Understanding Uncertainties in Model-Based Predictions of Aedes aegypti Population Dynamics
Lloyd, Alun
/Principal Findings: This study quantifies uncertainties in the predicted mosquito population dynamicsUnderstanding Uncertainties in Model-Based Predictions of Aedes aegypti Population Dynamics. The development of spatial models for Ae. aegypti provides a promising start toward model-guided vector control
Predicting the dynamics of animal behaviour in field populations
Cushing, Jim. M.
Department of Fish and Wildlife Resources, Division of Statistics, University of Idaho zBiology Department, Andrews of Arizona **Department of Biological Sciences, Walla Walla College (Received 9 November 2005; initial advances in the interface between dynamical systems theory and population biology (Cushing et al. 2003
Kuhn, A; Munns, W R; Champlin, D; McKinney, R; Tagliabue, M; Serbst, J; Gleason, T
2001-01-01
An age-classified projection matrix model has been developed to extrapolate the chronic (28-35 d) 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 the population behavior of A. bahia held (for more than three generations) under controlled laboratory exposure conditions. The research involved the performance of a standard life-cycle test and a multigenerational (greater than three mysid generations, 55 d) assay using A. bahia to experimentally evaluate model predictions regarding population-level risks of chemical exposure. The organic compound para-nonylphenol was chosen as the chemical stressor in assays. This compound is a ubiquitous contaminant and suspected endocrine disruptor. Utilizing data obtained during the standard life-cycle test, aggregate estimates of population growth rate (lambda) and measured p-nonylphenol concentration were used to develop an exposure-response model of population-level effects. These estimates provided the basis of predictions for the long-term dynamics of mysid populations exposed to p-nonylphenol. The veracity of the mysid population model was evaluated through quantitative comparisons of model predictions based on the life-cycle test with dynamics of the experimental populations (multigenerational assay results). The results indicate that the population model was able to project within a few micrograms per liter the concentration where population-level effects would begin to occur (projected 16 micrograms/L from the model vs measured 19 micrograms/L from the multigenerational assay). PMID:11351411
Sakaris, P.C.; Irwin, E.R.
2010-01-01
We developed stochastic matrix models to evaluate the effects of hydrologic alteration and variable mortality on the population dynamics of a lotie fish in a regulated river system. Models were applied to a representative lotic fish species, the flathead catfish (Pylodictis olivaris), for which two populations were examined: a native population from a regulated reach of the Coosa River (Alabama, USA) and an introduced population from an unregulated section of the Ocmulgee River (Georgia, USA). Size-classified matrix models were constructed for both populations, and residuals from catch-curve regressions were used as indices of year class strength (i.e., recruitment). A multiple regression model indicated that recruitment of flathead catfish in the Coosa River was positively related to the frequency of spring pulses between 283 and 566 m3/s. For the Ocmulgee River population, multiple regression models indicated that year class strength was negatively related to mean March discharge and positively related to June low flow. When the Coosa population was modeled to experience five consecutive years of favorable hydrologic conditions during a 50-year projection period, it exhibited a substantial spike in size and increased at an overall 0.2% annual rate. When modeled to experience five years of unfavorable hydrologic conditions, the Coosa population initially exhibited a decrease in size but later stabilized and increased at a 0.4% annual rate following the decline. When the Ocmulgee River population was modeled to experience five years of favorable conditions, it exhibited a substantial spike in size and increased at an overall 0.4% annual rate. After the Ocmulgee population experienced five years of unfavorable conditions, a sharp decline in population size was predicted. However, the population quickly recovered, with population size increasing at a 0.3% annual rate following the decline. In general, stochastic population growth in the Ocmulgee River was more erratic and variable than population growth in the Coosa River. We encourage ecologists to develop similar models for other lotic species, particularly in regulated river systems. Successful management of fish populations in regulated systems requires that we are able to predict how hydrology affects recruitment and will ultimately influence the population dynamics of fishes. ?? 2010 by the Ecological Society of America.
Predicting Culex pipiens/restuans population dynamics by interval lagged weather data
2013-01-01
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
Nichols, J.M.; Moniz, L.; Nichols, J.D.; Pecora, L.M.; Cooch, E.
2005-01-01
A number of important questions in ecology involve the possibility of interactions or ?coupling? among potential components of ecological systems. The basic question of whether two components are coupled (exhibit dynamical interdependence) is relevant to investigations of movement of animals over space, population regulation, food webs and trophic interactions, and is also useful in the design of monitoring programs. For example, in spatially extended systems, coupling among populations in different locations implies the existence of redundant information in the system and the possibility of exploiting this redundancy in the development of spatial sampling designs. One approach to the identification of coupling involves study of the purported mechanisms linking system components. Another approach is based on time series of two potential components of the same system and, in previous ecological work, has relied on linear cross-correlation analysis. Here we present two different attractor-based approaches, continuity and mutual prediction, for determining the degree to which two population time series (e.g., at different spatial locations) are coupled. Both approaches are demonstrated on a one-dimensional predator?prey model system exhibiting complex dynamics. Of particular interest is the spatial asymmetry introduced into the model as linearly declining resource for the prey over the domain of the spatial coordinate. Results from these approaches are then compared to the more standard cross-correlation analysis. In contrast to cross-correlation, both continuity and mutual prediction are clearly able to discern the asymmetry in the flow of information through this system.
Storkey, J; Holst, N; Břjer, O Q; Bigongiali, F; Bocci, G; Colbach, N; Dorner, Z; Riemens, M M; Sartorato, I; Sřnderskov, M; Verschwele, A
2015-01-01
A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed, populated and analysed, initially using data for 19 common European weeds, to begin to consolidate trait data in a single repository. The initial choice of traits was driven by the requirements of empirical models of weed population dynamics to identify correlations between traits and model parameters. These relationships were used to build a generic model, operating at the level of functional traits, to simulate the impact of increasing herbicide and fertiliser use on virtual weeds along gradients of seed weight and maximum height. The model generated ‘fitness contours’ (defined as population growth rates) within this trait space in different scenarios, onto which two sets of weed species, defined as common or declining in the UK, were mapped. The effect of increasing inputs on the weed flora was successfully simulated; 77% of common species were predicted to have stable or increasing populations under high fertiliser and herbicide use, in contrast with only 29% of the species that have declined. Future development of the WTDB will aim to increase the number of species covered, incorporate a wider range of traits and analyse intraspecific variability under contrasting management and environments. PMID:26190870
Velez de Mendizabal, Nieves; Hutmacher, Matthew M.; Troconiz, Ińaki F.; Gońi, Joaquín; Villoslada, Pablo; Bagnato, Francesca; Bies, Robert R.
2013-01-01
Background Relapsing-remitting dynamics are a hallmark of autoimmune diseases such as Multiple Sclerosis (MS). A clinical relapse in MS reflects an acute focal inflammatory event in the central nervous system that affects signal conduction by damaging myelinated axons. Those events are evident in T1-weighted post-contrast magnetic resonance imaging (MRI) as contrast enhancing lesions (CEL). CEL dynamics are considered unpredictable and are characterized by high intra- and inter-patient variability. Here, a population approach (nonlinear mixed-effects models) was applied to analyse of CEL progression, aiming to propose a model that adequately captures CEL dynamics. Methods and Findings We explored several discrete distribution models to CEL counts observed in nine MS patients undergoing a monthly MRI for 48 months. All patients were enrolled in the study free of immunosuppressive drugs, except for intravenous methylprednisolone or oral prednisone taper for a clinical relapse. Analyses were performed with the nonlinear mixed-effect modelling software NONMEM 7.2. Although several models were able to adequately characterize the observed CEL dynamics, the negative binomial distribution model had the best predictive ability. Significant improvements in fitting were observed when the CEL counts from previous months were incorporated to predict the current month’s CEL count. The predictive capacity of the model was validated using a second cohort of fourteen patients who underwent monthly MRIs during 6-months. This analysis also identified and quantified the effect of steroids for the relapse treatment. Conclusions The model was able to characterize the observed relapsing-remitting CEL dynamic and to quantify the inter-patient variability. Moreover, the nature of the effect of steroid treatment suggested that this therapy helps resolve older CELs yet does not affect newly appearing active lesions in that month. This model could be used for design of future longitudinal studies and clinical trials, as well as for the evaluation of new therapies. PMID:24039924
Peterman, W E; Semlitsch, R D
2014-10-01
Many patterns observed in ecology, such as species richness, life history variation, habitat use, and distribution, have physiological underpinnings. For many ectothermic organisms, temperature relationships shape these patterns, but for terrestrial amphibians, water balance may supersede temperature as the most critical physiologically limiting factor. Many amphibian species have little resistance to water loss, which restricts them to moist microhabitats, and may significantly affect foraging, dispersal, and courtship. Using plaster models as surrogates for terrestrial plethodontid salamanders (Plethodon albagula), we measured water loss under ecologically relevant field conditions to estimate the duration of surface activity time across the landscape. Surface activity time was significantly affected by topography, solar exposure, canopy cover, maximum air temperature, and time since rain. Spatially, surface activity times were highest in ravine habitats and lowest on ridges. Surface activity time was a significant predictor of salamander abundance, as well as a predictor of successful recruitment; the probability of a juvenile salamander occupying an area with high surface activity time was two times greater than an area with limited predicted surface activity. Our results suggest that survival, recruitment, or both are demographic processes that are affected by water loss and the ability of salamanders to be surface-active. Results from our study extend our understanding of plethodontid salamander ecology, emphasize the limitations imposed by their unique physiology, and highlight the importance of water loss to spatial population dynamics. These findings are timely for understanding the effects that fluctuating temperature and moisture conditions predicted for future climates will have on plethodontid salamanders. PMID:25154754
Life-History variation predicts the effects of dmographic sochasticity on avian population Dynamics
Steinar Engen; Anders Pape Mřller; Henri Weimerskirch; Wolfgang Fiedler; Erik Matthysen; M. M. Lambrechts; A. Badyaev; P. H. Becker; J. E. Brommer; D. Bukacinski; M. Bukacinski; H. Christensen; J. Dickinson; Feu du C; F. R. Gehlbach; D. Heg; H. Hötker; J. Merilä; J. T. Nielsen; W. Rendell; R. J. Robertson; D. L. Thomson; J. Török; Hecke Van P
2004-01-01
Comparative analyses of avian population fluctuations have shown large interspecific differences in population variability that have been difficult to relate to variation in general ecological characteristics. Here we show that interspecific variation in demographic stochasticity, caused by random variation among individuals in their fitness contributions, can be predicted from a knowledge of the species' position along a \\
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...
Wu, Qinglong L; Hahn, Martin W
2006-09-01
One of the key questions in microbial ecology is if seasonal patterns of bacterial community composition (BCC) observed in one year repeat in the following years. We have investigated if the recorded annual dynamics of a species-like Polynucleobacter (subcluster PnecB) population allowed the prediction of the population dynamics in another year. The abundance of PnecB bacteria in the pelagic of temperate Lake Mondsee was investigated by fluorescence in situ hybridization (FISH) over three consecutive years. The PnecB bacteria formed a persistent population, and were present in the entire water body of the lake. Two of the three investigated years differed strongly in summer temperatures and precipitation, which resulted in markedly different growth conditions. But despite of these different environmental conditions, the PnecB population demonstrated remarkably similar seasonal dynamics in the three investigated years. Water temperature was the best predictor of the population dynamics during the first half of the annual cycles. Statistical analysis also indicated influences of phytoplankton and metazooplankton successions on the PnecB population dynamics. Furthermore, 65 lakes and ponds were investigated for the presence of PnecB bacteria. They were detected in the majority (78%) of circum-neutral and alkaline freshwater habitats, but not in any investigated acidic or saline habitat. PMID:16913925
Holland, E Penelope; James, Alex; Ruscoe, Wendy A; Pech, Roger P; Byrom, Andrea E
2015-01-01
Accurate predictions of the timing and magnitude of consumer responses to episodic seeding events (masts) are important for understanding ecosystem dynamics and for managing outbreaks of invasive species generated by masts. While models relating consumer populations to resource fluctuations have been developed successfully for a range of natural and modified ecosystems, a critical gap that needs addressing is better prediction of resource pulses. A recent model used change in summer temperature from one year to the next (?T) for predicting masts for forest and grassland plants in New Zealand. We extend this climate-based method in the framework of a model for consumer-resource dynamics to predict invasive house mouse (Mus musculus) outbreaks in forest ecosystems. Compared with previous mast models based on absolute temperature, the ?T method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ?T on the likelihood of an outbreak occurring. The improved climate-based method for predicting resource pulses and consumer responses provides a straightforward rule of thumb for determining, with one year's advance warning, whether management intervention might be required in invaded ecosystems. The approach could be applied to consumer-resource systems worldwide where climatic variables are used to model the size and duration of resource pulses, and may have particular relevance for ecosystems where global change scenarios predict increased variability in climatic events. PMID:25785866
Holland, E. Penelope; James, Alex; Ruscoe, Wendy A.; Pech, Roger P.; Byrom, Andrea E.
2015-01-01
Accurate predictions of the timing and magnitude of consumer responses to episodic seeding events (masts) are important for understanding ecosystem dynamics and for managing outbreaks of invasive species generated by masts. While models relating consumer populations to resource fluctuations have been developed successfully for a range of natural and modified ecosystems, a critical gap that needs addressing is better prediction of resource pulses. A recent model used change in summer temperature from one year to the next (?T) for predicting masts for forest and grassland plants in New Zealand. We extend this climate-based method in the framework of a model for consumer–resource dynamics to predict invasive house mouse (Mus musculus) outbreaks in forest ecosystems. Compared with previous mast models based on absolute temperature, the ?T method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ?T on the likelihood of an outbreak occurring. The improved climate-based method for predicting resource pulses and consumer responses provides a straightforward rule of thumb for determining, with one year’s advance warning, whether management intervention might be required in invaded ecosystems. The approach could be applied to consumer–resource systems worldwide where climatic variables are used to model the size and duration of resource pulses, and may have particular relevance for ecosystems where global change scenarios predict increased variability in climatic events. PMID:25785866
Loehman, Rachel A; Elias, Joran; Douglass, Richard J; Kuenzi, Amy J; Mills, James N; Wagoner, Kent
2012-04-01
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
Vucetich, John A; Hebblewhite, Mark; Smith, Douglas W; Peterson, Rolf O
2011-11-01
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
Ezanno, P; Aubry-Kientz, M; Arnoux, S; Cailly, P; L'Ambert, G; Toty, C; Balenghien, T; Tran, A
2015-06-01
An accurate understanding and prediction of mosquito population dynamics are needed to identify areas where there is a high risk of mosquito-borne disease spread and persistence. Simulation tools are relevant for supporting decision-makers in the surveillance of vector populations, as models of vector population dynamics provide predictions of the greatest risk periods for vector abundance, which can be particularly helpful in areas with a highly variable environment. We present a generic weather-driven model of mosquito population dynamics, which was applied to one species of each of the genera Anopheles, Culex, and Aedes, located in the same area and thus affected by similar weather conditions. The predicted population dynamics of Anopheles hyrcanus, Culex pipiens, and Aedes caspius were not similar. An. hyrcanus was abundant in late summer. Cx. pipiens was less abundant but throughout the summer. The abundance of both species showed a single large peak with few variations between years. The population dynamics of Ae. caspius showed large intra- and inter-annual variations due to pulsed egg hatching. Predictions of the model were compared to longitudinal data on host-seeking adult females. Data were previously obtained using CDC-light traps baited with carbon dioxide dry ice in 2005 at two sites (Marais du Viguerat and Tour Carbonničre) in a favourable temperate wetland of southern France (Camargue). The observed and predicted periods of maximal abundance for An. hyrcanus and Cx. pipiens tallied very well. Pearson's coefficients for these two species were over 75% for both species. The model also reproduced the major trends in the intra-annual fluctuations of Ae. caspius population dynamics, with peaks occurring in early summer and following the autumn rainfall events. Few individuals of this species were trapped so the comparison of predicted and observed dynamics was not relevant. A global sensitivity analysis of the species-specific models enabled us to identify the parameters most influencing the maximal abundance of mosquitoes. These key parameters were almost similar between species, but not with the same contributions. The emergence of adult mosquitoes was identified as a key process in the population dynamics of all of the three species considered here. Parameters associated with adult emergence therefore need to be precisely known to achieve accurate predictions. Our model is a flexible and efficient tool that predicts mosquito abundance based on local environmental factors. It is useful to and already used by a mosquito surveillance manager in France. PMID:25623972
Ciss, Mamadou; Parisey, Nicolas; Moreau, Fabrice; Dedryver, Charles-Antoine; Pierre, Jean-Sébastien
2014-04-01
We expose here a detailed spatially explicit model of aphid population dynamics at the scale of a whole country (Metropolitan France). It is based on convection-diffusion-reaction equations, driven by abiotic and biotic factors. The target species is the grain aphid, Sitobion avenae F., considering both its winged and apterous morphs. In this preliminary work, simulations for year 2004 (an outbreak case) produced realistic aphid densities, and showed that both spatial and temporal S. avenae population dynamics can be represented as an irregular wave of population peak densities from southwest to northeast of the country, driven by gradients or differences in temperature, wheat phenology, and wheat surfaces. This wave pattern fits well to our knowledge of S. avenae phenology. The effects of three insecticide spray regimes were simulated in five different sites and showed that insecticide sprays were ineffective in terms of yield increase after wheat flowering. After suitable validation, which will require some further years of observations, the model will be used to forecast aphid densities in real time at any date or growth stage of the crop anywhere in the country. It will be the backbone of a decision support system, forecasting yield losses at the level of a field. The model intends then to complete the punctual forecasting provided by older models by a comprehensive spatial view on a large area and leads to the diminution of insecticide sprayings in wheat crops. PMID:24271722
Coupling between evolutionary and population dynamics in experimental microbial populations
NASA Astrophysics Data System (ADS)
Sanchez, Alvaro; Gore, Jeff
2012-02-01
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.
EFFICIENT MODEL PREDICTIVE CONTROL WITH PREDICTION DYNAMICS
Foss, Bjarne A.
EFFICIENT MODEL PREDICTIVE CONTROL WITH PREDICTION DYNAMICS Stian Drageset, Lars Imsland and Bjarne robust model predictive control (MPC) strategy us- ing augmented ellipsoidal invariant sets is enhanced Introduction Model predictive control (MPC) has gained significant pop- ularity in industry as a tool
Population Dynamics Algebra 5/Trig
Lega, Joceline
Population Dynamics Algebra 5/Trig Spring 2010 Instructions: There are none! This contains equations, population growth can be modeled by a function of the form P(t) = KP0ert K + P0(ert - 1) where t is time, P(t) the population at time t, P0 the population at time t = 0, r the growth rate, and K
Imitation dynamics predict vaccinating behaviour.
Bauch, Chris T
2005-08-22
There exists an interplay between vaccine coverage, disease prevalence and the vaccinating behaviour of individuals. Moreover, because of herd immunity, there is also a strategic interaction between individuals when they are deciding whether or not to vaccinate, because the probability that an individual becomes infected depends upon how many other individuals are vaccinated. To understand this potentially complex interplay, a game dynamic model is developed in which individuals adopt strategies according to an imitation dynamic (a learning process), and base vaccination decisions on disease prevalence and perceived risks of vaccines and disease. The model predicts that oscillations in vaccine uptake are more likely in populations where individuals imitate others more readily or where vaccinating behaviour is more sensitive to changes in disease prevalence. Oscillations are also more likely when the perceived risk of vaccines is high. The model reproduces salient features of the time evolution of vaccine uptake and disease prevalence during the whole-cell pertussis vaccine scare in England and Wales during the 1970s. This suggests that using game theoretical models to predict, and even manage, the population dynamics of vaccinating behaviour may be feasible. PMID:16087421
Imitation dynamics predict vaccinating behaviour
Bauch, Chris T
2005-01-01
There exists an interplay between vaccine coverage, disease prevalence and the vaccinating behaviour of individuals. Moreover, because of herd immunity, there is also a strategic interaction between individuals when they are deciding whether or not to vaccinate, because the probability that an individual becomes infected depends upon how many other individuals are vaccinated. To understand this potentially complex interplay, a game dynamic model is developed in which individuals adopt strategies according to an imitation dynamic (a learning process), and base vaccination decisions on disease prevalence and perceived risks of vaccines and disease. The model predicts that oscillations in vaccine uptake are more likely in populations where individuals imitate others more readily or where vaccinating behaviour is more sensitive to changes in disease prevalence. Oscillations are also more likely when the perceived risk of vaccines is high. The model reproduces salient features of the time evolution of vaccine uptake and disease prevalence during the whole-cell pertussis vaccine scare in England and Wales during the 1970s. This suggests that using game theoretical models to predict, and even manage, the population dynamics of vaccinating behaviour may be feasible. PMID:16087421
Perturbation Theory for Population Dynamics
Francisco M. Fernandez
2007-12-20
We prove that a recently proposed homotopy perturbation method for the treatment of population dynamics is just the Taylor expansion of the population variables about initial time. Our results show that this perturbation method fails to provide the global features of the ecosystem dynamics.
Evolutionary Games and Population Dynamics
Hofbauer, Josef
and Lotka-Volterra Equations Logistic growth Population dynamics and density dependence Exponential growthEvolutionary Games and Population Dynamics Josef Hofbauer, Karl Sigmund CAMBRIDGE UNIVERSITY PRESS Logistic growth The recurrence relation x' = Rx(l -- x) Stable and unstable fixed points Bifurcations
Two complementary paradigms for analysing population dynamics.
Krebs, Charles J
2002-01-01
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. PMID:12396513
Population dynamic theory of size-dependent cannibalism
David Claessen; Roos de A. M; L. Persson
2004-01-01
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
Red blood cell population dynamics.
Higgins, John M
2015-03-01
Hematology analyzers provide a static snapshot of the circulating population of red blood cells (RBCs). The RBC population is rapidly changing, with more than 2 million RBCs turning over every second in the typical healthy adult. The static snapshot provided by the complete blood count does not capture many of the dynamic aspects of this population, such as the rate of RBC maturation and the rate of RBC turnover. By integrating basic science with hematology analyzer measurements, it is possible to estimate the rates of these dynamic processes, yielding new insights into human physiology, with potential diagnostic application. PMID:25676371
Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V
2013-09-01
Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate. PMID:24772388
Population dynamics in compressible flows
Roberto Benzi; Mogens H. Jensen; David R. Nelson; Prasad Perlekar; Simone Pigolotti; Federico Toschi
2012-03-28
Organisms often grow, migrate and compete in liquid environments, as well as on solid surfaces. However, relatively little is known about what happens when competing species are mixed and compressed by fluid turbulence. In these lectures we review our recent work on population dynamics and population genetics in compressible velocity fields of one and two dimensions. We discuss why compressible turbulence is relevant for population dynamics in the ocean and we consider cases both where the velocity field is turbulent and when it is static. Furthermore, we investigate populations in terms of a continuos density field and when the populations are treated via discrete particles. In the last case we focus on the competition and fixation of one species compared to another
Dose-structured population dynamics.
Ginn, Timothy R; Loge, Frank J
2007-07-01
Applied population dynamics modeling is relied upon with increasing frequency to quantify how human activities affect human and non-human populations. Current techniques include variously the population's spatial transport, age, size, and physiology, but typically not the life-histories of exposure to other important things occurring in the ambient environment, such as chemicals, heat, or radiation. Consequently, the effects of such 'abiotic' aspects of an ecosystem on populations are only currently addressed through individual-based modeling approaches that despite broad utility are limited in their applicability to realistic ecosystems [V. Grimm, Ten years of individual-based modeling in ecology: what have we learned and what could we learn in the future? Ecol. Model. 115 (1999) 129-148][1]. We describe a new category of population dynamics modeling, wherein population dynamical states of the biotic phases are structured on dose, and apply this framework to demonstrate how chemical species or other ambient aspects can be included in population dynamics in three separate examples involving growth suppression in fish, inactivation of microorganisms with ultraviolet irradiation, and metabolic lag in population growth. Dose-structuring is based on a kinematic approach that is a simple generalization of age-structuring, views the ecosystem as a multi-component mixture with reacting biotic/abiotic components. The resulting model framework accommodates (a) different memories of exposure as in recovery from toxic ambient conditions, (b) differentiation between exogenous and endogenous sources of variation in population response, and (c) quantification of acute or sub-acute effects on populations arising from life-history exposures to abiotic species. Classical models do not easily address the very important fact that organisms differ and have different experiences over their life cycle. The dose structuring is one approach to incorporate some of these elements into the existing structures of the classical models, while retaining many of the features (and other limitations) of classical models. PMID:17296208
PREDICTING WILDLIFE POPULATION EFFECTS FROM MULTIPLE STRESSORS
The U.S. Environmental Protection Agency's National Health and Environmental Effects Research Laboratory (NHEERL) is developing tools for predicting risks of multiple stressors to wildlife populations, which support the development of risk-based protective criteria. NHEERL's res...
Predicting protein dynamics from structural ensembles
Copperman, J
2015-01-01
The biological properties of proteins are uniquely determined by their structure and dynamics. A protein in solution populates a structural ensemble of metastable configurations around the global fold. From overall rotation to local fluctuations, the dynamics of proteins can cover several orders of magnitude in time scales. We propose a simulation-free coarse-grained approach which utilizes knowledge of the important metastable folded states of the protein to predict the protein dynamics. This approach is based upon the Langevin Equation for Protein Dynamics (LE4PD), a Langevin formalism in the coordinates of the protein backbone. The linear modes of this Langevin formalism organize the fluctuations of the protein, so that more extended dynamical cooperativity relates to increasing energy barriers to mode diffusion. The accuracy of the LE4PD is verified by analyzing the predicted dynamics across a set of seven different proteins for which both relaxation data and NMR solution structures are available. Using e...
Modeling sandhill crane population dynamics
Johnson, D.H.
1979-01-01
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.
Ecosystem engineers: feedback and population dynamics.
Cuddington, K; Wilson, W G; Hastings, A
2009-04-01
All organisms alter their abiotic environment, but ecosystem engineers are species with abiotic effects that may have to be explicitly accounted for when making predictions about population and community dynamics. The goal of this analysis is to identify those conditions in which engineering leads to population dynamics that are qualitatively different than one would predict using models that incorporate only biotic interactions. We present a simple model coupling an ecosystem engineer and the abiotic environment. We assume that the engineer alters environmental conditions at a rate dependent on engineer density and that the environment decays back to original conditions at an exponential rate. We determine when the feedback to population dynamics through environmental state can lead to altered equilibrium densities, bistability, or runaway growth of the engineer population. The conditions leading to changes in dynamics, such as susceptibility of a system to engineering or alteration of density-dependent and density-independent controls, define cases in which the engineering concept is essential for ecological understanding. PMID:19239352
Evolutionary dynamics in structured populations
Nowak, Martin A.; Tarnita, Corina E.; Antal, Tibor
2010-01-01
Evolutionary dynamics shape the living world around us. At the centre of every evolutionary process is a population of reproducing individuals. The structure of that population affects evolutionary dynamics. The individuals can be molecules, cells, viruses, multicellular organisms or humans. Whenever the fitness of individuals depends on the relative abundance of phenotypes in the population, we are in the realm of evolutionary game theory. Evolutionary game theory is a general approach that can describe the competition of species in an ecosystem, the interaction between hosts and parasites, between viruses and cells, and also the spread of ideas and behaviours in the human population. In this perspective, we review the recent advances in evolutionary game dynamics with a particular emphasis on stochastic approaches in finite sized and structured populations. We give simple, fundamental laws that determine how natural selection chooses between competing strategies. We study the well-mixed population, evolutionary graph theory, games in phenotype space and evolutionary set theory. We apply these results to the evolution of cooperation. The mechanism that leads to the evolution of cooperation in these settings could be called ‘spatial selection’: cooperators prevail against defectors by clustering in physical or other spaces. PMID:20008382
Population mixture model for nonlinear telomere dynamics
NASA Astrophysics Data System (ADS)
Itzkovitz, Shalev; Shlush, Liran I.; Gluck, Dan; Skorecki, Karl
2008-12-01
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.
Sun, Zhong Xiang; Zhai, Yi Fan; Zhang, Jian Qing; Kang, Kui; Cai, Jing Heng; Fu, Yonggui; Qiu, Jie Qi; Shen, Jia Wei; Zhang, Wen Qing
2015-02-01
Identifying the molecular markers for complex quantitative traits in natural populations promises to provide novel insight into genetic mechanisms of adaptation and to aid in forecasting population dynamics. In this study, we investigated single nucleotide polymorphisms (SNPs) using candidate gene approach from high- and low-fecundity populations of the brown planthopper (BPH) Nilaparvata lugens Stĺl (Hemiptera: Delphacidae) divergently selected for fecundity. We also tested whether the population fecundity can be predicted by a few SNPs. Seven genes (ACE, fizzy, HMGCR, LpR, Sxl, Vg and VgR) were inspected for SNPs in N. lugens, which is a serious insect pest of rice. By direct sequencing of the complementary DNA and promoter sequences of these candidate genes, 1033 SNPs were discovered within high- and low-fecundity BPH populations. A panel of 121 candidate SNPs were selected and genotyped in 215 individuals from 2 laboratory populations (HFP and LFP) and 3 field populations (GZP, SGP and ZSP). Prior to association tests, population structure and linkage disequilibrium (LD) among the 3 field populations were analysed. The association results showed that 7 SNPs were significantly associated with population fecundity in BPH. These significant SNPs were used for constructing general liner models with stepwise regression. The best predictive model was composed of 2 SNPs (ACE-862 and VgR-816 ) with very good fitting degree. We found that 29% of the phenotypic variation in fecundity could be accounted for by only two markers. Using two laboratory populations and a complete independent field population, the predictive accuracy was 84.35-92.39%. The predictive model provides an efficient molecular method to predict BPH fecundity of field populations and provides novel insights for insect population management. PMID:25581109
Evolutionary Game Theory and Population Dynamics
Miekisz, Jacek
Evolutionary Game Theory and Population Dynamics Jacek Mi¸ekisz Institute of Applied Mathematics replicator dynamics and stochastic dynamics of finite populations. We show the almost global asymptotic the long-run behaviour of stochastic dynamics in well-mixed populations and in spatial games with local
Predictive models of forest dynamics.
Purves, Drew; Pacala, Stephen
2008-06-13
Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data. PMID:18556548
Stochastic Gain in Population Dynamics
NASA Astrophysics Data System (ADS)
Traulsen, Arne; Röhl, Torsten; Schuster, Heinz Georg
2004-07-01
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.
Population size predicts technological complexity in Oceania
Kline, Michelle A.; Boyd, Robert
2010-01-01
Much human adaptation depends on the gradual accumulation of culturally transmitted knowledge and technology. Recent models of this process predict that large, well-connected populations will have more diverse and complex tool kits than small, isolated populations. While several examples of the loss of technology in small populations are consistent with this prediction, it found no support in two systematic quantitative tests. Both studies were based on data from continental populations in which contact rates were not available, and therefore these studies do not provide a test of the models. Here, we show that in Oceania, around the time of early European contact, islands with small populations had less complicated marine foraging technology. This finding suggests that explanations of existing cultural variation based on optimality models alone are incomplete because demography plays an important role in generating cumulative cultural adaptation. It also indicates that hominin populations with similar cognitive abilities may leave very different archaeological records, a conclusion that has important implications for our understanding of the origin of anatomically modern humans and their evolved psychology. PMID:20392733
Understanding EA Dynamics via Population Fitness Distributions
George Mason University
Understanding EA Dynamics via Population Fitness Distributions Elena Popovici epopovic of understanding how the fitness distribution of an EA population changes over time. 1 Introduction and Background Although a sense of the importance of population fitness distributions is deeply ingrained
INVESTIGATION Population Dynamics and Evolutionary History
Stinchcombe, John
INVESTIGATION Population Dynamics and Evolutionary History of the Weedy Vine Ipomoea hederacea that North American I. hederacea has experienced a recent founder event, and/or population dynamics are best.g., bottlenecks) and because current population dynamics may not reflect the past conditions that shaped patterns
Aphid population dynamics: does resistance to parasitism inuence population size?
Hufbauer, Ruth A.
Aphid population dynamics: does resistance to parasitism inŻuence population size? R . A . H U F B.S.A. Abstract. 1. Insect population size is regulated by both intrinsic traits of organisms and extrinsic and extrinsic factors can interact in their effects on population size. 2. Pea aphids Acyrthosiphon pisum Harris
Population Ecology Wolf Population Dynamics in the U.S.
Mitchell, Mike
of factors driving recruitment and human-caused mortality rates in wolf populations in the Northern Rocky recruitment and human-caused mortality affect annual wolf population growth rates and that humanPopulation Ecology Wolf Population Dynamics in the U.S. Northern Rocky Mountains Are Affected
Flood trends and population dynamics
NASA Astrophysics Data System (ADS)
Di Baldassarre, G.
2012-04-01
Since the earliest recorded civilizations, such as those in Mesopotamia and Egypt that developed in the fertile floodplains of the Tigris and Euphrates and Nile rivers, humans tend to settle in flood prone areas as they offer favorable conditions for economic development. However, floodplains are also exposed to flood disasters that might cause severe socio-economic and environmental damages not to mention losses of human lives. A flood event turns to be a disaster when it coincides with a vulnerable environment exceeding society's capacity to manage the adverse consequences. This presentation discusses the link between hydrological risk and population change by referring to the outcomes of scientific works recently carried out in Africa and Europe. More specifically, it is shown that the severity of flood disasters, currently affecting more than 100 million people a year, might be seriously exacerbated because of population change. In fact, flood exposure and/or vulnerability might increase because of rapid population growth (and its spatial and temporal dynamics, e.g. urbanization) in the African continent and because of population ageing in many European countries. Lastly, timely and economically sustainable actions to mitigate this increasing hydrological risk are critically evaluated.
Evolutionary Dynamics and Diversity in Microbial Populations
NASA Astrophysics Data System (ADS)
Thompson, Joel; Fisher, Daniel
2013-03-01
Diseases such as flu and cancer adapt at an astonishing rate. In large part, viruses and cancers are so difficult to prevent because they are continually evolving. Controlling such ``evolutionary diseases'' requires a better understanding of the underlying evolutionary dynamics. It is conventionally assumed that adaptive mutations are rare and therefore will occur and sweep through the population in succession. Recent experiments using modern sequencing technologies have illuminated the many ways in which real population sequence data does not conform to the predictions of conventional theory. We consider a very simple model of asexual evolution and perform simulations in a range of parameters thought to be relevant for microbes and cancer. Simulation results reveal complex evolutionary dynamics typified by competition between lineages with different sets of adaptive mutations. This dynamical process leads to a distribution of mutant gene frequencies different than expected under the conventional assumption that adaptive mutations are rare. Simulated gene frequencies share several conspicuous features with data collected from laboratory-evolved yeast and the worldwide population of influenza.
Dynamical Predictability of Monthly Means.
NASA Astrophysics Data System (ADS)
Shukla, J.
1981-12-01
We have attempted to determine the theoretical upper limit of dynamical predictability of monthly means for prescribed nonfluctuating external forcings. We have extended the concept of `classical' predictability, which primarily refers to the lack of predictability due mainly to the instabilities of synoptic-scale disturbances, to the predictability of time averages, which are determined by the predictability of low-frequency planetary waves. We have carded out 60-day integrations of a global general circulation model with nine different initial conditions but identical boundary conditions of sea surface temperature, snow, sea ice and soil moisture. Three of these initial conditions are the observed atmospheric conditions on 1 January of 1975, 1976 and 1977. The other six initial conditions are obtained by superimposing over the observed initial conditions a random perturbation comparable to the errors of observation. The root-mean-square (rms) error of random perturbations at all the grid points and all the model levels is 3 m s1 in u and v components of wind. The rms vector wind error between the observed initial conditions is >15 m s1.It is hypothesized that for a given averaging period, if the rms error among the time averages predicted from largely different initial conditions becomes comparable to the rms error among the time averages predicted from randomly perturbed initial conditions, the time averages are dynamically unpredictable. We have carried out the analysis of variance to compare the variability, among the three groups, due to largely different initial conditions, and within each group due to random perturbations.It is found that the variances among the first 30-day means, predicted from largely different initial conditions, are significantly different from the variances due to random perturbations in the initial conditions, whereas the variances among 30-day means for days 31-60 are not distinguishable from the variances due to random initial perturbations. The 30-day means for days 16-46 over certain areas are also significantly different from the valances due to random perturbations.These results suggest that the evolution of long waves remains sufficiently predictable at least up to one month, and possibly up to 45 days, so that the combined effects of their own nonpredictability and their depredictabilization by synoptic-scale instabilities is not large enough to degrade the dynamical prediction of monthly means. The Northern Hemisphere appears to be more predictable than the Southern Hemisphere.It is noteworthy that the lack of predictability for the second month is not because the model simulations relax to the same model state but because of very large departures in the simulated model states. This suggests that, with improvements in model resolution and physical parameterizations, there is potential for extending the predictability of time averages even beyond one month.Here, we have examined only the dynamical predictability, because the boundary conditions are identical in all the integrations. Based on these results, and the possibility of additional predictability due to the influence of persistent anomalies of sea surface temperature, sea ice, snow and soil moisture, it is suggested that there is sufficient physical basis to undertake a systematic program to establish the feasibility of predicting monthly means by numerical integrations of realistic dynamical models.
