; Hsu, Ju-Chun

2011-12-01

294

Population dynamics of long-tailed ducks breeding on the Yukon-Kuskokwim Delta, Alaska

Population estimates for long-tailed ducks in North America have declined by nearly 50% over the past 30 years. Life history and population dynamics of this species are difficult to ascertain, because the birds nest at low densities across a broad range of habitat types. Between 1991 and 2004, we collected information on productivity and survival of long-tailed ducks at three locations on the Yukon-Kuskokwim Delta. Clutch size averaged 7.1 eggs, and nesting success averaged 30%. Duckling survival to 30 days old averaged 10% but was highly variable among years, ranging from 0% to 25%. Apparent annual survival of adult females based on mark-recapture of nesting females was estimated at 74%. We combined these estimates of survival and productivity into a matrix-based population model, which predicted an annual population decline of 19%. Elasticities indicated that population growth rate (?) was most sensitive to changes in adult female survival. Further, the relatively high sensitivity of ? to duckling survival suggests that low duckling survival may be a bottleneck to productivity in some years. These data represent the first attempt to synthesize a population model for this species. Although our analyses were hampered by the small sample sizes inherent in studying a dispersed nesting species, our model provides a basis for management actions and can be enhanced as additional data become available.

Schamber, Jason L.; Flint, Paul L.; Grand, J. Barry; Wilson, Heather M.; Morse, Julie A.

2009-01-01

295

Predictions about sex-specific, spatial density-dependent dispersal and their demographic and genetic consequences were tested in experimental populations of root voles (Microtus oeconomus). Each population consisted of two demes inhabiting equal-sized habitat patches imbedded in a barren matrix area. We used a neutral two-allele allozyme marker to monitor gene flow. Initially, the two demes were genetically distinct and had different densities so that the size of a high-density deme (genotype bb) was four times larger than that of a low-density deme (genotype aa). The sex-specific dispersal pattern was in accordance with our prediction. Male dispersal was unconditional on deme-specific densities, and the majority of the first-generation males became dispersed from both demes, whereas female dispersal was strongly density dependent, so that dispersal took place exclusively from the high-density to the low-density deme. The demographic implication of this dispersal pattern was that the initial density difference between the demes was quickly canceled out. We built a mathematical model that predicted that the initially rare allele (a) would increase in frequency given the dispersal pattern, and this was supported by our experimental data. This result relies mostly on the density-independent male-dispersal strategy, which presumably stems from inbreeding avoidance. Our study highlights the importance of incorporating sex-specific dispersal strategies in population genetic models. Sex-biased dispersal may act as a deterministic force counteracting the tendency for stochastic loss of alleles in small and fragmented populations. PMID:10686164

Aars; Ims

2000-02-01

296

The population dynamics of fisheries stock enhancement, and its potential for generating benefits over and above those obtainable from optimal exploitation of wild stocks alone are poorly understood and highly controversial. I review pertinent knowledge of fish population biology, and extend the dynamic pool theory of fishing to stock enhancement by unpacking recruitment, incorporating regulation in the recruited stock, and accounting for biological differences between wild and hatchery fish. I then analyse the dynamics of stock enhancement and its potential role in fisheries management, using the candidate stock of North Sea sole as an example and considering economic as well as biological criteria. Enhancement through release of recruits or advanced juveniles is predicted to increase total yield and stock abundance, but reduce abundance of the naturally recruited stock component through compensatory responses or overfishing. Economic feasibility of enhancement is subject to strong constraints, including trade-offs between the costs of fishing and hatchery releases. Costs of hatchery fish strongly influence optimal policy, which may range from no enhancement at high cost to high levels of stocking and fishing effort at low cost. Release of genetically maladapted fish reduces the effectiveness of enhancement, and is most detrimental overall if fitness of hatchery fish is only moderately compromised. As a temporary measure for the rebuilding of depleted stocks, enhancement cannot substitute for effort limitation, and is advantageous as an auxiliary measure only if the population has been reduced to a very low proportion of its unexploited biomass. Quantitative analysis of population dynamics is central to the responsible use of stock enhancement in fisheries management, and the necessary tools are available.

Lorenzen, Kai

2005-01-01

297

Fast dynamics perturbation analysis for prediction of protein functional sites

Background We present a fast version of the dynamics perturbation analysis (DPA) algorithm to predict functional sites in protein structures. The original DPA algorithm finds regions in proteins where interactions cause a large change in the protein conformational distribution, as measured using the relative entropy Dx. Such regions are associated with functional sites. Results The Fast DPA algorithm, which accelerates DPA calculations, is motivated by an empirical observation that Dx in a normal-modes model is highly correlated with an entropic term that only depends on the eigenvalues of the normal modes. The eigenvalues are accurately estimated using first-order perturbation theory, resulting in a N-fold reduction in the overall computational requirements of the algorithm, where N is the number of residues in the protein. The performance of the original and Fast DPA algorithms was compared using protein structures from a standard small-molecule docking test set. For nominal implementations of each algorithm, top-ranked Fast DPA predictions overlapped the true binding site 94% of the time, compared to 87% of the time for original DPA. In addition, per-protein recall statistics (fraction of binding-site residues that are among predicted residues) were slightly better for Fast DPA. On the other hand, per-protein precision statistics (fraction of predicted residues that are among binding-site residues) were slightly better using original DPA. Overall, the performance of Fast DPA in predicting ligand-binding-site residues was comparable to that of the original DPA algorithm. Conclusion Compared to the original DPA algorithm, the decreased run time with comparable performance makes Fast DPA well-suited for implementation on a web server and for high-throughput analysis.

Ming, Dengming; Cohn, Judith D; Wall, Michael E

2008-01-01

298

Parsimonious snow model explains reindeer population dynamics and ranging behavior

NASA Astrophysics Data System (ADS)

Winter snow is a key factor affecting polar ecosystems. One example is the strong negative correlation of winter precipitation with fluctuations in population in some high-arctic animal populations. Ice layers within and at the base of the snowpack have particularly deleterious effects on such populations. Svalbard reindeer have small home ranges and are vulnerable to local "locked pasture" events due to ground-ice formation. When pastures are locked, reindeer are faced with the decision of staying, living off a diminishing fat store, or trying to escape beyond the unknown spatial borders of the ice. Both strategies may inhibit reproduction and increase mortality, leading to population declines. Here we assess the impact of winter snow and ice on the population dynamics of an isolated herd of Svalbard reindeer near Ny-Ĺlesund, monitored annually since 1978, with a retrospective analysis of the winter snowpack. Because there are no long-term observational records of snow or snow properties, such as ice layers, we must recourse to snowpack modeling. A parsimonious model of snow and ground-ice thickness is driven with daily temperature and precipitation data collected at a nearby weather station. The model uses the degree-day concept and has three adjustable parameters which are tuned to correlate model snow and ground-ice thicknesses to the limited observations available: April snow accumulation measurements on two local glaciers, and a limited number of ground-ice observations made in recent years. Parameter values used are comparable to those reported elsewhere. We find that modeled mean winter ground-ice thickness explains a significant percentage of the observed variance in reindeer population growth rate. Adding other explanatory parameters, such as modeled mean winter snowpack thickness or previous years' population size does not significanly improve the relation. Furthermore, positioning data from a small subset of reindeer show that model icing events are highly correlated to an immediate increase in range displacement between 5-day observations, suggesting that Svalbard reindeer use space opportunistically in winter, a behavioral trait that may buffer some of the negative effects of the expected climate change in the Arctic.

Kohler, J.; Aanes, R.; Hansen, B. B.; Loe, L.; Severinsen, T.; Stien, A.

2008-12-01

299

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

300

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

2013-04-09

301

A recently discovered population of the North American grey squirrel (Sciurus carolinen- sis), introduced to Ticino Park, Lombardy (N Italy), is likely to spread into continuous prealpine broadleaf forests of Lombardy and the south of Switzerland. We used GRASS GIS and Spatially Explicit Population Dynamics Models as a conservation tool to predict the spread of grey squirrels and to test

Clara Tattoni; Damiano G. Preatoni; Peter W. W. Lurz; Steven P. Rushton; Guido Tosi; Sandro Bertolino; Lucas A. Wauters

2004-01-01

302

Soay sheep on the island of Hirta exhibit periodic population collapses that have been proposed to result from nonlinear interactions between weather, population density, and age structure. Here we employ a diagnostic approach to reanalyze the data from 1985 to 2004 and find that climate mainly affects the equilibrium population size, thus acting as a lateral perturbation. From this, we derive a simple energetic model for a population interacting with its food supply in the presence of variable winter weather. This model explains the strong nonlinearity in the Soay sheep population regulation function and provides a framework for evaluating climatic perturbations. We examined two integrative climatic indexes, one representing effects on forage production and the other representing the severity of winter weather. Results suggest that the latter has the main effect on Soay sheep population dynamics. Models incorporating this variable provided fairly accurate predictions of Soay sheep population fluctuations. The diagnostic approach offers an objective way to develop simple, nonstructured population models that are useful for understanding the causes of population fluctuations and predicting population changes, provided they are based on a careful consideration of the underlying biological and/or ecological mechanisms. PMID:17109320