Dynamic seasonal prediction and predictability of the monsoon
Kang, In-Sik
15 Dynamic seasonal prediction and predictability of the monsoon In-Sik Kang and Jagadish Shukla In this chapter we present a historical review of the hypothesis of boundary forced predictability of the monsoon and the limitations and challenges in dynamical seasonal prediction of monsoon rainfall. We also present an assessment
A quantitative model of honey bee colony population dynamics.
Khoury, David S; Myerscough, Mary R; Barron, Andrew B
2011-01-01
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
Modeling population dynamics: A quantile approach.
Chavas, Jean-Paul
2015-04-01
The paper investigates the modeling of population dynamics, both conceptually and empirically. It presents a reduced form representation that provides a flexible characterization of population dynamics. It leads to the specification of a threshold quantile autoregression (TQAR) model, which captures nonlinear dynamics by allowing lag effects to vary across quantiles of the distribution as well as with previous population levels. The usefulness of the model is illustrated in an application to the dynamics of lynx population. We find statistical evidence that the quantile autoregression parameters vary across quantiles (thus rejecting the AR model as well as the TAR model) as well as with past populations (thus rejecting the quantile autoregression QAR model). The results document the nature of dynamics and cycle in the lynx population over time. They show how both the period of the cycle and the speed of population adjustment vary with population level and environmental conditions. PMID:25661501
Modelling social dynamics of a structured population.
Primicerio, Mario
(with or without the presence of other populations, criminals, guards, prisoners, etc) under differentModelling social dynamics of a structured population. Abstract We present a model for the dynamics of a population where the age distribution and the social structure are taken into account. This results
An Individual-Based Model of Zebrafish Population Dynamics Accounting for Energy Dynamics
Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R. R.
2015-01-01
Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level. PMID:25938409
An individual-based model of zebrafish population dynamics accounting for energy dynamics.
Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R R
2015-01-01
Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level. PMID:25938409
Modeling Population Dynamics: a Graphical Approach
de Boer, Rob J.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3 Population growth: replication 11 3.1 Density dependent death . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2 Exponential growth and decay . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2Modeling Population Dynamics: a Graphical Approach Rob J. de Boer Theoretical Biology
Population dynamics at high Reynolds number
Prasad Perlekar; Roberto Benzi; David R. Nelson; Federico Toschi
2010-09-03
We study the statistical properties of population dynamics evolving in a realistic two-dimensional compressible turbulent velocity field. We show that the interplay between turbulent dynamics and population growth and saturation leads to quasi-localization and a remarkable reduction in the carrying capacity. The statistical properties of the population density are investigated and quantified via multifractal scaling analysis. We also investigate numerically the singular limit of negligibly small growth rates and delocalization of population ridges triggered by uniform advection.
Co-infection alters population dynamics of infectious disease
Susi, Hanna; Barrčs, Benoit; Vale, Pedro F.; Laine, Anna-Liisa
2015-01-01
Co-infections by multiple pathogen strains are common in the wild. Theory predicts co-infections to have major consequences for both within- and between-host disease dynamics, but data are currently scarce. Here, using common garden populations of Plantago lanceolata infected by two strains of the pathogen Podosphaera plantaginis, either singly or under co-infection, we find the highest disease prevalence in co-infected treatments both at the host genotype and population levels. A spore-trapping experiment demonstrates that co-infected hosts shed more transmission propagules than singly infected hosts, thereby explaining the observed change in epidemiological dynamics. Our experimental findings are confirmed in natural pathogen populations—more devastating epidemics were measured in populations with higher levels of co-infection. Jointly, our results confirm the predictions made by theoretical and experimental studies for the potential of co-infection to alter disease dynamics across a large host–pathogen metapopulation. PMID:25569306
Co-infection alters population dynamics of infectious disease.
Susi, Hanna; Barrčs, Benoit; Vale, Pedro F; Laine, Anna-Liisa
2015-01-01
Co-infections by multiple pathogen strains are common in the wild. Theory predicts co-infections to have major consequences for both within- and between-host disease dynamics, but data are currently scarce. Here, using common garden populations of Plantago lanceolata infected by two strains of the pathogen Podosphaera plantaginis, either singly or under co-infection, we find the highest disease prevalence in co-infected treatments both at the host genotype and population levels. A spore-trapping experiment demonstrates that co-infected hosts shed more transmission propagules than singly infected hosts, thereby explaining the observed change in epidemiological dynamics. Our experimental findings are confirmed in natural pathogen populations-more devastating epidemics were measured in populations with higher levels of co-infection. Jointly, our results confirm the predictions made by theoretical and experimental studies for the potential of co-infection to alter disease dynamics across a large host-pathogen metapopulation. PMID:25569306
Annealing schedule from population dynamics Stefan Bornholdt*
Bornholdt, Stefan
Annealing schedule from population dynamics Stefan Bornholdt* Institut fuÂ¨r Theoretische Physik received 30 November 1998 We introduce a dynamical annealing schedule for population-based optimization known from simulated annealing 8 , an optimization algorithm where noise is introduced by means
Size Dependent Population Dynamics of Microtus Ochrogaster
Sauer, John R.; Slade, Norman A.
1986-06-01
Vol. 127, No. 6 The American Naturalist June 1986 SIZE-DEPENDENT POPULATION DYNAMICS OF MICROTUS OCHROGASTER Lefkovitch (1965#) generalized Leslie's (1945) matrix model of age-structured population growth to include stage-transition matrices... and Werner 1978) have used stage-transition matrices to analyze population dynamics in discrete time, but vertebrate biologists have not, perhaps because of the lack of reliable "stages" into which animals with distinct rates of fecundity and survival can...
Consumption driven population dynamics (CDPD)
Richard P. Bentley
2006-01-01
Ecologists have long pursued a cohesive mathematical structure describing the interactions between the multitudes of species populating the web of life. Consumption dependence offers a logical approach built upon the mechanism of mass-energy flow necessary to all life processes. Consumption, defined as that fraction of satiation currently enjoyed by a local species population, will affect that population's birth rate, natural
Corrigendum Evolutionary games and population dynamics
Hauert, Christoph
Corrigendum Evolutionary games and population dynamics: maintenance of cooperation in public goods games The analysis of our model for the maintenance of cooperation in public goods games based on a feedback between ecological dynamics and game dynamics was incomplete. In addition to the scenarios
Population dynamics of interacting spiking neurons
NASA Astrophysics Data System (ADS)
Mattia, Maurizio; del Giudice, Paolo
2002-11-01
A dynamical equation is derived for the spike emission rate ?(t) of a homogeneous network of integrate-and-fire (IF) neurons in a mean-field theoretical framework, where the activity of the single cell depends both on the mean afferent current (the ``field'') and on its fluctuations. Finite-size effects are taken into account, by a stochastic extension of the dynamical equation for the ? their effect on the collective activity is studied in detail. Conditions for the local stability of the collective activity are shown to be naturally and simply expressed in terms of (the slope of) the single neuron, static, current-to-rate transfer function. In the framework of the local analysis, we studied the spectral properties of the time-dependent collective activity of the finite network in an asynchronous state; finite-size fluctuations act as an ongoing self-stimulation, which probes the spectral structure of the system on a wide frequency range. The power spectrum of ? exhibits modes ranging from very high frequency (depending on spike transmission delays), which are responsible for instability, to oscillations at a few Hz, direct expression of the diffusion process describing the population dynamics. The latter ``diffusion'' slow modes do not contribute to the stability conditions. Their characteristic times govern the transient response of the network; these reaction times also exhibit a simple dependence on the slope of the neuron transfer function. We speculate on the possible relevance of our results for the change in the characteristic response time of a neural population during the learning process which shapes the synaptic couplings, thereby affecting the slope of the transfer function. There is remarkable agreement of the theoretical predictions with simulations of a network of IF neurons with a constant leakage term for the membrane potential.
Evolutionary games and population dynamics: maintenance of cooperation
Hauert, Christoph
Evolutionary games and population dynamics: maintenance of cooperation in public goods games, cooperation should decrease and vanish, as predicted by classical models for cooperation in evolutionary game theory, such as the Prisoner's Dilemma and public goods games. Traditional approaches to studying
Complex population dynamics and complex causation: devils, details and demography
Benton, Tim G; Plaistow, Stewart J; Coulson, Tim N
2006-01-01
Population dynamics result from the interplay of density-independent and density-dependent processes. Understanding this interplay is important, especially for being able to predict near-term population trajectories for management. In recent years, the study of model systems—experimental, observational and theoretical—has shed considerable light on the way that the both density-dependent and -independent aspects of the environment affect population dynamics via impacting on the organism's life history and therefore demography. These model-based approaches suggest that (i) individuals in different states differ in their demographic performance, (ii) these differences generate structure that can fluctuate independently of current total population size and so can influence the dynamics in important ways, (iii) individuals are strongly affected by both current and past environments, even when the past environments may be in previous generations and (iv) dynamics are typically complex and transient due to environmental noise perturbing complex population structures. For understanding population dynamics of any given system, we suggest that ‘the devil is in the detail’. Experimental dissection of empirical systems is providing important insights into the details of the drivers of demographic responses and therefore dynamics and should also stimulate theory that incorporates relevant biological mechanism. PMID:16720388
Learning stable, regularised latent models of neural population dynamics
Sahani, Maneesh
Learning stable, regularised latent models of neural population dynamics Lars Buesing, Jakob H models of population dynamics Abstract Ongoing advances in experimental technique are making commonplace. Latent population models, including Gaussian-process factor analysis and hidden linear dynamical system
Immigration-extinction dynamics of stochastic populations
NASA Astrophysics Data System (ADS)
Meerson, Baruch; Ovaskainen, Otso
2013-07-01
How high should be the rate of immigration into a stochastic population in order to significantly reduce the probability of observing the population become extinct? Is there any relation between the population size distributions with and without immigration? Under what conditions can one justify the simple patch occupancy models, which ignore the population distribution and its dynamics in a patch, and treat a patch simply as either occupied or empty? We answer these questions by exactly solving a simple stochastic model obtained by adding a steady immigration to a variant of the Verhulst model: a prototypical model of an isolated stochastic population.
NASA Astrophysics Data System (ADS)
Olsen, C.; Lintz, H. E.; Peckham, S. D.
2013-12-01
We do not fully understand reasons behind extinction of populations and species. Consequently, our ability to anticipate extinction (which can be considered a permanent type of an ecological threshold) has remained elusive. In particular, it is not clear how the attributes of episodic disturbance regimes can elicit extinction. Here, I test a stochastic model that predicts population extinction based on attributes of the disturbance regime and population growth rates using phytoplankton in a test tube. I examined the response of phytoplankton (Thalassiosira weissflogii) to stochastic disturbances implemented by having MATLAB control a hydraulic pump that episodically removed portions of the population through time in between episodes of population recovery. My experiment demonstrated evidence that a theoretical or mathematical threshold predicted to exist in theory may actually apply to a diatom population dynamics in a test tube; however, my results also open new questions about how the statistical attributes of the disturbance regimes under study may alter the predicted time to population extinction.
Understanding EA Dynamics via Population Fitness Distributions
George Mason University
Understanding EA Dynamics via Population Fitness Distributions Elena Popovici and Kenneth De Jong population fitness distribution rather than just "best-so-far" curves. But characterizing how repeated fitness landscapes. Our approach is to study empirically derived fitness distributions, both qual
Detection, Diversity, and Population Dynamics of Waterborne Phytophthora ramorum Populations.
Eyre, C A; Garbelotto, M
2015-01-01
Sudden oak death, the tree disease caused by Phytophthora ramorum, has significant environmental and economic impacts on natural forests on the U.S. west coast, plantations in the United Kingdom, and in the worldwide nursery trade. Stream baiting is vital for monitoring and early detection of the pathogen in high-risk areas and is performed routinely; however, little is known about the nature of water-borne P. ramorum populations. Two drainages in an infested California forest were monitored intensively using stream-baiting for 2 years between 2009 and 2011. Pathogen presence was determined both by isolation and polymerase chain reaction (PCR) from symptomatic bait leaves. Isolates were analyzed using simple sequence repeats to study population dynamics and genetic structure through time. Isolation was successful primarily only during spring conditions, while PCR extended the period of pathogen detection to most of the year. Water populations were extremely diverse, and changed between seasons and years. A few abundant genotypes dominated the water during conditions considered optimal for aerial populations, and matched those dominant in aerial populations. Temporal patterns of genotypic diversification and evenness were identical among aerial, soil, and water populations, indicating that all three substrates are part of the same epidemiological cycle, strongly influenced by rainfall and sporulation on leaves. However, there was structuring between substrates, likely arising due to reduced selection pressure in the water. Additionally, water populations showed wholesale mixing of genotypes without the evident spatial autocorrelation present in leaf and soil populations. PMID:25026455
Pathwise thermodynamic structure in population dynamics.
Sughiyama, Yuki; Kobayashi, Tetsuya J; Tsumura, Koji; Aihara, Kazuyuki
2015-03-01
We reveal thermodynamic structure in population dynamics with phenotype switching. Mean fitness for a population of organisms is determined by a thermodynamic variational principle described by the large deviation of phenotype-switching dynamics. Owing to this variational principle, a response relation of the mean fitness with respect to changes of environments and phenotype-switching dynamics is represented as a thermodynamic differential form. Furthermore, we discuss the strength of the selection by using the difference between time-forward and time-backward (retrospective) processes. PMID:25871067
Bidirectional Dynamics for Protein Secondary Structure Prediction
Pollastri, Gianluca
Bidirectional Dynamics for Protein Secondary Structure Prediction Pierre Baldi1 , Sřren Brunak2 of several successful applications (mostly based on hidden Markov models), the general class of sequence-Verlag Berlin Heidelberg 2000 #12;Bidirectional Dynamics for Protein Secondary Structure Prediction 81 chains
Predictive Dynamic Security Assessment through Advanced Computing
Huang, Zhenyu; Diao, Ruisheng; Jin, Shuangshuang; Chen, Yousu
2014-11-30
Abstract— Traditional dynamic security assessment is limited by several factors and thus falls short in providing real-time information to be predictive for power system operation. These factors include the steady-state assumption of current operating points, static transfer limits, and low computational speed. This addresses these factors and frames predictive dynamic security assessment. The primary objective of predictive dynamic security assessment is to enhance the functionality and computational process of dynamic security assessment through the use of high-speed phasor measurements and the application of advanced computing technologies for faster-than-real-time simulation. This paper presents algorithms, computing platforms, and simulation frameworks that constitute the predictive dynamic security assessment capability. Examples of phasor application and fast computation for dynamic security assessment are included to demonstrate the feasibility and speed enhancement for real-time applications.
The analysis of crow population dynamics as a surveillance tool.
Ludwig, A; Bigras-Poulin, M; Michel, P
2009-12-01
West Nile virus (WNV) infection, a zoonotic disease for which birds act as a reservoir, first appeared in North America in August 1999. It was first reported in Quebec in 2002. The Quebec surveillance system for WNV has several components, including the surveillance of mortality in corvid populations, which includes the American crow (Corvus brachyrhynchos). The main objectives of this study are to better understand the population dynamics of this species in Quebec and to evaluate the impact of WNV on these dynamics. We obtained observation data for living crows in this province for the period of 1990-2005 and then conducted a spectral analysis of these data. To study changes in crow population dynamics, the analysis was carried out before and after the appearance of WNV and space was divided in two different areas (urban and non-urban). Our results show the importance of cycles with periods of less than 1 year in non-urban areas and cycles with periods of greater than 1 year in urban areas in the normal population dynamics of the species. We obtained expected fluctuations in bird densities using an algorithm derived from spectral decomposition. When we compared these predictions with data observed after 2002, we found marked perturbations in population dynamics beginning in 2003 and lasting up to 2005. In the discussion, we present various hypotheses based on the behaviour of the American crow to explain the normal population dynamics observed in this species and the effect of type of area (urban versus non-urban). We also discuss how the predictive algorithm could be used as a disease surveillance tool and as a measure of the impact of a disease on wild fauna. PMID:19811623
Harvest and dynamics of duck populations
Sedinger, James S.; Herzog, Mark P.
2012-01-01
The role of harvest in the dynamics of waterfowl populations continues to be debated among scientists and managers. Our perception is that interested members of the public and some managers believe that harvest influences North American duck populations based on calls for more conservative harvest regulations. A recent review of harvest and population dynamics of North American mallard (Anas platyrhynchos) populations (Pöysä et al. 2004) reached similar conclusions. Because of the importance of this issue, we reviewed the evidence for an impact of harvest on duck populations. Our understanding of the effects of harvest is limited because harvest effects are typically confounded with those of population density; regulations are typically most liberal when populations are greatest. This problem also exists in the current Adaptive Harvest Management Program (Conn and Kendall 2004). Consequently, even where harvest appears additive to other mortality, this may be an artifact of ignoring effects of population density. Overall, we found no compelling evidence for strong additive effects of harvest on survival in duck populations that could not be explained by other factors.
Predictive information in a sensory population
Marre, Olivier; Berry, Michael J.; Bialek, William
2015-01-01
Guiding behavior requires the brain to make predictions about the future values of sensory inputs. Here, we show that efficient predictive computation starts at the earliest stages of the visual system. We compute how much information groups of retinal ganglion cells carry about the future state of their visual inputs and show that nearly every cell in the retina participates in a group of cells for which this predictive information is close to the physical limit set by the statistical structure of the inputs themselves. Groups of cells in the retina carry information about the future state of their own activity, and we show that this information can be compressed further and encoded by downstream predictor neurons that exhibit feature selectivity that would support predictive computations. Efficient representation of predictive information is a candidate principle that can be applied at each stage of neural computation. PMID:26038544
Ability of matrix models to explain the past and predict the future of plant populations.
Crone, Elizabeth E; Ellis, Martha M; Morris, William F; Stanley, Amanda; Bell, Timothy; Bierzychudek, Paulette; Ehrlén, Johan; Kaye, Thomas N; Knight, Tiffany M; Lesica, Peter; Oostermeijer, Gerard; Quintana-Ascencio, Pedro F; Ticktin, Tamara; Valverde, Teresa; Williams, Jennifer L; Doak, Daniel F; Ganesan, Rengaian; McEachern, Kathyrn; Thorpe, Andrea S; Menges, Eric S
2013-10-01
Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage-based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts' 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data-collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk-averse decisions than to expect precise forecasts from models. PMID:23565966
Ability of matrix models to explain the past and predict the future of plant populations.
McEachern, Kathryn; Crone, Elizabeth E.; Ellis, Martha M.; Morris, William F.; Stanley, Amanda; Bell, Timothy; Bierzychudek, Paulette; Ehrlen, Johan; Kaye, Thomas N.; Knight, Tiffany M.; Lesica, Peter; Oostermeijer, Gerard; Quintana-Ascencio, Pedro F.; Ticktin, Tamara; Valverde, Teresa; Williams, Jennifer I.; Doak, Daniel F.; Ganesan, Rengaian; Thorpe, Andrea S.; Menges, Eric S.
2013-01-01
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.
Evolutionary and Population Dynamics: A Coupled Approach
Cremer, Jonas; Frey, Erwin
2011-01-01
We study the interplay of population growth and evolutionary dynamics using a stochastic model based on birth and death events. In contrast to the common assumption of an independent population size, evolution can be strongly affected by population dynamics in general. Especially for fast reproducing microbes which are subject to selection, both types of dynamics are often closely intertwined. We illustrate this by considering different growth scenarios. Depending on whether microbes die or stop to reproduce (dormancy), qualitatively different behaviors emerge. For cooperating bacteria, a permanent increase of costly cooperation can occur. Even if not permanent, cooperation can still increase transiently due to demographic fluctuations. We validate our analysis via stochastic simulations and analytic calculations. In particular, we derive a condition for an increase in the level of cooperation.
Multispecies population dynamics of prebiotic compositional assemblies.
Markovitch, Omer; Lancet, Doron
2014-09-21
Present life portrays a two-tier phenomenology: molecules compose supramolecular structures, such as cells or organisms, which in turn portray population behaviors, including selection, evolution and ecological dynamics. Prebiotic models have often focused on evolution in populations of self-replicating molecules, without explicitly invoking the intermediate molecular-to-supramolecular transition. Here, we explore a prebiotic model that allows one to relate parameters of chemical interaction networks within molecular assemblies to emergent population dynamics. We use the graded autocatalysis replication domain (GARD) model, which simulates the network dynamics within amphiphile-containing molecular assemblies, and exhibits quasi-stationary compositional states termed compotype species. These grow by catalyzed accretion, divide and propagate their compositional information to progeny in a replication-like manner. The model allows us to ask how molecular network parameters influence assembly evolution and population dynamics parameters. In 1000 computer simulations, each embodying different parameter set of the global chemical interaction network parameters, we observed a wide range of behaviors. These were analyzed by a multi species logistic model often used for analyzing population ecology (r-K or Lotka-Volterra competition model). We found that compotypes with a larger intrinsic molecular repertoire show a higher intrinsic growth (r) and lower carrying capacity (K), as well as lower replication fidelity. This supports a prebiotic scenario initiated by fast-replicating assemblies with a high molecular diversity, evolving into more faithful replicators with narrower molecular repertoires. PMID:24831416
Irruptive population dynamics in Yellowstone pronghorn.
White, P J; Bruggeman, Jason E; Garrott, Robert A
2007-09-01
Irruptive population dynamics appear to be widespread in large herbivore populations, but there are few empirical examples from long time series with small measurement error and minimal harvests. We analyzed an 89-year time series of counts and known removals for pronghorn (Antilocapra americana) in Yellowstone National Park of the western United States during 1918-2006 using a suite of density-dependent, density-independent, and irruptive models to determine if the population exhibited irruptive dynamics. Information-theoretic model comparison techniques strongly supported irruptive population dynamics (Leopold model) and density dependence during 1918-1946, with the growth rate slowing after counts exceeded 600 animals. Concerns about sagebrush (Artemisia spp.) degradation led to removals of >1100 pronghorn during 1947-1966, and counts decreased from approximately 700 to 150. The best models for this period (Gompertz, Ricker) suggested that culls replaced intrinsic density-dependent mechanisms. Contrary to expectations, the population did not exhibit enhanced demographic vigor soon after the termination of the harvest program, with counts remaining between 100 and 190 animals during 1967 1981. However, the population irrupted (Caughley model with a one-year lag) to a peak abundance of approximately 600 pronghorn during 1982-1991, with a slowing in growth rate as counts exceeded 500. Numbers crashed to 235 pronghorn during 1992-1995, perhaps because important food resources (e.g., sagebrush) on the winter range were severely diminished by high densities of browsing elk, mule deer, and pronghorn. Pronghorn numbers remained relatively constant during 1996-2006, at a level (196-235) lower than peak abundance, but higher than numbers following the release from culling. The dynamics of this population supported the paradigm that irruption is a fundamental pattern of growth in many populations of large herbivores with high fecundity and delayed density-dependent effects on recruitment when forage and weather conditions become favorable after range expansion or release from harvesting. Incorporating known removals into population models that can describe a wide range of dynamics can greatly improve our interpretation of observed dynamics in intensively managed populations. PMID:17913126
Fast stochastic algorithm for simulating evolutionary population dynamics
Tsimring, Lev S.
Fast stochastic algorithm for simulating evolutionary population dynamics William H. Mather1 stochastic process of population dynamics driven by mutations and selection, and the details dynamics can only be addressed through simulations. However, accurate simulations of realistically large
The Dynamics and Predictability of Tropical Cyclones
Sippel, Jason A.
2010-01-15
Through methodology unique for tropical cyclones in peer-reviewed literature, this study explores how the dynamics of moist convection affects the predictability of tropical cyclogenesis. Mesoscale models are used to perform short-range ensemble...
ORIGINAL ARTICLE Quantitative population dynamics of
Girguis, Peter R.
ORIGINAL ARTICLE Quantitative population dynamics of microbial communities in plankton, Cambridge, MA, USA and 2 College of Oceanic and Atmospheric Sciences, Hatfield Marine Science Center, Oregon and geochemistry. MFCs were batch-fed with plankton, and two systems were maintained at different potentials
Stoichiometry and population dynamics Tom Andersen,1
Elser, Jim
REVIEW Stoichiometry and population dynamics Tom Andersen,1 * James J. Elser2 and Dag O. Hessen1 1, stoichiometry, trophic efficiency. Ecology Letters (2004) 7: 884900 I N T R O DU C T I O N Few aspects. This falls within an emerging branch of ecology, now labeled Ôecological stoichiometryŐ (Sterner & Elser 2002
Population dynamic theory of size-dependent cannibalism.
Claessen, David; de Roos, André M.; Persson, Lennart
2004-01-01
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 chaos; (iii) stabilization by damping population cycles caused by other interactions; (iv) bistability such that, depending on the initial conditions, the population converges to one of two possible stable states; and (v) modification of the population size structure. The same effects of cannibalism may be caused by different combinations of aspects of cannibalism. By contrast, the same combination of aspects may lead to different effects. For particular cannibalistic species, the consequences of cannibalism will depend on the presence and details of the four defining aspects. Empirical evidence for the emerged theory of cannibalism is discussed briefly. The implications of the described dynamic effects of cannibalism are discussed in the context of community structure, making a comparison with the community effects of intraguild predation. PMID:15101690
Dynamics of newly established elk populations
Sargeant, G.A.; Oehler, M.W., Sr.
2007-01-01
The dynamics of newly established elk (Cervus elaphus) populations can provide insights about maximum sustainable rates of reproduction, survival, and increase. However, data used to estimate rates of increase typically have been limited to counts and rarely have included complementary estimates of vital rates. Complexities of population dynamics cannot be understood without considering population processes as well as population states. We estimated pregnancy rates, survival rates, age ratios, and sex ratios for reintroduced elk at Theodore Roosevelt National Park, North Dakota, USA; combined vital rates in a population projection model; and compared model projections with observed elk numbers and population ratios. Pregnancy rates in January (early in the second trimester of pregnancy) averaged 54.1% (SE = 5.4%) for subadults and 91.0% (SE = 1.7%) for adults, and 91.6% of pregnancies resulted in recruitment at 8 months. Annual survival rates of adult females averaged 0.96 (95% CI = 0.94-0.98) with hunting included and 0.99 (95% CI = 0.97-0.99) with hunting excluded from calculations. Our fitted model explained 99.8% of past variation in population estimates and represents a useful new tool for short-term management planning. Although we found no evidence of temporal variation in vital rates, variation in population composition caused substantial variation in projected rates of increase (??=1.20-1.36). Restoring documented hunter harvests and removals of elk by the National Park Service led to a potential rate of ?? = 1.26. Greater rates of increase substantiated elsewhere were within the expected range of chance variation, given our model and estimates of vital rates. Rates of increase realized by small elk populations are too variable to support inferences about habitat quality or density dependence.
Spreading dynamics on heterogeneous populations: Multitype network approach
NASA Astrophysics Data System (ADS)
Vazquez, Alexei
2006-12-01
I study the spreading of infectious diseases in heterogeneous populations. The population structure is described by a contact graph where vertices represent agents and edges represent disease transmission channels among them. The population heterogeneity is taken into account by the agent’s subdivision in types and the mixing matrix among them. I introduce a type-network representation for the mixing matrix, allowing an intuitive understanding of the mixing patterns and the calculations. Using an iterative approach I obtain recursive equations for the probability distribution of the outbreak size as a function of time. I demonstrate that the expected outbreak size and its progression in time are determined by the largest eigenvalue of the reproductive number matrix and the characteristic distance between agents on the contact graph. Finally, I discuss the impact of intervention strategies to halt epidemic outbreaks. This work provides both a qualitative understanding and tools to obtain quantitative predictions for the spreading dynamics of heterogeneous populations.
Spreading dynamics on heterogeneous populations: multitype network approach.
Vazquez, Alexei
2006-12-01
I study the spreading of infectious diseases in heterogeneous populations. The population structure is described by a contact graph where vertices represent agents and edges represent disease transmission channels among them. The population heterogeneity is taken into account by the agent's subdivision in types and the mixing matrix among them. I introduce a type-network representation for the mixing matrix, allowing an intuitive understanding of the mixing patterns and the calculations. Using an iterative approach I obtain recursive equations for the probability distribution of the outbreak size as a function of time. I demonstrate that the expected outbreak size and its progression in time are determined by the largest eigenvalue of the reproductive number matrix and the characteristic distance between agents on the contact graph. Finally, I discuss the impact of intervention strategies to halt epidemic outbreaks. This work provides both a qualitative understanding and tools to obtain quantitative predictions for the spreading dynamics of heterogeneous populations. PMID:17280128
Prediction of HAMR Debris Population Distribution Released from GEO Space
NASA Astrophysics Data System (ADS)
Rosengren, A.; Scheeres, D.
2012-09-01
The high area-to-mass ratio (HAMR) debris population is thought to have origins in the GEO region. Many of these objects are uncharacterized with apparent area-to-mass ratios of up to 30 meters squared per kilogram. The orbits of HAMR objects are highly perturbed due to the combined effect of solar radiation pressure (SRP), anomalies of the Earth gravitational field, and third-body gravitational interactions induced by the Sun and the Moon. A sound understanding of their nature, orbital evolution, and possible origin is critical for space situational awareness. The study of the orbital evolution of HAMR objects, taking into account both short-period and long-period terms, requires numerical integration of the precise set of differential equations, and the investigation of a broad range of possible parameter values. However, such computations become very costly when continuously applied over a period of several decades, as is necessary in the case of HAMR debris. It therefore seems reasonable to investigate the equations that govern the long-term behavior of orbits; such equations can be derived by the method of averaging. We have validated a semi-analytical averaged theory of HAMR object orbit evolution against high precision numerical integrations, and are able to capture the extreme dynamical behaviors reported for these objects. This new averaged model, explicitly given in terms of the eccentricity and angular momentum vectors, is several hundred times faster to numerically integrate than the non-averaged Newtonian counterpart, and provides a very accurate description of the long-term behavior. Using this model, it is possible to make predictions of how a population of HAMR objects, released into GEO orbit, will evolve over time. Our earlier analyses revealed that the population would have a range of orbits much different than circular GEO. Their orbits will suffer a sub-yearly oscillation in the eccentricity and inclination evolutions, and a longer-term drift in inclination. When the nodal rate of the system is commensurate with the nodal rate of the Moon, the perturbations build up more effectively over long periods to produce significant effects on the orbit. Such resonances, which occurs for a class of HAMR objects that are not cleared out of orbit, gives rise to strongly changing dynamics over longer time periods. In this paper, we present the averaged model, and discuss its fundamental predictions and comparisons with explicit long-term numerical integrations of HAMR objects in GEO space. Using this tool, we study a range of HAMR objects, released in geostationary orbit, with various area-to-mass ratios, and predict the spatiotemporal distribution of the population. We identified a unique systematic structure associated with their distribution in inclination and ascending node phase space. Given that HAMR objects are the most difficult to target from an observational point of view, this work will have many implications for the space surveillance community, and will allow observers to implement better search strategies for this class of debris.
ERIC Educational Resources Information Center
Klaff, Vivian; Handler, Paul
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…
Predicting the response of populations to environmental change
Ives, A.R.
1995-04-01
When subject to long-term directional environmental perturbations, changes in population densities depend on the positive and negative feedbacks operating through interactions within and among species in a community. This paper develops techniques to predict the long-term responses of population densities to environmental changes using data on short-term population fluctuations driven by short-term environmental variability. In addition to giving quantitative predictions, the techniques also reveal how different qualitative patterns of species interactions either buffer or accentuate population responses to environmental trends. All of the predictions are based on regression coefficients extracted from time series data, and they can therefore be applied with a minimum of mathematical and statistical gymnastics. 48 refs., 10 figs., 4 tabs.
Dynamics of protein distributions in cell populations
NASA Astrophysics Data System (ADS)
Brenner, Naama; Farkash, Keren; Braun, Erez
2006-09-01
A population of cells exhibits wide phenotypic variation even if it is genetically homogeneous. In particular, individual cells differ from one another in the amount of protein they express under a given regulatory system under fixed conditions. Here we study how protein distributions in a population of the yeast S. cerevisiae are shaped by a balance of processes: protein production—an intracellular process—and protein dilution due to cell division—a population process. We measure protein distributions by employing reporter green fluorescence protein (gfp) under the regulation of the yeast GAL system under conditions where it is metabolically essential. Cell populations are grown in chemostats, thus allowing control of the environment and stable measurements of distribution dynamics over many generations. Despite the essential functional role of the GAL system in a pure galactose medium, steady-state distributions are found to be universally broad, with exponential tails and a large standard-deviation-to-mean ratio. Under several different perturbations the dynamics of the distribution is observed to be asymmetric, with a much longer time to build a wide expression distribution from below compared with a fast relaxation of the distribution toward steady state from above. These results show that the main features of the protein distributions are largely determined by population effects and are less sensitive to the intracellular biochemical noise.
2012. 1 101 Cognitive Computing III: Deep Dynamic Prediction -
, population coding) / . (dynamic systems, Bayesian brain) . (physical computing models) . 2) . . . , . [18,19]. (Bayesian brain) . 2 Population Code [18,19] #12;104 II Cognitive) . . Rule-based System Models Connectionist Network Models Population Coding Models Dynamic System Models
Steady state thermodynamics in population dynamics
Sughiyama, Yuki
2015-01-01
We report that population dynamics in fluctuating environment accompanies mathematically equivalent structure to steady state thermodynamics. By employing the structure, population growth in fluctuating environment is decomposed into housekeeping and excess parts. The housekeeping part represents the integral of stationary growth rate for each condition during a history of the environmental change. The excess part accounts for the excess growth generated when environment is switched. Focusing on the excess growth, we obtain Clausius inequality, which gives the upper bound of the excess growth. The equality is shown to be achieved in quasistatic environmental changes. We also clarify that this bound can be evaluated by "lineage fitness" that is an experimentally observable quantity.
Link between Population Dynamics and Dynamics of Darwinian Evolution Geza Meszena*
Meszéna, Géza
Link between Population Dynamics and Dynamics of Darwinian Evolution Ge´za Mesze´na* Department 10 April 2005; published 12 August 2005) We provide the link between population dynamics and the dynamics of Darwinian evolution via studying the joint population dynamics of similar populations
Sanchez, Alvaro
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 ...
Population growth dynamics of carbon nanotubes.
Bedewy, Mostafa; Meshot, Eric R; Reinker, Michael J; Hart, A John
2011-11-22
Understanding the population growth behavior of filamentary nanostructures, such as carbon nanotubes (CNTs), is hampered by the lack of characterization techniques capable of probing statistical variations with high spatial resolution. We present a comprehensive methodology for studying the population growth dynamics of vertically aligned CNT forests, utilizing high-resolution spatial mapping of synchrotron X-ray scattering and attenuation, along with real-time height kinetics. We map the CNT alignment and dimensions within CNT forests, revealing broadening and focusing of size distributions during different stages of the process. Then, we calculate the number density and mass density of the CNT population versus time, which are true measures of the reaction kinetics. We find that the mass-based kinetics of a CNT population is accurately represented by the S-shaped Gompertz model of population growth, although the forest height and CNT length kinetics are essentially linear. Competition between catalyst activation and deactivation govern the rapid initial acceleration and slow decay of the CNT number density. The maximum CNT density (i.e., the overall catalyst activity) is limited by gas-phase reactions and catalyst-surface interactions, which collectively exhibit autocatalytic behavior. Thus, we propose a comprehensive picture of CNT population growth which combines both chemical and mechanical cooperation. Our findings are relevant to both bulk and substrate-based CNT synthesis methods and provide general insights into the self-assembly and collective growth of filamentary nanostructures. PMID:22023221
Galactic civilizations - Population dynamics and interstellar diffusion
NASA Technical Reports Server (NTRS)
Newman, W. I.; Sagan, C.
1981-01-01
A model is developed of the interstellar diffusion of galactic civilizations which takes into account the population dynamics of such civilizations. The problem is formulated in terms of potential theory, with a family of nonlinear partial differential and difference equations specifying population growth and diffusion for an organism with advantageous genes that undergoes random dispersal while increasing in population locally, and a population at zero population growth. In the case of nonlinear diffusion with growth and saturation, it is found that the colonization wavefront from the nearest independently arisen galactic civilization can have reached the earth only if its lifetime exceeds 2.6 million years, or 20 million years if discretization can be neglected. For zero population growth, the corresponding lifetime is 13 billion years. It is concluded that the earth is uncolonized not because interstellar spacefaring civilizations are rare, but because there are too many worlds to be colonized in the plausible colonization lifetime of nearby civilizations, and that there exist no very old galactic civilizations with a consistent policy of the conquest of inhabited worlds.
Delay differential systems for tick population dynamics.
Fan, Guihong; Thieme, Horst R; Zhu, Huaiping
2015-11-01
Ticks play a critical role as vectors in the transmission and spread of Lyme disease, an emerging infectious disease which can cause severe illness in humans or animals. To understand the transmission dynamics of Lyme disease and other tick-borne diseases, it is necessary to investigate the population dynamics of ticks. Here, we formulate a system of delay differential equations which models the stage structure of the tick population. Temperature can alter the length of time delays in each developmental stage, and so the time delays can vary geographically (and seasonally which we do not consider). We define the basic reproduction number [Formula: see text] of stage structured tick populations. The tick population is uniformly persistent if [Formula: see text] and dies out if [Formula: see text]. We present sufficient conditions under which the unique positive equilibrium point is globally asymptotically stable. In general, the positive equilibrium can be unstable and the system show oscillatory behavior. These oscillations are primarily due to negative feedback within the tick system, but can be enhanced by the time delays of the different developmental stages. PMID:25348048
Linking Dynamical and Population Genetic Models of Persistent Viral Infection
Kelly, John K.; Williamson, Scott; Orive, Maria E.; Smith, Marilyn S.; Holt, Robert D.
2003-07-01
This article develops a theoretical framework to link dynamical and population genetic models of persistent viral infection. This linkage is useful because, while the dynamical and population genetic theories have developed ...
Global quantitative predictions of complex laser dynamics
NASA Astrophysics Data System (ADS)
Wieczorek, Sebastian; Simpson, Thomas B.; Krauskopf, Bernd; Lenstra, Daan
2002-04-01
We demonstrate unprecedented agreement between a theoretical two-dimensional bifurcation diagram and the corresponding experimental stability map of an optically injected semiconductor laser over a large range of relevant injection parameter values. The bifurcation diagram encompasses both local and global bifurcations mapping out regions of regular, chaotic, and multistable behavior in considerable detail. This demonstrates the power of dynamical systems modeling for the quantitative prediction of nonlinear dynamics and chaos of semiconductor lasers.
Global quantitative predictions of complex laser dynamics.
Wieczorek, Sebastian; Simpson, Thomas B; Krauskopf, Bernd; Lenstra, Daan
2002-04-01
We demonstrate unprecedented agreement between a theoretical two-dimensional bifurcation diagram and the corresponding experimental stability map of an optically injected semiconductor laser over a large range of relevant injection parameter values. The bifurcation diagram encompasses both local and global bifurcations mapping out regions of regular, chaotic, and multistable behavior in considerable detail. This demonstrates the power of dynamical systems modeling for the quantitative prediction of nonlinear dynamics and chaos of semiconductor lasers. PMID:12005911
Population dynamics a source of diversity Zdenek Pospisil
Pospí?il, Zdenek
Population dynamics a source of diversity Zdenek Posp´isil Masaryk University, Faculty of science;Introduction General theory of population dynamics Models with discrete time Models with continuous time Population dynamics 2 / 18 #12;Introduction Introduction A bit of history Sources, textbooks Software
Ecological Modelling 170 (2003) 129140 Learning population dynamics models
Dzeroski, Saso
2003-01-01
Ecological Modelling 170 (2003) 129140 Learning population dynamics models from data and domain about processes in population dynamics domains, and a method to transform such knowledge-driven modeling; Knowledge-based modeling; Machine learning; Population dynamics; Process-based modeling
Using Domain Knowledge on Population Dynamics Modeling for Equation Discovery
Dzeroski, Saso
Using Domain Knowledge on Population Dynamics Modeling for Equation Discovery Ljupco Todorovski. In this paper, we propose a for- malism for integration of the population dynamics modeling knowledge the process of automated modeling of population dynamics. The equation discovery system Lagramge [7] has made
Dynamic Populations in Genetic Algorithms Zhanshan (Sam) Ma
Krings, Axel W.
Dynamic Populations in Genetic Algorithms Zhanshan (Sam) Ma University of Idaho Computer Science. Moscow, ID 83843, USA krings@cs.uidaho.edu ABSTRACT Biological populations are dynamic in both space in nature. In this paper, we explore the effects of dynamic (fluctuating) populations on the performance
Linking habitat selection, emigration and population dynamics of freshwater fishes
McMahon, Thomas E.
behaviour, population dynamics, meta- populations T. E. McMahon, Department of Ecology, Fish and WildlifeLinking habitat selection, emigration and population dynamics of freshwater fishes: a synthesis of ideas and approaches Life, and the freedom to move, are one. (Haida proverb) Introduction Population
Reliability of ENSO Dynamical Predictions YOUMIN TANG AND RICHARD KLEEMAN
Tang, Youmin
Reliability of ENSO Dynamical Predictions YOUMIN TANG AND RICHARD KLEEMAN Courant Institute, the authors have explored several important issues relating to ENSO predictability including reliability measures of ENSO dynamical predictions and the dominant precursors that control reliability. It was found
Role of noise in population dynamics cycles
NASA Astrophysics Data System (ADS)
Tomé, Tânia; de Oliveira, Mário J.
2009-06-01
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.
THEORETICAL POPULATION BIOLDGY 28, 359-381 (1985) Population Dynamics of Gene Transfer
Rose, Michael R.
1985-01-01
THEORETICAL POPULATION BIOLDGY 28, 359-381 (1985) Population Dynamics of Gene Transfer to obligatory genetic exchange, and thus the origin of sex, requires either population dynamics which of genetic change in bacterial populations, one taking on a variety of specific forms. A model capturing some
Dynamically hot galaxies. II - Global stellar populations
NASA Technical Reports Server (NTRS)
Bender, Ralf; Burstein, David; Faber, S. M.
1993-01-01
The global relationship between the stellar populations and the structural properties of dynamically hot galaxies (DHGs) is investigated using the same sample as was analyzed by Bender et al. (1992), which includes giant ellipticals, low-luminosity ellipticals, compact ellipticals, diffuse dwarf ellipticals, dwarf spheroidals, and bulges. It was found that all DHGs follow a single relationship between global stellar population (represented by Mg2 index or B-V color) and central velocity dispersion sigma(0), and that the Mg2-sigma(0) relation is significantly tighter than the relation between the Mg2 index and absolute luminosity. The relation between central Mg2 index and bulk B-V color was also found to be tight.
Evolutionary dynamics in finite populations with zealots.
Nakajima, Yohei; Masuda, Naoki
2015-02-01
We investigate evolutionary dynamics of two-strategy matrix games with zealots in finite populations. Zealots are assumed to take either strategy regardless of the fitness. When the strategy selected by the zealots is the same, the fixation of the strategy selected by the zealots is a trivial outcome. We study fixation time in this scenario. We show that the fixation time is divided into three main regimes, in one of which the fixation time is short, and in the other two the fixation time is exponentially long in terms of the population size. Different from the case without zealots, there is a threshold selection intensity below which the fixation is fast for an arbitrary payoff matrix. We illustrate our results with examples of various social dilemma games. PMID:24610380
Assessing the dynamics of wild populations
Eberhardt, L.L.
1985-01-01
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.
Assessing tiger population dynamics using photographic capture-recapture sampling
Karanth, K.U.; Nichols, J.D.; Kumar, N.S.; Hines, J.E.
2006-01-01
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.
Assessing tiger population dynamics using photographic capture-recapture sampling.
Karanth, K Ullas; Nichols, James D; Kumar, N Samba; Hines, James E
2006-11-01
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 gamma" = gamma' = 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 tau = 0.18 +/- 0.11. During the period when the sampled area was of constant size, the estimated population size N(t) varied from 17 +/- 1.7 to 31 +/- 2.1 tigers, with a geometric mean rate of annual population change estimated as lambda = 1.03 +/- 0.020, representing a 3% annual increase. The estimated recruitment of new animals, B(t), 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. PMID:17168036
Price dynamics in political prediction markets
Majumder, Saikat Ray; Diermeier, Daniel; Rietz, Thomas A.; Amaral, Luís A. Nunes
2009-01-01
Prediction markets, in which contract prices are used to forecast future events, are increasingly applied to various domains ranging from political contests to scientific breakthroughs. However, the dynamics of such markets are not well understood. Here, we study the return dynamics of the oldest, most data-rich prediction markets, the Iowa Electronic Presidential Election “winner-takes-all” markets. As with other financial markets, we find uncorrelated returns, power-law decaying volatility correlations, and, usually, power-law decaying distributions of returns. However, unlike other financial markets, we find conditional diverging volatilities as the contract settlement date approaches. We propose a dynamic binary option model that captures all features of the empirical data and can potentially provide a tool with which one may extract true information events from a price time series. PMID:19155442
Predicting Agent Strategy Mix of Evolving Populations Sabyasachi Saha
Sen, Sandip
Predicting Agent Strategy Mix of Evolving Populations Sabyasachi Saha Department of Math & Computer rather re- ceive help than give it. Evolutionary tournaments with competing help-giving strategies can model scenarios where agents periodi- cally adopt strategies that are outperforming others in the popula
Circuit theory predicts gene flow in plant and animal populations
Beier, Paul
Circuit theory predicts gene flow in plant and animal populations Brad H. McRae* and Paul Beier like dispersal and gene flow is essential for conserving endangered species in fragmented landscapes an ecological connectivity model that overcomes this obstacle by borrowing from electrical circuit theory
Synconset Waves and Chains: Spiking Onsets in Synchronous Populations Predict and Are Predicted by
Narayanan, Rishikesh
Synconset Waves and Chains: Spiking Onsets in Synchronous Populations Predict and Are Predicted Synfire waves are propagating spike packets in synfire chains, which are feedforward chains embedded in random networks. Although synfire waves have proved to be effective quantification for network activity
Monitoring microbial population dynamics at low densities
NASA Astrophysics Data System (ADS)
Julou, Thomas; Desprat, Nicolas; Bensimon, David; Croquette, Vincent
2012-07-01
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.
Building the bridge between animal movement and population dynamics
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
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. PMID:20566505
Hidden hysteresis – population dynamics can obscure gene network dynamics
2013-01-01
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. PMID:23800122
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 prediction. The model acco...
Technology Transfer Automated Retrieval System (TEKTRAN)
Climate change could alter the population growth of dominant species, leading to profound effects on community structure and ecosystem dynamics. Understanding the links between historical variation in climate and population vital rates (survival, growth, recruitment) is one way to predict the impact...
Saara J. DeWalt
2006-01-01
Introduction of biological control agents to reduce the abundance of exotic invasive plant species is often considered necessary but risky. I used matrix projection models to investigate the current population dynamics of Clidemia hirta (Melastomataceae), an invasive shrub, in two rainforest stands on the island of Hawaii and to predict the efficacy of hypothetical biological control agents in reducing population
Application of optimal prediction to molecular dynamics
Barber IV, John Letherman
2004-12-01
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.
847Parkyn et al.--Crayfish growth and population dynamics Growth and population dynamics of crayfish
Waikato, University of
in density and biomass in pasture streams, but com- munity composition has changed to favour pollution of crayfish Paranephrops planifrons in streams within native forest and pastoral land uses STEPHANIE M. PARKYN Zealand Abstract Population dynamics of crayfish (Paranephrops planifrons White) in streams draining
Mechanical reaction-diffusion model for bacterial population dynamics
Ngamsaad, Waipot
2015-01-01
The effect of mechanical interaction between cells on the spreading of bacterial population was investigated in one-dimensional space. A nonlinear reaction-diffusion equation has been formulated as a model for this dynamics. In this model, the bacterial cells are treated as the rod-like particles that interact, when contacting each other, through the hard-core repulsion. The repulsion introduces the exclusion process that causes the fast diffusion in bacterial population at high density. The propagation of the bacterial density as the traveling wave front in long time behavior has been analyzed. The analytical result reveals that the front speed is enhanced by the exclusion process---and its value depends on the packing fraction of cell. The numerical solutions of the model have been solved to confirm this prediction.
Dynamic analysis of a parasite population model
NASA Astrophysics Data System (ADS)
Sibona, G. J.; Condat, C. A.
2002-03-01
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.
Aggregation of Variables and Applications to Population Dynamics
Bravo de la Parra, Rafael
presents several applications in population and community dynamics. 5.1 Introduction Ecology aims appeared. Nowadays, lots of ecolog- ical models consider more and more details. Lots of populations5 Aggregation of Variables and Applications to Population Dynamics P. Auger1,5 , R. Bravo de la
Pair Approximations of Takeover Dynamics in Regular Population Structures
Eppstein, Margaret J.
Pair Approximations of Takeover Dynamics in Regular Population Structures Joshua L. Payne Joshua spreads throughout the population (a.k.a. takeover time analysis). While models of takeover dynamics have of spread of infectious disease throughout a population. Similarly, in evolutionary systems, the topology
Long-term dynamics of Typha populations
Grace, J.B.; Wetzel, R.G.
1998-01-01
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.
Predicting dynamic topography from mantle circulation models
NASA Astrophysics Data System (ADS)
Webb, Peter; Davies, J. Huw
2013-04-01
Dynamic topography is anomalous vertical motions of Earth's surface associated with viscous flow in the mantle. Deformable boundaries, such as the surface, CMB and phase transition boundaries, within a fluid (Earth's mantle) are deflected by viscous flow. Denser than average, sinking mantle creates inward deflections of Earth's surface. Equally, upwelling flow creates bulges in the surface; large plumes are commonly thought to produce superswells, such as the anomalously high elevation of Southern Africa. Dynamic topography appears to operate on a number of length scales. Mantle density anomalies estimated from seismic tomography indicate long wavelength dynamic topography at present day of around 2 km amplitude (e.g. Conrand & Husson, 2009) whilst continental scale studies suggest vertical motions of a few hundred metres. Furthermore, time scales must be an important factor to consider when assessing dynamic topography. Stable, dense lower mantle 'piles' may contribute to dynamic surface topography; as they appear stable over reasonably long time scales, long wavelength dynamic topography may be a fairly constant feature over the recent geological past. Shorter wavelength, smaller amplitude dynamic topography may be due to more transient features of mantle convection. Studies on a continental scale reveal shorter term changes in dynamic topography of the order of a few hundred metres (e.g. Roberts & White, 2010; Heine et al., 2010). Understanding dynamic topography is complicated by the fact it is difficult to observe as the signal is often masked by isostatic effects. We use forward mantle convection models with 300 million years of recent plate motion history as the surface boundary condition to generate a present day distribution of density anomalies associated with subducted lithosphere. From the modelled temperature and density fields we calculate the normal stress at or near the surface of the model. As the models generally have a free slip surface where no vertical motion is allowed, an excess or deficit of stress exists near the surface. A pointwise force balance between this stress excess and the weight of rock above is used to calculate the anomalous elevation associated with the stress. Here we present some of the results obtained from mantle circulation models. We look at different ways of predicting dynamic topography, including the depth at which the stress field is calculated and by removing lithospheric density anomalies from the calculation. We also assess the impact of crustal thickness and isostasy on the predictions of dynamic topography.
SPECTRAL PROPERTIES AND POPULATION DYNAMICS OF THE HARMFUL DINOFLAGELLATE
Gilbes, Fernando
SPECTRAL PROPERTIES AND POPULATION DYNAMICS OF THE HARMFUL DINOFLAGELLATE Cochlodinium, no previous efforts have been conducted to understand the population dynamics of this organism within this bay. This pioneer study assessed the role of climatological and physical-chemical parameters on the bloom dynamics
POPULATION ECOLOGY Population Dynamics of the Colorado Potato Beetle in an
POPULATION ECOLOGY Population Dynamics of the Colorado Potato Beetle in an Agroecosystem with Tomatoes and Potatoes with Management Implications to Processing Tomatoes CHRIS L. HARDING,1 S. J Environ. Entomol. 31(6): 1110Đ1118 (2002) ABSTRACT We evaluated the population dynamics of Colorado potato
Developing and evaluating prediction models in rehabilitation populations.
Seel, Ronald T; Steyerberg, Ewout W; Malec, James F; Sherer, Mark; Macciocchi, Stephen N
2012-08-01
This article presents a 3-part framework for developing and evaluating prediction models in rehabilitation populations. First, a process for developing and refining prognostic research questions and the scientific approach to prediction models is presented. Primary components of the scientific approach include the study design and sampling of patients, outcome measurement, selecting predictor variable(s), minimizing methodologic sources of bias, assuring a sufficient sample size for statistical power, and selecting an appropriate statistical model. Examples focus on prediction modeling using samples of rehabilitation patients. Second, a brief overview for statistically building and validating multivariable prediction models is provided, which includes the following 7 steps: data inspection, coding of predictors, model specification, model estimation, model performance, model validation, and model presentation. Third, we propose a set of primary considerations for evaluating prediction model studies using specific quality indicators as criteria to help stakeholders evaluate the quality of a prediction model study. Lastly, we offer perspectives on the future development and use of rehabilitation prediction models. PMID:22840880
Prediction Model for Gastric Cancer Incidence in Korean Population
Kim, Sohee; Shin, Aesun; Yang, Hye-Ryung; Park, Junghyun; Choi, Il Ju; Kim, Young-Woo; Kim, Jeongseon; Nam, Byung-Ho
2015-01-01
Background Predicting high risk groups for gastric cancer and motivating these groups to receive regular checkups is required for the early detection of gastric cancer. The aim of this study is was to develop a prediction model for gastric cancer incidence based on a large population-based cohort in Korea. Method Based on the National Health Insurance Corporation data, we analyzed 10 major risk factors for gastric cancer. The Cox proportional hazards model was used to develop gender specific prediction models for gastric cancer development, and the performance of the developed model in terms of discrimination and calibration was also validated using an independent cohort. Discrimination ability was evaluated using Harrell’s C-statistics, and the calibration was evaluated using a calibration plot and slope. Results During a median of 11.4 years of follow-up, 19,465 (1.4%) and 5,579 (0.7%) newly developed gastric cancer cases were observed among 1,372,424 men and 804,077 women, respectively. The prediction models included age, BMI, family history, meal regularity, salt preference, alcohol consumption, smoking and physical activity for men, and age, BMI, family history, salt preference, alcohol consumption, and smoking for women. This prediction model showed good accuracy and predictability in both the developing and validation cohorts (C-statistics: 0.764 for men, 0.706 for women). Conclusions In this study, a prediction model for gastric cancer incidence was developed that displayed a good performance. PMID:26186332
Prediction and Control in a Dynamic Environment
Osman, Magda; Speekenbrink, Maarten
2011-01-01
The present study compared the accuracy of cue-outcome knowledge gained during prediction-based and control-based learning in stable and unstable dynamic environments. Participants either learnt to make cue-interventions in order to control an outcome, or learnt to predict the outcome from observing changes to the cue values. Study 1 (N?=?60) revealed that in tests of control, after a short period of familiarization, performance of Predictors was equivalent to Controllers. Study 2 (N?=?28) showed that Controllers showed equivalent task knowledge when to compared to Predictors. Though both Controllers and Predictors showed good performance at test, overall Controllers showed an advantage. The cue-outcome knowledge acquired during learning was sufficiently flexible to enable successful transfer to tests of control and prediction. PMID:22419913
Predicting the dynamics of protein abundance.
Mehdi, Ahmed M; Patrick, Ralph; Bailey, Timothy L; Bodén, Mikael
2014-05-01
Protein synthesis is finely regulated across all organisms, from bacteria to humans, and its integrity underpins many important processes. Emerging evidence suggests that the dynamic range of protein abundance is greater than that observed at the transcript level. Technological breakthroughs now mean that sequencing-based measurement of mRNA levels is routine, but protocols for measuring protein abundance remain both complex and expensive. This paper introduces a Bayesian network that integrates transcriptomic and proteomic data to predict protein abundance and to model the effects of its determinants. We aim to use this model to follow a molecular response over time, from condition-specific data, in order to understand adaptation during processes such as the cell cycle. With microarray data now available for many conditions, the general utility of a protein abundance predictor is broad. Whereas most quantitative proteomics studies have focused on higher organisms, we developed a predictive model of protein abundance for both Saccharomyces cerevisiae and Schizosaccharomyces pombe to explore the latitude at the protein level. Our predictor primarily relies on mRNA level, mRNA-protein interaction, mRNA folding energy and half-life, and tRNA adaptation. The combination of key features, allowing for the low certainty and uneven coverage of experimental observations, gives comparatively minor but robust prediction accuracy. The model substantially improved the analysis of protein regulation during the cell cycle: predicted protein abundance identified twice as many cell-cycle-associated proteins as experimental mRNA levels. Predicted protein abundance was more dynamic than observed mRNA expression, agreeing with experimental protein abundance from a human cell line. We illustrate how the same model can be used to predict the folding energy of mRNA when protein abundance is available, lending credence to the emerging view that mRNA folding affects translation efficiency. The software and data used in this research are available at http://bioinf.scmb.uq.edu.au/proteinabundance/. PMID:24532840
Predictability of population displacement after the 2010 Haiti earthquake
Lu, Xin; Bengtsson, Linus; Holme, Petter
2012-01-01
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
Population Dynamics: Rate of Change in Population Size Track Population Size over Time
Caraco, Thomas
.5) N2.5 = 180 e - 2 N2.5 = 24.36 24 #12;3 Exponential Growth Population dynamics Density as constant Density-independent and time-independent Discrete-time parallel to exponential growth ttt NNN;2 180 x = 1080 x = 1080/180 = 6 recaptures (n = 42) Exponential-Growth Problem Let r = 0.8 and N5 = 180
Prediction of predator-prey populations modelled by perturbed ODEs.
Froda, Sorana; Nkurunziza, Sévérien
2007-03-01
In this paper we explore a stochastic model in continuous time for predator-prey interactions, which accounts for the periodical behaviour observed in many animal populations. More precisely, we consider a solution to the classical Lotka-Volterra system of equations, but we view the actual population sizes as random perturbations of the solutions to this ODE system. Namely, we assume that the perturbations follow correlated Ornstein-Uhlenbeck processes; this approach generalizes the one of Froda and Colavita [Aust N Z J Stat 2:235-254, 2005] who considered only i.i.d. errors. This type of perturbed deterministic model allows to perform parameter estimation and to predict population sizes at future times. On the other hand, the present model refines the previous one since it takes into account the variability due to external factors and the time dependence in the random component. Moreover, this more flexible model improves the predictions of population sizes at future times. In order to illustrate this last point, we analyse two data sets. PMID:17151886
Anatomy of a chaotic attractor: subtle model-predicted patterns revealed in population data.
King, Aaron A; Costantino, R F; Cushing, J M; Henson, Shandelle M; Desharnais, Robert A; Dennis, Brian
2004-01-01
Mathematically, chaotic dynamics are not devoid of order but display episodes of near-cyclic temporal patterns. This is illustrated, in interesting ways, in the case of chaotic biological populations. Despite the individual nature of organisms and the noisy nature of biological time series, subtle temporal patterns have been detected. By using data drawn from chaotic insect populations, we show quantitatively that chaos manifests itself as a tapestry of identifiable and predictable patterns woven together by stochasticity. We show too that the mixture of patterns an experimentalist can expect to see depends on the scale of the system under study. PMID:14681555
Dynamics of neural populations: stability and synchrony.
Sirovich, Lawrence; Omurtag, Ahmet; Lubliner, Kip
2006-03-01
A population formulation of neuronal activity is employed to study an excitatory network of (spiking) neurons receiving external input as well as recurrent feedback. At relatively low levels of feedback, the network exhibits time stationary asynchronous behavior. A stability analysis of this time stationary state leads to an analytical criterion for the critical gain at which time asynchronous behavior becomes unstable. At instability the dynamics can undergo a supercritical Hopf bifurcation and the population passes to a synchronous state. Under different conditions it can pass to synchrony through a subcritical Hopf bifurcation. And at high gain a network can reach a runaway state, in finite time, after which the network no longer supports bounded solutions. The introduction of time delayed feedback leads to a rich range of phenomena. For example, for a given external input, increasing gain produces transition from asynchrony, to synchrony, to asynchrony and finally can lead to divergence. Time delay is also shown to strongly mollify the amplitude of synchronous oscillations. Perhaps, of general importance, is the result that synchronous behavior can exist only for a narrow range of time delays, which range is an order of magnitude smaller than periods of oscillation. PMID:16613792
Population of dynamically formed triples in dense stellar systems
Natalia Ivanova
2005-09-18
In dense stellar systems, frequent dynamical interactions between binaries lead to the formation of multiple systems. In this contribution we discuss the dynamical formation of hierarchically stable triples: the formation rate, main characteristics of dynamically formed population of triples and the impact of the triples formation on the population of close binaries. In particular, we estimate how much the population of blue stragglers and compact binaries could be affected.
Dynamics of a black bear population within a desert metapopulation
Eric C. Hellgren; David P. Onorato; J. Raymond Skiles
2005-01-01
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,
Population dynamics at digester overload conditions.
Schoen, Michael A; Sperl, Daniel; Gadermaier, Maria; Goberna, Marta; Franke-Whittle, Ingrid; Insam, Heribert; Ablinger, Josef; Wett, Bernhard
2009-12-01
Two different case studies concerning potential overload situations of anaerobic digesters were investigated and mathematically modelled by means of the Anaerobic Digestion Model No. 1 (ADM1). The first scenario included a digester failure at a municipal WWTP which occurred during revision works of the upstream digester within a two-step digestion system when the sludge was directly by-passed to the 2nd-step reactor. Secondly, the non-occurrence of a highly expected upset situation in a lab-scale digester fed with cattle manure was investigated. ADM1 was utilized to derive indicators which were used to investigate the relationship between digester stability and biomass population dynamics. Conventional design parameters such as the organic loading rate appeared unsuitable for process description under dynamic conditions. Indicators reflecting the biokinetic state (e.g. F(net)/M(net) or the VFA/alkalinity ratio) are more adequate for the assessment of the stability of reactors in transient situations. PMID:19586768
Topological Criteria of Global Attraction with Applications in Population Dynamics
Arias, Cristina M.
Topological Criteria of Global Attraction with Applications in Population Dynamics Alfonso Ruiz-Herrera Ciencia, Spain 1 #12;2 A. Ruiz-Herrera for planar discrete-time dynamical systems. In this framework, we
Extreme Events: Dynamics, Statistics and Prediction
NASA Astrophysics Data System (ADS)
Ghil, M.
2013-05-01
In this talk, I will review some recent work on extreme events, their causes and consequences. The review covers theoretical aspects of time series analysis and of extreme value theory, as well as of the deterministic modeling of extreme events, via continuous and discrete dynamic models. The applications include climatic, seismic and socio-economic events, along with their prediction. Two important results refer to (i) the complementarity of spectral analysis of a time series in terms of the continuous and the discrete part of its power spectrum; and (ii) the need for coupled modeling of natural and socio-economic systems. Both these results have implications for the study and prediction of natural hazards and their human impacts. US GDP data used in validating the vulnerability paradox found in a Non-Equilibrium Dynamical Model (NEDyM) for studying the impact of extreme events on a dynamic economy. The paradoxical result is that natural hazards affect more strongly an economy in expansion than when it is in a recession. The connection to the macroeconomic data is given by fluctuation-dissipation theory.
Effects of an invasive plant on population dynamics in toads.
Greenberg, Daniel A; Green, David M
2013-10-01
When populations decline in response to unfavorable environmental change, the dynamics of their population growth shift. In populations that normally exhibit high levels of variation in recruitment and abundance, as do many amphibians, declines may be difficult to identify from natural fluctuations in abundance. However, the onset of declines may be evident from changes in population growth rate in sufficiently long time series of population data. With data from 23 years of study of a population of Fowler's toad (Anaxyrus [ = Bufo] fowleri) at Long Point, Ontario (1989-2011), we sought to identify such a shift in dynamics. We tested for trends in abundance to detect a change point in population dynamics and then tested among competing population models to identify associated intrinsic and extrinsic factors. The most informative models of population growth included terms for toad abundance and the extent of an invasive marsh plant, the common reed (Phragmites australis), throughout the toads' marshland breeding areas. Our results showed density-dependent growth in the toad population from 1989 through 2002. After 2002, however, we found progressive population decline in the toads associated with the spread of common reeds and consequent loss of toad breeding habitat. This resulted in reduced recruitment and population growth despite the lack of significant loss of adult habitat. Our results underscore the value of using long-term time series to identify shifts in population dynamics coincident with the advent of population decline. PMID:23692126
Predicting Protein Interactions by Brownian Dynamics Simulations
Meng, Xuan-Yu; Xu, Yu; Zhang, Hong-Xing; Mezei, Mihaly; Cui, Meng
2012-01-01
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. PMID:22500075
cologists studying population dynam-ics prefer not to bother with the possi-
White, Douglas R.
E cologists studying population dynam- ics prefer not to bother with the possi- bility Jr and theoretician Stephen Ellner -- teamed up to study the population dynamics of rotifers (Fig. 1). Clearly, there is some sort of dynamical connection between the two populations in allcases
Dynamics of population rate codes in ensembles of neocortical neurons
Tsodyks, Misha
Dynamics of population rate codes in ensembles of neocortical neurons Silberberg, G.1 , Bethge, M.2- dicating that neuronal ensembles faithfully transmit rapidly changing signals to each other. Apart from signal-to-noise issues, population codes are funda- mentally constrained by the neuronal dynamics
Dynamics of two phytoplankton populations under predation.
Kengwoung-Keumo, Jean-Jacques
2014-12-01
The aim of this paper is to investigate the manner in which predation and single-nutrient competition affect the dynamics of a non-toxic and a toxic phytoplankton species in a homogeneous environment (such as a chemostat). We allow for the possibility that both species serve as prey for an herbivorous zooplankton species. We assume that the toxic phytoplankton species produces toxins that affect only its own growth (autotoxicity). The autotoxicity assumption is ecologically explained by the fact that the toxin-producing phytoplankton is not mature enough to produce toxins that will affect the growth of its nontoxic competitor. We show that, in the absence of phytotoxic interactions and nutrient recycling, our model exhibits uniform persistence. The removal rates are distinct and we use general response functions. Finally, numerical simulations are carried out to show consistency with theoretical analysis. Our model has similarities with other food-chain models. As such, our results may be relevant to a wider spectrum of population models, not just those focused on plankton. Some open problems are discussed at the end of this paper. PMID:25365603
Microbial population dynamics by digital in-line holographic microscopy
Frentz, Zak; Kuehn, Seppe; Hekstra, Doeke; Leibler, Stanislas
2010-01-01
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. PMID:20815617
Evolutionary dynamics with fluctuating population sizes and strong mutualism
NASA Astrophysics Data System (ADS)
Chotibut, Thiparat; Nelson, David R.
2015-08-01
Game theory ideas provide a useful framework for studying evolutionary dynamics in a well-mixed environment. This approach, however, typically enforces a strictly fixed overall population size, deemphasizing natural growth processes. We study a competitive Lotka-Volterra model, with number fluctuations, that accounts for natural population growth and encompasses interaction scenarios typical of evolutionary games. We show that, in an appropriate limit, the model describes standard evolutionary games with both genetic drift and overall population size fluctuations. However, there are also regimes where a varying population size can strongly influence the evolutionary dynamics. We focus on the strong mutualism scenario and demonstrate that standard evolutionary game theory fails to describe our simulation results. We then analytically and numerically determine fixation probabilities as well as mean fixation times using matched asymptotic expansions, taking into account the population size degree of freedom. These results elucidate the interplay between population dynamics and evolutionary dynamics in well-mixed systems.
Local Population Dynamics in Metapopulation Models: Implications for Conservation
Jorge E. Lopez; Catherine A. Pfister
2001-01-01
Habitat fragmentation and the division of populations into spatially separated units have led to the increasing use of metapopulation models to characterize these populations. One prominent model that has served as a heuristic tool was introduced by Levins and is based on a collection of simplifying assump- tions that exclude information on the dynamics and spatial distribution of local populations.
Leisure Today: Population Dynamics--The Changing Face of America.
ERIC Educational Resources Information Center
Dunn, Diana R., Ed.; And Others
1981-01-01
A collection of articles examines the changing character of the American population and the importance of planning new recreation and leisure services to meet changing population needs. Included are discussions on demography and population dynamics; the effects of immigration; changing work and life styles; and changes in family structure and…
Ahumada, Jorge A; Lapointe, Dennis; Samuel, Michael D
2004-11-01
We present a population model to understand the effects of temperature and rainfall on the population dynamics of the southern house mosquito, Culex quinquefasciatus Say, along an elevational gradient in Hawaii. We use a novel approach to model the effects of temperature on population growth by dynamically incorporating developmental rate into the transition matrix, by using physiological ages of immatures instead of chronological age or stages. We also model the effects of rainfall on survival of immatures as the cumulative number of days below a certain rain threshold. Finally, we incorporate density dependence into the model as competition between immatures within breeding sites. Our model predicts the upper altitudinal distributions of Cx. quinquefasciatus on the Big Island of Hawaii for self-sustaining mosquito and migrating summer sink populations at 1,475 and 1,715 m above sea level, respectively. Our model predicts that mosquitoes at lower elevations can grow under a broader range of rainfall parameters than middle and high elevation populations. Density dependence in conjunction with the seasonal forcing imposed by temperature and rain creates cycles in the dynamics of the population that peak in the summer and early fall. The model provides a reasonable fit to the available data on mosquito abundance for the east side of Mauna Loa, Hawaii. The predictions of our model indicate the importance of abiotic conditions on mosquito dynamics and have important implications for the management of diseases transmitted by Cx. quinquefasciatus in Hawaii and elsewhere. PMID:15605655
Hart, Edmund M; Avilés, Leticia
2014-01-01
Reconstructing the dynamics of populations is complicated by the different types of stochasticity experienced by populations, in particular if some forms of stochasticity introduce bias in parameter estimation in addition to error. Identification of systematic biases is critical when determining whether the intrinsic dynamics of populations are stable or unstable and whether or not populations exhibit an Allee effect, i.e., a minimum size below which deterministic extinction should follow. Using a simulation model that allows for Allee effects and a range of intrinsic dynamics, we investigated how three types of stochasticity--demographic, environmental, and random catastrophes--affect our ability to reconstruct the intrinsic dynamics of populations. Demographic stochasticity aside, which is only problematic in small populations, we find that environmental stochasticity--positive and negative environmental fluctuations--caused increased error in parameter estimation, but bias was rarely problematic, except at the highest levels of noise. Random catastrophes, events causing large-scale mortality and likely to be more common than usually recognized, caused immediate bias in parameter estimates, in particular when Allee effects were large. In the latter case, population stability was predicted when endogenous dynamics were actually unstable and the minimum viable population size was overestimated in populations with small or non-existent Allee effects. Catastrophes also generally increased extinction risk, in particular when endogenous Allee effects were large. We propose a method for identifying data points likely resulting from catastrophic events when such events have not been recorded. Using social spider colonies (Anelosimus spp.) as models for populations, we show that after known or suspected catastrophes are accounted for, reconstructed growth parameters are consistent with intrinsic dynamical instability and substantial Allee effects. Our results are applicable to metapopulation or time series data and are relevant for predicting extinction in conservation applications or the management of invasive species. PMID:25360620
Hart, Edmund M.; Avilés, Leticia
2014-01-01
Reconstructing the dynamics of populations is complicated by the different types of stochasticity experienced by populations, in particular if some forms of stochasticity introduce bias in parameter estimation in addition to error. Identification of systematic biases is critical when determining whether the intrinsic dynamics of populations are stable or unstable and whether or not populations exhibit an Allee effect, i.e., a minimum size below which deterministic extinction should follow. Using a simulation model that allows for Allee effects and a range of intrinsic dynamics, we investigated how three types of stochasticity—demographic, environmental, and random catastrophes— affect our ability to reconstruct the intrinsic dynamics of populations. Demographic stochasticity aside, which is only problematic in small populations, we find that environmental stochasticity—positive and negative environmental fluctuations—caused increased error in parameter estimation, but bias was rarely problematic, except at the highest levels of noise. Random catastrophes, events causing large-scale mortality and likely to be more common than usually recognized, caused immediate bias in parameter estimates, in particular when Allee effects were large. In the latter case, population stability was predicted when endogenous dynamics were actually unstable and the minimum viable population size was overestimated in populations with small or non-existent Allee effects. Catastrophes also generally increased extinction risk, in particular when endogenous Allee effects were large. We propose a method for identifying data points likely resulting from catastrophic events when such events have not been recorded. Using social spider colonies (Anelosimus spp.) as models for populations, we show that after known or suspected catastrophes are accounted for, reconstructed growth parameters are consistent with intrinsic dynamical instability and substantial Allee effects. Our results are applicable to metapopulation or time series data and are relevant for predicting extinction in conservation applications or the management of invasive species. PMID:25360620
Weakly Chaotic Population Dynamics in Random Ecological Networks
Shin-ichi Sasa; Tsuyoshi Chawanya
1994-08-12
Population dynamics in random ecological networks are investigated by analyzing a simple deterministic equation. It is found that a sequence of abrupt changes of populations punctuating quiescent states characterize the long time behavior. An asymptotic analysis is developed by introducing a log-scaled time, and it is shown that such a dynamical process behaves as non-steady weak chaos in which population disturbances grow algebraically in time. Also, some relevance of our study to taxonomic data of biological extinction is mentioned.