Berryman, Alan; Lima, Mauricio

2006-10-12

303

In this paper, we describe a technique to evaluate the evolutionary dynamics of the timing of spawning for iteroparous species. The life cycle of the species consists of three life stages, embryonic, juvenile and adult whereby the transitions of life stages (gametogenesis, birth and maturation) occur at species-specific sizes. The dynamics of the population is studied in a semi-chemostat environment where the inflowing food concentration is periodic (annual). A dynamic energy budget-based continuous-time model is used to describe the uptake of the food, storage in reserves and allocation of the energy to growth, maintenance, development (embryos, juveniles) and reproduction (adults). A discrete-event process is used for modelling reproduction. At a fixed spawning date of the year, the reproduction buffer is emptied and a new cohort is formed by eggs with a fixed size and energy content. The population consists of cohorts: for each year one consisting of individuals with the same age which die after their last reproduction event. The resulting mathematical model is a finite-dimensional set of ordinary differential equations with fixed 1-year periodic boundary conditions yielding a stroboscopic map. We will study the evolutionary development of the population using the adaptive dynamics approach. The trait is the timing of spawning. Pairwise and mutual invasibility plots are calculated using bifurcation analysis of the stroboscopic map. The evolutionary singular strategy value belonging to the evolutionary endpoint for the trait allows for an interpretation of the reproduction strategy of the population. In a case study, parameter values from the literature for the bivalve Macoma balthica are used.

Kooi, B. W.; van der Meer, J.

2010-01-01

304

The dynamics of an infectious disease in a population with birth pulses

In most models of population dynamics increases in population due to births are assumed to be time-independent, but many species of wild animal give birth only during a single period of the year. We propose a model for the dynamics of a fatal infectious disease in a wild animal population for which births occur in a single pulse once per

M. G. Roberts; R. R. Kao

1998-01-01

305

Analysis of urban - rural population dynamics of China: a multiregional life table approach

This is the second of two papers in which the urban - rural population dynamics of China is analyzed. Urban - rural population life tables are constructed in this paper. The differential urban and rural population dynamics are revealed by the calculations of life expectations, net reproduction expectations, and net migraproduction expectations in the urban and rural regions of China.

J Shen

1993-01-01

306

Climate variation and regional gradients in population dynamics of two hole-nesting passerines

Latitudinal gradients in population dynamics can arise through regional variation in the deterministic components of the population dynamics and the stochastic factors. Here, we demonstrate an increase with latitude in the contribution of a large-scale climate pattern, the North Atlantic Oscillation (NAO), to the fluctuations in size of populations of two European hole-nesting passerine species. However, this influence of climate

B.-E. Saether; Steinar Engen; A. P. Mřller; Erik Matthysen; Frank Adriaensen; Wolfgang Fiedler; Agu Leivits; Marcel M. Lambrechts; Marcel E. Visser; Tycho Anker-Nilssen; C. Both; A. A. Dhondt; R. H. McCleery; J. McMeeking; J. Potti; O. W. Rřstad; D. L. Thomson

2003-01-01

307

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

308

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. PMID:23437313

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

2013-02-21

309

Evolutionary dynamics of rhizopine within spatially structured rhizobium populations

Symbiosis between legumes and nitrogen-fixing bacteria is thought to bring mutual benefit to each participant. However, it is not known how rhizobia benefit from nodulating legume hosts because they fix nitrogen only after becoming bacteroids, which are terminally differentiated cells that cannot reproduce. Because undifferentiated rhizobia in and around the nodule can reproduce, evolution of symbiotic nitrogen fixation may depend upon kin selection. In some hosts, these kin may persist in the nodule as viable, undifferentiated bacteria. In other hosts, no viable rhizobia survive to reproduce after nodule senescence. Bacteroids in these hosts may benefit their free-living kin by enhancing production of plant root exudates. However, unrelated non-mutualists may also benefit from increased plant exudates. Rhizopines, compounds produced by bacteroids in nodules and catabolized only by related free-living rhizobia, may provide a mechanism by which bacteroids can preferentially benefit kin. Despite this apparent advantage, rhizopine genotypes are relatively rare. We constructed a mathematical model to examine how mixing within rhizobium populations influences the evolution of rhizopine genotypes. Our model predicts that the success of rhizopine genotypes is strongly dependent upon the spatial genetic structure of the bacterial population; rhizopine is more likely to dominate well-mixed populations. Further, for a given level of mixing, we find that rhizopine evolves under a positive frequency-dependent process in which stochastic accumulation of rhizopine alleles is necessary for rhizopine establishment. This process leads to increased spatial structure in rhizobium populations, and suggests that rhizopine may expand the conditions under which nitrogen fixation can evolve via kin selection.

Simms, E. L.; Bever, J. D.

1998-01-01

310

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

311

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

312

"Population dynamics of crustaceans": introduction to the symposium.

Crustaceans are a globally-distributed faunal group, found across all habitats from the equator to the poles. They are an ideal focal assemblage for assessment of the impacts of climatic change and anthropogenic disturbance on nonmodel systems, such as how sea currents influence the movements of zooplankton communities in the open ocean, or how ecosystem processes affect phytoplanktonic species with restricted geographic distributions across a cluster of island lakes that could be a new model system for studies of speciation. This symposium introduced early-career researchers working in the fields of phylogeography, ecogenomics, fisheries management, and ecosystem processes with the aim of highlighting the different genetic and ecological approaches to the study of population dynamics of freshwater, estuarine, and marine crustacean species. PMID:21856734

Buhay, Jennifer E

2011-08-19

313

Neural Population Dynamics Modeled by Mean-Field Graphs

NASA Astrophysics Data System (ADS)

In this work we apply random graph theory approach to describe neural population dynamics. There are important advantages of using random graph theory approach in addition to ordinary and partial differential equations. The mathematical theory of large-scale random graphs provides an efficient tool to describe transitions between high- and low-dimensional spaces. Recent advances in studying neural correlates of higher cognition indicate the significance of sudden changes in space-time neurodynamics, which can be efficiently described as phase transitions in the neuropil medium. Phase transitions are rigorously defined mathematically on random graph sequences and they can be naturally generalized to a class of percolation processes called neuropercolation. In this work we employ mean-field graphs with given vertex degree distribution and edge strength distribution. We demonstrate the emergence of collective oscillations in the style of brains.

Kozma, Robert; Puljic, Marko

2011-09-01

314

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

315

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

316

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...

317

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

318

Population dynamics in a metastable neon magneto-optical trap

NASA Astrophysics Data System (ADS)

We observe the population dynamics within a metastable neon magneto-optical trap (MOT) through the measurement of the average squared Clebsch-Gordan coefficient C2 over a range of laser detunings. The magnitude of C2 is dependent on the internal quantum state of an atom interacting with the light field and is found to show a strong dependence on the applied laser detuning. Previously it has been reported [Townsend , Phys. Rev. APLRAAN1050-294710.1103/PhysRevA.52.1423 52, 1423 (1995)] that trapped atoms in a MOT are pumped towards the states that interact most strongly with the local field and therefore the measured value of C2 is larger than the average over all possible transitions. For the 3P2-to-3D3 cooling transition in metastable neon the average C2 value is equal to 0.46; however, we have measured 0.29±0.03

Glover, R. D.; Calvert, J. E.; Sang, R. T.

2013-02-01

319

Postfire seedling dynamics and performance in Pinus halepensis Mill. populations

NASA Astrophysics Data System (ADS)

Postfire dynamics of Aleppo pine seedling density, survival and growth were assessed in five burned forests of Attica, Greece (Stamata, Villia, Avlona, Kapandriti and Agios Stefanos) through the establishment of permanent experimental plots. All emerging seedlings were tagged and their survival and growth monitored at regular intervals. Seedling density dynamics show an initial, steep increase (to maximum values 2.9-4.6 seedlings m -2) followed by a gradual decrease that levels off at the second and third postfire year (1.3-3.0 seedlings m -2); similarly, postfire seedling survival more or less stabilised at 30-50%, 2-3 years after fire. On the basis of density and mortality trends as well as relevant bibliographic data, it is predicted that very dense, mature forests (10.000 trees ha -1 or more) will be reinstated within 15-20 years. During the first 5-7 postfire years, seedling/sapling annual height followed linear trends with various yearly rates, ranging mostly between 8 and 15 cm (and 27-30 cm in two exceptional, fast growing cases). Within an individual growth season, seedling height dynamics were found to follow sigmoid curves with growth increment peaks in mid-spring. The time (on a monthly basis) of seedling emergence did not affect seedling growth or survival. On the other hand, for the first time under natural conditions, it has been shown that cotyledon number per seedling, an indirect measure of both seed size and initial photosynthetic capacity, significantly affected seedling survival but not growth. Seedlings bearing a higher number of cotyledons, presumably derived from larger seeds, showed greater survival at the end of the first postfire year than seedlings with fewer cotyledons. A postfire selective pressure, favouring large seed size, is postulated to counteract with a contrasting one, which favours small seed size, expressed during fire-free conditions.