DEMOGRAPHIC PROCESSES: POPULATION DYNAMICS IN HETEROGENEOUS LANDSCAPES
Few topics have attracted the attention of ecologists more than fluctuations in the numbers of plants and animals through time and their variation in abundance through space. nderstanding population fluctuations, and thus population conservation, requires understanding the links ...
Tremblay, Raymond L; Raventos, Josep; Ackerman, James D
2015-09-01
Background and Aims Evaluation of population projection matrices (PPMs) that are focused on asymptotically based properties of populations is a commonly used approach to evaluate projected dynamics of managed populations. Recently, a set of tools for evaluating the properties of transient dynamics has been expanded to evaluate PPMs and to consider the dynamics of populations prior to attaining the stable-stage distribution, a state that may never be achieved in disturbed or otherwise ephemeral habitats or persistently small populations. This study re-evaluates data for a tropical orchid and examines the value of including such analyses in an integrative approach.Methods Six small populations of Lepanthes rubripetala were used as a model system and the R software package popdemo was used to produce estimates of the indices for the asymptotic growth rate (lambda), sensitivities, reactivity, first-time step attenuation, maximum amplification, maximum attenuation, maximal inertia and maximal attenuation. The response in lambda to perturbations of demographic parameters using transfer functions and multiple perturbations on growth, stasis and fecundity were also determined. The results were compared with previously published asymptotic indices.Key Results It was found that combining asymptotic and transient dynamics expands the understanding of possible population changes. Comparison of the predicted density from reactivity and first-time step attenuation with the observed change in population size in two orchid populations showed that the observed density was within the predicted range. However, transfer function analysis suggests that the traditional approach of measuring perturbation of growth rates and persistence (inertia) may be misleading and is likely to result in erroneous management decisions.Conclusions Based on the results, an integrative approach is recommended using traditional PPMs (asymptotic processes) with an evaluation of the diversity of dynamics that may arise when populations are not at a stable-stage distribution (transient processes). This method is preferable for designing rapid and efficient interventions after disturbances, and for developing strategies to establish new populations. PMID:25814059
Helms, Sandra E; Hunter, Mark D
2005-09-01
In the attempt to use results from small-scale studies to make large-scale predictions, it is critical that we take into account the greater spatial heterogeneity encountered at larger spatial scales. An important component of this heterogeneity is variation in plant quality, which can have a profound influence on herbivore population dynamics. This influence is particularly relevant when we consider that the strength of density dependence can vary among host plants and that the strength of density dependence determines the difference between exponential and density- dependent growth. Here, we present some simple models and analyses designed to examine the impact of variable plant quality on the dynamics of insect herbivore populations, and specifically the consequences of variation in the strength of density dependence among host plants. We show that average values of herbivore population growth parameters, calculated from plants that vary in quality, do not predict overall population growth. Furthermore, we illustrate that the quality of a few individual plants within a larger plant population can dominate herbivore population growth. Our results demonstrate that ignoring spatial heterogeneity that exists in herbivore population growth on plants that differ in quality can lead to a misunderstanding of the mechanisms that underlie population dynamics. PMID:15891845
Population dynamics of Yellowstone grizzly bears
Knight, R.R.; Eberhardt, L.L.
1985-04-01
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.
Modelling Food and Population Dynamics in Honey Bee Colonies
Khoury, David S.; Barron, Andrew B.; Myerscough, Mary R.
2013-01-01
Honey bees (Apis mellifera) are increasingly in demand as pollinators for various key agricultural food crops, but globally honey bee populations are in decline, and honey bee colony failure rates have increased. This scenario highlights a need to understand the conditions in which colonies flourish and in which colonies fail. To aid this investigation we present a compartment model of bee population dynamics to explore how food availability and bee death rates interact to determine colony growth and development. Our model uses simple differential equations to represent the transitions of eggs laid by the queen to brood, then hive bees and finally forager bees, and the process of social inhibition that regulates the rate at which hive bees begin to forage. We assume that food availability can influence both the number of brood successfully reared to adulthood and the rate at which bees transition from hive duties to foraging. The model predicts complex interactions between food availability and forager death rates in shaping colony fate. Low death rates and high food availability results in stable bee populations at equilibrium (with population size strongly determined by forager death rate) but consistently increasing food reserves. At higher death rates food stores in a colony settle at a finite equilibrium reflecting the balance of food collection and food use. When forager death rates exceed a critical threshold the colony fails but residual food remains. Our model presents a simple mathematical framework for exploring the interactions of food and forager mortality on colony fate, and provides the mathematical basis for more involved simulation models of hive performance. PMID:23667418
Modelling food and population dynamics in honey bee colonies.
Khoury, David S; Barron, Andrew B; Myerscough, Mary R
2013-01-01
Honey bees (Apis mellifera) are increasingly in demand as pollinators for various key agricultural food crops, but globally honey bee populations are in decline, and honey bee colony failure rates have increased. This scenario highlights a need to understand the conditions in which colonies flourish and in which colonies fail. To aid this investigation we present a compartment model of bee population dynamics to explore how food availability and bee death rates interact to determine colony growth and development. Our model uses simple differential equations to represent the transitions of eggs laid by the queen to brood, then hive bees and finally forager bees, and the process of social inhibition that regulates the rate at which hive bees begin to forage. We assume that food availability can influence both the number of brood successfully reared to adulthood and the rate at which bees transition from hive duties to foraging. The model predicts complex interactions between food availability and forager death rates in shaping colony fate. Low death rates and high food availability results in stable bee populations at equilibrium (with population size strongly determined by forager death rate) but consistently increasing food reserves. At higher death rates food stores in a colony settle at a finite equilibrium reflecting the balance of food collection and food use. When forager death rates exceed a critical threshold the colony fails but residual food remains. Our model presents a simple mathematical framework for exploring the interactions of food and forager mortality on colony fate, and provides the mathematical basis for more involved simulation models of hive performance. PMID:23667418
Population dynamics of the Concho water snake
Mueller, James Michael
1990-01-01
and standard errors for the 1989 age class of a Concho water snake population at Lake Moonen, Texas. 22 8 Jolly-Seber estimates and standard errors for the 1988 age class of a Concho water snake population on Turkey Bend of the Colorado River, Texas. 23 9... Model A' estimates and standard errors for the 1987 age class of a Concho water snake population on the Concho River at paint Rock, Texas. 23 10 Model A' estimates and standard errors for the 1988 age class of a Concha water snake population...
Dynamic situation assessment and prediction (DSAP)
NASA Astrophysics Data System (ADS)
Sisti, Alex F.
2003-09-01
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.
Population dynamics of the spruce bark beetle: A long-term study1 Lorenzo Marini1
factor. Although temperature-related metrics are known to have strong28 individual effect on I insect17 performance and host tree resistance. Although there are theoretical predictions and empirical18 density feedback, and abiotic factors in driving Ips typographus population dynamics. We22 analyzed
The role of population inertia in predicting the outcome of stage-structured biological invasions.
Guiver, Chris; Dreiwi, Hanan; Filannino, Donna-Maria; Hodgson, Dave; Lloyd, Stephanie; Townley, Stuart
2015-07-01
Deterministic dynamic models for coupled resident and invader populations are considered with the purpose of finding quantities that are effective at predicting when the invasive population will become established asymptotically. A key feature of the models considered is the stage-structure, meaning that the populations are described by vectors of discrete developmental stage- or age-classes. The vector structure permits exotic transient behaviour-phenomena not encountered in scalar models. Analysis using a linear Lyapunov function demonstrates that for the class of population models considered, a large so-called population inertia is indicative of successful invasion. Population inertia is an indicator of transient growth or decline. Furthermore, for the class of models considered, we find that the so-called invasion exponent, an existing index used in models for invasion, is not always a reliable comparative indicator of successful invasion. We highlight these findings through numerical examples and a biological interpretation of why this might be the case is discussed. PMID:25914143
Predicting NCLEX-RN success in a diverse student population.
Alameida, Marshall D; Prive, Alice; Davis, Harvey C; Landry, Lynette; Renwanz-Boyle, Andrea; Dunham, Michelle
2011-05-01
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
Araújo, Rita M.; Serrăo, Ester A.; Sousa-Pinto, Isabel; Ĺberg, Per
2014-01-01
Persistence of populations at range edges relies on local population dynamics and fitness, in the case of geographically isolated populations of species with low dispersal potential. Focusing on spatial variations in demography helps to predict the long-term capability for persistence of populations across the geographical range of species’ distribution. The demography of two ecological and phylogenetically close macroalgal species with different life history characteristics was investigated by using stochastic, stage-based matrix models. Populations of Ascophyllum nodosum and Fucus serratus were sampled for up to 4 years at central locations in France and at their southern range limits in Portugal. The stochastic population growth rate (?s) of A. nodosum was lower and more variable in central than in southern sites whilst for F. serratus this trend was reversed with ?s much lower and more variable in southern than in central populations. Individuals were larger in central than in southern populations for both species, which was reflected in the lower transition probabilities of individuals to larger size classes and higher probability of shrinkage in the southern populations. In both central and southern populations elasticity analysis (proportional sensitivity) of population growth rate showed that fertility elements had a small contribution to ?s that was more sensitive to changes in matrix transitions corresponding to survival. The highest elasticities were found for loop transitions in A. nodosum and for growth to larger size classes in F. serratus. Sensitivity analysis showed high selective pressure on individual growth for both species at both locations. The results of this study highlight the deterministic role of species-specific life-history traits in population demography across the geographical range of species. Additionally, this study demonstrates that individuals’ life-transitions differ in vulnerability to environmental variability and shows the importance of vegetative compared to reproductive stages for the long-term persistence of populations. PMID:24651480
Complex population dynamics and the coalescent under neutrality.
Volz, Erik M
2012-01-01
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
Gorsich, Erin E; Ezenwa, Vanessa O; Cross, Paul C; Bengis, Roy G; Jolles, Anna E
2015-07-01
Chronic infections may have negative impacts on wildlife populations, yet their effects are difficult to detect in the absence of long-term population monitoring. Brucella abortus, the bacteria responsible for bovine brucellosis, causes chronic infections and abortions in wild and domestic ungulates, but its impact on population dynamics is not well understood. We report infection patterns and fitness correlates of bovine brucellosis in African buffalo based on (1) 7 years of cross-sectional disease surveys and (2) a 4-year longitudinal study in Kruger National Park (KNP), South Africa. We then used a matrix population model to translate these observed patterns into predicted population-level effects. Annual brucellosis seroprevalence ranged from 8·7% (95% CI = 1·8-15·6) to 47·6% (95% CI = 35·1-60·1) increased with age until adulthood (>6) and varied by location within KNP. Animals were on average in worse condition after testing positive for brucellosis (F = -5·074, P < 0·0001), and infection was associated with a 2·0 (95% CI = 1·1-3·7) fold increase in mortality (?(2) = 2·039, P = 0·036). Buffalo in low body condition were associated with lower reproductive success (F = 2·683, P = 0·034), but there was no association between brucellosis and pregnancy or being observed with a calf. For the range of body condition scores observed in the population, the model-predicted growth rate was ? = 1·11 (95% CI = 1·02-1·21) in herds without brucellosis and ? = 1·00 (95% CI = 0·85-1·16) when brucellosis seroprevalence was 30%. Our results suggest that brucellosis infection can potentially result in reduced population growth rates, but because these effects varied with demographic and environmental conditions, they may remain unseen without intensive, longitudinal monitoring. PMID:25714466
Gerber, Brian D; Kendall, William L; Hooten, Mevin B; Dubovsky, James A; Drewien, Roderick C
2015-09-01
Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment. Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression. Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring-summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect. Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond. Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions. PMID:25808951
Modeling seasonal interactions in the population dynamics of migratory birds
Runge, M.C.; Marra, P.P.
2005-01-01
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.
Xiu, Peng
a statistical population dynamics model (MULTIFAN- CL) suggest that recruitment of three tuna species populations, a spatial environmental population dynamic model (SEPODYM) has been developed (Bertignac et al1 Modelling climate-related variability of tuna populations from a coupled ocean-biogeochemical-populations
Sexual abuse predicts functional somatic symptoms: An adolescent population study.
Bonvanie, Irma J; van Gils, Anne; Janssens, Karin A M; Rosmalen, Judith G M
2015-08-01
The main aim of this study was to investigate the effect of childhood sexual abuse on medically not well explained or functional somatic symptoms (FSSs) in adolescents. We hypothesized that sexual abuse predicts higher levels of FSSs and that anxiety and depression contribute to this relationship. In addition, we hypothesized that more severe abuse is associated with higher levels of FSSs and that sexual abuse is related to gastrointestinal FSSs in particular. This study was part of the Tracking Adolescents' Individual Lives Survey (TRAILS): a general population cohort which started in 2001 (N=2,230; 50.8% girls, mean age 11.1 years). The current study uses data of 1,680 participants over four assessment waves (75% of baseline, mean duration of follow-up: 8 years). FSSs were measured by the Somatic Complaints subscale of the Youth Self-Report at all waves. Sexual abuse before the age of sixteen was assessed retrospectively with a questionnaire at T4. To test the hypotheses linear mixed models were used adjusted for age, sex, socioeconomic status, anxiety and depression. Sexual abuse predicted higher levels of FSSs after adjustment for age sex and socioeconomic status (B=.06) and after additional adjustment for anxiety and depression (B=.03). While sexual abuse involving physical contact significantly predicted the level of FSSs (assault; B=.08, rape; B=.05), non-contact sexual abuse was not significantly associated with FSSs (B=.04). Sexual abuse was not a stronger predictor of gastrointestinal FSSs (B=.06) than of all FSSs. Further research is needed to clarify possible mechanisms underlying relationship between sexual abuse and FSSs. PMID:26142915
Dual Population-Based Incremental Learning for Problem Optimization in Dynamic Environments
Yang, Shengxiang
Dual Population-Based Incremental Learning for Problem Optimization in Dynamic Environments: dynamic optimization, population-based incremental learning, dualism, evolutionary algorithms 1 of Population-Based Incremental Learning (PBIL) algorithms, a class of EAs, for solving dynamic optimization
Hauert, Christoph
Coevolutionary Dynamics: From Finite to Infinite Populations Arne Traulsen,1,2,* Jens Christian dynamics assuming implicitly infinite population sizes. Only recently have stochastic processes been introduced to study evolutionary dynamics in finite populations. However, the relationship between
Ecological Modelling xxx (2005) xxxxxx Transient population dynamics: Relations to life
Rockwell, Robert F.
2005-01-01
Ecological Modelling xxx (2005) xxxxxx Transient population dynamics: Relations to life history, whereas the sub-adult survival sensitivity decreased. Transient population dynamics of long-lived, slow is reached. Meanwhile, the population dynamics are `transient' becau
Deterministic evolutionary game dynamics in finite populations Philipp M. Altrock* and Arne Traulsen
Traulsen, Arne
Deterministic evolutionary game dynamics in finite populations Philipp M. Altrock* and Arne dynamics describes the spreading of successful strategies in a population of reproducing individuals reproductive fitness and spread in the population. Traditionally, evolutionary game dynamics is considered
Ecological Modelling 185 (2005) 283297 Transient population dynamics: Relations to life
Rockwell, Robert F.
2005-01-01
Ecological Modelling 185 (2005) 283297 Transient population dynamics: Relations to life history, whereas the sub-adult survival sensitivity decreased. Transient population dynamics of long-lived, slow is reached. Meanwhile, the population dynamics are `transient' be
Synchronous dynamics and rates of extinction in spatially structured populations
Heino, Mikko
in dynamics among the subpopulations. Global disturbances and to a lesser extent, migration, are capable, mammals and birds (Ranta et al. 1995b), butterfly, moth and aphid populations in the British Isles
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...
Population dynamics, production, and prey consumption of fathead minnows (Pimephales
) in prairie wetlands: a bioenergetics approach W.G. Duffy Abstract: I assessed the population dynamics of fathead minnows (Pimephales promelas) in prairie wetlands and developed a bioenergetics model to estimate
Galactic civilizations: Population dynamics and interstellar diffusion
NASA Technical Reports Server (NTRS)
Newman, W. I.; Sagan, C.
1978-01-01
The interstellar diffusion of galactic civilizations is reexamined by potential theory; both numerical and analytical solutions are derived for the nonlinear partial differential equations which specify a range of relevant models, drawn from blast wave physics, soil science, and, especially, population biology. An essential feature of these models is that, for all civilizations, population growth must be limited by the carrying capacity of the environment. Dispersal is fundamentally a diffusion process; a density-dependent diffusivity describes interstellar emigration. Two models are considered: the first describing zero population growth (ZPG), and the second which also includes local growth and saturation of a planetary population, and for which an asymptotic traveling wave solution is found.
Stochastic dynamics and logistic population growth
NASA Astrophysics Data System (ADS)
Méndez, Vicenç; Assaf, Michael; Campos, Daniel; Horsthemke, Werner
2015-06-01
The Verhulst model is probably the best known macroscopic rate equation in population ecology. It depends on two parameters, the intrinsic growth rate and the carrying capacity. These parameters can be estimated for different populations and are related to the reproductive fitness and the competition for limited resources, respectively. We investigate analytically and numerically the simplest possible microscopic scenarios that give rise to the logistic equation in the deterministic mean-field limit. We provide a definition of the two parameters of the Verhulst equation in terms of microscopic parameters. In addition, we derive the conditions for extinction or persistence of the population by employing either the momentum-space spectral theory or the real-space Wentzel-Kramers-Brillouin approximation to determine the probability distribution function and the mean time to extinction of the population. Our analytical results agree well with numerical simulations.
Multiyear Population Dynamics of Ditylenchus dipsaci Associated with Phlox subulata.
Schnabelrauch, L S; Sink, K C; Bird, G W; Laemmlen, F F
1980-07-01
Field population densities of Ditylenchus dipsaci associated with shoot tissue of Phlox subulata were monitored during two consecutive growing seasons and intervening periods of overwintering and plant storage. The population density increased significantly through four peaks during the first growing season, and decreased significantly during storage at 5-7 C or overwintering in the field. During the second growing season, there was only a single increase to a moderate population density, followed by a severe population decline associated with the poor physiological condition of the host. A simple model is proposed to explain the population dynamics of D. dipsaci during the first growing season. PMID:19300697
Diversity waves in collapse-driven population dynamics
Maslov, Sergei
2015-01-01
Populations of species in ecosystems are constrained by the availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by the reduction in size of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt collapses of the entire population of a single species freeing up resources for the remaining ones. This mechanism may be relevant for communities of bacteria, with strain-specific collapses caused e.g. by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent property of the population dynamics in our system are cyclic "diversity waves" triggered by collapses of globally dominating populations. The population diversity in the environment peaks at the beginning of each wave and exponentially decreases afterwards. Population ...
Explaining "Noise" as Environmental Variations in Population Dynamics
Ginn, Timothy R.; Loge, Frank J.; Scheibe, Timothy D.
2007-03-01
The impacts of human activities on our own and other populations on the plant are making news at an alarming pace. Global warming, ocean and freshwater contamination and acidification, deforestation, habitat destruction and incursion, and in general a burgeoning human population are associated with a complete spectrum of changes to the dynamics of populations. Effects on songbirds, insects, coral reefs, ocean mammals, anadromous fishes, just to name a few, and humans, have been linked to human industry and population growth. The linkage, however, remains often ghostly and often tenuous at best, because of the difficulty in quantitatively combining ecological processes with environmental fate and transport processes. Establishing quantitative tools, that is, models, for the combined dynamics of populations and environmental chemical/thermal things is needed. This truly interdisciplinary challenge is briefly reviewed, and two approaches to integrating chemical and biological intermingling are addressed in the context of salmon populations in the Pacific Northwest.
Stage-Structured Population Dynamics of AEDES AEGYPTI
NASA Astrophysics Data System (ADS)
Yusoff, Nuraini; Budin, Harun; Ismail, Salemah
Aedes aegypti is the main vector in the transmission of dengue fever, a vector-borne disease affecting world population living in tropical and sub-tropical countries. Better understanding of the dynamics of its population growth will help in the efforts of controlling the spread of this disease. In looking at the population dynamics of Aedes aegypti, this paper explored the stage-structured modeling of the population growth of the mosquito using the matrix population model. The life cycle of the mosquito was divided into five stages: eggs, larvae, pupae, adult1 and adult2. Developmental rates were obtained for the average Malaysian temperature and these were used in constructing the transition matrix for the matrix model. The model, which was based only on temperature, projected that the population of Aedes aegypti will blow up with time, which is not realistic. For further work, other factors need to be taken into account to obtain a more realistic result.
The 5:1 Neptune Resonance: Dynamics and Population
NASA Astrophysics Data System (ADS)
Pike, Rosemary E.; Kavelaars, J. J.; Gladman, Brett; Petit, Jean-Marc; Alexandersen, Mike
2014-11-01
Based on 4 objects detected with semi-major axes near the 5:1 external resonance with Neptune, we estimate a substantial and previously unrecognized population of objects, perhaps more significant than the 3:2 (Plutino) resonance population. These external resonances are largely unexplored in both observations and dynamical simulations. However, understanding the characteristics and trapping history for objects in these populations is critical for constraining the dynamical history of the solar system. The 4 objects detected in the Canada-France Ecliptic Plane Survey (CFEPS) were classified using dynamical integrations. Three are resonant, and the last appears to be a resonant drop-off. The 3 objects are taken to be representative of the steady-state population, so by using these detections and the CFEPS characterization (pointings and detection limits) we calculate a population estimate for this resonance at ~3000(+5000 -2000) with Hg<8. This is at least as large as the Plutinos (3:2 resonance) at 90% confidence. The small number of detected objects results in such a large population estimate due to the numerous biases against detecting objects with semimajor axes at 88AU. Based on the dynamical behavior of the known objects, the trapping mechanism for the 5:1 resonance appears to be resonance sticking from the scattering objects. The long resonance lifetimes of some dynamical clones suggests that a steady state population could be maintained through periodic sticking.
A delayed-recruitment model of population dynamics, with an application to baleen whale populations
Colin W. Clark
1976-01-01
This paper studies the delay equation xk+1=?xk+F(xk-ß), which has been employed as a model of baleen whale population dynamics. The two main questions discussed are (a) stability of equilibria, and (b) optimal exploitation policies.
Dynamics of single-species population growth: stability or chaos
Mueller, L.D.; Ayala, F.J.
1981-01-01
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.
Dynamic population mapping using mobile phone data.
Deville, Pierre; Linard, Catherine; Martin, Samuel; Gilbert, Marius; Stevens, Forrest R; Gaughan, Andrea E; Blondel, Vincent D; Tatem, Andrew J
2014-11-11
During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography. PMID:25349388
Dynamic population mapping using mobile phone data
Deville, Pierre; Martin, Samuel; Gilbert, Marius; Stevens, Forrest R.; Gaughan, Andrea E.; Blondel, Vincent D.; Tatem, Andrew J.
2014-01-01
During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography. PMID:25349388
Population Dynamics and Range Expansion in Nine-Banded Armadillos
Oli, Madan K.
Population Dynamics and Range Expansion in Nine- Banded Armadillos William J. Loughry1 *, Carolina. The nine-banded armadillo (Dasypus novemcinctus) is a conspicuous example of a successful invader, having-mark-recapture data from a population of armadillos in northern Florida in order to estimate, and examine
How should environmental stress affect the population dynamics of disease?
Holt, Robert D.
118525, University of Florida, Gainesville, FL 32611-8525, USA *Correspondence: E-mail: lafferty and disease in natural populations. Keywords Disease, dynamics, host, infectious, model, pollution, population in pollution (Khan 1990), malnutrition (Beck & Levander 2000) and thermal stress from climate change (Harvell
2011-01-01
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. PMID:21975225
A Particle Population Control Method for Dynamic Monte Carlo
NASA Astrophysics Data System (ADS)
Sweezy, Jeremy; Nolen, Steve; Adams, Terry; Zukaitis, Anthony
2014-06-01
A general particle population control method has been derived from splitting and Russian Roulette for dynamic Monte Carlo particle transport. A well-known particle population control method, known as the particle population comb, has been shown to be a special case of this general method. This general method has been incorporated in Los Alamos National Laboratory's Monte Carlo Application Toolkit (MCATK) and examples of it's use are shown for both super-critical and sub-critical systems.
Spatio-temporal dynamics before population collapse
Dai, Lei, Ph. D. Massachusetts Institute of Technology
2014-01-01
Theory predicts that the approach of catastrophic thresholds in natural systems may result in an increasingly slow recovery from small perturbations, a phenomenon called critical slowing down. In this thesis, we used ...
Lawrence, J.E.
Are phytoplankton population density maxima predictable through analysis of host and viral genomic sizes therefore supports predictions of taxon-speci˘c phytoplankton population density thresholds beyond Synechococcus densities can drive the selection of populations of viruses with shorter lytic cycles and smaller
Vanwonterghem, Inka; Jensen, Paul D; Dennis, Paul G; Hugenholtz, Philip; Rabaey, Korneel; Tyson, Gene W
2014-10-01
A replicate long-term experiment was conducted using anaerobic digestion (AD) as a model process to determine the relative role of niche and neutral theory on microbial community assembly, and to link community dynamics to system performance. AD is performed by a complex network of microorganisms and process stability relies entirely on the synergistic interactions between populations belonging to different functional guilds. In this study, three independent replicate anaerobic digesters were seeded with the same diverse inoculum, supplied with a model substrate, ?-cellulose, and operated for 362 days at a 10-day hydraulic residence time under mesophilic conditions. Selective pressure imposed by the operational conditions and model substrate caused large reproducible changes in community composition including an overall decrease in richness in the first month of operation, followed by synchronised population dynamics that correlated with changes in reactor performance. This included the synchronised emergence and decline of distinct Ruminococcus phylotypes at day 148, and emergence of a Clostridium and Methanosaeta phylotype at day 178, when performance became stable in all reactors. These data suggest that many dynamic functional niches are predictably filled by phylogenetically coherent populations over long time scales. Neutral theory would predict that a complex community with a high degree of recognised functional redundancy would lead to stochastic changes in populations and community divergence over time. We conclude that deterministic processes may play a larger role in microbial community dynamics than currently appreciated, and under controlled conditions it may be possible to reliably predict community structural and functional changes over time. PMID:24739627
On Some Perturbation Approaches to Population Dynamics
Francisco M. Fernandez
2008-06-02
We show that the Adomian decomposition method, the time--series expansion, the homotopy--perturbation method, and the variational--iteration method completely fail to provide a reasonable description of the dynamics of the simplest prey--predator system.
Using stochastic population process models to predict the impact of climate change
NASA Astrophysics Data System (ADS)
van der Meer, Jaap; Beukema, J. J.; Dekker, Rob
2013-09-01
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.
Synchronization and Stability in Noisy Population Dynamics
Sabrina B. L. Araujo; M. A. M. de Aguiar
2008-02-15
We study the stability and synchronization of predator-prey populations subjected to noise. The system is described by patches of local populations coupled by migration and predation over a neighborhood. When a single patch is considered, random perturbations tend to destabilize the populations, leading to extinction. If the number of patches is small, stabilization in the presence of noise is maintained at the expense of synchronization. As the number of patches increases, both the stability and the synchrony among patches increase. However, a residual asynchrony, large compared with the noise amplitude, seems to persist even in the limit of infinite number of patches. Therefore, the mechanism of stabilization by asynchrony recently proposed by R. Abta et. al., combining noise, diffusion and nonlinearities, seems to be more general than first proposed.
Complex Population Dynamics in Mussels Arising from Density-Linked Stochasticity
Wootton, J. Timothy; Forester, James D.
2013-01-01
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. PMID:24086617
Predictions of a population of cataclysmic variables in globular clusters
NASA Technical Reports Server (NTRS)
Di Stefano, R.; Rappaport, S.
1994-01-01
We have studied the number of cataclysmic variables (CVs) that should be active in globular clusters during the present epoch as a result of binary formation via two-body tidal capture. We predict the orbital period and luminosity distributions of CVs in globular clusters. The results arebased on Monte Carlo simulations combined with evolution calculations appropriate to each system formed during the lifetime of two specific globular clusters, omega Cen and 47 Tuc. From our study of these two clusters, which represent the range of core densities and states of mass segregation that are likely to be interesting, we extrapolate our results to the Galactic globlular cluster system. Although there is at present little direct observational evidence of CVs in globular clusters, we find that there should be a large number of active systems. We predict that there should be more than approximately 100 CVs in both 47 Tuc and omega Cen and several thousand in the Galactic globular cluster system. These numbers are based on two-body processes alone and represent a lower bound on the number of systems that may have been formed as a result of stellar interaction within globular clusters. The relation between these calculations and the paucity of optically detected CVs in globular clusters is discussed. Should future observations fail to find convincing evidence of a substantial population of cluster CVs, then the two-body tidal capture scenario is likely to be seriously constrained. Of the CVs we espect in 47 Tuc and omega Cen, approximately 45 and 20, respectively, should have accretion luminosities above 10(exp 33) ergs/s. If one utilizes a relation for converting accretion luminosity to hard X-ray luminosity that is based on observations of Galactic plane CVs, even these sources will not exhibit X-ray luminosities above 10(exp 33) ergs/s. While we cannot account directly for the most luminous subset of the low-luminosity globular cluster X-ray sources without assuming an evolutionary pattern that is different from that of the majority of CVs in the disk, we are able to account for all of the observed lower luminosity subset of these sources, many of which have been recently discovered through ROSAT observations. In order for our predicted integrated cluster X-ray luminosities to be consistent with observational upper limits, the relation between accretion and X-ray luminosities should be something like that inferred from the Galactic plane population of CVs. Our calculations predict a large number of systems with L(sub acc) is less than 10(exp 32) ergs/s. Although our calculations imply that globular clusters should have an enhancement of CVs relative to the number thought to be present in the Galactic disk, this enhancement is at most roughly an order of magnitude, not comparable to the factor of approximately 100 for low-mass X-ray binaries (LMXBs).
Jochem, Warren C [ORNL; Sims, Kelly M [ORNL; Bright, Eddie A [ORNL; Urban, Marie L [ORNL; Rose, Amy N [ORNL; Coleman, Phil R [ORNL; Bhaduri, Budhendra L [ORNL
2013-01-01
In recent years, uses of high-resolution population distribution databases are increasing steadily for environmental, socioeconomic, public health, and disaster-related research and operations. With the development of daytime population distribution, temporal resolution of such databases has been improved. However, the lack of incorporation of transitional population, namely business and leisure travelers, leaves a significant population unaccounted for within the critical infrastructure networks, such as at transportation hubs. This paper presents two general methodologies for estimating passenger populations in airport and cruise port terminals at a high temporal resolution which can be incorporated into existing population distribution models. The methodologies are geographically scalable and are based on, and demonstrate how, two different transportation hubs with disparate temporal population dynamics can be modeled utilizing publicly available databases including novel data sources of flight activity from the Internet which are updated in near-real time. The airport population estimation model shows great potential for rapid implementation for a large collection of airports on a national scale, and the results suggest reasonable accuracy in the estimated passenger traffic. By incorporating population dynamics at high temporal resolutions into population distribution models, we hope to improve the estimates of populations exposed to or at risk to disasters, thereby improving emergency planning and response, and leading to more informed policy decisions.
Population dynamics and regulation in the cave salamander Speleomantes strinatii
NASA Astrophysics Data System (ADS)
Salvidio, Sebastiano
2007-05-01
Time series analysis has been used to evaluate the mechanisms regulating population dynamics of mammals and insects, but has been rarely applied to amphibian populations. In this study, the influence of endogenous (density-dependent) and exogenous (density-independent) factors regulating population dynamics of the terrestrial plethodontid salamander Speleomantes strinatii was analysed by means of time series and multiple regression analyses. During the period 1993 2005, S. strinatii population abundance, estimated by a standardised temporary removal method, displayed relatively low fluctuations, and the autocorrelation function (ACF) analysis showed that the time series had a noncyclic structure. The partial rate correlation function (PRCF) indicated that a strong first-order negative feedback dominated the endogenous dynamics. Stepwise multiple regression analysis showed that the only climatic factor influencing population growth rate was the minimum winter temperature. Thus, at least during the study period, endogenous, density-dependent negative feedback was the main factor affecting the growth rate of the salamander population, whereas stochastic environmental variables, such as temperature and rainfall, seemed to play a minor role in regulation. These results stress the importance of considering both exogenous and endogenous factors when analysing amphibian long-term population dynamics.
Modelling the Dynamics of an Aedes albopictus Population
Basuki, Thomas Anung; Barbuti, Roberto; Maggiolo-Schettini, Andrea; Milazzo, Paolo; Rossi, Elisabetta; 10.4204/EPTCS.33.2
2010-01-01
We present a methodology for modelling population dynamics with formal means of computer science. This allows unambiguous description of systems and application of analysis tools such as simulators and model checkers. In particular, the dynamics of a population of Aedes albopictus (a species of mosquito) and its modelling with the Stochastic Calculus of Looping Sequences (Stochastic CLS) are considered. The use of Stochastic CLS to model population dynamics requires an extension which allows environmental events (such as changes in the temperature and rainfalls) to be taken into account. A simulator for the constructed model is developed via translation into the specification language Maude, and used to compare the dynamics obtained from the model with real data.
Growth dynamics and the evolution of cooperation in microbial populations
Cremer, Jonas; Frey, Erwin; 10.1038/srep00281
2012-01-01
Microbes providing public goods are widespread in nature despite running the risk of being exploited by free-riders. However, the precise ecological factors supporting cooperation are still puzzling. Following recent experiments, we consider the role of population growth and the repetitive fragmentation of populations into new colonies mimicking simple microbial life-cycles. Individual-based modeling reveals that demographic fluctuations, which lead to a large variance in the composition of colonies, promote cooperation. Biased by population dynamics these fluctuations result in two qualitatively distinct regimes of robust cooperation under repetitive fragmentation into groups. First, if the level of cooperation exceeds a threshold, cooperators will take over the whole population. Second, cooperators can also emerge from a single mutant leading to a robust coexistence between cooperators and free-riders. We find frequency and size of population bottlenecks, and growth dynamics to be the major ecological facto...
Bounds on the dynamics of sink populations with noisy immigration.
Eager, Eric Alan; Guiver, Chris; Hodgson, Dave; Rebarber, Richard; Stott, Iain; Townley, Stuart
2014-03-01
Sink populations are doomed to decline to extinction in the absence of immigration. The dynamics of sink populations are not easily modelled using the standard framework of per capita rates of immigration, because numbers of immigrants are determined by extrinsic sources (for example, source populations, or population managers). Here we appeal to a systems and control framework to place upper and lower bounds on both the transient and future dynamics of sink populations that are subject to noisy immigration. Immigration has a number of interpretations and can fit a wide variety of models found in the literature. We apply the results to case studies derived from published models for Chinook salmon (Oncorhynchus tshawytscha) and blowout penstemon (Penstemon haydenii). PMID:24373938
Sequence tag-based analysis of microbial population dynamics.
Abel, Sören; Abel zur Wiesch, Pia; Chang, Hsiao-Han; Davis, Brigid M; Lipsitch, Marc; Waldor, Matthew K
2015-03-01
We describe sequence tag-based analysis of microbial populations (STAMP) for characterization of pathogen population dynamics during infection. STAMP analyzes the frequency changes of genetically 'barcoded' organisms to quantify population bottlenecks and infer the founding population size. Analyses of intraintestinal Vibrio cholerae revealed infection-stage and region-specific host barriers to infection and showed unexpected V. cholerae migration counter to intestinal flow. STAMP provides a robust, widely applicable analytical framework for high-confidence characterization of in vivo microbial dissemination. PMID:25599549
Population dynamics in meerkats, Suricata suricatta
Bateman, Andrew
2013-03-12
to smell eggs that have been forgotten for days in field bags that sit in 40°C heat. Specifically, thanks to Tom Flower, Rob Sutcliffe, Dave Bell, and Nate Thavarajah for showing me the ropes and for filling data requests and interpreting the results... Chapter One — Introduction 9 implications for vulnerable populations of cooperatively breeding species, such as in the high-profile case of African wild dogs, Lycaon pictus (Courchamp et al. 2000, Courchamp and Macdonald 2001). Although component...