Daskalakou, Evangelia N.; Thanos, Costas A.

2010-09-01

320

Prediction of the Madden-Julian oscillation with the POAMA dynamical prediction system

NASA Astrophysics Data System (ADS)

Predictions of the Madden-Julian oscillation (MJO) are assessed using a 10-member ensemble of hindcasts from POAMA, the Australian Bureau of Meteorology coupled ocean-atmosphere seasonal prediction system. The ensemble of hindcasts was initialised from observed atmosphere and ocean initial conditions on the first of each month during 1980-2006. The MJO is diagnosed using the Wheeler-Hendon Real-time Multivariate MJO (RMM) index, which involves projection of daily data onto the leading pair of eigenmodes from an analysis of zonal winds at 200 and 850 hPa and outgoing longwave radiation (OLR) averaged about the equator. Forecasts of the two component (RMM1 and RMM2) index are quantitatively compared with observed behaviour derived from NCEP reanalyses and satellite OLR using the bivariate correlation skill, root-mean-square error (RMSE), and measures of the MJO amplitude and phase error. Comparison is also made with a simple vector autoregressive (VAR) prediction model of RMM as a benchmark. Using the full hindcast set, we find that the MJO can be predicted with the POAMA ensemble out to about 21 days as measured by the bivariate correlation exceeding 0.5 and the bivariate RMSE remaining below ~1.4 (which is the value for a climatological forecast). The VAR model, by comparison, drops to a correlation of 0.5 by about 12 days. The prediction limit from POAMA increases by less than 2 days for times when the MJO has large initial amplitude, and has little sensitivity to the initial phase of the MJO. The VAR model, on the other hand, shows a somewhat larger increase in skill for times of strong MJO variability and has greater sensitivity to initial phase, with lower skill for times when MJO convection is developing in the Indian Ocean. The sensitivity to season is, however, greater for POAMA, with maximum skill occurring in the December-January-February season and minimum skill in June-July-August. Examination of the MJO amplitudes shows that individual POAMA members have slightly above observed amplitude after a spin-up of about 10 days, whereas examination of the MJO phase error reveals that the model has a consistent tendency to propagate the MJO slightly slower than observed. Finally, an estimate of potential predictability of the MJO in POAMA hindcasts suggests that actual MJO prediction skill may be further improved through continued development of the dynamical prediction system.

Rashid, Harun A.; Hendon, Harry H.; Wheeler, Matthew C.; Alves, Oscar

2011-02-01

321

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.

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

2011-01-01

322

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; Anglčs, Sílvia; Garcés, Esther

2010-02-01

323

Dynamics of Double Subduction: Numerical Predictions and Critical Observations.

NASA Astrophysics Data System (ADS)

Double subduction is a complex geodynamic process in which two plates following each other are synchronously subducted in the same direction. Double subduction episodes are characteristic for both modern and ancient plate tectonics and are, in particular, inferred in the history of the Himalayan collision zone. However, our knowledge about this process is limited by conceptual schemes and double subduction remains unexplained in terms of physical factors controlling its initiation, duration, dynamics as well as its relation to magmatic activity. We present first results on numerical simulation of double subduction process. Our current high-resolution 2D coupled geochemical-petrological-thermomechanical numerical model employs visco-plastic rheology of rocks and allows simultaneous treatment of heat, mass and water transport, metamorphic phase transformation, partial melting and melt extraction. We studied the influence of different physical factors on initiation, duration and dynamics of the process. In particular we explored the effect of varying convergence rate (0.0 - 7.0 cm/yr), age of the slab (10 - 100 Myrs), water propagation velocity (0 - 10 cm/yr) and dislocation creep activation volume (0.6 - 1.0 J/bar). Depending on these physical parameters (primarily on dimensionless ratio between convergence rate and water percolation velocity) numerical experiments show large variations in double subduction dynamics characterized by (i) different amount of shortening/extension in two simultaneously developing subduction zones, (ii) strong spatial and temporal oscillations of magmatic productivity (separated magmatic episodes) within two parallel volcanic arcs, and (iii) different modes of interaction of two subducting slabs (penetrating/non- penetrating) with the 660 km discontinuity. We compare numerical results with two geologically and geophysically investigated examples of double subduction: the past Karakoram and Kohistan Arcs and the active Izu-Bonin- Marianas and Ryukyu Arcs. Numerical predictions show important similarities with geological information and shed new light in interpreting the natural case stories. In particular, they allow deciphering magmatic and structural/kinematic interplays during double subduction tectonics.

Mishin, Y.; Gerya, T.; Burg, J.

2007-12-01

324

HLA-DP2 binding prediction by molecular dynamics simulations

Major histocompatibility complex (MHC) II proteins bind peptide fragments derived from pathogen antigens and present them at the cell surface for recognition by T cells. MHC proteins are divided into Class I and Class II. Human MHC Class II alleles are grouped into three loci: HLA-DP, HLA-DQ, and HLA-DR. They are involved in many autoimmune diseases. In contrast to HLA-DR and HLA-DQ proteins, the X-ray structure of the HLA-DP2 protein has been solved quite recently. In this study, we have used structure-based molecular dynamics simulation to derive a tool for rapid and accurate virtual screening for the prediction of HLA-DP2-peptide binding. A combinatorial library of 247 peptides was built using the “single amino acid substitution” approach and docked into the HLA-DP2 binding site. The complexes were simulated for 1 ns and the short range interaction energies (Lennard–Jones and Coulumb) were used as binding scores after normalization. The normalized values were collected into quantitative matrices (QMs) and their predictive abilities were validated on a large external test set. The validation shows that the best performing QM consisted of Lennard–Jones energies normalized over all positions for anchor residues only plus cross terms between anchor-residues.

Doytchinova, Irini; Petkov, Peicho; Dimitrov, Ivan; Atanasova, Mariyana; Flower, Darren R

2011-01-01

325

Bats face unprecedented threats from habitat loss, climate change, disease, and wind power development, and populations of many species are in decline. A better ability to quantify bat population status and trend is urgently needed in order to develop effective conservation strategies. We used a Bayesian autoregressive approach to develop dynamic distribution models for Myotis lucifugus, the little brown bat, across a large portion of northwestern USA, using a four-year detection history matrix obtained from a regional monitoring program. This widespread and abundant species has experienced precipitous local population declines in northeastern USA resulting from the novel disease white-nose syndrome, and is facing likely range-wide declines. Our models were temporally dynamic and accounted for imperfect detection. Drawing on species-energy theory, we included measures of net primary productivity (NPP) and forest cover in models, predicting that M. lucifugus occurrence probabilities would covary positively along those gradients. Despite its common status, M. lucifugus was only detected during -50% of the surveys in occupied sample units. The overall naive estimate for the proportion of the study region occupied by the species was 0.69, but after accounting for imperfect detection, this increased to -0.90. Our models provide evidence of an association between NPP and forest cover and M. lucifugus distribution, with implications for the projected effects of accelerated climate change in the region, which include net aridification as snowpack and stream flows decline. Annual turnover, the probability that an occupied sample unit was a newly occupied one, was estimated to be low (-0.04-0.14), resulting in flat trend estimated with relatively high precision (SD = 0.04). We mapped the variation in predicted occurrence probabilities and corresponding prediction uncertainty along the productivity gradient. Our results provide a much needed baseline against which future anticipated declines in M. lucifugus occurrence can be measured. The dynamic distribution modeling approach has broad applicability to regional bat monitoring efforts now underway in several countries and we suggest ways to improve and expand our grid-based monitoring program to gain robust insights into bat population status and trend across large portions of North America. PMID:22827121

Rodhouse, Thomas J; Ormsbee, Patricia C; Irvine, Kathryn M; Vierling, Lee A; Szewczak, Joseph M; Vierling, Kerri T

2012-06-01

326

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

327

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...

328

Summary 1. A general problem in population ecology is to predict under which conditions stochastic variation in the environment has the stronger effect on ecological processes. By analysing temporal variation in a fitness-related trait, body mass, in 21 Norwegian moose Alces alces (L.) populations, we examined whether the influence of temporal variation in different environmental variables were related to different

IVAR HERFINDAL; BERNT-ERIK SAETHER; ERLING JOHAN SOLBERG; REIDAR ANDERSEN; KJELL ARILD HŘGDA

2006-01-01

329

Background. A valid and practical measure of comor- bid illness burden in dialysis populations is greatly needed to enable unbiased comparisons of clinical out- comes. We compare the discriminatory accuracy of 1 year mortality predictions derived from four comor- bidity instruments in a large representative US dialysis population. Methods. Comorbidity information was collected using the Index of Coexistent Diseases (ICED)

Dana C. Miskulin; Alice A. Martin; Richard Brown; Nancy E. Fink; Josef Coresh; Neil R. Powe; Philip G. Zager; Klemens B. Meyer; Andrew S. Levey

330

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

331

National Technical Information Service (NTIS)

The report gives results of a study to: (1) develop a mathematical model describing fish populations as a function of life process dynamics and facilities that impose additional mortality on fish populations; and (2) improve objective impingement impact p...

P. A. Hackney T. A. McDonough D. L. DeAngelis M. E. Cochran

1980-01-01

332

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

333

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

334

The impact of population dynamics on public policy: the perspective of political gerontology.

Dramatic increases in the proportion of older persons in the U.S. is an area of profound and direct political and policy impact; not only are there increasing numbers of older persons, but the politically relevant characteristics of tomorrow's elderly differentiate them from today's and yesterday's elderly. Recent findings are summarized which contradict the view that the aged and the issue of aging are not increasingly salient aspects of politics in the U.S. A brief consideration of the Social Security issue highlights the potential importance of this issue. The changing age structure of the population summarized in the Old-Age Dependency Ratios is seen as more relevant to the possible conflict over policy allocations than is the scenario described by the Total Dependency Ratios. With respect to the cohort concept of age group differences and age-group phenomena, the flow of cohorts through the population system represents the succession of potentially unique generational entities whose characteristics and location in the flow of population can substantially influence society and politics. The most explosive policy issue deriving from the changing age structure of the American population surrounds the national Social Security system, while operational solutions for predicted Social Security "bankruptcy" might be fiscal or economic in nature, the fundamental decisions are derived from political philosophy and political influence. Policy responses to demographic pressure will be a product of political dynamics, and the following areas of political inquiry describe the likely foundation of old-age influence upon American politics: 1) political participation; 2) political attitudes; 3) partisan flexibility; and 4) organizational activity. Predictions that population patterns are likely to produce political controversies, and that in this context, age is likely to grow as a political issue, should not be surprising. PMID:11632723

Cutler, N E

1977-01-01

335

The demographic drivers of local population dynamics in two rare migratory birds

The exchange of individuals among populations can have strong effects on the dynamics and persistence of a given population.\\u000a Yet, estimation of immigration rates remains one of the greatest challenges for animal demographers. Little empirical knowledge\\u000a exists about the effects of immigration on population dynamics. New integrated population models fitted using Bayesian methods\\u000a enable simultaneous estimation of fecundity, survival and

Michael SchaubThomas; Thomas S. Reichlin; Fitsum Abadi; Marc Kéry; Lukas Jenni; Raphaël Arlettaz

336

Review of the interplay between population dynamics and malaria transmission in Ethiopia

Background: The rapid growth of human population in malaria endemic areas has become a threat leading to the resurgence of the disease. Population growth and ecological changes in malarious areas have important implications for malaria control due to the adverse effects of the disease on the population. Objective: To examine the relationship between different aspects of population dynamics and malaria

Wakgari Deressa; Ahmed Ali; Yemane Berhane

337

Annual monitoring of the population dynamics of the oriental fruit fly, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) using methyl eugenol-baited traps was conducted throughout the year during 1997, 2000, 2003 and 2004 in Ruili, Yunnan Province, China. Temperature, rainfall and host-plant species were analyzed with respect to population fluctuation of the fly. During the study periods the fruit fly occurred throughout

Peng Chen; Hui Ye; Jianhong Liu

2006-01-01

338

The interest of environmental management is in the long-term health of populations and ecosystems. However, toxicity is usually assessed in short-term experiments with individuals. Modelling based on dynamic energy budget (DEB) theory aids the extraction of mechanistic information from the data, which in turn supports educated extrapolation to the population level. To illustrate the use of DEB models in this extrapolation, we analyse a dataset for life cycle toxicity of copper in the earthworm Dendrobaena octaedra. We compare four approaches for the analysis of the toxicity data: no model, a simple DEB model without reserves and maturation (the Kooijman–Metz formulation), a more complex one with static reserves and simplified maturation (as used in the DEBtox software) and a full-scale DEB model (DEB3) with explicit calculation of reserves and maturation. For the population prediction, we compare two simple demographic approaches (discrete time matrix model and continuous time Euler–Lotka equation). In our case, the difference between DEB approaches and population models turned out to be small. However, differences between DEB models increased when extrapolating to more field-relevant conditions. The DEB3 model allows for a completely consistent assessment of toxic effects and therefore greater confidence in extrapolating, but poses greater demands on the available data.

Jager, Tjalling; Klok, Chris

2010-01-01

339

Nonlinearities Lead to Qualitative Differences in Population Dynamics of Predator-Prey Systems

Since typically there are many predators feeding on most herbivores in natural communities, understanding multiple predator effects is critical for both community and applied ecology. Experiments of multiple predator effects on prey populations are extremely demanding, as the number of treatments and the amount of labour associated with these experiments increases exponentially with the number of species in question. Therefore, researchers tend to vary only presence/absence of the species and use only one (supposedly realistic) combination of their numbers in experiments. However, nonlinearities in density dependence, functional responses, interactions between natural enemies etc. are typical for such systems, and nonlinear models of population dynamics generally predict qualitatively different results, if initial absolute densities of the species studied differ, even if their relative densities are maintained. Therefore, testing combinations of natural enemies without varying their densities may not be sufficient. Here we test this prediction experimentally. We show that the population dynamics of a system consisting of 2 natural enemies (aphid predator Adalia bipunctata (L.), and aphid parasitoid, Aphidius colemani Viereck) and their shared prey (peach aphid, Myzus persicae Sulzer) are strongly affected by the absolute initial densities of the species in question. Even if their relative densities are kept constant, the natural enemy species or combination thereof that most effectively suppresses the prey may depend on the absolute initial densities used in the experiment. Future empirical studies of multiple predator – one prey interactions should therefore use a two-dimensional array of initial densities of the studied species. Varying only combinations of natural enemies without varying their densities is not sufficient and can lead to misleading results.

Ameixa, Olga M. C. C.; Messelink, Gerben J.; Kindlmann, Pavel

2013-01-01

340

Nonlinearities lead to qualitative differences in population dynamics of predator-prey systems.

Since typically there are many predators feeding on most herbivores in natural communities, understanding multiple predator effects is critical for both community and applied ecology. Experiments of multiple predator effects on prey populations are extremely demanding, as the number of treatments and the amount of labour associated with these experiments increases exponentially with the number of species in question. Therefore, researchers tend to vary only presence/absence of the species and use only one (supposedly realistic) combination of their numbers in experiments. However, nonlinearities in density dependence, functional responses, interactions between natural enemies etc. are typical for such systems, and nonlinear models of population dynamics generally predict qualitatively different results, if initial absolute densities of the species studied differ, even if their relative densities are maintained. Therefore, testing combinations of natural enemies without varying their densities may not be sufficient. Here we test this prediction experimentally. We show that the population dynamics of a system consisting of 2 natural enemies (aphid predator Adalia bipunctata (L.), and aphid parasitoid, Aphidius colemani Viereck) and their shared prey (peach aphid, Myzus persicae Sulzer) are strongly affected by the absolute initial densities of the species in question. Even if their relative densities are kept constant, the natural enemy species or combination thereof that most effectively suppresses the prey may depend on the absolute initial densities used in the experiment. Future empirical studies of multiple predator - one prey interactions should therefore use a two-dimensional array of initial densities of the studied species. Varying only combinations of natural enemies without varying their densities is not sufficient and can lead to misleading results. PMID:23638107

Ameixa, Olga M C C; Messelink, Gerben J; Kindlmann, Pavel

2013-04-25

341

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

342

Orbital decay prediction for the Relay Mirror Experiment using static and dynamic atmospheric models

This study compares the performance of static and dynamic atmospheric density models as used for predicting decay of an orbiting vehicle. The greatest source of error in low earth orbit prediction is from atmospheric density prediction and modeling. This study provides insight to the effect of unpredictable solar activity on orbit decay predictions. Observations were collected from two independent tracking

Richard L. Fennessey; Mark A. Reynolds; Daniel E. Snow

1993-01-01

343

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

344

Predicting Movie Prices Through Dynamic Social Network Analysis

This paper explores the effectiveness of social network analysis and sentiment analysis in predicting trends. Our research focuses on predicting the success of new movies over their first four weeks in the box office after opening. Specifically, we try to predict prices on the Hollywood Stock Exchange (HSX), a prediction market on movie gross income, and predict the ratio of

Lyric Doshi; Jonas Krauss; Stefan Nann; Peter Gloor

2010-01-01

345

THE POPULATION DYNAMICS OF VARROA MITES IN HONEY BEE COLONIES: PART 1 - THE VARROA POP PROGRAM

Technology Transfer Automated Retrieval System (TEKTRAN)

A mathematical model of population interactions between Varroa destructor and a honey bee colony is described. The program bases colony population growth on weather conditions, time of year, initial colony population size, queen fecundity, and worker longevity. Varroa population growth is predicte...