Extinction rate fragility in population dynamics
M. Khasin; M. I. Dykman
2009-04-10
Population extinction is a rare event which requires overcoming an effective barrier. We show that the extinction rate can be fragile: a small change in the system parameters leads to an exponentially strong change of the rate, with the barrier height depending on the parameters nonanalytically. General conditions of the fragility are established. The fragility is found in one of the best-known models of epidemiology, the SIS model. The analytical expressions are compared with simulations.
Impact of transient climate change upon Grouse population dynamics in the Italian Alps
NASA Astrophysics Data System (ADS)
Pirovano, Andrea; Bocchiola, Daniele
2010-05-01
Understanding the effect of short to medium term weather condition, and of transient global warming upon wildlife species life history is essential to predict the demographic consequences therein, and possibly develop adaptation strategies, especially in game species, where hunting mortality may play an important role in population dynamics. We carried out a preliminary investigation of observed impact of weather variables upon population dynamics indexes of three alpine Grouse species (i.e. Rock Ptarmigan, Lagopus Mutus, Black Grouse, Tetrao Tetrix, Rock Partridge, Alectoris Graeca), nested within central Italian Alps, based upon 15 years (1995-2009) of available censuses data, provided by the Sondrio Province authority. We used a set of climate variables already highlighted within recent literature for carrying considerable bearing on Grouse population dynamics, including e.g. temperature at hatching time and during winter, snow cover at nesting, and precipitation during nursing period. We then developed models of Grouses' population dynamics by explicitly driving population change according to their dependence upon the significant weather variables and population density and we evaluated objective indexes to assess the so obtained predictive power. Eventually, we develop projection of future local climate, based upon locally derived trends, and upon projections from GCMs (A2 IPCC storyline) already validated for the area, to project forward in time (until 2100 or so) the significant climatic variables, which we then use to force population dynamics models of the target species. The projected patterns obtained through this exercise are discussed and compared against those expected under stationary climate conditions at present, and preliminary conclusions are drawn.
Dynamical Interactions Between Human Populations and Landscapes in Barrier Island Environments
NASA Astrophysics Data System (ADS)
McNamara, D. E.; Werner, B. T.
2003-12-01
Although much research has focused on how humans affect landscapes or how landform processes affect humans, little attention has been paid to dynamical interactions between the two. Based on the hypothesis that landscape and human dynamics both self-organize into a temporal hierarchy of scale-separated behaviors, we model the evolution of a coupled human population and barrier island system. Barrier islands are represented as a series of alongshore nodes, with each node specifying the width, height, cross-shore position, and profile of the island and the beach width, dune position and dune height. These characteristics evolve according to rules governing sediment transport during acretionary phases, erosion from storms, dune growth and migration, tidal delta formation, overwash, inlet formation, alongshore sediment transport, and dune and backbarrier vegetation growth. At each of these nodes, human populations and their cultural accoutrements are represented by mean property value, fraction of land used for tourist accommodations and tourist population. The dynamics of these variables is determined by simulating the competition for economic resources amongst the local population and the desire of the tourist population for adequate recreational beaches. The human and barrier subsystems are coupled through beach replenishment and a dependence of tourist population on beach width. Model results fall into three general categories of dynamical behavior, as classified by the (linearized) time scale of recovery from perturbations for the uncoupled systems. When the time scale for barrier islands is much less than that of the human population, the long-time-scale evolution of the barrier island follows human dynamics. In the reverse case, the long-time-scale evolution of the human population follows barrier dynamics. When the time scales are similar, new long-time-scale, spatially varying behavior of the coupled system emerges. Implications for prediction and optimization strategies will be discussed.
A general method for modeling population dynamics and its applications.
Shestopaloff, Yuri K
2013-12-01
Studying populations, be it a microbe colony or mankind, is important for understanding how complex systems evolve and exist. Such knowledge also often provides insights into evolution, history and different aspects of human life. By and large, populations' prosperity and decline is about transformation of certain resources into quantity and other characteristics of populations through growth, replication, expansion and acquisition of resources. We introduce a general model of population change, applicable to different types of populations, which interconnects numerous factors influencing population dynamics, such as nutrient influx and nutrient consumption, reproduction period, reproduction rate, etc. It is also possible to take into account specific growth features of individual organisms. We considered two recently discovered distinct growth scenarios: first, when organisms do not change their grown mass regardless of nutrients availability, and the second when organisms can reduce their grown mass by several times in a nutritionally poor environment. We found that nutrient supply and reproduction period are two major factors influencing the shape of population growth curves. There is also a difference in population dynamics between these two groups. Organisms belonging to the second group are significantly more adaptive to reduction of nutrients and far more resistant to extinction. Also, such organisms have substantially more frequent and lesser in amplitude fluctuations of population quantity for the same periodic nutrient supply (compared to the first group). Proposed model allows adequately describing virtually any possible growth scenario, including complex ones with periodic and irregular nutrient supply and other changing parameters, which present approaches cannot do. PMID:24057917
Inferences about ungulate population dynamics derived from age ratios
Harris, N.C.; Kauffman, M.J.; Mills, L.S.
2008-01-01
Age ratios (e.g., calf:cow for elk and fawn:doe for deer) are used regularly to monitor ungulate populations. However, it remains unclear what inferences are appropriate from this index because multiple vital rate changes can influence the observed ratio. We used modeling based on elk (Cervus elaphus) life-history to evaluate both how age ratios are influenced by stage-specific fecundity and survival and how well age ratios track population dynamics. Although all vital rates have the potential to influence calf:adult female ratios (i.e., calf:xow ratios), calf survival explained the vast majority of variation in calf:adult female ratios due to its temporal variation compared to other vital rates. Calf:adult female ratios were positively correlated with population growth rate (??) and often successfully indicated population trajectories. However, calf:adult female ratios performed poorly at detecting imposed declines in calf survival, suggesting that only the most severe declines would be rapidly detected. Our analyses clarify that managers can use accurate, unbiased age ratios to monitor arguably the most important components contributing to sustainable ungulate populations, survival rate of young and ??. However, age ratios are not useful for detecting gradual declines in survival of young or making inferences about fecundity or adult survival in ungulate populations. Therefore, age ratios coupled with independent estimates of population growth or population size are necessary to monitor ungulate population demography and dynamics closely through time.
Miller, David A.; Clark, W.R.; Arnold, S.J.; Bronikowski, A.M.
2011-01-01
Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (??s) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on ?? s. The magnitude of variation in the proportion of gravid females and its effect on ??s was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on ??s was 4- 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life-history traits in the two ecotypes, which, in turn, affect population dynamics. M-slow populations have evolved life-history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long-term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life-history evolution. ?? 2011 by the Ecological Society of America.
NASA Astrophysics Data System (ADS)
Lehodey, Patrick; Senina, Inna; Murtugudde, Raghu
2008-09-01
An enhanced version of the spatial ecosystem and population dynamics model SEAPODYM is presented to describe spatial dynamics of tuna and tuna-like species in the Pacific Ocean at monthly resolution over 1° grid-boxes. The simulations are driven by a bio-physical environment predicted from a coupled ocean physical-biogeochemical model. This new version of SEAPODYM includes expanded definitions of habitat indices, movements, and natural mortality based on empirical evidences. A thermal habitat of tuna species is derived from an individual heat budget model. The feeding habitat is computed according to the accessibility of tuna predator cohorts to different vertically migrating and non-migrating micronekton (mid-trophic) functional groups. The spawning habitat is based on temperature and the coincidence of spawning fish with presence or absence of predators and food for larvae. The successful larval recruitment is linked to spawning stock biomass. Larvae drift with currents, while immature and adult tuna can move of their own volition, in addition to being advected by currents. A food requirement index is computed to adjust locally the natural mortality of cohorts based on food demand and accessibility to available forage components. Together these mechanisms induce bottom-up and top-down effects, and intra- (i.e. between cohorts) and inter-species interactions. The model is now fully operational for running multi-species, multi-fisheries simulations, and the structure of the model allows a validation from multiple data sources. An application with two tuna species showing different biological characteristics, skipjack ( Katsuwonus pelamis) and bigeye ( Thunnus obesus), is presented to illustrate the capacity of the model to capture many important features of spatial dynamics of these two different tuna species in the Pacific Ocean. The actual validation is presented in a companion paper describing the approach to have a rigorous mathematical parameter optimization [Senina, I., Sibert, J., Lehodey, P., 2008. Parameter estimation for basin-scale ecosystem-linked population models of large pelagic predators: application to skipjack tuna. Progress in Oceanography]. Once this evaluation and parameterization is complete, it may be possible to use the model for management of tuna stocks in the context of climate and ecosystem variability, and to investigate potential changes due to anthropogenic activities including global warming and fisheries pressures and management scenarios.
Unstable dynamics and population limitation in mountain hares.
Newey, Scott; Dahl, Fredrik; Willebrand, Tomas; Thirgood, Simon
2007-11-01
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
Predictability of threshold exceedances in dynamical systems
Tamas Bodai
2015-05-10
In a low-order model of the general circulation of the atmosphere we examine the predictability of threshold exceedance events of certain observables. The likelihood of such binary events -- the cornerstone also for the categoric (as opposed to probabilistic) prediction of threshold exceedences -- is established from long time series of one or more observables of the same system. The prediction skill is measured by a summary index of the ROC curve that relates the hit- and false alarm rates. Our results for the examined systems confirm a counterintuitive (and seemingly contrafactual) statement that was previously formulated for more simple autoregressive stochastic processes. Namely, we find that exceedances of higher thresholds are more predictable; or in other words: rare extremes are more predictable than frequent typical events. We find this to hold provided that the bin size for binning time series data is optimized, but not necessarily otherwise. We argue that when there is a sufficient amount of data depending on the precision of observation, the skill of data-driven categoric prediction of threshold exceedences approximates the skill of the model-driven counterpart of the same kind of prediction, assuming strictly no model errors. Therefore, stronger extremes in terms of higher threshold levels are more predictable both in case of data- and model-driven prediction. Furthermore, we show that a quantity commonly regarded as a measure of predictability, the finite-time maximal Lyapunov exponent, does not correspond directly to the ROC-based measure of prediction skill when they are viewed as functions of the prediction lead time and the threshold level. This points to the fact that even if the Lyapunov exponent as an intrinsic property of the system, measuring the instability of trajectories, determines predictability, it does that in a nontrivial manner.
Population Dynamics of Borrelia burgdorferi in Lyme Disease
Binder, Sebastian C.; Telschow, Arndt; Meyer-Hermann, Michael
2012-01-01
Many chronic inflammatory diseases are known to be caused by persistent bacterial or viral infections. A well-studied example is the tick-borne infection by the gram-negative spirochaetes of the genus Borrelia in humans and other mammals, causing severe symptoms of chronic inflammation and subsequent tissue damage (Lyme Disease), particularly in large joints and the central nervous system, but also in the heart and other tissues of untreated patients. Although killed efficiently by human phagocytic cells in vitro, Borrelia exhibits a remarkably high infectivity in mice and men. In experimentally infected mice, the first immune response almost clears the infection. However, approximately 1 week post infection, the bacterial population recovers and reaches an even larger size before entering the chronic phase. We developed a mathematical model describing the bacterial growth and the immune response against Borrelia burgdorferi in the C3H mouse strain that has been established as an experimental model for Lyme disease. The peculiar dynamics of the infection exclude two possible mechanistic explanations for the regrowth of the almost cleared bacteria. Neither the hypothesis of bacterial dissemination to different tissues nor a limitation of phagocytic capacity were compatible with experiment. The mathematical model predicts that Borrelia recovers from the strong initial immune response by the regrowth of an immune-resistant sub-population of the bacteria. The chronic phase appears as an equilibration of bacterial growth and adaptive immunity. This result has major implications for the development of the chronic phase of Borrelia infections as well as on potential protective clinical interventions. PMID:22470370
Prediction of the MaddenJulian oscillation with the POAMA dynamical prediction system
Hendon, Harry
Prediction of the MaddenJulian oscillation with the POAMA dynamical prediction system Harun A. Rashid · Harry H. Hendon · Matthew C. Wheeler · Oscar Alves Received: 23 June 2009 / Accepted: 27 January 2010 Ó Springer-Verlag 2010 Abstract Predictions of the MaddenJulian oscillation (MJO) are assessed
[Population dynamics and aspects of health policy].
del Rey Calero, J
1994-01-01
This work explains basic demographic concepts and their relevance to health planning. It describes population growth as the result of the interplay of fertility, mortality, and migration, and explains the demographic and epidemiologic transitions. A summary view of economic conditions since World War II considers increases in spending on health and welfare in the context of overall economic conditions, especially in Spain, where unemployment and inflation have been problems. The influence of declining fertility on the age structure, and hence on health expenditures, is explained. Spain's population age 65 and over will increase to 15.2% of the total by 1996. 35% of hospital stays are for individuals over age 65, and the elderly tend to require longer stays. The distinction between life expectancy and life expectancy without disability is explained. Life expectancy at birth in Spain averages 76.4 years, while life expectancy without disability averages 61 years. The quest for equity is an objective of public health, but countries at different levels of development have greatly varying health expenditures. Programs to control infant mortality have been highly successful and cost effective, while programs for adults have been more complex to evaluate because of the influence of life styles. Health investments in poor countries generally have favorable cost-benefit ratios. Not all investments in richer countries have favorable ratios. The European Union is attempting to define a minimal level of health services to be offered by member nations to their citizens. PMID:7978122
Prediction of breed composition in an admixed cattle population.
Frkonja, A; Gredler, B; Schnyder, U; Curik, I; Sölkner, J
2012-12-01
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
Stochastic Population Dynamics of a Montane Ground-Dwelling Squirrel
Hostetler, Jeffrey A.; Kneip, Eva; Van Vuren, Dirk H.; Oli, Madan K.
2012-01-01
Understanding the causes and consequences of population fluctuations is a central goal of ecology. We used demographic data from a long-term (1990–2008) study and matrix population models to investigate factors and processes influencing the dynamics and persistence of a golden-mantled ground squirrel (Callospermophilus lateralis) population, inhabiting a dynamic subalpine habitat in Colorado, USA. The overall deterministic population growth rate ? was 0.94±SE 0.05 but it varied widely over time, ranging from 0.45±0.09 in 2006 to 1.50±0.12 in 2003, and was below replacement (?<1) for 9 out of 18 years. The stochastic population growth rate ?s was 0.92, suggesting a declining population; however, the 95% CI on ?s included 1.0 (0.52–1.60). Stochastic elasticity analysis showed that survival of adult females, followed by survival of juvenile females and litter size, were potentially the most influential vital rates; analysis of life table response experiments revealed that the same three life history variables made the largest contributions to year-to year changes in ?. Population viability analysis revealed that, when the influences of density dependence and immigration were not considered, the population had a high (close to 1.0 in 50 years) probability of extinction. However, probability of extinction declined to as low as zero when density dependence and immigration were considered. Destabilizing effects of stochastic forces were counteracted by regulating effects of density dependence and rescue effects of immigration, which allowed our study population to bounce back from low densities and prevented extinction. These results suggest that dynamics and persistence of our study population are determined synergistically by density-dependence, stochastic forces, and immigration. PMID:22479616
Kendall, B E; Fox, G A
1998-08-01
Spatial extent can have two important consequences for population dynamics: It can generate spatial structure, in which individuals interact more intensely with neighbors than with more distant conspecifics, and it allows for environmental heterogeneity, in which habitat quality varies spatially. Studies of these features are difficult to interpret because the models are complex and sometimes idiosyncratic. Here we analyze one of the simplest possible spatial population models, to understand the mathematical basis for the observed patterns: two patches coupled by dispersal, with dynamics in each patch governed by the logistic map. With suitable choices of parameters, this model can represent spatial structure, environmental heterogeneity, or both in combination. We synthesize previous work and new analyses on this model, with two goals: to provide a comprehensive baseline to aid our understanding of more complex spatial models, and to generate predictions about the effects of spatial structure and environmental heterogeneity on population dynamics. Spatial structure alone can generate positive, negative, or zero spatial correlations between patches when dispersal rates are high, medium, or low relative to the complexity of the local dynamics. It can also lead to quasiperiodicity and hyperchaos, which are not present in the nonspatial model. With density-independent dispersal, spatial structure cannot destabilize equilibria or periodic orbits that would be stable in the absence of space. When densities in the two patches are uncorrelated, the probability that the population in a patch reaches extreme low densities is reduced relative to the same patch in isolation; this "rescue effect" would reduce the probability of metapopulation extinction beyond the simple effect of spreading of risk. Pure environmental heterogeneity always produces positive spatial correlations. The dynamics of the entire population is approximated by a nonspatial model with mean patch characteristics. This approximation worsens as the difference between the patches increases and the dispersal rate decreases: Under extreme conditions, destabilization of equilibria and periodic orbits occurs at mean parameter values lower than those predicted by the mean parameters. Apparent within-patch dynamics are distorted: The local population appears to have the wrong growth parameter and a constant number of immigrants (or emigrants) per generation. Adding environmental heterogeneity to spatial structure increases the occurrence of spatially correlated population dynamics, but the resulting temporal dynamics are more complex than would be predicted by the mean parameter values. The three classes of spatial pattern (positive, negative, and zero correlation), while still mathematically distinct, become increasingly similar phenomenologically. PMID:9680486
Namazi-Rad, Mohammad-Reza; Mokhtarian, Payam; Perez, Pascal
2014-01-01
Generating a reliable computer-simulated synthetic population is necessary for knowledge processing and decision-making analysis in agent-based systems in order to measure, interpret and describe each target area and the human activity patterns within it. In this paper, both synthetic reconstruction (SR) and combinatorial optimisation (CO) techniques are discussed for generating a reliable synthetic population for a certain geographic region (in Australia) using aggregated- and disaggregated-level information available for such an area. A CO algorithm using the quadratic function of population estimators is presented in this paper in order to generate a synthetic population while considering a two-fold nested structure for the individuals and households within the target areas. The baseline population in this study is generated from the confidentialised unit record files (CURFs) and 2006 Australian census tables. The dynamics of the created population is then projected over five years using a dynamic micro-simulation model for individual- and household-level demographic transitions. This projection is then compared with the 2011 Australian census. A prediction interval is provided for the population estimates obtained by the bootstrapping method, by which the variability structure of a predictor can be replicated in a bootstrap distribution. PMID:24733522
Real-Time Bioluminescent Tracking of Cellular Population Dynamics
Close, Dan [University of Tennessee, Knoxville (UTK)] [University of Tennessee, Knoxville (UTK); Sayler, Gary Steven [ORNL] [ORNL; Xu, Tingting [ORNL] [ORNL; Ripp, Steven Anthony [ORNL] [ORNL
2014-01-01
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.
Turbulent dynamics in a XVIIth century population.
Bonneuil, N
1990-01-01
"A reconstruction of the population of the Pays de Caux [France] (1589-1700) yields the time series of a fertility behavior indicator....An attempt is made to explain this general temporal structure by using a simulation model based on the autoregulation model (the so-called European Marriage Pattern), putting into play a choice of the spouse function, a fertility function, modalities of marriage and remarriage, under the environmental forcing of the reconstructed mortality conditions. The correspondence between reconstruction and simulation turns out to be quite good....A second simulation with simulated mortality conditions shows a bifurcation point: as the mean frequency of crisis increases, the state of the system leaves the lower level and concentrates more and more in the higher level." (SUMMARY IN FRE) PMID:12283331
Population dynamics: Social security, markets, and families
Lee, Ronald D.; Lee, Sang-Hyop
2015-01-01
Upward intergenerational flows – from the working ages to old age – are increasing substantially in the advanced industrialized countries and are much larger than in developing countries. Population aging is the most important factor leading to this change. Thus, in the absence of a major demographic shift, e.g., a return to high fertility, an increase in upward flows is inevitable. Even so, three other important factors will influence the magnitudes of upward flows. First, labor income varies at older ages due to differences in average age at retirement, productivity, unemployment, and hours worked. Second, the age patterns of consumption at older ages vary primarily due to differences in spending on health. Third, spending on human capital, i.e., spending child health and education, varies. Human capital spending competes with spending on the elderly, but it also increases the productivity of subsequent generations of workers and the resources available to support consumption in old age. All contemporary societies rely on a variety of institutions and economic mechanisms to shift economic resources from the working ages to the dependent ages – the young and the old. Three institutions dominate intergenerational flows: governments which implement social security, education, and other public transfer programs; markets which are key to the accumulation of assets, e.g., funded pensions and housing; and families which provide economic support to children in all societies and to the elderly in many. The objectives of this paper are, first, to describe how population aging and other changes influence the direction and magnitude of intergenerational flows; and, second, to contrast the institutional approaches to intergenerational flows as they are practiced around the world. The paper relies extensively on National Transfer Accounts, a system for measuring economic flows across age in a manner consistent with the UN System of National Accounts. These accounts are currently being constructed by research teams located in 33 countries on six continents representing wide variations in the level of development, demographics, and policies regarding intergenerational transfers.
Simple mathematical models do not accurately predict early SIV dynamics.
Noecker, Cecilia; Schaefer, Krista; Zaccheo, Kelly; Yang, Yiding; Day, Judy; Ganusov, Vitaly V
2015-03-01
Upon infection of a new host, human immunodeficiency virus (HIV) replicates in the mucosal tissues and is generally undetectable in circulation for 1-2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the "standard" mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV). First, we found that the mode of virus production by infected cells (budding vs. bursting) has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral dose. These results suggest that, in order to appropriately model early HIV/SIV dynamics, additional factors must be considered in the model development. These may include variability in monkey susceptibility to infection, within-host competition between different viruses for target cells at the initial site of virus replication in the mucosa, innate immune response, and possibly the inclusion of several different tissue compartments. The sobering news is that while an increase in model complexity is needed to explain the available experimental data, testing and rejection of more complex models may require more quantitative data than is currently available. PMID:25781919
Dynamic stall progress in analysis and prediction
NASA Technical Reports Server (NTRS)
Carr, L. W.
1985-01-01
A comprehensive review of research in dynamic stall is presented with applications for helicopters, fighter aircraft, and wind turbines illustrated and evaluated. Emphasis is placed on review of research contributing to better understanding of the dynamic stall mechanism, including influence of type of motion, Mach number, Reynolds number, and three-dimensional effects.
Human population as a dynamic factor in environmental degradation
John Harte
2007-01-01
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
Network evolution induced by the dynamical rules of two populations
NASA Astrophysics Data System (ADS)
Platini, Thierry; Zia, R. K. P.
2010-10-01
We study the dynamical properties of a finite dynamical network composed of two interacting populations, namely extrovert (a) and introvert (b). In our model, each group is characterized by its size (Na and Nb) and preferred degree (?a and \\kappa_b\\ll \\kappa_a ). The network dynamics is governed by the competing microscopic rules of each population that consist of the creation and destruction of links. Starting from an unconnected network, we give a detailed analysis of the mean field approach which is compared to Monte Carlo simulation data. The time evolution of the restricted degrees langkbbrang and langkabrang presents three time regimes and a non-monotonic behavior well captured by our theory. Surprisingly, when the population sizes are equal Na = Nb, the ratio of the restricted degree ?0 = langkabrang/langkbbrang appears to be an integer in the asymptotic limits of the three time regimes. For early times (defined by t < t1 = ?b) the total number of links presents a linear evolution, where the two populations are indistinguishable and where ?0 = 1. Interestingly, in the intermediate time regime (defined for t_1\\lt t\\lt t_2\\propto \\kappa_a and for which ?0 = 5), the system reaches a transient stationary state, where the number of contacts among introverts remains constant while the number of connections increases linearly in the extrovert population. Finally, due to the competing dynamics, the network presents a frustrated stationary state characterized by a ratio ?0 = 3.
2012-01-01
Background Risk prediction models for hepatocellular carcinoma are available for individuals with chronic hepatitis B virus (HBV) and hepatitis C virus (HCV) infections who are at high risk but not for the general population with average or unknown risk. We developed five simple risk prediction models based on clinically available data from the general population. Methods A prospective cohort of 428 584 subjects from a private health screening firm in Taiwan was divided into two subgroups—one with known HCV test results (n = 130 533 subjects) and the other without (n = 298 051 subjects). A total of 1668 incident hepatocellular carcinomas occurred during an average follow-up of 8.5 years. Model inputs included age, sex, health history–related variables; HBV or HCV infection–related variables; serum levels of alanine transaminase (ALT), aspartate transaminase (AST), and alfa-fetoprotein (AFP), as well as other variables of routine blood panels for liver function. Cox proportional hazards regression method was used to identify risk predictors of hepatocellular carcinoma. Receiver operating characteristic curves were used to assess discriminatory accuracy of the models. Models were internally validated. All statistical tests were two-sided. Results Age, sex, health history, HBV and HCV status, and serum ALT, AST, AFP levels were statistically significant independent predictors of hepatocellular carcinoma risk (all P < .05). Use of serum transaminases only in a model showed a higher discrimination compared with HBV or HCV only (for transaminases, area under the curve [AUC] = 0.912, 95% confidence interval [CI] = 0.909 to 0.915; for HBV, AUC = 0.840, 95% CI = 0.833 to 0.848; and for HCV, AUC = 0.841, 95% CI = 0.834 to 0.847). Adding HBV and HCV data to the transaminase-only model improved the discrimination (AUC = 0.933, 95% CI = 0.929 to 0.949). Internal validation showed high discriminatory accuracy and calibration of these models. Conclusion Models with transaminase data were best able to predict hepatocellular carcinoma risk even among subjects with unknown or HBV- or HCV-negative infection status. PMID:23073549
Global Population Dynamics and Hot Spots of Response to Climate Change
NSDL National Science Digital Library
Eric Post (Pennsylvania State University; )
2009-06-01
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 speciesâ?? 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.
The DynaMine webserver: predicting protein dynamics from sequence.
Cilia, Elisa; Pancsa, Rita; Tompa, Peter; Lenaerts, Tom; Vranken, Wim F
2014-07-01
Protein dynamics are important for understanding protein function. Unfortunately, accurate protein dynamics information is difficult to obtain: here we present the DynaMine webserver, which provides predictions for the fast backbone movements of proteins directly from their amino-acid sequence. DynaMine rapidly produces a profile describing the statistical potential for such movements at residue-level resolution. The predicted values have meaning on an absolute scale and go beyond the traditional binary classification of residues as ordered or disordered, thus allowing for direct dynamics comparisons between protein regions. Through this webserver, we provide molecular biologists with an efficient and easy to use tool for predicting the dynamical characteristics of any protein of interest, even in the absence of experimental observations. The prediction results are visualized and can be directly downloaded. The DynaMine webserver, including instructive examples describing the meaning of the profiles, is available at http://dynamine.ibsquare.be. PMID:24728994
Dynamics and Predictability of Hurricane Dolly (2008)
NASA Astrophysics Data System (ADS)
Fang, J.; Zhang, F.; Weng, Y.
2008-12-01
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.
Muller, Clemma J; MacLehose, Richard F
2014-01-01
Background: We review three common methods to estimate predicted probabilities following confounder-adjusted logistic regression: marginal standardization (predicted probabilities summed to a weighted average reflecting the confounder distribution in the target population); prediction at the modes (conditional predicted probabilities calculated by setting each confounder to its modal value); and prediction at the means (predicted probabilities calculated by setting each confounder to its mean value). That each method corresponds to a different target population is underappreciated in practice. Specifically, prediction at the means is often incorrectly interpreted as estimating average probabilities for the overall study population, and furthermore yields nonsensical estimates in the presence of dichotomous confounders. Default commands in popular statistical software packages often lead to inadvertent misapplication of prediction at the means. Methods: Using an applied example, we demonstrate discrepancies in predicted probabilities across these methods, discuss implications for interpretation and provide syntax for SAS and Stata. Results: Marginal standardization allows inference to the total population from which data are drawn. Prediction at the modes or means allows inference only to the relevant stratum of observations. With dichotomous confounders, prediction at the means corresponds to a stratum that does not include any real-life observations. Conclusions: Marginal standardization is the appropriate method when making inference to the overall population. Other methods should be used with caution, and prediction at the means should not be used with binary confounders. Stata, but not SAS, incorporates simple methods for marginal standardization. PMID:24603316
Disentangling seasonal bacterioplankton population dynamics by high-frequency sampling.
Lindh, Markus V; Sjöstedt, Johanna; Andersson, Anders F; Baltar, Federico; Hugerth, Luisa W; Lundin, Daniel; Muthusamy, Saraladevi; Legrand, Catherine; Pinhassi, Jarone
2015-07-01
Multiyear comparisons of bacterioplankton succession reveal that environmental conditions drive community shifts with repeatable patterns between years. However, corresponding insight into bacterioplankton dynamics at a temporal resolution relevant for detailed examination of variation and characteristics of specific populations within years is essentially lacking. During 1 year, we collected 46 samples in the Baltic Sea for assessing bacterial community composition by 16S rRNA gene pyrosequencing (nearly twice weekly during productive season). Beta-diversity analysis showed distinct clustering of samples, attributable to seemingly synchronous temporal transitions among populations (populations defined by 97% 16S rRNA gene sequence identity). A wide spectrum of bacterioplankton dynamics was evident, where divergent temporal patterns resulted both from pronounced differences in relative abundance and presence/absence of populations. Rates of change in relative abundance calculated for individual populations ranged from 0.23 to 1.79 day(-1) . Populations that were persistently dominant, transiently abundant or generally rare were found in several major bacterial groups, implying evolution has favoured a similar variety of life strategies within these groups. These findings suggest that high temporal resolution sampling allows constraining the timescales and frequencies at which distinct populations transition between being abundant or rare, thus potentially providing clues about physical, chemical or biological forcing on bacterioplankton community structure. PMID:25403576
Genomic predictability of interconnected bi-parental maize populations
Technology Transfer Automated Retrieval System (TEKTRAN)
Intense structuring of plant breeding populations leads to new challenges for genomic selection (GS) not encountered in animal breeding. One important open question is how the training population (TP) should be constructed from multiple related or unrelated small bi-parental families. Knowing the pr...
Sandra E. Helms; Mark D. Hunter
2005-01-01
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
Bender, Brendan C; Schindler, Emilie; Friberg, Lena E
2015-01-01
In oncology trials, overall survival (OS) is considered the most reliable and preferred endpoint to evaluate the benefit of drug treatment. Other relevant variables are also collected from patients for a given drug and its indication, and it is important to characterize the dynamic effects and links between these variables in order to improve the speed and efficiency of clinical oncology drug development. However, the drug-induced effects and causal relationships are often difficult to interpret because of temporal differences. To address this, population pharmacokinetic-pharmacodynamic (PKPD) modelling and parametric time-to-event (TTE) models are becoming more frequently applied. Population PKPD and TTE models allow for exploration towards describing the data, understanding the disease and drug action over time, investigating relevance of biomarkers, quantifying patient variability and in designing successful trials. In addition, development of models characterizing both desired and adverse effects in a modelling framework support exploration of risk-benefit of different dosing schedules. In this review, we have summarized population PKPD modelling analyses describing tumour, tumour marker and biomarker responses, as well as adverse effects, from anticancer drug treatment data. Various model-based metrics used to drive PD response and predict OS for oncology drugs and their indications are also discussed. PMID:24134068
NASA Technical Reports Server (NTRS)
Holms, A. G.
1974-01-01
Monte Carlo studies using population models intended to represent response surface applications are reported. Simulated experiments were generated by adding pseudo random normally distributed errors to population values to generate observations. Model equations were fitted to the observations and the decision procedure was used to delete terms. Comparison of values predicted by the reduced models with the true population values enabled the identification of deletion strategies that are approximately optimal for minimizing prediction errors.
Sunlu, F S; Demir, I; Onkal Engin, G; Buyukisik, B; Sunlu, U; Koray, T; Kukrer, S
2009-06-01
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
Interactions between predation and resources shape zooplankton population dynamics.
Nicolle, Alice; Hansson, Lars-Anders; Brodersen, Jakob; Nilsson, P Anders; Brönmark, Christer
2011-01-01
Identifying the relative importance of predation and resources in population dynamics has a long tradition in ecology, while interactions between them have been studied less intensively. In order to disentangle the effects of predation by juvenile fish, algal resource availability and their interactive effects on zooplankton population dynamics, we conducted an enclosure experiment where zooplankton were exposed to a gradient of predation of roach (Rutilus rutilus) at different algal concentrations. We show that zooplankton populations collapse under high predation pressure irrespective of resource availability, confirming that juvenile fish are able to severely reduce zooplankton prey when occurring in high densities. At lower predation pressure, however, the effect of predation depended on algal resource availability since high algal resource supply buffered against predation. Hence, we suggest that interactions between mass-hatching of fish, and the strong fluctuations in algal resources in spring have the potential to regulate zooplankton population dynamics. In a broader perspective, increasing spring temperatures due to global warming will most likely affect the timing of these processes and have consequences for the spring and summer zooplankton dynamics. PMID:21304980
Modeling the Evolutionary Dynamics of Plasmids in Spatial Populations
Modeling the Evolutionary Dynamics of Plasmids in Spatial Populations Brian D. Connelly, Luis Zaman of Computation--Self-modifying machines General Terms Experimentation, Theory Keywords Artificial life, plasmid the relationship between selection for plasmid- encoded adaptations and the costs of plasmid carriage in spatial
Reproduction and Population Dynamics in the Calcareous Sponge, Leucetta losangelensis
Shuster, Stephen M.
Reproduction and Population Dynamics in the Calcareous Sponge, Leucetta losangelensis Dannielle Leucetta losangelensis is a common intertidal calcareous sponge inhabiting the northern Gulf of California and reproductive behavior, we censused sponges inhabiting a mid-intertidal boulder field near Puerto Peńasco
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...
Binary populations and stellar dynamics in young clusters
D. Vanbeveren; H. Belkus; J. Van Bever; N. Mennekens
2008-01-17
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, Eta Carinae, Zeta Puppis, Gamma Velorum and WR 140.
Food-dependent individual growth and population dynamics in fishes*
Roos, André M. de
Food-dependent individual growth and population dynamics in fishes* L. PERSSON AND A. M. DE ROOS on food intake. Yet, this dependence of individual development on food levels has only to a limited extent individuals. The addition of cannibalism may dampen these cycles, the extent to which is dependent on life
Modelling microbial population dynamics in nitritation processes Elisabetta Giusti a
. A modified Activated Sludge Model No. 3 (ASM3) with two-step nitrification-denitrifi- cation. Environmental January 2011 Accepted 1 February 2011 Available online 3 March 2011 Keywords: Microbial kinetics Activated sludge modelling Parameter estimation Population dynamics Nitritation a b s t r a c t In the wastewater
Population Dynamics: A Curriculum Guide for Elementary and Secondary Teachers.
ERIC Educational Resources Information Center
Byrne, Robert; And Others
Presented is one of five Wildlife and Environmental Education Teaching units that deal with resource management in a way that includes man as user and manager of natural resources. Included are activities (with their suggested grade levels) that deal with population dynamics. Fifteen supportive activities are described. A list of recommended films…
Interactions between Predation and Resources Shape Zooplankton Population Dynamics
Nicolle, Alice; Hansson, Lars-Anders; Brodersen, Jakob; Nilsson, P. Anders; Brönmark, Christer
2011-01-01
Identifying the relative importance of predation and resources in population dynamics has a long tradition in ecology, while interactions between them have been studied less intensively. In order to disentangle the effects of predation by juvenile fish, algal resource availability and their interactive effects on zooplankton population dynamics, we conducted an enclosure experiment where zooplankton were exposed to a gradient of predation of roach (Rutilus rutilus) at different algal concentrations. We show that zooplankton populations collapse under high predation pressure irrespective of resource availability, confirming that juvenile fish are able to severely reduce zooplankton prey when occurring in high densities. At lower predation pressure, however, the effect of predation depended on algal resource availability since high algal resource supply buffered against predation. Hence, we suggest that interactions between mass-hatching of fish, and the strong fluctuations in algal resources in spring have the potential to regulate zooplankton population dynamics. In a broader perspective, increasing spring temperatures due to global warming will most likely affect the timing of these processes and have consequences for the spring and summer zooplankton dynamics. PMID:21304980
Inference from a Deterministic Population Dynamics Model for Bowhead Whales
Adrian E. Raftery; Geof H. Givens; Judith E. Zeh
1995-01-01
We consider the problem of inference about a quantity of interest given different sources of information linked by a deterministic population dynamics model. Our approach consists of translating all the available information into a joint premodel distribution on all the model inputs and outputs and then restricting this to the submanifold defined by the model to obtain the joint postmodel
Inference from a Deterministic Population Dynamics Model for Bowhead Whales
Givens, Geof H.