346

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. PMID:23390602

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

2013-02-01

347

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

348

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

349

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. PMID:21775327

Russell, James C; Ruffino, Lise

2011-07-20

350

Population dynamics and environmental degradation in Nepal: An interpretation

When the relationship between population and environment is examined, and the central role in global consumption of natural resources played by the 15 percent of global population living in the developed world is acknowledged, the relationship between population growth in developing countries and the natural resource base on which the majority of the global population currently depends for daily survival

Yagya Bahadur Karki

1993-01-01

351

Review of Gizzard Shad Population Dynamics at the Northwestern Edge of Its Range

Gizzard shad Dorosoma cepedianum is widely distributed in North America, and South Dakota marks the northwestern edge of its native range. To date, most research regarding population dynamics of gizzard shad has been con- ducted in more southerly waters. We reviewed the dynamics and biology of giz- zard shad populations in South Dakota and compared this information with that reported

Melissa R. Wuellne R; W. Willis

352

The population dynamics of fisheries stock enhancement, and its potential for generating benefits over and above those obtainable from optimal exploitation of wild stocks alone are poorly understood and highly con- troversial. I review pertinent knowledge of fish population biology, and extend the dynamic pool theory of fishing to stock enhancement by unpacking recruitment, incorporating regulation in the recruited stock,

Kai Lorenzen

2005-01-01

353

Aircraft T-tail flutter predictions using computational fluid dynamics

NASA Astrophysics Data System (ADS)

The paper presents the application of computational aeroelasticity (CA) methods to the analysis of a T-tail stability in transonic regime. For this flow condition unsteady aerodynamics show a significant dependency from the aircraft equilibrium flight configuration, which rules both the position of shock waves in the flow field and the load distribution on the horizontal tail plane. Both these elements have an influence on the aerodynamic forces, and so on the aeroelastic stability of the system. The numerical procedure proposed allows to investigate flutter stability for a free-flying aircraft, iterating until convergence the following sequence of sub-problems: search for the trimmed condition for the deformable aircraft; linearize the system about the stated equilibrium point; predict the aeroelastic stability boundaries using the inferred linear model. An innovative approach based on sliding meshes allows to represent the changes of the computational fluid domain due to the motion of control surfaces used to trim the aircraft. To highlight the importance of keeping the linear model always aligned to the trim condition, and at the same time the capabilities of the computational fluid dynamics approach, the method is applied to a real aircraft with a T-tail configuration: the P180.

Attorni, A.; Cavagna, L.; Quaranta, G.

2011-02-01

354

Prediction of the Interactive Dynamics of Stimulated Emotions: Chaos, Limit Cycles and Stability

The paper attempts to model the interactive dynamics of competitive\\/co-operative emotions, aroused by audio-visual stimulus. Parameter variations of the dynamics results in three specific dynamic behavior including chaos, limit cycles and stability. An analysis of the dynamics yields the parametric conditions for stability and chaos. Known audio-visual stimulus is used to predict the emotive state of the dynamics from the

Madhumala Ghosh; Aruna Chakraborty; Amit Konar; Atulya Nagar

2008-01-01

355

The question of how the structure of a neuronal network affects its functionality has gained a lot of attention in neuroscience. However, the vast majority of the studies on structure-dynamics relationships consider few types of network structures and assess limited numbers of structural measures. In this in silico study, we employ a wide diversity of network topologies and search among many possibilities the aspects of structure that have the greatest effect on the network excitability. The network activity is simulated using two point-neuron models, where the neurons are activated by noisy fluctuation of the membrane potential and their connections are described by chemical synapse models, and statistics on the number and quality of the emergent network bursts are collected for each network type. We apply a prediction framework to the obtained data in order to find out the most relevant aspects of network structure. In this framework, predictors that use different sets of graph-theoretic measures are trained to estimate the activity properties, such as burst count or burst length, of the networks. The performances of these predictors are compared with each other. We show that the best performance in prediction of activity properties for networks with sharp in-degree distribution is obtained when the prediction is based on clustering coefficient. By contrast, for networks with broad in-degree distribution, the maximum eigenvalue of the connectivity graph gives the most accurate prediction. The results shown for small ([Formula: see text]) networks hold with few exceptions when different neuron models, different choices of neuron population and different average degrees are applied. We confirm our conclusions using larger ([Formula: see text]) networks as well. Our findings reveal the relevance of different aspects of network structure from the viewpoint of network excitability, and our integrative method could serve as a general framework for structure-dynamics studies in biosciences. PMID:23935998

Mäki-Marttunen, Tuomo; A?imovi?, Jugoslava; Ruohonen, Keijo; Linne, Marja-Leena

2013-07-25

356

Structure-Dynamics Relationships in Bursting Neuronal Networks Revealed Using a Prediction Framework

The question of how the structure of a neuronal network affects its functionality has gained a lot of attention in neuroscience. However, the vast majority of the studies on structure-dynamics relationships consider few types of network structures and assess limited numbers of structural measures. In this in silico study, we employ a wide diversity of network topologies and search among many possibilities the aspects of structure that have the greatest effect on the network excitability. The network activity is simulated using two point-neuron models, where the neurons are activated by noisy fluctuation of the membrane potential and their connections are described by chemical synapse models, and statistics on the number and quality of the emergent network bursts are collected for each network type. We apply a prediction framework to the obtained data in order to find out the most relevant aspects of network structure. In this framework, predictors that use different sets of graph-theoretic measures are trained to estimate the activity properties, such as burst count or burst length, of the networks. The performances of these predictors are compared with each other. We show that the best performance in prediction of activity properties for networks with sharp in-degree distribution is obtained when the prediction is based on clustering coefficient. By contrast, for networks with broad in-degree distribution, the maximum eigenvalue of the connectivity graph gives the most accurate prediction. The results shown for small () networks hold with few exceptions when different neuron models, different choices of neuron population and different average degrees are applied. We confirm our conclusions using larger () networks as well. Our findings reveal the relevance of different aspects of network structure from the viewpoint of network excitability, and our integrative method could serve as a general framework for structure-dynamics studies in biosciences.

Maki-Marttunen, Tuomo; Acimovic, Jugoslava; Ruohonen, Keijo; Linne, Marja-Leena

2013-01-01

357

Despite various attempts to establish population models as standard tools in pesticide risk assessment, population models still receive limited acceptance by risk assessors and authorities in Europe. A main criticism of risk assessors is that population models are often not, or not sufficiently, validated. Hence the realism of population-level risk assessments conducted with such models remains uncertain. We therefore developed an individual-based population model for the common vole, Microtus arvalis, and demonstrate how population models can be validated in great detail based on published data. The model is developed for application in pesticide risk assessment, therefore, the validation covers all areas of the biology of the common vole that are relevant for the analysis of potential effects and recovery after application of pesticides. Our results indicate that reproduction, survival, age structure, spatial behavior, and population dynamics reproduced from the model are comparable to field observations. Also interannual population cycles, which are frequently observed in field studies of small mammals, emerge from the population model. These cycles were shown to be caused by the home range behavior and dispersal. As observed previously in the field, population cycles in the model were also stronger for longer breeding season length. Our results show how validation can help to evaluate the realism of population models, and we discuss the importance of taking field methodology and resulting bias into account. Our results also demonstrate how population models can help to test or understand biological mechanisms in population ecology. PMID:23086922

Wang, Magnus

2013-02-19

358

1. The role of climate variability in determining the spatial and temporal patterns of numerical fluctuations is a central problem in ecology. The influence of the North Atlantic Oscillation (NAO) index on the population dynamics and spatial synchrony of the green spruce aphid Elatobium abietinum across the UK was shown. 2. Fifteen overlapping time series within the UK were analysed; we used nonparametric models for determining the feedback nonlinear structure and the climatic effects. The spatial synchrony of these populations and the relationship between synchrony and NAO was estimated. 3. From the 15 time series across the UK, 11 showed positive and significant NAO effects. In most of the cases the NAO effects were nonlinear showing strong negative effects of low values. The NAO variation improve the explained variance of the first-order feedback models in 14.5%; ranging from 0% to 48%. All data showed strong-nonlinear (concave) feedback structure. In most of the localities the explained variance by the first-order feedback was about 50-60%. 4. The spatial synchrony of the per capita growth rates and residuals is high across long distances for those populations affected by NAO. The correlation function predicts a spatial scale of synchrony of about 350-400 km for NAO influenced populations. 5. We think that simple population theoretical models describing the link between NAO fluctuations and green spruce aphid dynamics may be fundamental for predicting and simulating the consequences of different climatic scenarios of the future. PMID:17584384

Saldańa, Silverio; Lima, Mauricio; Estay, Sergio

2007-07-01

359

Human cases of hantavirus pulmonary syndrome caused by Sin Nombre virus are the endpoint of complex ecological cascade from weather conditions, population dynamics of deer mice, to prevalence of SNV in deer mice. Using population trajectories from the literature and mathematical modeling, we analyze the time lag between deer mouse population peaks and peaks in SNV antibody prevalence in deer mice. Because the virus is not transmitted vertically, rapid population growth can lead initially to reduced prevalence, but the resulting higher population size may later increase contact rates and generate increased prevalence. Incorporating these factors, the predicted time lag ranges from 0 to 18 months, and takes on larger values when host population size varies with a longer period or higher amplitude, when mean prevalence is low and when transmission is frequency-dependent. Population size variation due to variation in birth rates rather than death rates also increases the lag. Predicting future human outbreaks of hantavirus pulmonary syndrome may require taking these effects into account. PMID:17701378

Adler, Frederick R; Pearce-Duvet, Jessica M C; Dearing, M Denise

2007-08-16

360

We develop a set of equations to describe the population dynamics of many interacting species in food webs. Predator-prey interactions are nonlinear, and are based on ratio-dependent functional responses. The equations account for competition for resources between members of the same species, and between members of different species. Predators divide their total hunting/foraging effort between the available prey species according to an evolutionarily stable strategy (ESS). The ESS foraging behaviour does not correspond to the predictions of optimal foraging theory. We use the population dynamics equations in simulations of the Webworld model of evolving ecosystems. New species are added to an existing food web due to speciation events, whilst species become extinct due to coevolution and competition. We study the dynamics of species-diversity in Webworld on a macro-evolutionary time-scale. Coevolutionary interactions are strong enough to cause continuous overturn of species, in contrast to our previous Webworld simulations with simpler population dynamics. Although there are significant fluctuations in species diversity because of speciation and extinction, very large-scale extinction avalanches appear to be absent from the dynamics, and we find no evidence for self-organized criticality. PMID:11162055

Drossel, B; Higgs, P G; McKane, A J

2001-01-01

361

Crosses between populations or species often display an asymmetry in the fitness of reciprocal F1 hybrids. This pattern, referred to as isolation asymmetry or Darwin's Corollary to Haldane's Rule, has been observed in taxa from plants to vertebrates, yet we still know little about which factors determine its magnitude and direction. Here, we show that differences in offspring size predict the direction of isolation asymmetry observed in crosses between populations of a placental fish, Heterandria formosa. In crosses between populations with differences in offspring size, high rates of hybrid inviability occur only when the mother is from a population characterized by small offspring. Crosses between populations that display similarly sized offspring, whether large or small, do not result in high levels of hybrid inviability in either direction. We suggest this asymmetric pattern of reproductive isolation is due to a disruption of parent-offspring coadaptation that emerges from selection for differently sized offspring in different populations. PMID:23883573

Schrader, Matthew; Fuller, Rebecca C; Travis, Joseph

2013-07-24

362

Postcollapse dynamics of self-gravitating Brownian particles and bacterial populations

NASA Astrophysics Data System (ADS)

We address the postcollapse dynamics of a self-gravitating gas of Brownian particles in D dimensions in both canonical and microcanonical ensembles. In the canonical ensemble, the postcollapse evolution is marked by the formation of a Dirac peak with increasing mass. The density profile outside the peak evolves self-similarly with decreasing central density and increasing core radius. In the microcanonical ensemble, the postcollapse regime is marked by the formation of a “binarylike” structure surrounded by an almost uniform halo with high temperature. These results are consistent with thermodynamical predictions in astrophysics. We also show that the Smoluchowski-Poisson system describing the collapse of self-gravitating Brownian particles in a strong-friction limit is isomorphic to a simplified version of the Keller-Segel equations describing the chemotactic aggregation of bacterial populations. Therefore, our study has direct applications in this biological context.

Sire, Clément; Chavanis, Pierre-Henri

2004-06-01

363

Plant litter feedback and population dynamics in an annual plant, Cardamine pensylvanica

The presence of litter has the potential to alter the population dynamics of plants. In this paper, we explore the effects\\u000a of litter on population dynamics using a simple experimental laboratory system with populations of the annual crucifer, Cardamine pensylvanica. Using a factorial experiment with four densities and three litter levels, we determined the effect of litter on biomass\\u000a and

Jane Molofsky; Janna Lanza; Elizabeth E. Crone

2000-01-01

364

Skagerrak populations of Atlantic cod (Gadus morhua L.) have been surveyed at several fixed stations since 1919. These coastal populations consist of local stocks with a low age of maturity and a short life span. We investigated 60 time-series of 0-group juveniles (i.e. young of the year) sampled annually from 1945 to 1994. An age-structured model was developed which incorporates asymmetrical interactions between the juvenile cohorts (0-group and 1-group; i.e. one-year-old juveniles) and stochastic reproduction. The model was expressed in delay coordinates in order to estimate model parameters directly from the time-series and thereby test the model predictions. The autocovariance structure of the time-series was consistent with the delay coordinates model superimposed upon a long-term trend. The model illustrates how both regulatory (density-dependent) and disruptive (stochastic) forces are crucial in shaping the dynamics of the coastal cod populations. The age-structured life cycle acts to resonance the stochasticity inherent in the recruitment process.

Stenseth, N. C.; rnstad, O. N. Bj; Falck, W.; Fromentin, J.-M.; ter, J. Gj s; Gray, J. S.

1999-01-01

365

Effects of nano-titanium dioxide on freshwater algal population dynamics.

To make predictions about the possible effects of nanomaterials across environments and taxa, toxicity testing must incorporate not only a variety of organisms and endpoints, but also an understanding of the mechanisms that underlie nanoparticle toxicity. Here, we report the results of a laboratory experiment in which we examined how titanium dioxide nanoparticles impact the population dynamics and production of biomass across a range of freshwater algae. We exposed 10 of the most common species of North American freshwater pelagic algae (phytoplankton) to five increasing concentrations of n-TiO(2) (ranging from controls to 300 mg n-TiO(2) L(-1)). We then examined the effects of n-TiO(2) on the population growth rates and biomass production of each algal species over a period of 25 days. On average, increasing concentrations of n-TiO(2) had no significant effects on algal growth rates (p = 0.376), even though there was considerable species-specific variation in responses. In contrast, exposure to n-TiO(2) tended to increase maximum biomass achieved by species in culture (p = 0.06). Results suggest that titanium dioxide nanoparticles could influence certain aspects of population growth of freshwater phytoplankton, though effects are unlikely at environmentally relevant concentrations. PMID:23071735

Kulacki, Konrad J; Cardinale, Bradley J

2012-10-10

366

Monterey Bay, CA is an Eastern boundary upwelling system that is nitrogen limited much of the year. In order to resolve population dynamics of microorganisms important for nutrient cycling in this region, we deployed the Environmental Sample Processor with quantitative PCR assays targeting both ribosomal RNA genes and functional genes for subclades of cyanobacteria (Synechococcus) and ammonia-oxidizing Archaea (Thaumarchaeota) populations. Results showed a strong correlation between Thaumarchaea abundances and nitrate during the spring upwelling but not the fall sampling period. In relatively stratified fall waters, the Thaumarchaeota community reached higher numbers than in the spring, and an unexpected positive correlation with chlorophyll concentration was observed. Further, we detected drops in Synechococcus abundance that occurred on short (that is, daily) time scales. Upwelling intensity and blooms of eukaryotic phytoplankton strongly influenced Synechococcus distributions in the spring and fall, revealing what appear to be the environmental limitations of Synechococcus populations in this region. Each of these findings has implications for Monterey Bay biogeochemistry. High-resolution sampling provides a better-resolved framework within which to observe changes in the plankton community. We conclude that controls on these ecosystems change on smaller scales than are routinely assessed, and that more predictable trends will be uncovered if they are evaluated within seasonal (monthly), rather than on annual or interannual scales.

Robidart, Julie C; Preston, Christina M; Paerl, Ryan W; Turk, Kendra A; Mosier, Annika C; Francis, Christopher A; Scholin, Christopher A; Zehr, Jonathan P

2012-01-01

367

Arthroplasty Utilization in the United States is Predicted by Age-Specific Population Groups

Osteoarthritis is a common indication for hip and knee arthroplasty. An accurate assessment of current trends in healthcare utilization as they relate to arthroplasty may predict the needs of a growing elderly population in the United States. First, incidence data was queried from the United States Nationwide Inpatient Sample from 1993 to 2009. Patients undergoing total knee and hip arthroplasty were identified. Then, the United States Census Bureau was queried for population data from the same study period as well as to provide future projections. Arthroplasty followed linear regression models with the population group >64 years in both hip and knee groups. Projections for procedure incidence in the year 2050 based on these models were calculated to be 1,859,553 cases (hip) and 4,174,554 cases (knee). The need for hip and knee arthroplasty is expected to grow significantly in the upcoming years, given population growth predictions.