Inference from a Deterministic Population Dynamics Model for Bowhead Whales Adrian E. Raftery, Geof on a generalization of the Bayes factor idea. A key quantity used by the International Whaling Commission (IWC) in making decisions about bowhead whales, Balaena mysticetus, is the replacement yield, RY. Information
2002 Poultry Science Association, Inc. POPULATION DYNAMICS OF MANURE
Kaufman, Phillip E.
2002 Poultry Science Association, Inc. POPULATION DYNAMICS OF MANURE INHABITING ARTHROPODS UNDER AN INTEGRATED PEST MANAGEMENT (IPM) PROGRAM IN NEW YORK POULTRY FACILITIES--3 CASE STUDIES P. E. KAUFMAN,1 M, Plant Managers SUMMARY Many arthropods inhabit caged-layer poultry manure, including pest and beneficial
Binary populations and stellar dynamics in young clusters
Vanbeveren, D; Van Bever, J; Mennekens, N
2008-01-01
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, Eta Carinae, Zeta Puppis, Gamma Velorum and WR 140.
Binary Populations and Stellar Dynamics in Young Clusters
NASA Astrophysics Data System (ADS)
Vanbeveren, D.; Belkus, H.; Van Bever, J.; Mennekens, N.
2008-06-01
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.
Amplification Dynamics: Predicting the Effect of HIV on Tuberculosis Outbreaks
Blower, Sally
Amplification Dynamics: Predicting the Effect of HIV on Tuberculosis Outbreaks *Travis C. Porco, U.S.A. Summary: HIV affects the pathogenesis and the transmission of Mycobacterium tuberculosis. We the probability and the expected severity of tuberculosis out- breaks. Our predictions reveal that an HIV epidemic
System dynamics: A Complementary Tool for Predictive microbiology
Gabriela Guadalupe Gastélum-Reynoso; Enrique Palou; Aurelio López-Malo
One of the most important concerns for food industry is safety. Predictive microbiology is the application of mathematical models to describe microbial behavior in order to prevent food spoilage as well as food-borne illness. Because of complexity of microbial behavior and food systems, predictive microbiology presents some limitations. System dynamics could be a useful alternative and complementary tool to model
Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction
McGovern, Amy
Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction Amy McGovern1 dis- covery methods for use on mesoscale weather data. Severe weather phenomena such as tornados, thun, current techniques for predicting severe weather are tied to specific characteristics of the radar systems
Evaluation of predictive accuracy in structural dynamic models
NASA Technical Reports Server (NTRS)
Hasselman, T. K.; Chrostowski, Jon D.
1989-01-01
The evaluation of the predictive accuracy of dynamic models for future large space structures is addressed. Mass and stiffness uncertainties derived from a comparison of analytical and experimental modes are used to evaluate the uncertainty of response predictions based on the analytical model.
DYNAMIC IMAGE SIMULATIONS FOR ADAPTIVE SENSOR PERFORMANCE PREDICTIONS
Kerekes, John
DYNAMIC IMAGE SIMULATIONS FOR ADAPTIVE SENSOR PERFORMANCE PREDICTIONS Michael D. Presnara,b , John. A suite of tools is required for adaptive sensor performance prediction when evaluating design parameter) sensor- reaching radiance imagery that matches real-life conditions can provide insight into sensor
Mutatis Mutandis: Safe and Predictable Dynamic Software Updating
Hicks, Michael
presents Proteus, a core calculus that models dynamic software updating, a service for fixing bugs and adding features to a running program. Proteus permits a program's type structure to change dynamically, to make update success more predictable. We have implemented Proteus for C, and briefly discuss our
Predicting Reading Ability for Bilingual Latino Children Using Dynamic Assessment
ERIC Educational Resources Information Center
Petersen, Douglas B.; Gillam, Ronald B.
2015-01-01
This study investigated the predictive validity of a dynamic assessment designed to evaluate later risk for reading difficulty in bilingual Latino children at risk for language impairment. During kindergarten, 63 bilingual Latino children completed a dynamic assessment nonsense-word recoding task that yielded pretest to posttest gain scores,…
How predictable : modeling rates of change in individuals and populations
Krumme, Katherine
2013-01-01
This thesis develops methodologies to measure rates of change in individual human behavior, and to capture statistical regularities in change at the population level, in three pieces: i) a model of individual rate of change ...
Uncovering epidemiological dynamics in heterogeneous host populations using phylogenetic methods.
Stadler, Tanja; Bonhoeffer, Sebastian
2013-03-19
Host population structure has a major influence on epidemiological dynamics. However, in particular for sexually transmitted diseases, quantitative data on population contact structure are hard to obtain. Here, we introduce a new method that quantifies host population structure based on phylogenetic trees, which are obtained from pathogen genetic sequence data. Our method is based on a maximum-likelihood framework and uses a multi-type branching process, under which each host is assigned to a type (subpopulation). In a simulation study, we show that our method produces accurate parameter estimates for phylogenetic trees in which each tip is assigned to a type, as well for phylogenetic trees in which the type of the tip is unknown. We apply the method to a Latvian HIV-1 dataset, quantifying the impact of the intravenous drug user epidemic on the heterosexual epidemic (known tip states), and identifying superspreader dynamics within the men-having-sex-with-men epidemic (unknown tip states). PMID:23382421
Diversity Waves in Collapse-Driven Population Dynamics
Maslov, Sergei; Sneppen, Kim
2015-01-01
Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe reduction in size of the population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g. by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is characterized by cyclic ‘‘diversity waves’’ triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances have bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies. PMID:26367172
Diversity Waves in Collapse-Driven Population Dynamics.
Maslov, Sergei; Sneppen, Kim
2015-09-01
Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe reduction in size of the population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g. by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is characterized by cyclic ''diversity waves'' triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances have bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies. PMID:26367172
Diversity waves in collapse-driven population dynamics
Maslov, Sergei; Sneppen, Kim
2015-09-14
Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe collapses of the entire population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g.more »by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is cyclic ‘‘diversity waves’’ triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances are characterized by a bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies.« less
The population dynamics of an endemic collectible cactus
NASA Astrophysics Data System (ADS)
Mandujano, María C.; Bravo, Yolotzin; Verhulst, Johannes; Carrillo-Angeles, Israel; Golubov, Jordan
2015-02-01
Astrophytum is one of most collected genera in the cactus family. Around the world several species are maintained in collections and yearly, several plants are taken from their natural habitats. Populations of Astorphytum capricorne are found in the northern Chihuahuan desert, Mexico, and as many endemic cactus species, it has a highly restricted habitat. We conducted a demographic study from 2008 to 2010 of the northern populations found at Cuatro Ciénegas, Mexico. We applied matrix population models, included simulations, life table response experiments and descriptions of the population dynamics to evaluate the current status of the species, and detect key life table stages and demographic processes. Population growth rate decreased in both years and only 4% individual mortality can be attributed to looting, and a massive effort is needed to increase seedling recruitment and reduce adult mortality. The fate of individuals differed between years even having the same annual rainfall mainly in accentuated stasis, retrogression and high mortality in all size classes, which coupled with low seed production, no recruitment and collection of plants are the causes contributing to population decline, and hence, increase the risk in which A. capricorne populations are found. Reintroduction of seedlings and lowering adult mortality are urgently needed to revert the alarming demographic condition of A. capricorne populations.
Population dynamics and climate change: what are the links?
Stephenson, Judith; Newman, Karen; Mayhew, Susannah
2010-06-01
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
Stochastic simulation of structured skin cell population dynamics.
Nakaoka, Shinji; Aihara, Kazuyuki
2013-03-01
The epidermis is the outmost skin tissue. It operates as a first defense system to process inflammatory signals and responds by producing inflammatory mediators that promote the recruitment of immune cells. Various skin diseases such as atopic dermatitis occur as a result of the defect of proper skin barrier function and successive impaired inflammatory responses. The onset of such a skin disease links to the disturbed epidermal homeostasis regulated by appropriate self-renewal and differentiation of epidermal stem cells. The theory of physiologically structured population models provides a versatile framework to formulate mathematical models which describe the growth dynamics of a cell population such as the epidermis. In this paper, we develop an algorithm to implement stochastic simulation for a class of physiologically structured population models. We demonstrate that the developed algorithm is applicable to several cell population models and typical age-structured population models. On the basis of the developed algorithm, we investigate stochastic dynamics of skin cell populations and spread of inflammation. It is revealed that demographic stochasticity can bring considerable impact on the outcome of inflammation spread at the tissue level. PMID:23255068
Modeling structured population dynamics using data from unmarked individuals
Grant, Evan; Zipkin, Elise; Thorson, James T.; See, Kevin; Lynch, Heather J.; Kanno, Yoichiro; Chandler, Richard; Letcher, Benjamin H.; Royle, J. Andrew
2014-01-01
The study of population dynamics requires unbiased, precise estimates of abundance and vital rates that account for the demographic structure inherent in all wildlife and plant populations. Traditionally, these estimates have only been available through approaches that rely on intensive mark–recapture data. We extended recently developed N-mixture models to demonstrate how demographic parameters and abundance can be estimated for structured populations using only stage-structured count data. Our modeling framework can be used to make reliable inferences on abundance as well as recruitment, immigration, stage-specific survival, and detection rates during sampling. We present a range of simulations to illustrate the data requirements, including the number of years and locations necessary for accurate and precise parameter estimates. We apply our modeling framework to a population of northern dusky salamanders (Desmognathus fuscus) in the mid-Atlantic region (USA) and find that the population is unexpectedly declining. Our approach represents a valuable advance in the estimation of population dynamics using multistate data from unmarked individuals and should additionally be useful in the development of integrated models that combine data from intensive (e.g., mark–recapture) and extensive (e.g., counts) data sources.
Identifying interactions among salmon populations from observed dynamics.
Fujiwara, Masami
2008-01-01
A simple direct correlation analysis of individual counts between different populations often fails to characterize the true nature of population interactions; however, the most common data type available for population studies is count data, and one of the most important objectives in population and community ecology is to identify interactions among populations. Here, I examine the dynamics of the spawning abundance of fall-run chinook salmon spawning within the California Central Valley and the Klamath Basin, California, and the Columbia River Basin, Oregon. I analyzed multiple time series from each watershed using a multivariate time-series technique called maximum autocorrelation factor analysis. This technique was used for finding common underlying trends in escapement abundance within each watershed. These trends were further investigated to identify potential resource-mediated interactions among the three groups of salmon. Each group is affected by multiple trends that are likely to be affected by environmental factors. In addition, some of the trends are coherent with each other, and the differences in population dynamics originate from variations in the relative importance of these trends among the three watershed groups. PMID:18376540
Metamodels for Transdisciplinary Analysis of Wildlife Population Dynamics
Lacy, Robert C.; Miller, Philip S.; Nyhus, Philip J.; Pollak, J. P.; Raboy, Becky E.; Zeigler, Sara L.
2013-01-01
Wildlife population models have been criticized for their narrow disciplinary perspective when analyzing complexity in coupled biological – physical – human systems. We describe a “metamodel” approach to species risk assessment when diverse threats act at different spatiotemporal scales, interact in non-linear ways, and are addressed by distinct disciplines. A metamodel links discrete, individual models that depict components of a complex system, governing the flow of information among models and the sequence of simulated events. Each model simulates processes specific to its disciplinary realm while being informed of changes in other metamodel components by accessing common descriptors of the system, populations, and individuals. Interactions among models are revealed as emergent properties of the system. We introduce a new metamodel platform, both to further explain key elements of the metamodel approach and as an example that we hope will facilitate the development of other platforms for implementing metamodels in population biology, species risk assessments, and conservation planning. We present two examples – one exploring the interactions of dispersal in metapopulations and the spread of infectious disease, the other examining predator-prey dynamics – to illustrate how metamodels can reveal complex processes and unexpected patterns when population dynamics are linked to additional extrinsic factors. Metamodels provide a flexible, extensible method for expanding population viability analyses beyond models of isolated population demographics into more complete representations of the external and intrinsic threats that must be understood and managed for species conservation. PMID:24349567
Cohort variation, climate effects and population dynamics in a short-lived lizard.
Le Galliard, Jean François; Marquis, Olivier; Massot, Manuel
2010-11-01
1. Demographic theory and empirical studies indicate that cohort variation in demographic traits has substantial effects on population dynamics of long-lived vertebrates but cohort effects have been poorly investigated in short-lived species. 2. Cohort effects were quantified in the common lizard (Zootoca vivipara Jacquin 1787), a short-lived ectothermic vertebrate, for body size, reproductive traits and age-specific survival with mark-recapture data collected from 1989 to 2005 in two wetlands. We assessed cohort variation and covariation in demographic traits, tested the immediate and delayed effects of climate conditions (temperature and rainfall), and predicted consequences for population growth. 3. Most demographic traits exhibited cohort variation, but this variation was stronger for juvenile growth and survival, sub-adult survival and breeding phenology than for other traits. 4. Cohort variation was partly explained by a web of immediate and delayed effects of climate conditions. Rainfall and temperature influenced distinct life-history traits and the periods of gestation and early juvenile life were critical stages for climate effects. 5. Cohort covariation between demographic traits was usually weak, apart from a negative correlation between juvenile and sub-adult body growth suggesting compensatory responses. An age-structured population model shows that cohort variation influences population growth mainly through direct numerical effects of survival variation early in life. 6. An understanding of cohort effects is necessary to predict critical life stages and climatic determinants of population dynamics, and therefore demographic responses to future climate warming. PMID:20649911
Comparing Dynamical and Stellar Population Mass-to-Light Ratio Estimates
Roelof S. de Jong; Eric Bell
2006-04-19
We investigate the mass-to-light ratios of stellar populations as predicted by stellar population synthesis codes and compare those to dynamical/gravitational measurements. In Bell & de Jong (2001) we showed that population synthesis models predict a tight relation between the color and mass-to-light ratio of a stellar population. The normalization of this relation depends critically on the shape of the stellar IMF at the low-mass end. These faint stars contribute significantly to the mass, but insignificantly to the luminosity and color of a stellar system. In Bell & de Jong (2001) we used rotation curves to normalize the relation, but rotation curves provide only an upper limit to the stellar masses in a system. Here we compare stellar and dynamical masses for a range of stellar systems in order to constrain the mass normalization of stellar population models. We find that the normalization of Bell & de Jong (2001) should be lowered by about 0.05-0.1 dex in M/L. This is consistent with a Kroupa (2001), Chabrier (2003) or a Kennicutt (1983) IMF, but does not leave much room for other unseen components.
Heterogeneous Structure of Stem Cells Dynamics: Statistical Models and Quantitative Predictions
NASA Astrophysics Data System (ADS)
Bogdan, Paul; Deasy, Bridget M.; Gharaibeh, Burhan; Roehrs, Timo; Marculescu, Radu
2014-04-01
Understanding stem cell (SC) population dynamics is essential for developing models that can be used in basic science and medicine, to aid in predicting cells fate. These models can be used as tools e.g. in studying patho-physiological events at the cellular and tissue level, predicting (mal)functions along the developmental course, and personalized regenerative medicine. Using time-lapsed imaging and statistical tools, we show that the dynamics of SC populations involve a heterogeneous structure consisting of multiple sub-population behaviors. Using non-Gaussian statistical approaches, we identify the co-existence of fast and slow dividing subpopulations, and quiescent cells, in stem cells from three species. The mathematical analysis also shows that, instead of developing independently, SCs exhibit a time-dependent fractal behavior as they interact with each other through molecular and tactile signals. These findings suggest that more sophisticated models of SC dynamics should view SC populations as a collective and avoid the simplifying homogeneity assumption by accounting for the presence of more than one dividing sub-population, and their multi-fractal characteristics.
Nonequilibrium Population Dynamics of Phenotype Conversion of Cancer Cells
Zhou, Joseph Xu; Pisco, Angela Oliveira; Qian, Hong; Huang, Sui
2014-01-01
Tumorigenesis is a dynamic biological process that involves distinct cancer cell subpopulations proliferating at different rates and interconverting between them. In this paper we proposed a mathematical framework of population dynamics that considers both distinctive growth rates and intercellular transitions between cancer cell populations. Our mathematical framework showed that both growth and transition influence the ratio of cancer cell subpopulations but the latter is more significant. We derived the condition that different cancer cell types can maintain distinctive subpopulations and we also explain why there always exists a stable fixed ratio after cell sorting based on putative surface markers. The cell fraction ratio can be shifted by changing either the growth rates of the subpopulations (Darwinism selection) or by environment-instructed transitions (Lamarckism induction). This insight can help us to understand the dynamics of the heterogeneity of cancer cells and lead us to new strategies to overcome cancer drug resistance. PMID:25438251
Evolutionary dynamics of group interactions on structured populations: a review
Perc, Matjaž; Gómez-Gardeńes, Jesús; Szolnoki, Attila; Floría, Luis M.; Moreno, Yamir
2013-01-01
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
Noest, André J; van Wezel, Richard J A
2012-02-01
At the onset of visually ambiguous or conflicting stimuli, our visual system quickly 'chooses' one of the possible percepts. Interrupted presentation of the same stimuli has revealed that each percept-choice depends strongly on the history of previous choices and the duration of the interruptions. Recent psychophysics and modeling has discovered increasingly rich dynamical structure in such percept-choice sequences, and explained or predicted these patterns in terms of simple neural mechanisms: fast cross-inhibition and slow shunting adaptation that also causes a near-threshold facilitatory effect. However, we still lack a clear understanding of the dynamical interactions between two distinct, temporally interleaved, percept-choice sequences-a type of experiment that probes which feature-level neural network connectivity and dynamics allow the visual system to resolve the vast ambiguity of everyday vision. Here, we fill this gap. We first show that a simple column-structured neural network captures the known phenomenology, and then identify and analyze the crucial underlying mechanism via two stages of model-reduction: A 6-population reduction shows how temporally well-separated sequences become coupled via adaptation in neurons that are shared between the populations driven by either of the two sequences. The essential dynamics can then be reduced further, to a set of iterated adaptation-maps. This enables detailed analysis, resulting in the prediction of phase-diagrams of possible sequence-pair patterns and their response to perturbations. These predictions invite a variety of future experiments. PMID:21717181
Life history and environmental influences on population dynamics in sockeye salmon
Reynolds, John D.
ARTICLE Life history and environmental influences on population dynamics in sockeye salmon Douglas, the environment, and population dynamics is a central goal in ecology. We compared 15 populations of sockeye traits and environmental conditions in explaining variation in population dynamics. We used life history
Prediction of competitive microbial growth in mixed culture at dynamic temperature patterns.
Fujikawa, Hiroshi; Sakha, Mohammad Z
2014-01-01
A novel competition model developed with the new logistic model and the Lotka-Volterra model successfully predicted the growth of bacteria in mixed culture using the mesophiles Staphylococcus aureus, Escherichia coli, and Salmonella at a constant temperature in our previous studies. In this study, we further studied the prediction of the growth of those bacteria in mixed culture at dynamic temperatures with various initial populations with the competition model. First, we studied the growth kinetics of the species in a monoculture at various constant temperatures ranging from 16? to 32?. With the analyzed data in the monoculture, we then examined the prediction of bacterial growth in mixed culture with two and three species. The growth of the bacteria in the mixed culture at dynamic temperatures was successfully predicted with the model. The residuals between the observed and predicted populations at the data points were <0.5 log at most points, being 83.3% and 84.2% for the two-species mixture and the three-species mixture, respectively. The present study showed that the model could be applied to the competitive growth in mixed culture at dynamic temperature patterns. PMID:25252643
The effect of EIF dynamics on the cryopreservation process of a size distributed cell population.
Fadda, S; Briesen, H; Cincotti, A
2011-06-01
Typical mathematical modeling of cryopreservation of cell suspensions assumes a thermodynamic equilibrium between the ice and liquid water in the extracellular solution. This work investigates the validity of this assumption by introducing a population balance approach for dynamic extracellular ice formation (EIF) in the absence of any cryo-protectant agent (CPA). The population balance model reflects nucleation and diffusion-limited growth in the suspending solution whose driving forces are evaluated in the relevant phase diagram. This population balance description of the extracellular compartment has been coupled to a model recently proposed in the literature [Fadda et al., AIChE Journal, 56, 2173-2185, (2010)], which is capable of quantitatively describing and predicting internal ice formation (IIF) inside the cells. The cells are characterized by a size distribution (i.e. through another population balance), thus overcoming the classic view of a population of identically sized cells. From the comparison of the system behavior in terms of the dynamics of the cell size distribution it can be concluded that the assumption of a thermodynamic equilibrium in the extracellular compartment is not always justified. Depending on the cooling rate, the dynamics of EIF needs to be considered. PMID:21463613
Comprehensive Assessment and Mathematical Modeling of T Cell Population Dynamics and Homeostasis1
de Boer, Rob J.
Comprehensive Assessment and Mathematical Modeling of T Cell Population Dynamics and Homeostasis1 current view of T cell differentiation and population dynamics is assembled from pieces of data obtained for the quantitative aspects of cell dynamics. In addition, the temporal parameters of the population dynamics
Hyper-Learning for Population-Based Incremental Learning in Dynamic Environments
Yang, Shengxiang
Hyper-Learning for Population-Based Incremental Learning in Dynamic Environments Shengxiang Yang in dynamic environments, especially in cyclic dynamic environments. The third type uses multi-population to the fourth type of approaches for EAs in dynamic environments. The population-based incremental learning
Bernard, Samuel
From Single-Cell Genetic Architecture to Cell Population Dynamics: Quantitatively Decomposing, Texas ABSTRACT Phenotypic cell-to-cell variability or cell population heterogeneity originates from two fundamentally different sources: unequal partitioning of cellular material at cell division and stochastic
Russell, Tanya L.; Lwetoijera, Dickson W.; Knols, Bart G. J.; Takken, Willem; Killeen, Gerry F.; Ferguson, Heather M.
2011-01-01
Understanding the endogenous factors that drive the population dynamics of malaria mosquitoes will facilitate more accurate predictions about vector control effectiveness and our ability to destabilize the growth of either low- or high-density insect populations. We assessed whether variation in phenotypic traits predict the dynamics of Anopheles gambiae sensu lato mosquitoes, the most important vectors of human malaria. Anopheles gambiae dynamics were monitored over a six-month period of seasonal growth and decline. The population exhibited density-dependent feedback, with the carrying capacity being modified by rainfall (97% wAICc support). The individual phenotypic expression of the maternal (p = 0.0001) and current (p = 0.040) body size positively influenced population growth. Our field-based evidence uniquely demonstrates that individual fitness can have population-level impacts and, furthermore, can mitigate the impact of exogenous drivers (e.g. rainfall) in species whose reproduction depends upon it. Once frontline interventions have suppressed mosquito densities, attempts to eliminate malaria with supplementary vector control tools may be attenuated by increased population growth and individual fitness. PMID:21389034
Huxman, Travis E; Kimball, Sarah; Angert, Amy L; Gremer, Jennifer R; Barron-Gafford, Greg A; Venable, D Lawrence
2013-07-01
Global change requires plant ecologists to predict future states of biological diversity to aid the management of natural communities, thus introducing a number of significant challenges. One major challenge is considering how the many interacting features of biological systems, including ecophysiological processes, plant life histories, and species interactions, relate to performance in the face of a changing environment. We have employed a functional trait approach to understand the individual, population, and community dynamics of a model system of Sonoran Desert winter annual plants. We have used a comprehensive approach that connects physiological ecology and comparative biology to population and community dynamics, while emphasizing both ecological and evolutionary processes. This approach has led to a fairly robust understanding of past and contemporary dynamics in response to changes in climate. In this community, there is striking variation in physiological and demographic responses to both precipitation and temperature that is described by a trade-off between water-use efficiency (WUE) and relative growth rate (RGR). This community-wide trade-off predicts both the demographic and life history variation that contribute to species coexistence. Our framework has provided a mechanistic explanation to the recent warming, drying, and climate variability that has driven a surprising shift in these communities: cold-adapted species with more buffered population dynamics have increased in relative abundance. These types of comprehensive approaches that acknowledge the hierarchical nature of biology may be especially useful in aiding prediction. The emerging, novel and nonstationary climate constrains our use of simplistic statistical representations of past plant behavior in predicting the future, without understanding the mechanistic basis of change. PMID:23838034
Coupling in goshawk and grouse population dynamics in Finland.
Tornberg, Risto; Lindén, Andreas; Byholm, Patrik; Ranta, Esa; Valkama, Jari; Helle, Pekka; Lindén, Harto
2013-04-01
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
Population Dynamics of the Stationary Phase Utilizing the ARGOS Method
NASA Astrophysics Data System (ADS)
Algarni, S.; Charest, A. J.; Iannacchione, G. S.
2015-03-01
The Area Recorded Generalized Optical Scattering (ARGOS) approach to light scattering employs large image capture array allowing for a well-defined geometry in which images may be manipulated to extract structure with intensity at a specific scattering wave vector (I(q)) and dynamics with intensity at a specific scattering wave vector over time (I (q,t)). The ARGOS method provides morphological dynamics noninvasively over a long time period and allows for a variety of aqueous conditions. This is important because traditional growth models do not provide for conditions similar to the natural environment. The present study found that the population dynamics of bacteria do not follow a traditional growth model and that the ARGOS method allowed for the observation of bacterial changes in terms of individual particles and population dynamics in real time. The observations of relative total intensity suggest that there is no stationary phase and that the bacterial population demonstrates sinusoidal type patterns consistently subsequent to the log phase growth. These observation were compared to shape changes by modeling fractal dimension and size changes by modeling effective radius.
Composite forces shape population dynamics of copepod crustaceans.
Twombly, S; Wang, Guiming; Hobbs, N Thompson
2007-03-01
Understanding the processes that control species abundance and distribution is a major challenge in ecology, yet for a large number of potentially important organisms, we know little about the biotic and abiotic factors that influence population size. One group of aquatic organisms that defies traditional demographic analyses is the Crustacea, particularly those with complex life cycles. We used likelihood techniques and information theoretics to evaluate a suite of models representing alternative hypotheses on factors controlling the abundance of two copepod crustaceans in a small, tropical floodplain lake. Quantitative zooplankton samples were collected at three stations in a Venezuelan floodplain lake from June through December 1984; the average sampling interval was two days. We constructed a series of models with stage structure that incorporated six biotic and abiotic covariates in various combinations to account for temporal changes in abundance of these target species and in their population growth rates. Our analysis produced several novel insights into copepod population dynamics. We found that multiple forces affected the abundance of particular stages, that these factors differed between species as well as among stages within each species, and that biotic processes had the largest effects on copepod population dynamics. Density dependence had a large effect on the survival of Oithona amazonica copepodites and on population growth rate of Diaptomus negrensis. PMID:17503594
Predicting Online Harassment Victimization among a Juvenile Population
ERIC Educational Resources Information Center
Bossler, Adam M.; Holt, Thomas J.; May, David C.
2012-01-01
Online harassment can consist of threatening, worrisome, emotionally hurtful, or sexual messages delivered via an electronic medium that can lead victims to feel fear or distress much like real-world harassment and stalking. This activity is especially prevalent among middle and high school populations who frequently use technology as a means to…
Dynamic Predictions of Semi-Arid Land Cover Change
NASA Astrophysics Data System (ADS)
Foster-Wittig, T. A.
2011-12-01
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
Modeling Tools Predict Flow in Fluid Dynamics
NASA Technical Reports Server (NTRS)
2010-01-01
"Because rocket engines operate under extreme temperature and pressure, they present a unique challenge to designers who must test and simulate the technology. To this end, CRAFT Tech Inc., of Pipersville, Pennsylvania, won Small Business Innovation Research (SBIR) contracts from Marshall Space Flight Center to develop software to simulate cryogenic fluid flows and related phenomena. CRAFT Tech enhanced its CRUNCH CFD (computational fluid dynamics) software to simulate phenomena in various liquid propulsion components and systems. Today, both government and industry clients in the aerospace, utilities, and petrochemical industries use the software for analyzing existing systems as well as designing new ones."
Seasonally modulated evolutionary dynamics of finite populations: metastable Floquet states
Tkachenko, Olena; Denisov, Sergey; Zaburdaev, Vasily; Hänggi, Peter
2015-01-01
Mating strategies of many biological species are season-dependent. In evolutionary game theory this can be modelled with two finite opposite-sex populations whose members are playing against each other following rules which are modulated in time. By combining Floquet theory and the concept of quasi-stationary distributions, we show the existence of metastable time-periodic states in the stochastic evolution of the populations. These long-lived states describe a fraction of players that are still modifying their strategies and exhibit dynamics beyond the reach of mean-field theory.
Predicting and Improving Text Readability for Target Reader Populations
, applications for target users such as deaf students, second language learners and low literacy adults users (e.g., hearing-impaired readers); (ii) Predicting the reading level of text, where approaches vary from psycho-linguistic measurements (e.g. reading time) to standard readability measures applied
Predictive markers in calpastatin for tenderness in commercial pig populations
Technology Transfer Automated Retrieval System (TEKTRAN)
The identification of predictive DNA markers for pork quality would allow U.S. pork producers and breeders to more quickly and efficiently select genetically superior animals for production of consistent, high quality meat. Genome scans have identified QTL for tenderness on pig chromosome 2 which ha...
Exploring iris colour prediction and ancestry inference in admixed populations of South America.
Freire-Aradas, A; Ruiz, Y; Phillips, C; Marońas, O; Söchtig, J; Tato, A Gómez; Dios, J Álvarez; de Cal, M Casares; Silbiger, V N; Luchessi, A D; Luchessi, A D; Chiurillo, M A; Carracedo, Á; Lareu, M V
2014-11-01
New DNA-based predictive tests for physical characteristics and inference of ancestry are highly informative tools that are being increasingly used in forensic genetic analysis. Two eye colour prediction models: a Bayesian classifier - Snipper and a multinomial logistic regression (MLR) system for the Irisplex assay, have been described for the analysis of unadmixed European populations. Since multiple SNPs in combination contribute in varying degrees to eye colour predictability in Europeans, it is likely that these predictive tests will perform in different ways amongst admixed populations that have European co-ancestry, compared to unadmixed Europeans. In this study we examined 99 individuals from two admixed South American populations comparing eye colour versus ancestry in order to reveal a direct correlation of light eye colour phenotypes with European co-ancestry in admixed individuals. Additionally, eye colour prediction following six prediction models, using varying numbers of SNPs and based on Snipper and MLR, were applied to the study populations. Furthermore, patterns of eye colour prediction have been inferred for a set of publicly available admixed and globally distributed populations from the HGDP-CEPH panel and 1000 Genomes databases with a special emphasis on admixed American populations similar to those of the study samples. PMID:25051225
Berthier, K; Langlais, M; Auger, P; Pontier, D
2000-01-01
Feline panleucopenia virus (FPLV) was introduced in 1977 on Marion Island (in the southern Indian Ocean) with the aim of eradicating the cat population and provoked a huge decrease in the host population within six years. The virus can be transmitted either directly through contacts between infected and healthy cats or indirectly between a healthy cat and the contaminated environment: a specific feature of the virus is its high rate of survival outside the host. In this paper, a model was designed in order to take these two modes of transmission into account. The results showed that a mass-action incidence assumption was more appropriate than a proportionate mixing one in describing the dynamics of direct transmission. Under certain conditions the virus was able to control the host population at a low density. The indirect transmission acted as a reservoir supplying the host population with a low but sufficient density of infected individuals which allowed the virus to persist. The dynamics of the infection were more affected by the demographic parameters of the healthy hosts than by the epidemiological ones. Thus, demographic parameters should be precisely measured in field studies in order to obtain accurate predictions. The predicted results of our model were in good agreement with observations. PMID:11416908
Non-linearity and heterogeneity in modeling of population dynamics.
Karev, Georgy P
2014-12-01
The study of population growth reveals that the behaviors that follow the power law appear in numerous biological, demographical, ecological, physical and other contexts. Parabolic models appear to be realistic approximations of real-life replicator systems, while hyperbolic models were successfully applied to problems of global demography and appear relevant in quasispecies and hypercycle modeling. Nevertheless, it is not always clear why non-exponential growth is observed empirically and what possible origins of the non-exponential models are. In this paper the power equation is considered within the frameworks of inhomogeneous population models; it is proven that any power equation describes the total population size of a frequency-dependent model with Gamma-distributed Malthusian parameter. Additionally, any super-exponential equation describes the dynamics of inhomogeneous Malthusian density-dependent population model. All statistical characteristics of the underlying inhomogeneous models are computed explicitly. The results of this analysis show that population heterogeneity can be a reasonable explanation for power law accurately describing total population growth. PMID:25262656
Intrinsic chaos and external noise in population dynamics
J. A. Gonzalez; L. Trujillo; A. Escalante
2003-05-21
We address the problem of the relative importance of the intrinsic chaos and the external noise in determining the complexity of population dynamics. We use a recently proposed method for studying the complexity of nonlinear random dynamical systems. The new measure of complexity is defined in terms of the average number of bits per time-unit necessary to specify the sequence generated by the system. This measure coincides with the rate of divergence of nearby trajectories under two different realizations of the noise. In particular, we show that the complexity of a nonlinear time-series model constructed from sheep populations comes completely from the environmental variations. However, in other situations, intrinsic chaos can be the crucial factor. This method can be applied to many other systems in biology and physics.
Prediction-based dynamic load-sharing heuristics
NASA Technical Reports Server (NTRS)
Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.
1993-01-01
The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.
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...
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...
Dynamic energy budget theory and population ecology: lessons from Daphnia
Nisbet, Roger M.; McCauley, Edward; Johnson, Leah R.
2010-01-01
Dynamic energy budget (DEB) theory offers a perspective on population ecology whose starting point is energy utilization by, and homeostasis within, individual organisms. It is natural to ask what it adds to the existing large body of individual-based ecological theory. We approach this question pragmatically—through detailed study of the individual physiology and population dynamics of the zooplankter Daphnia and its algal food. Standard DEB theory uses several state variables to characterize the state of an individual organism, thereby making the transition to population dynamics technically challenging, while ecologists demand maximally simple models that can be used in multi-scale modelling. We demonstrate that simpler representations of individual bioenergetics with a single state variable (size), and two life stages (juveniles and adults), contain sufficient detail on mass and energy budgets to yield good fits to data on growth, maturation and reproduction of individual Daphnia in response to food availability. The same simple representations of bioenergetics describe some features of Daphnia mortality, including enhanced mortality at low food that is not explicitly incorporated in the standard DEB model. Size-structured, population models incorporating this additional mortality component resolve some long-standing questions on stability and population cycles in Daphnia. We conclude that a bioenergetic model serving solely as a ‘regression’ connecting organismal performance to the history of its environment can rest on simpler representations than those of standard DEB. But there are associated costs with such pragmatism, notably loss of connection to theory describing interspecific variation in physiological rates. The latter is an important issue, as the type of detailed study reported here can only be performed for a handful of species. PMID:20921052
Dynamics of an oligosporous actinomycete population in chernozem soil
G. M. Zenova; N. V. Mikhailova; D. G. Zvyagintsev
2000-01-01
Investigation of the dynamics of an oligosporous actinomycete population in chernozem soil in the course of succession induced\\u000a by soil wetting allowed us to reveal the time intervals and conditions optimal for the isolation of particular oligosporous\\u000a actinomycetes. Saccharopolysporas and microbisporas proved to be best isolated in the early and late stages of succession,\\u000a whereas actinomycetes of the subgroupActinomadura and
Development of paradigms for the dynamics of structured populations
Not Available
1994-10-01
This is a technical progress report on the dynamics of predator-prey systems in a patchy environment. A new phenomenon that might contribute to outbreaks in systems of discrete patches has been determined using a discrete time model with both spatial and age structure. A model for a single species in a patchy environment with migration, local population growth and disasters with in patches has been formulated and a brief description is included.
Inferring unobserved multistrain epidemic sub-populations using synchronization dynamics
Eric Forgoston; Leah B. Shaw; Ira B. Schwartz
2014-10-30
A new method is proposed to infer unobserved epidemic sub-populations by exploiting the synchronization properties of multistrain epidemic models. A model for dengue fever is driven by simulated data from secondary infective populations. Primary infective populations in the driven system synchronize to the correct values from the driver system. Most hospital cases of dengue are secondary infections, so this method provides a way to deduce unobserved primary infection levels. We derive center manifold equations that relate the driven system to the driver system and thus motivate the use of synchronization to predict unobserved primary infectives. Synchronization stability between primary and secondary infections is demonstrated through numerical measurements of conditional Lyapunov exponents and through time series simulations.
Network Evolution Induced by the Dynamical Rules of Two Populations
Platini, T
2010-01-01
We study the dynamical properties of a finite dynamical network composed of two interacting populations, namely; extrovert ($a$) and introvert ($b$). In our model, each group is characterized by its size ($N_a$ and $N_b$) and preferred degree ($\\kappa_a$ and $\\kappa_b\\ll\\kappa_a$). The network dynamics is governed by the competing microscopic rules of each population that consist of the creation and destruction of links. Starting from an unconnected network, we give a detailed analysis of the mean field approach which is compared to Monte Carlo simulation data. The time evolution of the restricted degrees $\\moyenne{k_{bb}}$ and $\\moyenne{k_{ab}}$ presents three time regimes and a non monotonic behavior well captured by our theory. Surprisingly, when the population size are equal $N_a=N_b$, the ratio of the restricted degree $\\theta_0=\\moyenne{k_{ab}}/\\moyenne{k_{bb}}$ appears to be an integer in the asymptotic limits of the three time regimes. For early times (defined by $t
VCGDB: a dynamic genome database of the Chinese population
2014-01-01
Background The data released by the 1000 Genomes Project contain an increasing number of genome sequences from different nations and populations with a large number of genetic variations. As a result, the focus of human genome studies is changing from single and static to complex and dynamic. The currently available human reference genome (GRCh37) is based on sequencing data from 13 anonymous Caucasian volunteers, which might limit the scope of genomics, transcriptomics, epigenetics, and genome wide association studies. Description We used the massive amount of sequencing data published by the 1000 Genomes Project Consortium to construct the Virtual Chinese Genome Database (VCGDB), a dynamic genome database of the Chinese population based on the whole genome sequencing data of 194 individuals. VCGDB provides dynamic genomic information, which contains 35 million single nucleotide variations (SNVs), 0.5 million insertions/deletions (indels), and 29 million rare variations, together with genomic annotation information. VCGDB also provides a highly interactive user-friendly virtual Chinese genome browser (VCGBrowser) with functions like seamless zooming and real-time searching. In addition, we have established three population-specific consensus Chinese reference genomes that are compatible with mainstream alignment software. Conclusions VCGDB offers a feasible strategy for processing big data to keep pace with the biological data explosion by providing a robust resource for genomics studies; in particular, studies aimed at finding regions of the genome associated with diseases. PMID:24708222
Interacting trophic forcing and the population dynamics of herring.
Lindegren, Martin; Ostman, Orjan; Gĺrdmark, Anna
2011-07-01
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
Albers, D. J.; Hripcsak, George; Schmidt, Michael
2012-01-01
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. PMID:23272040
Predicting reading ability for bilingual Latino children using dynamic assessment.
Petersen, Douglas B; Gillam, Ronald B
2015-01-01
This study investigated the predictive validity of a dynamic assessment designed to evaluate later risk for reading difficulty in bilingual Latino children at risk for language impairment. During kindergarten, 63 bilingual Latino children completed a dynamic assessment nonsense-word recoding task that yielded pretest to posttest gain scores, residuum gain scores, and modifiability scores. At the end of first grade, the same participants completed criterion reading measures of word identification, decoding, and reading fluency. The dynamic assessment yielded high classification accuracy, with sensitivity and specificity at or above 80% for all three criterion reading measures, including 100% sensitivity for two out of the three first-grade measures. The dynamic assessment used in this study has promise as a means for predicting first-grade word-level reading ability in Latino, bilingual children. PMID:23629729
Population dynamics of Microtus pennsylvanicus in corridor-linked patches
Coffman, C.J.; Nichols, J.D.; Pollock, K.H.
2001-01-01
Corridors have become a key issue in the discussion of conservation planning: however, few empirical data exist on the use of corridors and their effects on population dynamics. The objective of this replicated, population level, capture-re-capture experiment on meadow voles was to estimate and compare population characteristics of voles between (1) corridor-linked fragments, (2) isolated or non-linked fragments, and (3) unfragmented areas. We conducted two field experiments involving 22600 captures of 5700 individuals. In the first, the maintained corridor study, corridors were maintained at the time of fragmentation, and in the second, the constructed corridor study, we constructed corridors between patches that had been fragmented for some period of time. We applied multistate capture-recapture models with the robust design to estimate adult movement and survival rates, population size, temporal variation in population size, recruitment, and juvenile survival rates. Movement rates increased to a greater extent on constructed corridor-linked grids than on the unfragmented or non-linked fragmented grids between the pre- and post-treatment periods. We found significant differences in local survival on the treated (corridor-linked) grids compared to survival on the fragmented and unfragmented grids between the pre- and post-treatment periods. We found no clear pattern of treatment effects on population size or recruitment in either study. However, in both studies, we found that unfragmented grids were more stable than the fragmented grids based on lower temporal variability in population size. To our knowledge, this is the first experimental study demonstrating that corridors constructed between existing fragmented populations can indeed cause increases in movement and associated changes in demography, supporting the use of constructed corridors for this purpose in conservation biology.
Drivers of waterfowl population dynamics: from teal to swans
Koons, David N.; Gunnarsson, Gunnar; Schmutz, Joel A.; Rotella, Jay J.
2014-01-01
Waterfowl are among the best studied and most extensively monitored species in the world. Given their global importance for sport and subsistence hunting, viewing and ecosystem functioning, great effort has been devoted since the middle part of the 20th century to understanding both the environmental and demographic mechanisms that influence waterfowl population and community dynamics. Here we use comparative approaches to summarise and contrast our understanding ofwaterfowl population dynamics across species as short-lived as the teal Anas discors and A.crecca to those such as the swans Cygnus sp. which have long life-spans. Specifically, we focus on population responses to vital rate perturbations across life history strategies, discuss bottom-up and top-down responses of waterfowlpopulations to global change, and summarise our current understanding of density dependence across waterfowl species. We close by identifying research needs and highlight ways to overcome the challenges of sustainably managing waterfowl populations in the 21st century.
Cumulative compressibility effects on population dynamics in turbulent flows
Prasad Perlekar; Roberto Benzi; David R. Nelson; Federico Toschi
2011-09-19
Bacteria and plankton populations living in oceans and lakes reproduce and die under the in- fluence of turbulent currents. Turbulent transport interacts in a complex way with the dynamics of populations because the typical reproduction time of microorganism is within the inertial range of turbulent time scales. In the present manuscript we quantitatively investigate the effect of flow compressibility on the dynamics of populations. While a small compressibility can be induced by several physical mechanisms, like density mismatch or the finite size of microorganisms with respect to the fluid turbulence, its effect on the the carrying capacity of the ecosystem can be dramatic. We report, for the first time, how a small compressibility can produce a sizeable reduction in the carrying capacity, due to an integrated effect made possible by the long replication times of the organisms with respect to turbulent time scales. A full statistical quantification of the fluctuations of population concentration field leads to data collapse over a broad range in parameter space.
Fish population dynamics in a seasonally varying wetland
DeAngelis, Donald L.; Trexler, Joel C.; Cosner, Chris; Obaza, Adam; Jopp, Fred
2010-01-01
Small fishes in seasonally flooded environments such as the Everglades are capable of spreading into newly flooded areas and building up substantial biomass. Passive drift cannot account for the rapidity of observed population expansions. To test the reaction-diffusion mechanism for spread of the fish, we estimated their diffusion coefficient and applied a reaction-diffusion model. This mechanism was also too weak to account for the spatial dynamics. Two other hypotheses were tested through modeling. The first--the 'refuge mechanism--hypothesizes that small remnant populations of small fishes survive the dry season in small permanent bodies of water (refugia), sites where the water level is otherwise below the surface. The second mechanism, which we call the 'dynamic ideal free distribution mechanism' is that consumption by the fish creates a prey density gradient and that fish taxis along this gradient can lead to rapid population expansion in space. We examined the two alternatives and concluded that although refugia may play an important role in recolonization by the fish population during reflooding, only the second, taxis in the direction of the flooding front, seems capable of matching empirical observations. This study has important implications for management of wetlands, as fish biomass is an essential support of higher trophic levels.
Nonlinear dynamics and predictability in the atmospheric sciences
M. Ghil; M. Kimoto; J. D. Neelin
1991-01-01
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
Nonlinear dynamics and predictability in the atmospheric sciences
Ghil, M.; Kimoto, M.; Neelin, J.D. )
1991-01-01
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.
NASA Technical Reports Server (NTRS)
Norby, W. P.; Ladd, J. A.; Yuhas, A. J.
1996-01-01
A procedure has been developed for predicting peak dynamic inlet distortion. This procedure combines Computational Fluid Dynamics (CFD) and distortion synthesis analysis to obtain a prediction of peak dynamic distortion intensity and the associated instantaneous total pressure pattern. A prediction of the steady state total pressure pattern at the Aerodynamic Interface Plane is first obtained using an appropriate CFD flow solver. A corresponding inlet turbulence pattern is obtained from the CFD solution via a correlation linking root mean square (RMS) inlet turbulence to a formulation of several CFD parameters representative of flow turbulence intensity. This correlation was derived using flight data obtained from the NASA High Alpha Research Vehicle flight test program and several CFD solutions at conditions matching the flight test data. A distortion synthesis analysis is then performed on the predicted steady state total pressure and RMS turbulence patterns to yield a predicted value of dynamic distortion intensity and the associated instantaneous total pressure pattern.
Bull, James J.; Gill, Jason J.
2014-01-01
The use of bacteriophages as antibacterial agents is being actively researched on a global scale. Typically, the phages used are isolated from the wild by plating on the bacteria of interest, and a far larger set of candidate phages is often available than can be used in any application. When an excess of phages is available, how should the best phages be identified? Here we consider phage-bacterial population dynamics as a basis for evaluating and predicting phage success. A central question is whether the innate dynamical properties of phages are the determinants of success, or instead, whether extrinsic, indirect effects can be responsible. We address the dynamical perspective, motivated in part by the absence of dynamics in previously suggested principles of phage therapy. Current mathematical models of bacterial-phage dynamics do not capture the realities of in vivo dynamics, nor is this likely to change, but they do give insight to qualitative properties that may be generalizable. In particular, phage adsorption rate may be critical to treatment success, so understanding the effects of the in vivo environment on host availability may allow prediction of useful phages prior to in vivo experimentation. Principles for predicting efficacy may be derived by developing a greater understanding of the in vivo system, or such principles could be determined empirically by comparing phages with known differences in their dynamic properties. The comparative approach promises to be a powerful method of discovering the key to phage success. We offer five recommendations for future study: (i) compare phages differing in treatment efficacy to identify the phage properties associated with success, (ii) assay dynamics in vivo, (iii) understand mechanisms of bacterial escape from phages, (iv) test phages in model infections that are relevant to the intended clinical applications, and (v) develop new classes of models for phage growth in spatially heterogeneous environments. PMID:25477869
A novel dynamic update framework for epileptic seizure prediction.
Han, Min; Ge, Sunan; Wang, Minghui; Hong, Xiaojun; Han, Jie
2014-01-01
Epileptic seizure prediction is a difficult problem in clinical applications, and it has the potential to significantly improve the patients' daily lives whose seizures cannot be controlled by either drugs or surgery. However, most current studies of epileptic seizure prediction focus on high sensitivity and low false-positive rate only and lack the flexibility for a variety of epileptic seizures and patients' physical conditions. Therefore, a novel dynamic update framework for epileptic seizure prediction is proposed in this paper. In this framework, two basic sample pools are constructed and updated dynamically. Furthermore, the prediction model can be updated to be the most appropriate one for the prediction of seizures' arrival. Mahalanobis distance is introduced in this part to solve the problem of side information, measuring the distance between two data sets. In addition, a multichannel feature extraction method based on Hilbert-Huang transform and extreme learning machine is utilized to extract the features of a patient's preseizure state against the normal state. At last, a dynamic update epileptic seizure prediction system is built up. Simulations on Freiburg database show that the proposed system has a better performance than the one without update. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices. PMID:25050381
A Novel Dynamic Update Framework for Epileptic Seizure Prediction
Wang, Minghui; Hong, Xiaojun; Han, Jie
2014-01-01
Epileptic seizure prediction is a difficult problem in clinical applications, and it has the potential to significantly improve the patients' daily lives whose seizures cannot be controlled by either drugs or surgery. However, most current studies of epileptic seizure prediction focus on high sensitivity and low false-positive rate only and lack the flexibility for a variety of epileptic seizures and patients' physical conditions. Therefore, a novel dynamic update framework for epileptic seizure prediction is proposed in this paper. In this framework, two basic sample pools are constructed and updated dynamically. Furthermore, the prediction model can be updated to be the most appropriate one for the prediction of seizures' arrival. Mahalanobis distance is introduced in this part to solve the problem of side information, measuring the distance between two data sets. In addition, a multichannel feature extraction method based on Hilbert-Huang transform and extreme learning machine is utilized to extract the features of a patient's preseizure state against the normal state. At last, a dynamic update epileptic seizure prediction system is built up. Simulations on Freiburg database show that the proposed system has a better performance than the one without update. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices. PMID:25050381
Technology Transfer Automated Retrieval System (TEKTRAN)
Host-plant quality influences insect population dynamics and the timing and extent of insect dispersal. An understanding of how these factors influence Homalodisca vitripennis, the glassy-winged sharpshooters’ development and movement is needed to better predict the spread of Pierce’s Disease (PD) ...
Survival and Population Dynamics of the Marabou Stork in an Isolated Population, Swaziland
Monadjem, Ara; Kane, Adam; Botha, Andre; Dalton, Desire; Kotze, Antoinette
2012-01-01
Investigating the ecology of long lived birds is particularly challenging owing to the time scales involved. Here an analysis is presented of a long term study of the survival and population dynamics of the marabou stork (Leptoptilos crumeniferus), a wide ranging scavenging bird from Sub-Saharan Africa. Using resightings data of tagged nestlings and free flying birds we show that the stork population can be divided into three general life stages with unique survival probabilities and fecundities. Fecundity of the storks is inversely related to rainfall during their breeding season. Corroborative evidence for a metapopulation structure is discussed highlighting the impact of the Swaziland birds on the ecology of the species in the broader region. The importance of tag loss or illegibility over time is highlighted. Clearly, any attempt at conserving a species will require a detailed understanding of its population structure, of the sort examined here. PMID:23029517
Phase Space Formulation of Population Dynamics in Ecology
Jesus Martinez-Linares
2013-04-08
A phase space theory for population dynamics in Ecology is presented. This theory applies for a certain class of dynamical systems, that will be called M-systems, for which a conserved quantity, the M-function, can be defined in phase space. This M-function is the generator of time displacements and contains all the dynamical information of the system. In this sense the M-function plays the role of the hamiltonian function for mechanical systems. In analogy with Hamilton theory we derive equations of motion as derivatives over the resource function in phase space. A M-bracket is defined which allows one to perform a geometrical approach in analogy to Poisson bracket of hamiltonian systems. We show that the equations of motion can be derived from a variational principle over a functional J of the trajectories. This functional plays for M-systems the same role than the action S for hamiltonian systems. Finally, three important systems in population dynamics, namely, Lotka-Volterra, self-feeding and logistic evolution, are shown to be M-systems.
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...
Aphid individual performance may not predict population responses to elevated CO2 or O3
Aphid individual performance may not predict population responses to elevated CO2 or O3 C A R O L I of the aphid Cepegillettea betulaefoliae Granovsky feeding on paper birch (Betula papyrifera Marsh.). In Year 1 surveyed natural aphid, predator and parasitoid populations throughout the growing season. Aphid growth
Arnan, Xavier; Molowny-Horas, Roberto; Rodrigo, Anselm; Retana, Javier
2012-01-01
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
Wildhaber, Mark L.; Wikle, Christopher K.; Anderson, Christopher J.; Franz, Kristie J.; Moran, Edward H.; Dey, Rima
2012-01-01
Climate change operates over a broad range of spatial and temporal scales. Understanding its effects on ecosystems requires multi-scale models. For understanding effects on fish populations of riverine ecosystems, climate predicted by coarse-resolution Global Climate Models must be downscaled to Regional Climate Models to watersheds to river hydrology to population response. An additional challenge is quantifying sources of uncertainty given the highly nonlinear nature of interactions between climate variables and community level processes. We present a modeling approach for understanding and accomodating uncertainty by applying multi-scale climate models and a hierarchical Bayesian modeling framework to Midwest fish population dynamics and by linking models for system components together by formal rules of probability. The proposed hierarchical modeling approach will account for sources of uncertainty in forecasts of community or population response. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. This understanding will aid evaluation of management options for coping with global climate change. In our initial analyses, we found that predicted pallid sturgeon population responses were dependent on the climate scenario considered.
Anatomy of a chaotic attractor: Subtle model-predicted patterns revealed in population data
Aaron A. King; R. F. Costantino; J. M. Cushing; Shandelle M. Henson; Robert A. Desharnais; Brian Dennis
2004-01-01
Mathematically, chaotic dynamics are not devoid of order but display episodes of near-cyclic temporal patterns. This is illustrated, in interesting ways, in the case of chaotic biological populations. Despite the individual nature of organisms and the noisy nature of biological time series, subtle temporal patterns have been detected. By using data drawn from chaotic insect populations, we show quantitatively that
Anatomy of a chaotic attractor: Subtle model- predicted patterns revealed in population data
Aaron A. King; R. F. Costantino; J. M. Cushing; Shandelle M. Henson; Robert A. Desharnais; Brian Dennis
2004-01-01
Mathematically, chaotic dynamics are not devoid of order but display episodes of near-cyclic temporal patterns. This is illustrated, in interesting ways, in the case of chaotic biological populations. Despite the individual nature of organisms and the noisy nature of biological time series, subtle temporal patterns have been de- tected. By using data drawn from chaotic insect populations, we show quantitatively
NASA Astrophysics Data System (ADS)
Bacher, Cédric; Gangnery, Aline
2006-08-01
We successfully tested a Dynamic Energy Budget (DEB) model of the oyster Crassostrea gigas using published environmental data and growth data collected in Thau lagoon (France). Estimates of most DEB parameters were based on independent datasets and only two parameters were calibrated using our datasets: the shape parameter, which was used to convert body volume into shell length, and the half-saturation coefficient, which controlled the functional response of assimilation to food concentration, represented by chlorophyll-a concentration. The DEB model proved to be robust and generic: it was able to reproduce oyster growth in Thau lagoon and other ecosystems. We also assessed population dynamics by coupling DEB equations and an Individual Based Model (IBM) of cultivated oyster populations. The results were compared with previously published simulations of harvested production and standing stock based on an empirical growth equation and a partial differential equation of population dynamics. Differences between the two studies were explained by the difference between the predictions of oyster growth with the empirical and the DEB models. We also accounted for growth variability between individuals and showed that IBM offers a powerful alternative to continuous equations when several physiological variables are involved.
Predicting dynamic performance limits for servosystems with saturating nonlinearities
NASA Technical Reports Server (NTRS)
Webb, J. A., Jr.; Blech, R. A.
1979-01-01
A generalized treatment for a system with a single saturating nonlinearity is presented and compared with frequency response plots obtained from an analog model of the system. Once the amplitude dynamics are predicted with the limit lines, an iterative technique is employed to determine the system phase response. The saturation limit line technique is used in conjunction with velocity and acceleration limits to predict the performance of an electro-hydraulic servosystem containing a single-stage servovalve. Good agreement was obtained between predicted performance and experimental data.
Dynamic bifurcations for predictability of climate tipping events
NASA Astrophysics Data System (ADS)
Surovyatkina, Elena; Kurths, Juergen
2014-05-01
Despite recent advances in understanding of the nonlinear processes responsible for changes in the climate system predicting the future abrupt climate changes remains an outstanding scientific challenge of special importance for the society. Better understanding of nonlinear mechanisms of tipping points is a major goal in treating this problem. Existed approaches to examine climatic tipping points allow identifying the climate-tipping events in the past but very limited to predict them in advance. Our recent theoretical findings suggest that for predicting tipping points it is crucial to distinguish which scenario of a bifurcation transition dominates: dynamic (predictable) or stochastic (unpredictable). In order to illustrate suggested approach we compare the features of dynamic and stochastic bifurcations in most common scenario of abrupt transition between two climate states. This scenario is associated with a saddle-node and a transcritical bifurcations. Such scenario has been used, in particularly, in the analysis of stability of the thermohaline circulation against freshwater flux, Indian summer monsoon against global change. We demonstrate the effect of the rate of change of the bifurcation parameter at dynamic bifurcation and noise effect at stochastic bifurcation transitions by theoretical estimates. We analyse pre-bifurcation noise-dependent and rate-dependent phenomena, and distinguish its roles as "precursors" of impending bifurcations for dynamic and stochastic transitions. We show that appropriate choice of "precursors" might lead to improving predictability of climate tipping points. Additionally, the evaluation of the role of dynamic and stochastic factors might be also useful for the assessment of the vulnerability of tipping elements to noise-induced changes. Finally, our preliminary investigations suggest that a hitherto neglected dynamic effect induced by such small parameter as rate of change of the bifurcation parameter may have had important influence on abrupt climate changes on the scale of the geological history of the Earth.
States of America Introduction A central theme in population ecology is to understand tStructural Perturbations to Population Skeletons: Transient Dynamics, Coexistence of Attractors, London, United Kingdom Abstract Background: Simple models of insect populations with non
Effects of Supplemental Food on Population Dynamics of Cotton Rats, Sigmodon Hispidus
Doonan, Terry J.; Slade, Norman A.
1995-04-01
Variation in resource abundance affects population dynamics by altering demographic processes and interactions among individuals in the population. For small mammals, food is likely to be a critical resource. Population densities should vary...
Host-parasite population dynamics under combined frequency-and density-dependent transmission
Knell, Rob
Host-parasite population dynamics under combined frequency- and density-dependent transmission population density (`density- dependent transmission'), but various alternative transmission functions have contact one another is independent of population density, leading to `frequency-dependent' transmission
Predator effects on prey population dynamics in open systems.
Peckarsky, Barbara L; Kerans, Billie L; Taylor, Brad W; McIntosh, Angus R
2008-05-01
Animal population dynamics in open systems are affected not only by agents of mortality and the influence of species interactions on behavior and life histories, but also by dispersal and recruitment. We used an extensive data set to compare natural loss rates of two mayfly species that co-occur in high-elevation streams varying in predation risk, and experience different abiotic conditions during larval development. Our goals were to generate hypotheses relating predation to variation in prey population dynamics and to evaluate alternative mechanisms to explain such variation. While neither loss rates nor abundance of the species that develops during snowmelt (Baetis bicaudatus) varied systematically with fish, loss rates of the species that develops during baseflow (Baetis B) were higher in streams containing brook trout than streams without fish; and surprisingly, larvae of this species were most abundant in trout streams. This counter-intuitive pattern could not be explained by a trophic cascade, because densities of intermediate predators (stoneflies) did not differ between fish and fishless streams and predation by trout on stoneflies was negligible. A statistical model estimated that higher recruitment and accelerated development enables Baetis B to maintain larger populations in trout streams despite higher mortality from predation. Experimental estimates suggested that predation by trout potentially accounts for natural losses of Baetis B, but not Baetis bicaudatus. Predation by stoneflies on Baetis is negligible in fish streams, but could make an important contribution to observed losses of both species in fishless streams. Non-predatory sources of loss were higher for B. bicaudatus in trout streams, and for Baetis B in fishless streams. We conclude that predation alone cannot explain variation in population dynamics of either species; and the relative importance of predation is species- and environment-specific compared to non-predatory losses, such as other agents of mortality and non-consumptive effects of predators. PMID:18322706
MODELLING THE POPULATION DYNAMICS OF THE ITCHA-ILGACHUZ CARIBOU HERD TO DETERMINE THE
MODELLING THE POPULATION DYNAMICS OF THE ITCHA-ILGACHUZ CARIBOU HERD TO DETERMINE THE EFFECTS: Master of Resource Management Project No.: 520 Title of Thesis: Modelling the population dynamics outfitters, all of whom hunt caribou from this herd. This project modelled the population dynamics
Agent-Based and Population-Based Modeling of Trust Dynamics1
Treur, Jan
Agent-Based and Population-Based Modeling of Trust Dynamics1 Syed Waqar Jaffry[1,2] and Jan Treur[1 trustee exists in a given population or group of agents. The dynamics of trust states over time can to obtain the trust state of the population. However, in an alternative way trust dynamics can be modelled
Wilde, Gene
Population Dynamics of the Smalleye Shiner, an Imperiled Cyprinid Fish Endemic to the Brazos River University, Lubbock, Texas 79409-3131, USA Abstract.--We studied the population dynamics of the smalleye the parameter estimates required for construction of an age-structured population dynamics model. We included
Hartvigsen, Gregg
and coevolution on population and community dynamics. Individual plants and herbivores resided in cellsˇect large-scale population and community dynamics. 1. INTRODUCTION The nature of plant and herbivores, translates into macro- scopic patterns of population dynamics and community structure
Huang, Minyi
Nash Certainty Equivalence in Large Population Stochastic Dynamic Games: Connections consider large population dynamic games and illuminate methodological connections with the theory of inter in a large population of weakly coupled agents. The weak coupling in both dynamics and costs is used to model
The Language Dynamics Equations of Population-Based Transition a Scenario for Creolization
Nakamura, Makoto
The Language Dynamics Equations of Population- Based Transition Â a Scenario for Creolization of the population dynamics. We propose that the transition rate in languages is sensitive to the distribution as differential equations which they call the lan- guage dynamics equations. Because the population
Effects of tick population dynamics and host densities on the persistence of tick-borne infections
Pugliese, Andrea
Effects of tick population dynamics and host densities on the persistence of tick-borne infections and pathogens, is affected by the dynamics of tick populations, and by their host densities. The effect of host. Keywords: Tick-borne infections; Tick population dynamics; Basic reproduction number; Host density
Bluegill Reproductive Biology and Population Dynamics in Four South Dakota Impoundments
Bluegill Reproductive Biology and Population Dynamics in Four South Dakota Impoundments BY Kris RJI Reproductive Biology and Population Dynamics in Four Small South Dakota Impoundments This thesis is approved Biology and Population Dynamics in Four South Dakota Impoundments Kris R. Edwards November 2007
Fukaya, Keiichi; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi
2014-11-01
Explanations for why population dynamics vary across the range of a species reflect two contrasting hypotheses: (i) temporal variability of populations is larger in the centre of the range compared to the margins because overcompensatory density dependence destabilizes population dynamics and (ii) population variability is larger near the margins, where populations are more susceptible to environmental fluctuations. In both of these hypotheses, positions within the range are assumed to affect population variability. In contrast, the fact that population variability is often related to mean population size implies that the spatial structure of the population size within the range of a species may also be a useful predictor of the spatial variation in temporal variability of population size over the range of the species. To explore how population temporal variability varies spatially and the underlying processes responsible for the spatial variation, we focused on the intertidal barnacle Chthamalus dalli and examined differences in its population dynamics along the tidal levels it inhabits. Changes in coverage of barnacle populations were monitored for 10.5 years at 25 plots spanning the elevational range of this species. Data were analysed by fitting a population dynamics model to estimate the effects of density-dependent and density-independent processes on population growth. We also examined the temporal mean-variance relationship of population size with parameters estimated from the population dynamics model. We found that the relative variability of populations tended to increase from the centre of the elevational range towards the margins because of an increase in the magnitude of stochastic fluctuations of growth rates. Thus, our results supported hypothesis (2). We also found that spatial variations in temporal population variability were well characterized by Taylor's power law, the relative population variability being inversely related to the mean population size. Results suggest that understanding the population dynamics of a species over its range may be facilitated by taking the spatial structure of population size into account as well as by considering changes in population processes as a function of position within the range of the species. PMID:24738826
Variation in the local population dynamics of the short-lived Opuntia macrorhiza (Cactaceae).
Haridas, C V; Keeler, Kathleen H; Tenhumberg, Brigitte
2015-03-01
Spatiotemporal variation in demographic rates can have profound effects for population persistence, especially for dispersal-limited species living in fragmented landscapes. Long-term studies of plants in such habitats help with understanding the impacts of fragmentation on population persistence but such studies are rare. In this work, we reanalyzed demographic data from seven years of the short-lived cactus Opuntia macrorhiza var. macrorhiza at five plots in Boulder, Colorado. Previous work combining data from all years and all plots predicted a stable population (deterministic log lamda approximately 0). This approach assumed that all five plots were part of a single population. Since the plots were located in a suburban-agricultural interface separated by highways, grazing lands, and other barriers, and O. macrorhiza is likely dispersal limited, we analyzed the dynamics of each plot separately using stochastic matrix models assuming each plot represented a separate population. We found that the stochastic population growth rate log lamdaS varied widely between populations (log lamdaS = 0.1497, 0.0774, -0.0230, -0.2576, -0.4989). The three populations with the highest growth rates were located close together in space, while the two most isolated populations had the lowest growth rates suggesting that dispersal between populations is critical for the population viability of O. macrorhiza. With one exception, both our prospective (stochastic elasticity) and retrospective (stochastic life table response experiments) analysis suggested that means of stasis and growth, especially of smaller plants, were most important for population growth rate. This is surprising because recruitment is typically the most important vital rate in a short-lived species such as O. macrorhiza. We found that elasticity to the variance was mostly negligible, suggesting that O. macrorhiza populations are buffered against large temporal variation. Finally, single-year elasticities to means of transitions to the smallest stage (mostly due to reproduction) and growth differed considerably from their long-term elasticities. It is important to be aware of this difference when using models to predict the effect of manipulating plant vital rates within the time frame of typical plant demographic studies. PMID:26236875
Scoring dynamics across professional team sports: tempo, balance and predictability
Merritt, Sears
2013-01-01
Despite growing interest in quantifying and modeling the scoring dynamics within professional sports games, relative little is known about what patterns or principles, if any, cut across different sports. Using a comprehensive data set of scoring events in nearly a dozen consecutive seasons of college and professional (American) football, professional hockey, and professional basketball, we identify several common patterns in scoring dynamics. Across these sports, scoring tempo---when scoring events occur---closely follows a common Poisson process, with a sport-specific rate. Similarly, scoring balance---how often a team wins an event---follows a common Bernoulli process, with a parameter that effectively varies with the size of the lead. Combining these processes within a generative model of gameplay, we find they both reproduce the observed dynamics in all four sports and accurately predict game outcomes. These results demonstrate common dynamical patterns underlying within-game scoring dynamics across prof...
Mutatis Mutandis: Safe and Predictable Dynamic Software Updating
Sewell, Peter
present Proteus, a core calculus for dy- namic software updating in C-like languages that is flexible, safe, and predictable. Proteus supports dynamic updates to functions (even active ones), to named types, capability, Proteus Permission to make digital or hard copies of all or part of this work for personal
Circuit Optimization Predicts Dynamic Networks for Chemosensory Orientation in the
Conery, John
Circuit Optimization Predicts Dynamic Networks for Chemosensory Orientation in the Nematode Eugene, OR 97403 shawn@lox.uoregon.edu Abstract The connectivity of the nervous system of the nematode suffi- cient to compute the sensorimotor transformation underlying C. elegans chemotaxis, a simple form
The Predictive Validity of Dynamic Assessment: A Review
ERIC Educational Resources Information Center
Caffrey, Erin; Fuchs, Douglas; Fuchs, Lynn S.
2008-01-01
The authors report on a mixed-methods review of 24 studies that explores the predictive validity of dynamic assessment (DA). For 15 of the studies, they conducted quantitative analyses using Pearson's correlation coefficients. They descriptively examined the remaining studies to determine if their results were consistent with findings from the…
Mammal population regulation, keystone processes and ecosystem dynamics.
Sinclair, A R E
2003-01-01
The theory of regulation in animal populations is fundamental to understanding the dynamics of populations, the causes of mortality and how natural selection shapes the life history of species. In mammals, the great range in body size allows us to see how allometric relationships affect the mode of regulation. Resource limitation is the fundamental cause of regulation. Top-down limitation through predators is determined by four factors: (i). body size; (ii). the diversity of predators and prey in the system; (iii). whether prey are resident or migratory; and (iv). the presence of alternative prey for predators. Body size in mammals has two important consequences. First, mammals, particularly large species, can act as keystones that determine the diversity of an ecosystem. I show how keystone processes can, in principle, be measured using the example of the wildebeest in the Serengeti ecosystem. Second, mammals act as ecological landscapers by altering vegetation succession. Mammals alter physical structure, ecological function and species diversity in most terrestrial biomes. In general, there is a close interaction between allometry, population regulation, life history and ecosystem dynamics. These relationships are relevant to applied aspects of conservation and pest management. PMID:14561329
Scale-invariant model of marine population dynamics
NASA Astrophysics Data System (ADS)
Capitán, José A.; Delius, Gustav W.
2010-06-01
A striking feature of the marine ecosystem is the regularity in its size spectrum: the abundance of organisms as a function of their weight approximately follows a power law over almost ten orders of magnitude. We interpret this as evidence that the population dynamics in the ocean is approximately scale-invariant. We use this invariance in the construction and solution of a size-structured dynamical population model. Starting from a Markov model encoding the basic processes of predation, reproduction, maintenance respiration, and intrinsic mortality, we derive a partial integro-differential equation describing the dependence of abundance on weight and time. Our model represents an extension of the jump-growth model and hence also of earlier models based on the McKendrick-von Foerster equation. The model is scale-invariant provided the rate functions of the stochastic processes have certain scaling properties. We determine the steady-state power-law solution, whose exponent is determined by the relative scaling between the rates of the density-dependent processes (predation) and the rates of the density-independent processes (reproduction, maintenance, and mortality). We study the stability of the steady-state against small perturbations and find that inclusion of maintenance respiration and reproduction in the model has a strong stabilizing effect. Furthermore, the steady state is unstable against a change in the overall population density unless the reproduction rate exceeds a certain threshold.
Population dynamics in the presence of quasispecies effects and changing environments
NASA Astrophysics Data System (ADS)
Forster, Robert Burke
2006-12-01
This thesis explores how natural selection acts on organisms such as viruses that have either highly error-prone reproduction or face variable environmental conditions or both. By modeling population dynamics under these conditions, we gain a better understanding of the selective forces at work, both in our simulations and hopefully also in real organisms. With an understanding of the important factors in natural selection we can forecast not only the immediate fate of an existing population but also in what directions such a population might evolve in the future. We demonstrate that the concept of a quasispecies is relevant to evolution in a neutral fitness landscape. Motivated by RNA viruses such as HIV, we use RNA secondary structure as our model system and find that quasispecies effects arise both rapidly and in realistically small populations. We discover that the evolutionary effects of neutral drift, punctuated equilibrium and the selection for mutational robustness extend to the concept of a quasispecies. In our study of periodic environments, we consider the tradeoffs faced by quasispecies in adapting to environmental change. We develop an analytical model to predict whether evolution favors short-term or long-term adaptation and validate our model through simulation. Our results bear directly on the population dynamics of viruses such as West Nile that alternate between two host species. More generally, we discover that a selective pressure exists under these conditions to fuse or split genes with complementary environmental functions. Lastly, we study the general effects of frequency-dependent selection on two strains competing in a periodic environment. Under very general assumptions, we prove that stable coexistence rather than extinction is the likely outcome. The population dynamics of this system may be as simple as stable equilibrium or as complex as deterministic chaos.
Finan, Patrick H.; Hessler, Eric E.; Amazeen, Polemnia G.; Butner, Jonathan; Zautra, Alex J.; Tennen, Howard
2011-01-01
Dynamical systems modeling was used to analyze fluctuations in the pain prediction process of people with rheumatoid arthritis. 170 people diagnosed with rheumatoid arthritis completed 29 consecutive days of diaries. Difference scores between pain predictions and next-day pain experience ratings provided a time series of pain prediction accuracy. Pain prediction accuracy oscillated over time. The oscillation amplitude was larger at the start of the diary than at the end, which indicates damping toward more accurate predictions. State-level psychological characteristics moderated the damping pattern such that the oscillations for patients with lower negative affect and higher pain control damped more quickly than the oscillations for their counterparts. Those findings suggest that low negative affect and high pain control generally contributed to a more accurate pain prediction process in the chronically ill. Positive affect did not differentiate the damping pattern but, within each oscillation cycle, patients with higher positive affect spent more time making inaccurate predictions than their counterparts. The current analyses highlight the need to account for change in data through dynamical modeling, which cannot be fully observed through traditional statistical techniques. PMID:20021776
Evolutionary dynamics for persistent cooperation in structured populations.
Li, Yan; Liu, Xinsheng; Claussen, Jens Christian; Guo, Wanlin
2015-06-01
The emergence and maintenance of cooperative behavior is a fascinating topic in evolutionary biology and social science. The public goods game (PGG) is a paradigm for exploring cooperative behavior. In PGG, the total resulting payoff is divided equally among all participants. This feature still leads to the dominance of defection without substantially magnifying the public good by a multiplying factor. Much effort has been made to explain the evolution of cooperative strategies, including a recent model in which only a portion of the total benefit is shared by all the players through introducing a new strategy named persistent cooperation. A persistent cooperator is a contributor who is willing to pay a second cost to retrieve the remaining portion of the payoff contributed by themselves. In a previous study, this model was analyzed in the framework of well-mixed populations. This paper focuses on discussing the persistent cooperation in lattice-structured populations. The evolutionary dynamics of the structured populations consisting of three types of competing players (pure cooperators, defectors, and persistent cooperators) are revealed by theoretical analysis and numerical simulations. In particular, the approximate expressions of fixation probabilities for strategies are derived on one-dimensional lattices. The phase diagrams of stationary states, and the evolution of frequencies and spatial patterns for strategies are illustrated on both one-dimensional and square lattices by simulations. Our results are consistent with the general observation that, at least in most situations, a structured population facilitates the evolution of cooperation. Specifically, here we find that the existence of persistent cooperators greatly suppresses the spreading of defectors under more relaxed conditions in structured populations compared to that obtained in well-mixed populations. PMID:26172749
Fang, Chi-Chun; Okuyama, Toshinori; Wu, Wen-Jer; Feng, Hai-Tung; Hsu, Ju-Chun
2011-12-01
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
Population dynamic of algae and bacteria in an oxidation channel.