Bashinskaya, Bronislava; Zimmerman, Ryan M.; Walcott, Brian P.; Antoci, Valentin

2013-01-01

368

Reversed optimality and predictive ecology: burrowing depth forecasts population change in a bivalve

Optimality reasoning from behavioural ecology can be used as a tool to infer how animals perceive their environment. Using optimality principles in a ‘reversed manner’ may enable ecologists to predict changes in population size before such changes actually happen. Here we show that a behavioural anti-predation trait (burrowing depth) of the marine bivalve Macoma balthica can be used as an indicator of the change in population size over the year to come. The per capita population growth rate between years t and t+1 correlated strongly with the proportion of individuals living in the dangerous top 4?cm layer of the sediment in year t: the more individuals in the top layer, the steeper the population decline. This is consistent with the prediction based on optimal foraging theory that animals with poor prospects should accept greater risks of predation. This study is among the first to document fitness forecasting in animals.

van Gils, Jan A.; Kraan, Casper; Dekinga, Anne; Koolhaas, Anita; Drent, Jan; de Goeij, Petra; Piersma, Theunis

2008-01-01

369

Optimality reasoning from behavioural ecology can be used as a tool to infer how animals perceive their environment. Using optimality principles in a 'reversed manner' may enable ecologists to predict changes in population size before such changes actually happen. Here we show that a behavioural anti-predation trait (burrowing depth) of the marine bivalve Macoma balthica can be used as an indicator of the change in population size over the year to come. The per capita population growth rate between years t and t+1 correlated strongly with the proportion of individuals living in the dangerous top 4 cm layer of the sediment in year t: the more individuals in the top layer, the steeper the population decline. This is consistent with the prediction based on optimal foraging theory that animals with poor prospects should accept greater risks of predation. This study is among the first to document fitness forecasting in animals. PMID:18940769

van Gils, Jan A; Kraan, Casper; Dekinga, Anne; Koolhaas, Anita; Drent, Jan; de Goeij, Petra; Piersma, Theunis

2009-02-23

370

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

2012-08-14

371

A large data set of relative food-consumption estimates (QlB) of marine and freshwater fish populations (n = 108 populations, 38 species) is documented and used to derive a predictive model for Q\\/B, using asymptotic weight, habitat temperature, a morphological variable and food type as indejxndent variables. Salinity is shown to have no effect on QfB in fish well adapted to

Maria Lourdes D. Palomares; Daniel PaulyB

1998-01-01

372

Reliability of Absolute and Relative Predictions of Population Persistence Based on Time Series

Abstract: Conventional,population,viability analysis (PVA) is often impractical,because,data are scarce for many threatened species. For this reason, simple count-based models are being advocated. The simplest of these models requires nothing more than a time series of abundance estimates, from which variance and,autocorrelation,in growth,rate are estimated,and,predictions,of population,persistence are generated. What remains unclear, however, is how many years of data are needed to

KELLY C. LOTTS; THOMAS A. WAITE; JOHN A. VUCETICH

2004-01-01

373

Forecasting the belief of the population: Prediction Markets, Social Media & Swine Flu

Abstract The belief of the population is very useful information but is hard to measure. Meth- ods such as voting and polling are both expensive and slow to run. Recently prediction markets have become,a popular method,to aggregate information and beliefs from the population using the market price as the mean,belief. The problem with these is that they have to be

Daniel Kristopher Harvey

2009-01-01

374

Prediction of additive and dominance effects in selected and 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

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

1992-01-01

375

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

376

An integrated CAE system for dynamic stress and fatigue life prediction of mechanical systems

This paper presents computer simulation methodology for dynamic stress time history computation to predict the fatigue life\\u000a of machine components using flexible multi-body dynamics. A hybrid method which employes stress superposition as a function\\u000a of constraint loads and component accelerations that are predicted by flexible body dynamic simulation is utilized and implemented\\u000a using established codes. A system integration methodology for

Hong Jae Yim; Sang Beom Lee

1996-01-01

377

Population dynamics of the rare plant Kosteletzkya pentacarpos (Malvaceae): a nine-year study

Rare plant species have extremely narrow distributions that can be reduced to a single or few populations. The rare long-lived plant Kosteletzkya pentacarpos is one such species because only two extant localities are known in the western Mediterranean. In this study, we analyse the population dynamics over nine years of the only population known in north-east Spain, which is located

JOAN PINO; F. XAVIER PICÓ; ENRIC DE ROA

2007-01-01

378

There are few quantitative data on the role of emergence from diapausing eggs in population dynamics of natural populations of zooplankton species; to our knowledge, all these concern copepods and ‘cladocerans’. We present here direct estimates of emergence from bottom resting eggs for another important category of freshwater zooplankton, namely rotifers. Three populations of rotifers of the genus Brachionus were

Elena A. Mnatsakanova; Leonard V. Polishchuk

1996-01-01

379

Quantitatively characterizing the social structure of a population provides important insight into the forces shaping key population processes. Moreover, long-term social dynamics provide an avenue for understanding population-level responses to changes in socioecological conditions. This is particularly true for species that show natal philopatry and highly stable hierarchically structured social units, such as the piscivorous resident killer whales of the

K. M. Parsons; K. C. Balcomb III; J. K. B. Ford; J. W. Durban

2009-01-01

380

The effects of the population density on individual animal growth, development, and reproduction has been extensively studied and reported in detail [1]. However, the existing explanations of these phenomena are incomplete and often inconsistent. The population dynamics of small rodents (especially at northern latitudes) exhibits large-amplitude oscillations called population cycles [2]. Their emergence is often attributed to the operation of

K. V. Maklakov; F. V. Kryazhimskii

2002-01-01

381

Development of high resolution population and social dynamics models and databases

High resolution population distribution data is critical for successfully addressing critical issues ranging from energy and socio-environmental research to public health to homeland security. Commonly available population data from Census is constrained both in space and time and does not capture the population dynamics as functions of space and time. This imposes a significant negative consequence on the fidelity of

Budhendra Bhaduri

2010-01-01

382

Improved dynamic geomagnetic rigidity cutoff modeling: Testing predictive accuracy

NASA Astrophysics Data System (ADS)

In the polar atmosphere, significant chemical and ionization changes occur during solar proton events (SPEs). The access of solar protons to this region is limited by the dynamically changing geomagnetic field. In this study, we have used riometer absorption observations to investigate the accuracy of a model to predict K p-dependent geomagnetic rigidity cutoffs, and hence the changing proton fluxes. The imaging riometer at Halley, Antarctica is ideally situated for such a study, as the rigidity cutoff sweeps back and forth across the instrument's field of view, providing a severe test of the rigidity cutoff model. Using observations from this riometer during five solar proton events, we have confirmed the basic accuracy of this rigidity model. However, we find that the model can be improved by setting a lower K p limit (i.e., K p = 5 instead of 6) at which the rigidity modeling saturates. We also find that, for L > 4.5, the apparent L-shell of the beam moves equatorward. In addition, the Sodankylä Ion and Neutral Chemistry (SIC) model is used to determine an empirical relationship between integral proton precipitation fluxes and nighttime ionosphere riometer absorption, in order to allow consideration of wintertime SPEs. We find that during the nighttime, the proton flux energy threshold is lowered to include protons with energies of >5 MeV in comparison with >10 MeV for the daytime empirical relationships. In addition, we provide an indication of the southern and northern geographic regions inside which SPEs play a role in modifying the neutral chemistry of the stratosphere and mesosphere.

Clilverd, Mark A.; Rodger, Craig J.; Moffat-Griffin, Tracy; Verronen, Pekka T.

2007-08-01

383

Recent advances in stochastic demography provide tools to examine the importance of random and periodic variation in vital rates for population dynamics. In this study, we explore with simulations the effect of disturbance regime on population dynamics and viability. We collected 7 years of demographic data in three populations of the perennial herb Primula farinosa, and used these data to examine how variation in vital rates affected population viability parameters (stochastic growth rate, lambda(S)), and how vital rates were related to weather conditions. Elasticity analysis indicated that the stochastic growth rate was very sensitive to changes in regeneration, quantified as the production, survival, and germination of seeds. In one of the study years, all seedlings and mature plants in the demography plots died. This extinction coincided with the driest summer during the study period. Simulations suggested that a future increase in the frequency of high-mortality years due to climate change would result in reduced population growth rate, and an increased importance of survival in the seed bank for population viability. The results illustrate how the limited demographic data typically available for many natural systems can be used in simulation models to assess how environmental change will affect population viability. PMID:20072788

Toräng, Per; Ehrlén, Johan; Agren, Jon

2010-01-14

384

Dynamical elements of predicting boreal spring tropical Atlantic sea-surface temperatures

NASA Astrophysics Data System (ADS)

The dynamical processes that contribute to the seasonal prediction of the tropical Atlantic sea-surface temperature (SST) anomalies from boreal winter into spring are explored with an atmospheric general circulation model coupled to a slab ocean. Taking advantage of the reduced-physics model that effectively isolates thermodynamic feedbacks from dynamic feedbacks, we examine the joint effect of local thermodynamic feedback and the remote influence of El Nińo-Southern Oscillation (ENSO) on the prediction of SST anomalies by conducting large ensembles of prediction runs. These prediction experiments yield the following findings: (1) in the northwestern part of the tropical Atlantic, the positive feedback between the surface heat flux and SST can play an important role in enhancing the predictability of the SST; (2) the remote influence from Pacific ENSO can enhance the SST predictability through a constructive interference with the local thermodynamic feedback, but can also make the SST prediction more difficult when the interference is destructive; (3) ocean dynamics plays a fundamental role for prediction of SST anomalies in the equatorial and south tropical Atlantic. To shed further light on the importance of the ocean dynamics, a statistical procedure of parameterizing the important ocean dynamics is developed within a linear dynamical framework. Prediction experiments with the parameterized ocean dynamics included in the simple coupled model result in an improved forecast skill in predicting the cross-equatorial SST gradient, which subsequently lead to a high skill of the model in predicting seasonal rainfall anomalies associated with variations in the Intertropical Convergence Zone during boreal spring. A diagnostic study suggests that the vertical advection of heat due to anomalous Ekman pumping/suction is a dominant contributing factor for causing equatorial SST anomalies, thereby, a major element of predictable dynamics in this region.

Barreiro, M.; Chang, P.; Ji, L.; Saravanan, R.; Giannini, A.

2005-04-01

385

Background: Cardiovascular disease (CVD) risk-prediction algorithms are key in determining one's eligibility for prevention strategies, but are often population-specific. Metabolic syndrome (MetS), a clustering of risk factors that increase the risk of CVD, does not currently have a risk-prediction algorithm available for prediction of CVD. The aim of this study was to compare the predictive capacities of an algorithm intended for 'healthy' individuals and one intended for 'diabetic' individuals.Methods: Individual-specific data from 2700 subjects defined as MetS but free of diagnosed CVD from the Australian Diabetes, Obesity and Lifestyle study was used to estimate 5-year risk of CVD using the two algorithms, and compared using Wilcoxon-signed rank test. CVD end point data was used to assess the performance using discrimination and calibration techniques of the two algorithms.Results: Five-year risk-prediction comparisons demonstrated that the UKPDS algorithm overpredicted risk in the younger age groups (25-54 years) and underpredicted risk in the older age groups (?55 years) compared to the Framingham algorithm. A total of 133 CVD events occurred over a median follow up of 5.0 years. Model performance analyses demonstrated both the Framingham and UKPDS algorithms were poor at discrimination (area under receiver operator curve 0.513 and 0.524, respectively) and calibration (Hosmer-Lemeshow 467.1 and 297.0, respectively).Conclusions: Neither the Framingham or UKPDS algorithms are ideal for prediction of CVD risk in a MetS population. This study highlights the need for development of population-specific risk-prediction algorithms for this growing population group. PMID:22588087

Zomer, Ella; Liew, Danny; Owen, Alice; Magliano, Dianna J; Ademi, Zanfina; Reid, Christopher M

2012-05-15

386

Influence of individual aggressiveness on the dynamics of competitive populations.

Two populations are subdivided into two categories of individuals (hawks and lows). Individuals fight to have access to a resource which is necessary for their survival. Conflicts occur between individuals belonging to the same population and to different populations. We investigate the long term effects of the conflicts on the stability of the community. The model is a set of ODE's with four variables corresponding to hawk and dove individuals of the two populations. Two time scales are considered. A fast time scale is used to describe frequent encounters and fightings between individuals trying to monopolize the resource. A slow time scale is used for the demography and the long term effects of encounters. We use aggregation methods in order to reduce this model into a system of two ODE's only for the total densities of the two populations which is found to be a classical Lotka-Volterra competition model. We study different cases of proportions of hawks and doves in both populations on the global coexistence and the mutual exclusion of the two populations. Pure dove tactics in both populations are unstable. In cases of mixed hawk and dove in both populations, there is coexistence. Pure dove or mixed hawk-dove tactics in one population can coexist with pure hawks in the other one when the costs of fightings between hawks are large enough. PMID:9436300

Sanchez, E; Auger, P; Bravo de la Parra, R

1997-11-01

387

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

388

How closely do acute lethal concentration estimates predict effects of toxicants on populations?

Acute lethal dose/concentration estimates are the most widely used measure of toxicity and these data often are used in ecological risk assessment. However, the value of the lethal concentration (LC50) as a toxicological endpoint for use in ecological risk assessment recently has been criticized. A question that has been asked frequently is how accurate is the LC50 for prediction of longer-term effects of toxicants on populations of organisms? To answer this question, Daphnia pulex populations were exposed to nominal concentrations equal to the 48-h acute LC50 of 6 insecticides, Actara, Aphistar diazinon, pymetrozine, Neemix, and Spinosad; and 8 agricultural adjuvants, Bond, Kinetic, Plyac, R-11, Silwet, Sylgard 309, Water Maxx, and X-77; for 10 d. None of the D. pulex populations exposed to the acute LC50 of these insecticides were 50% lower than the control populations at the end of the study; exposure to diazinon resulted in populations that were higher than expected (91% of the control). Exposure to Actara and Aphistar resulted in populations that were < 1 and 29% of the control, respectively. Exposure to Fulfill, Neemix, and Spinosad resulted in extinction. Extinction occurred after exposure to all of the adjuvants, except Silwet L-77 where the population was 31% of the control. These results corroborate other studies that indicate that the LC50 is not a good predictor of effects on population growth. Although lethal concentration estimates have their place in toxicology, namely to compare intrinsic toxicity of chemicals among species or susceptibility of a species to different chemicals over short time periods, population growth and growth-rate studies are necessary to predict toxicant effects on populations. PMID:16639892

Stark, John D

2005-04-01

389

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

390

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. PMID:16535405

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

1996-09-01

391

ERIC Educational Resources Information Center

|Background: For adult physical and mental health, the population mean predicts the proportion of individuals with "high" scores. This has not previously been investigated for child mental health. It is also unclear how far symptom scores on brief questionnaires provide an unbiased method of comparing children with different individual, family or…

Goodman, Anna; Goodman, Robert

2011-01-01

392

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 ...

393

The Predictive Ability of IQ and Working Memory Scores in Literacy in an Adult Population

ERIC Educational Resources Information Center

|Literacy problems are highly prevalent and can persist into adulthood. Yet, the majority of research on the predictive nature of cognitive skills to literacy has primarily focused on development and adolescent populations. The aim of the present study was to extend existing research to investigate the roles of IQ scores and Working Memory…

Alloway, Tracy Packiam; Gregory, David

2013-01-01

394

The Predictive Ability of IQ and Working Memory Scores in Literacy in an Adult Population

ERIC Educational Resources Information Center

Literacy problems are highly prevalent and can persist into adulthood. Yet, the majority of research on the predictive nature of cognitive skills to literacy has primarily focused on development and adolescent populations. The aim of the present study was to extend existing research to investigate the roles of IQ scores and Working Memory…

Alloway, Tracy Packiam; Gregory, David

2013-01-01

395

There is growing evidence that climate change causes an increase in variation in conditions for plant and animal populations.\\u000a This increase in variation, e.g. amplified inter-annual variability in temperature and rainfall has population dynamical consequences\\u000a because it raises the variation in vital demographic rates (survival, reproduction) in these populations. In turn, this amplified\\u000a environmental variability enlarges population extinction risk. This

Jana Verboom; Peter Schippers; Anouk Cormont; Marjolein Sterk; Claire C. Vos; Paul F. M. Opdam

2010-01-01

396

Stochastic population dynamics of clonal plants: Numerical experiments with ramet and genet models

Dynamics of ramer and genet populations were analyzed by use of stochastic matrix models. Based on field data, population\\u000a development and extinction rates during 50 simulated years were estimated for ramet populations of three speciesPotentilla anserina, Rubus saxatilis andLinnaea borealis. Only small initial populations (below 125–250 ramets), experienced a detectable risk of extinction within this time interval.\\u000a ForP. anserina andR.

Ove Eriksson

1994-01-01

397

A mathematical model has been constructed and verified to simulate dynamics of a microbial community in typical tundra. The model contains the following state variables: the population densities of three competing microbial species (exemplified by Arthrobacter, Pseudomonas, and Bacillus), indexes of their physiological state, concentration of available organic substrate, plant litter reserves, the amount of microbiovorous protozoans, and temperature. The mathematical model simulates adequately the qualitative features of microbial seasonal dynamics observed in tundra. The global warming and associated increase in primary productivity, as predicted by simulation, will relieve the pressure of L-selection and thus result in stabilization of the tundra microbial community. The model also predicts that aerobic decomposition of dead organic matter in solid will be accelerated compared to its formation. 24 refs., 7 figs., 1 tab.

Panikov, N.S.

1994-11-01

398

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

399

Dynamics of Encoding in a Population of Neurons

A simple encoder model, which is a reasonable idealization from known electrophysiological p