O'Farrill, N E; Travieso, L; Benítez, F; Bécares, E; Romo, S; Borja, R; Weiland, P; Sánchez, E
2003-04-01
A study on algae and bacteria population changes, as a function of time, was carried out in a pilot scale oxidation channel bioreactor using a carrousel system. Total Coliforms, Pseudomonas aeruginosa, and Streptococcus faecalis, the most common bacteria found in sewage, Scenedesmus obliquus and Chlorella vulgaris were the microalgae considered in this work. Physicochemical parameters such as COD, BOD, Chlorophyll a, nitrogen, and phosphorous compounds were studied and determined during the experiments. It was demonstrated that the level of wastewater contamination could be predicted based on the bacterial and algae composition. The relationships between the algae and bacteria population, and the variation of these microorganism populations as a measurement of the level of purification were established. The oxidation channel was able to remove a considerable amount of organic matter and pathogenic microorganisms in a relatively short time. The nitrification process could not be measured. The increase in the relative concentration of microalgae contributed toward improving the global efficiency of the system as well as reducing the pathogenic bacteria population. PMID:12716074
[Gypsy moth Lymantria dispar L. in the South Urals: Patterns in population dynamics and modelling].
Soukhovolsky, V G; Ponomarev, V I; Sokolov, G I; Tarasova, O V; Krasnoperova, P A
2015-01-01
The analysis is conducted on population dynamics of gypsy moth from different habitats of the South Urals. The pattern of cyclic changes in population density is examined, the assessment of temporal conjugation in time series of gypsy moth population dynamics from separate habitats of the South Urals is carried out, the relationships between population density and weather conditions are studied. Based on the results obtained, a statistical model of gypsy moth population dynamics in the South Urals is designed, and estimations are given of regulatory and modifying factors effects on the population dynamics. PMID:26201216
Spatial dynamics of a population with stage-dependent diffusion
NASA Astrophysics Data System (ADS)
Azevedo, F.; Coutinho, R. M.; Kraenkel, R. A.
2015-05-01
We explore the spatial dynamics of a population whose individuals go through life stages with very different dispersal capacities. We model it through a system of partial differential equations of the reaction-diffusion kind, with nonlinear diffusion terms that may depend on population density and on the stage. This model includes a few key biological ingredients: growth and saturation, life stage structure, small population effects, and diffusion dependent on the stage. In particular, we consider that adults exhibit two distinct classes: one highly mobile and the other less mobile but with higher fecundity rate, and the development of juveniles into one or the other depends on population density. We parametrize the model with estimated parameters of an insect species, the brown planthopper. We focus on a situation akin to an invasion of the species in a new habitat and find that the front of invasion is led by the most mobile adult class. We also show that the trade-off between dispersal and fecundity leads to invasion speed attaining its maximum at an intermediate value of the diffusion coefficient of the most mobile class.
New methods for inferring population dynamics from microbial sequences.
Pérez-Losada, Marcos; Porter, Megan L; Tazi, Loubna; Crandall, Keith A
2007-01-01
The reduced cost of high throughput sequencing, increasing automation, and the amenability of sequence data for evolutionary analysis are making DNA data (or the corresponding amino acid sequences) the molecular marker of choice for studying microbial population genetics and phylogenetics. Concomitantly, due to the ever-increasing computational power, new, more accurate (and sometimes faster), sequence-based analytical approaches are being developed and applied to these new data. Here we review some commonly used, recently improved, and newly developed methodologies for inferring population dynamics and evolutionary relationships using nucleotide and amino acid sequence data, including: alignment, model selection, bifurcating and network phylogenetic approaches, and methods for estimating demographic history, population structure, and population parameters (recombination, genetic diversity, growth, and natural selection). Because of the extensive literature published on these topics this review cannot be comprehensive in its scope. Instead, for all the methods discussed we introduce the approaches we think are particularly useful for analyses of microbial sequences and where possible, include references to recent and more inclusive reviews. PMID:16627010
Evolutionary Dynamics for Persistent Cooperation in Structured Populations
Li, Yan; Claussen, Jens Christian; Guo, Wanlin
2015-01-01
The emergence and maintenance of cooperative behavior is a fascinating topic in evolutionary biology and social science. The public goods game (PGG) is a paradigm for exploring cooperative behavior. In PGG, the total resulting payoff is divided equally among all participants. This feature still leads to the dominance of defection without substantially magnifying the public good by a multiplying factor. Much effort has been made to explain the evolution of cooperative strategies, including a recent model in which only a portion of the total benefit is shared by all the players through introducing a new strategy named persistent cooperation. A persistent cooperator is a contributor who is willing to pay a second cost to retrieve the remaining portion of the payoff contributed by themselves. In a previous study, this model was analyzed in the framework of well-mixed populations. This paper focuses on discussing the persistent cooperation in lattice-structured populations. The evolutionary dynamics of the structu...
Arbitrary nonlinearities in convective population dynamics with small diffusion
NASA Astrophysics Data System (ADS)
Peixoto, I. D.; Giuggioli, L.; Kenkre, V. M.
2005-10-01
Convective counterparts of variants of the nonlinear Fisher equation which describes reaction diffusion systems in population dynamics are studied with the help of an analytic prescription and shown to lead to interesting consequences for the evolution of population densities. The initial-value problem is solved explicitly for some cases, and for others it is shown how to find traveling-wave solutions analytically. The effect of adding diffusion to the convective equations is first studied through exact analysis through a piecewise linear representation of the nonlinearity. Using an appropriate small parameter suggested by that analysis, a perturbative treatment is developed to treat the case in which the convective evolution is augmented by a small amount of diffusion.
Krekels, Elke H J; Tibboel, Dick; Danhof, Meindert; Knibbe, Catherijne A J
2012-11-01
The pharmacokinetics of morphine in paediatrics have been widely studied using different approaches and modelling techniques. In this review, we explore advantages and disadvantages of the different data analysis techniques that have been applied, with specific focus on the accuracy of morphine clearance predictions by reported paediatric pharmacokinetic models. Twenty paediatric studies reported a wide range in morphine clearance values using traditional, rather descriptive methods. Clearance values were expressed per kilogram bodyweight, while maturation in clearance was described by comparing mean clearance per kilogram bodyweight between age-stratified subgroups. Population modelling allows for the analysis of sparse data, thereby limiting the burden to individual patients. Using this technique, continuous maturation profiles can be obtained on the basis of either fixed allometric scaling or comprehensive covariate analysis. While the models based on fixed allometric scaling resulted in complex maturation functions, all three paediatric population models for morphine yielded quite similar clearance predictions. The largest difference in clearance predictions between these three population models occurred in the first months of life, particularly in preterm neonates. Morphine clearance predictions by a physiologically based pharmacokinetic model were based on many continuous equations describing changes in underlying physiological processes across the full paediatric age range, and resulted in similar clearance predictions as well. However, preterm neonates could not be integrated in this model. In conclusion, the value of paediatric pharmacokinetic models is mostly dependent on clearance predictions and population concentration predictions, rather than on the individual description of data. For most pharmacokinetic models, however, the assessment of model performance was very limited and the accuracy of morphine clearance predictions as well as population concentration predictions was confirmed by formal evaluation and validation procedures for only one model. PMID:23018467
Kang, In-Sik
A statistical approach to Indian Ocean sea surface temperature prediction using a dynamical ENSO (SST) in the Indian Ocean. It is a linear regression model based on a lagged relationship between the Indian Ocean SST and the NINO3 SST. A new approach to the statistical modeling has been tried out
Front acceleration by dynamic selection in Fisher population waves
NASA Astrophysics Data System (ADS)
Bénichou, O.; Calvez, V.; Meunier, N.; Voituriez, R.
2012-10-01
We introduce a minimal model of population range expansion in which the phenotypes of individuals present no selective advantage and differ only in their diffusion rate. We show that such neutral phenotypic variability (i.e., that does not modify the growth rate) alone can yield phenotype segregation at the front edge, even in absence of genetic noise, and significantly impact the dynamical properties of the expansion wave. We present an exact asymptotic traveling wave solution and show analytically that phenotype segregation accelerates the front propagation. The results are compatible with field observations such as invasions of cane toads in Australia or bush crickets in Britain.
Periodically varying externally imposed environmental effects on population dynamics
NASA Astrophysics Data System (ADS)
Ballard, M.; Kenkre, V. M.; Kuperman, M. N.
2004-09-01
Effects of externally imposed periodic changes in the environment on population dynamics are studied with the help of a simple model. The environmental changes are represented by the temporal and spatial dependence of the competition terms in a standard equation of evolution. Possible applications of the analysis are on the one hand to bacteria in Petri dishes and on the other to rodents in the context of the spread of the Hantavirus epidemic. The analysis shows that spatiotemporal structures emerge, with interesting features which depend on the interplay of separately controllable aspects of the externally imposed environmental changes.
Time-delayed coupled logistic capacity model in population dynamics
NASA Astrophysics Data System (ADS)
Cáceres, Manuel O.
2014-08-01
This study proposes a delay-coupled system based on the logistic equation that models the interaction of a population with its varying environment. The integro-diferential equations of the model are presented in terms of a distributed time-delayed coupled logistic-capacity equation. The model eliminates the need for a prior knowledge of the maximum saturation environmental carrying capacity value. Therefore the dynamics toward the final attractor in a distributed time-delayed coupled logistic-capacity model is studied. Exact results are presented, and analytical conclusions have been done in terms of the two parameters of the model.
A Stochastic Super-Exponential Growth Model for Population Dynamics
NASA Astrophysics Data System (ADS)
Avila, P.; Rekker, A.
2010-11-01
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.
Epoch Lifetimes in the Dynamics of a Competing Population
NASA Astrophysics Data System (ADS)
Yeung, C. H.; Ma, Y. P.; Wong, K. Y. Michael
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.
Prediction of human population responses to toxic compounds by a collaborative competition.
Eduati, Federica; Mangravite, Lara M; Wang, Tao; Tang, Hao; Bare, J Christopher; Huang, Ruili; Norman, Thea; Kellen, Mike; Menden, Michael P; Yang, Jichen; Zhan, Xiaowei; Zhong, Rui; Xiao, Guanghua; Xia, Menghang; Abdo, Nour; Kosyk, Oksana
2015-09-01
The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson's r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal. PMID:26258538
Phonon-induced population dynamics and intersystem crossing in nitrogen-vacancy centers.
Goldman, M L; Sipahigil, A; Doherty, M W; Yao, N Y; Bennett, S D; Markham, M; Twitchen, D J; Manson, N B; Kubanek, A; Lukin, M D
2015-04-10
We report direct measurement of population dynamics in the excited state manifold of a nitrogen-vacancy (NV) center in diamond. We quantify the phonon-induced mixing rate and demonstrate that it can be completely suppressed at low temperatures. Further, we measure the intersystem crossing (ISC) rate for different excited states and develop a theoretical model that unifies the phonon-induced mixing and ISC mechanisms. We find that our model is in excellent agreement with experiment and that it can be used to predict unknown elements of the NV center's electronic structure. We discuss the model's implications for enhancing the NV center's performance as a room-temperature sensor. PMID:25910136
Phonon-Induced Population Dynamics and Intersystem Crossing in Nitrogen-Vacancy Centers
M. L. Goldman; A. Sipahigil; M. W. Doherty; N. Y. Yao; S. D. Bennett; M. Markham; D. J. Twitchen; N. B. Manson; A. Kubanek; M. D. Lukin
2015-03-03
We report direct measurement of population dynamics in the excited state manifold of a nitrogen-vacancy (NV) center in diamond. We quantify the phonon-induced mixing rate and demonstrate that it can be completely suppressed at low temperatures. Further, we measure the intersystem crossing (ISC) rate for different excited states and develop a theoretical model that unifies the phonon-induced mixing and ISC mechanisms. We find that our model is in excellent agreement with experiment and that it can be used to predict unknown elements of the NV center's electronic structure. We discuss the model's implications for enhancing the NV center's performance as a room-temperature sensor.
Auctions with Dynamic Populations: Efficiency and Revenue Maximization
NASA Astrophysics Data System (ADS)
Said, Maher
We study a stochastic sequential allocation problem with a dynamic population of privately-informed buyers. We characterize the set of efficient allocation rules and show that a dynamic VCG mechanism is both efficient and periodic ex post incentive compatible; we also show that the revenue-maximizing direct mechanism is a pivot mechanism with a reserve price. We then consider sequential ascending auctions in this setting, both with and without a reserve price. We construct equilibrium bidding strategies in this indirect mechanism where bidders reveal their private information in every period, yielding the same outcomes as the direct mechanisms. Thus, the sequential ascending auction is a natural institution for achieving either efficient or optimal outcomes.
Orbit determination and prediction study for Dynamic Explorer 2
NASA Technical Reports Server (NTRS)
Smith, R. L.; Nakai, Y.; Doll, C. E.
1983-01-01
Definitive orbit determination accuracy and orbit prediction accuracy for the Dynamic Explorer-2 (DE-2) are studied using the trajectory determination system for the period within six weeks of spacecraft reentry. Baseline accuracies using standard orbit determination models and methods are established. A promising general technique for improving the orbit determination accuracy of high drag orbits, estimation of random drag variations at perigee passages, is investigated. This technique improved the fit to the tracking data by a factor of five and improved the solution overlap consistency by a factor of two during a period in which the spacecraft perigee altitude was below 200 kilometers. The results of the DE-2 orbit predictions showed that improvement in short term prediction accuracy reduces to the problem of predicting future drag scale factors: the smoothness of the solar 10.7 centimeter flux density suggests that this may be feasible.
NASA Astrophysics Data System (ADS)
He, Zhuo-Ran; Wu, Tai-Lin; Ouyang, Qi; Tu, Yu-Hai
2012-09-01
Recent extensive studies of Escherichia coli (E. coli) chemotaxis have achieved a deep understanding of its microscopic control dynamics. As a result, various quantitatively predictive models have been developed to describe the chemotactic behavior of E. coli motion. However, a population-level partial differential equation (PDE) that rationally incorporates such microscopic dynamics is still insufficient. Apart from the traditional Keller-Segel (K-S) equation, many existing population-level models developed from the microscopic dynamics are integro-PDEs. The difficulty comes mainly from cell tumbles which yield a velocity jumping process. Here, we propose a Langevin approximation method that avoids such a difficulty without appreciable loss of precision. The resulting model not only quantitatively reproduces the results of pathway-based single-cell simulators, but also provides new inside information on the mechanism of E. coli chemotaxis. Our study demonstrates a possible alternative in establishing a simple population-level model that allows for the complex microscopic mechanisms in bacterial chemotaxis.
Impact of simian immunodeficiency virus infection on chimpanzee population dynamics.
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
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
Impact of Simian Immunodeficiency Virus Infection on Chimpanzee Population Dynamics
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
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
Prediction of HLA Class II Alleles Using SNPs in an African Population
Ayele, Fasil Tekola; Hailu, Elena; Finan, Chris; Aseffa, Abraham; Davey, Gail; Newport, Melanie J.; Rotimi, Charles N.; Adeyemo, Adebowale
2012-01-01
Background Despite the importance of the human leukocyte antigen (HLA) gene locus in research and clinical practice, direct HLA typing is laborious and expensive. Furthermore, the analysis requires specialized software and expertise which are unavailable in most developing country settings. Recently, in silico methods have been developed for predicting HLA alleles using single nucleotide polymorphisms (SNPs). However, the utility of these methods in African populations has not been systematically evaluated. Methodology/Principal Findings In the present study, we investigate prediction of HLA class II (HLA-DRB1 and HLA-DQB1) alleles using SNPs in the Wolaita population, southern Ethiopia. The subjects comprised 297 Ethiopians with genome-wide SNP data, of whom 188 had also been HLA typed and were used for training and testing the model. The 109 subjects with SNP data alone were used for empirical prediction using the multi-allelic gene prediction method. We evaluated accuracy of the prediction, agreement between predicted and HLA typed alleles, and discriminative ability of the prediction probability supplied by the model. We found that the model predicted intermediate (two-digit) resolution for HLA-DRB1 and HLA-DQB1 alleles at accuracy levels of 96% and 87%, respectively. All measures of performance showed high accuracy and reliability for prediction. The distribution of the majority of HLA alleles in the study was similar to that previously reported for the Oromo and Amhara ethnic groups from Ethiopia. Conclusions/Significance We demonstrate that HLA class II alleles can be predicted from SNP genotype data with a high level of accuracy at intermediate (two-digit) resolution in an African population. This finding offers new opportunities for HLA studies of disease epidemiology and population genetics in developing countries. PMID:22761960
Predicting the timing of dynamic events through sound: Bouncing balls.
Gygi, Brian; Giordano, Bruno L; Shafiro, Valeriy; Kharkhurin, Anatoliy; Zhang, Peter Xinya
2015-07-01
Dynamic information in acoustical signals produced by bouncing objects is often used by listeners to predict the objects' future behavior (e.g., hitting a ball). This study examined factors that affect the accuracy of motor responses to sounds of real-world dynamic events. In experiment 1, listeners heard 2-5 bounces from a tennis ball, ping-pong, basketball, or wiffle ball, and would tap to indicate the time of the next bounce in a series. Across ball types and number of bounces, listeners were extremely accurate in predicting the correct bounce time (CT) with a mean prediction error of only 2.58% of the CT. Prediction based on a physical model of bouncing events indicated that listeners relied primarily on temporal cues when estimating the timing of the next bounce, and to a lesser extent on the loudness and spectral cues. In experiment 2, the timing of each bounce pattern was altered to correspond to the bounce timing pattern of another ball, producing stimuli with contradictory acoustic cues. Nevertheless, listeners remained highly accurate in their estimates of bounce timing. This suggests that listeners can adopt their estimates of bouncing-object timing based on acoustic cues that provide most veridical information about dynamic aspects of object behavior. PMID:26233044
McGaughey, Alan
Predicting alloy vibrational mode properties using lattice dynamics calculations, molecular-defect scattering. The mode properties are then used to predict thermal conductivity under the VC approximation. For the Lennard-Jones alloys, where high-frequency modes make a significant contribution to thermal conductivity
Stochastic population dynamics in astrochemistry and aerosol science
NASA Astrophysics Data System (ADS)
Losert-Valiente Kroon, C. M.
Classical, non-equilibrium systems of diffusing species or entities undergoing depletion, evaporation and reaction processes are at the heart of many problems in Physics, Chemistry, Biology and Financial Mathematics. It is well known that fluctuations and correlations in statistical systems can have a profound influence on the macroscopic properties of the system. However, the traditional rate equations that describe the evolution of mean populations in time and space do not incorporate statistical fluctuations. This becomes an issue of great importance when population densities are low. In order to develop a stochastic description of birth-and-death processes beyond the mean field approximation I employ techniques in classical many-body Physics in a manner analogous to the treatment of quantum systems. I obtain promising results to understand and quantify the exact circumstances of the failure of the mean-field approximation in specific problems in Astrophysics, namely heterogeneous chemical reactions in interstellar clouds, and in Aerosol Science, namely heterogeneous nucleation processes, and deliver the means to manipulate the alternative stochastic framework according to the Doi-Peliti formalism. In this framework the mean population of a species is given by the average of a solution to a set of constraint equations over all realisations of the stochastic noise. The constraint equations are inhomogeneous stochastic partial differential equations with multiplicative real or complex Gaussian noise. In general, these equations cannot be solved analytically. Therefore I resort to the numerical implementation of the Doi-Peliti formalism. The main code is written in the GNU C language, some algebraic calculations are performed by means of the MapleV package. In the case of large population densities the stochastic framework renders the same results as the mean field approximation whereas for low population densities its predictions differ substantially from the calculations using the traditional model.
NASA Technical Reports Server (NTRS)
Schweikhard, W. G.; Chen, Y. S.
1986-01-01
The Melick method of inlet flow dynamic distortion prediction by statistical means is outlined. A hypothetic vortex model is used as the basis for the mathematical formulations. The main variables are identified by matching the theoretical total pressure rms ratio with the measured total pressure rms ratio. Data comparisons, using the HiMAT inlet test data set, indicate satisfactory prediction of the dynamic peak distortion for cases with boundary layer control device vortex generators. A method for the dynamic probe selection was developed. Validity of the probe selection criteria is demonstrated by comparing the reduced-probe predictions with the 40-probe predictions. It is indicated that the the number of dynamic probes can be reduced to as few as two and still retain good accuracy.
NASA Astrophysics Data System (ADS)
Schweikhard, W. G.; Chen, Y. S.
1986-04-01
The Melick method of inlet flow dynamic distortion prediction by statistical means is outlined. A hypothetic vortex model is used as the basis for the mathematical formulations. The main variables are identified by matching the theoretical total pressure rms ratio with the measured total pressure rms ratio. Data comparisons, using the HiMAT inlet test data set, indicate satisfactory prediction of the dynamic peak distortion for cases with boundary layer control device vortex generators. A method for the dynamic probe selection was developed. Validity of the probe selection criteria is demonstrated by comparing the reduced-probe predictions with the 40-probe predictions. It is indicated that the the number of dynamic probes can be reduced to as few as two and still retain good accuracy.
Farrer, Emily C; Ashton, Isabel W; Knape, Jonas; Suding, Katharine N
2014-04-01
Two sources of complexity make predicting plant community response to global change particularly challenging. First, realistic global change scenarios involve multiple drivers of environmental change that can interact with one another to produce non-additive effects. Second, in addition to these direct effects, global change drivers can indirectly affect plants by modifying species interactions. In order to tackle both of these challenges, we propose a novel population modeling approach, requiring only measurements of abundance and climate over time. To demonstrate the applicability of this approach, we model population dynamics of eight abundant plant species in a multifactorial global change experiment in alpine tundra where we manipulated nitrogen, precipitation, and temperature over 7 years. We test whether indirect and interactive effects are important to population dynamics and whether explicitly incorporating species interactions can change predictions when models are forecast under future climate change scenarios. For three of the eight species, population dynamics were best explained by direct effect models, for one species neither direct nor indirect effects were important, and for the other four species indirect effects mattered. Overall, global change had negative effects on species population growth, although species responded to different global change drivers, and single-factor effects were slightly more common than interactive direct effects. When the fitted population dynamic models were extrapolated under changing climatic conditions to the end of the century, forecasts of community dynamics and diversity loss were largely similar using direct effect models that do not explicitly incorporate species interactions or best-fit models; however, inclusion of species interactions was important in refining the predictions for two of the species. The modeling approach proposed here is a powerful way of analyzing readily available datasets which should be added to our toolbox to tease apart complex drivers of global change. PMID:24115317
Small error dynamics and the predictability of atmospheric flows
NASA Technical Reports Server (NTRS)
Farrell, Brian F.
1990-01-01
In this paper, linear small-error theory is applied to the study of weather predictability. A simple baroclinic shear model and a barotropic channel model with a localized jet are used as examples. It is shown that increase in error on synoptic forecast time scales is controlled by rapidly growing perturbations that are not of normal mode form. Unpredictable regimes are not necessarily associated with larger exponential growth rates than are relatively more predictable regimes. Model problems illustrating baroclinic and barotropic dynamics suggest that asymptotic measures of divergence in phase space, while applicable in the limit of infinite time, may not be appropriate over time intervals addressed by present synoptic forecast.
Prediction of Muscle Performance During Dynamic Repetitive Exercise
NASA Technical Reports Server (NTRS)
Byerly, D. L.; Byerly, K. A.; Sognier, M. A.; Squires, W. G.
2002-01-01
A method for predicting human muscle performance was developed. Eight test subjects performed a repetitive dynamic exercise to failure using a Lordex spinal machine. Electromyography (EMG) data was collected from the erector spinae. Evaluation of the EMG data using a 5th order Autoregressive (AR) model and statistical regression analysis revealed that an AR parameter, the mean average magnitude of AR poles, can predict performance to failure as early as the second repetition of the exercise. Potential applications to the space program include evaluating on-orbit countermeasure effectiveness, maximizing post-flight recovery, and future real-time monitoring capability during Extravehicular Activity.
Chakravorty, Rajib; Rawlinson, David; Zhang, Alan; Markham, John; Dowling, Mark R.; Wellard, Cameron; Zhou, Jie H. S.; Hodgkin, Philip D.
2014-01-01
Interest in cell heterogeneity and differentiation has recently led to increased use of time-lapse microscopy. Previous studies have shown that cell fate may be determined well in advance of the event. We used a mixture of automation and manual review of time-lapse live cell imaging to track the positions, contours, divisions, deaths and lineage of 44 B-lymphocyte founders and their 631 progeny in vitro over a period of 108 hours. Using this data to train a Support Vector Machine classifier, we were retrospectively able to predict the fates of individual lymphocytes with more than 90% accuracy, using only time-lapse imaging captured prior to mitosis or death of 90% of all cells. The motivation for this paper is to explore the impact of labour-efficient assistive software tools that allow larger and more ambitious live-cell time-lapse microscopy studies. After training on this data, we show that machine learning methods can be used for realtime prediction of individual cell fates. These techniques could lead to realtime cell culture segregation for purposes such as phenotype screening. We were able to produce a large volume of data with less effort than previously reported, due to the image processing, computer vision, tracking and human-computer interaction tools used. We describe the workflow of the software-assisted experiments and the graphical interfaces that were needed. To validate our results we used our methods to reproduce a variety of published data about lymphocyte populations and behaviour. We also make all our data publicly available, including a large quantity of lymphocyte spatio-temporal dynamics and related lineage information. PMID:24404133
Lorenzen, Kai
2005-01-01
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. PMID:15713596
Population dynamics of minimally cognitive individuals. Part 2: Dynamics of time-dependent knowledge
Schmieder, R.W.
1995-07-01
The dynamical principle for a population of interacting individuals with mutual pairwise knowledge, presented by the author in a previous paper for the case of constant knowledge, is extended to include the possibility that the knowledge is time-dependent. Several mechanisms are presented by which the mutual knowledge, represented by a matrix K, can be altered, leading to dynamical equations for K(t). The author presents various examples of the transient and long time asymptotic behavior of K(t) for populations of relatively isolated individuals interacting infrequently in local binary collisions. Among the effects observed in the numerical experiments are knowledge diffusion, learning transients, and fluctuating equilibria. This approach will be most appropriate to small populations of complex individuals such as simple animals, robots, computer networks, agent-mediated traffic, simple ecosystems, and games. Evidence of metastable states and intermittent switching leads them to envision a spectroscopy associated with such transitions that is independent of the specific physical individuals and the population. Such spectra may serve as good lumped descriptors of the collective emergent behavior of large classes of populations in which mutual knowledge is an important part of the dynamics.
Schmieder, R.W.
1995-07-01
The author presents a new approach for modeling the dynamics of collections of objects with internal structure. Based on the fact that the behavior of an individual in a population is modified by its knowledge of other individuals, a procedure for accounting for knowledge in a population of interacting objects is presented. It is assumed that each object has partial (or complete) knowledge of some (or all) other objects in the population. The dynamical equations for the objects are then modified to include the effects of this pairwise knowledge. This procedure has the effect of projecting out what the population will do from the much larger space of what it could do, i.e., filtering or smoothing the dynamics by replacing the complex detailed physical model with an effective model that produces the behavior of interest. The procedure therefore provides a minimalist approach for obtaining emergent collective behavior. The use of knowledge as a dynamical quantity, and its relationship to statistical mechanics, thermodynamics, information theory, and cognition microstructure are discussed.
Population dynamics of microbial communities in the zebrafish gut
NASA Astrophysics Data System (ADS)
Jemielita, Matthew; Taormina, Michael; Burns, Adam; Hampton, Jennifer; Rolig, Annah; Wiles, Travis; Guillemin, Karen; Parthasarathy, Raghuveer
2015-03-01
The vertebrate intestine is home to a diverse microbial community, which plays a crucial role in the development and health of its host. Little is known about the population dynamics and spatial structure of this ecosystem, including mechanisms of growth and interactions between species. We have constructed an experimental model system with which to explore these issues, using initially germ-free larval zebrafish inoculated with defined communities of fluorescently tagged bacteria. Using light sheet fluorescence microscopy combined with computational image analysis we observe and quantify the entire bacterial community of the intestine during the first 24 hours of colonization, during which time the bacterial population grows from tens to tens of thousands of bacteria. We identify both individual bacteria and clusters of bacteria, and quantify the growth rate and spatial distribution of these distinct subpopulations. We find that clusters of bacteria grow considerably faster than individuals and are located in specific regions of the intestine. Imaging colonization by two species reveals spatial segregation and competition. These data and their analysis highlight the importance of spatial organization in the establishment of gut microbial communities, and can provide inputs to physical models of real-world ecological dynamics.
The model of fungal population dynamics affected by nystatin
NASA Astrophysics Data System (ADS)
Voychuk, Sergei I.; Gromozova, Elena N.; Sadovskiy, Mikhail G.
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
Human mobility patterns predict divergent epidemic dynamics among cities.
Dalziel, Benjamin D; Pourbohloul, Babak; Ellner, Stephen P
2013-09-01
The epidemic dynamics of infectious diseases vary among cities, but it is unclear how this is caused by patterns of infectious contact among individuals. Here, we ask whether systematic differences in human mobility patterns are sufficient to cause inter-city variation in epidemic dynamics for infectious diseases spread by casual contact between hosts. We analyse census data on the mobility patterns of every full-time worker in 48 Canadian cities, finding a power-law relationship between population size and the level of organization in mobility patterns, where in larger cities, a greater fraction of workers travel to work in a few focal locations. Similarly sized cities also vary in the level of organization in their mobility patterns, equivalent on average to the variation expected from a 2.64-fold change in population size. Systematic variation in mobility patterns is sufficient to cause significant differences among cities in infectious disease dynamics-even among cities of the same size-according to an individual-based model of airborne pathogen transmission parametrized with the mobility data. This suggests that differences among cities in host contact patterns are sufficient to drive differences in infectious disease dynamics and provides a framework for testing the effects of host mobility patterns in city-level disease data. PMID:23864593
Reversed optimality and predictive ecology: burrowing depth forecasts population change in a bivalve
van Gils, Jan A.; Kraan, Casper; Dekinga, Anne; Koolhaas, Anita; Drent, Jan; de Goeij, Petra; Piersma, Theunis
2008-01-01
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
Srimath-Tirumula-Peddinti, Ravi Chandra Pavan Kumar; Neelapu, Nageswara Rao Reddy; Sidagam, Naresh
2015-01-01
Background Malarial incidence, severity, dynamics and distribution of malaria are strongly determined by climatic factors, i.e., temperature, precipitation, and relative humidity. The objectives of the current study were to analyse and model the relationships among climate, vector and malaria disease in district of Visakhapatnam, India to understand malaria transmission mechanism (MTM). Methodology Epidemiological, vector and climate data were analysed for the years 2005 to 2011 in Visakhapatnam to understand the magnitude, trends and seasonal patterns of the malarial disease. Statistical software MINITAB ver. 14 was used for performing correlation, linear and multiple regression analysis. Results/Findings Perennial malaria disease incidence and mosquito population was observed in the district of Visakhapatnam with peaks in seasons. All the climatic variables have a significant influence on disease incidence as well as on mosquito populations. Correlation coefficient analysis, seasonal index and seasonal analysis demonstrated significant relationships among climatic factors, mosquito population and malaria disease incidence in the district of Visakhapatnam, India. Multiple regression and ARIMA (I) models are best suited models for modeling and prediction of disease incidences and mosquito population. Predicted values of average temperature, mosquito population and malarial cases increased along with the year. Developed MTM algorithm observed a major MTM cycle following the June to August rains and occurring between June to September and minor MTM cycles following March to April rains and occurring between March to April in the district of Visakhapatnam. Fluctuations in climatic factors favored an increase in mosquito populations and thereby increasing the number of malarial cases. Rainfall, temperatures (20°C to 33°C) and humidity (66% to 81%) maintained a warmer, wetter climate for mosquito growth, parasite development and malaria transmission. Conclusions/Significance Changes in climatic factors influence malaria directly by modifying the behaviour and geographical distribution of vectors and by changing the length of the life cycle of the parasite. PMID:26110279
World Trade, disease and Florida's animal populations. The changing dynamics.
Coffman, L M
2000-01-01
One of Florida's three leading economic industries is agriculture. Agriculture feeds and enhances the lives of millions of people in Florida, the United States, and the entire world. Agriculture in Florida results in more than $6 billion in farm cash receipts, employment for more than 60,000 people a month, more than $18 billion in farm-related economic activity and stretches from the farm gate to the state's supermarkets with an impact of nearly $45 billion. The domestic and wild animal populations of Florida, our unique relationship to the Caribbean, Atlantic Ocean, Gulf of Mexico, Central and South America, as well as tourism, diverse human population growth and immigration, all add to the complexity of an environment capable of establishing many animals, animal pests and diseases not native to the United States. Never before have the dynamics of disease control involved as much challenge and diversity. Is the balance at risk, or is the risk over-balanced? Can science, economics and politics blend to maintain this balance? How will the balance affect world trade, disease control and the animal populations of Florida? PMID:11193619
Allele dynamics plots for the study of evolutionary dynamics in viral populations.
Steinbrück, Lars; McHardy, Alice Carolyn
2011-01-01
Phylodynamic techniques combine epidemiological and genetic information to analyze the evolutionary and spatiotemporal dynamics of rapidly evolving pathogens, such as influenza A or human immunodeficiency viruses. We introduce 'allele dynamics plots' (AD plots) as a method for visualizing the evolutionary dynamics of a gene in a population. Using AD plots, we propose how to identify the alleles that are likely to be subject to directional selection. We analyze the method's merits with a detailed study of the evolutionary dynamics of seasonal influenza A viruses. AD plots for the major surface protein of seasonal influenza A (H3N2) and the 2009 swine-origin influenza A (H1N1) viruses show the succession of substitutions that became fixed in the evolution of the two viral populations. They also allow the early identification of those viral strains that later rise to predominance, which is important for the problem of vaccine strain selection. In summary, we describe a technique that reveals the evolutionary dynamics of a rapidly evolving population and allows us to identify alleles and associated genetic changes that might be under directional selection. The method can be applied for the study of influenza A viruses and other rapidly evolving species or viruses. PMID:20959296
Prediction of Platinum Prices Using Dynamically Weighted Mixture of Experts
Lubinsky, Baruch; Marwala, Tshilidzi
2008-01-01
Neural networks are powerful tools for classification and regression in static environments. This paper describes a technique for creating an ensemble of neural networks that adapts dynamically to changing conditions. The model separates the input space into four regions and each network is given a weight in each region based on its performance on samples from that region. The ensemble adapts dynamically by constantly adjusting these weights based on the current performance of the networks. The data set used is a collection of financial indicators with the goal of predicting the future platinum price. An ensemble with no weightings does not improve on the naive estimate of no weekly change; our weighting algorithm gives an average percentage error of 63% for twenty weeks of prediction.
Rational Prediction with Molecular Dynamics for Hit Identification
Nichols, Sara E; Swift, Robert V; Amaro, Rommie E
2012-01-01
Although the motions of proteins are fundamental for their function, for pragmatic reasons, the consideration of protein elasticity has traditionally been neglected in drug discovery and design. This review details protein motion, its relevance to biomolecular interactions and how it can be sampled using molecular dynamics simulations. Within this context, two major areas of research in structure-based prediction that can benefit from considering protein flexibility, binding site detection and molecular docking, are discussed. Basic classification metrics and statistical analysis techniques, which can facilitate performance analysis, are also reviewed. With hardware and software advances, molecular dynamics in combination with traditional structure-based prediction methods can potentially reduce the time and costs involved in the hit identification pipeline. PMID:23110535
Measuring predictability of autonomous network transitions into bursting dynamics.
Mofakham, Sima; Zochowski, Michal
2015-01-01
Understanding spontaneous transitions between dynamical modes in a network is of significant importance. These transitions may separate pathological and normal functions of the brain. In this paper, we develop a set of measures that, based on spatio-temporal features of network activity, predict autonomous network transitions from asynchronous to synchronous dynamics under various conditions. These metrics quantify spike-timing distributions within a narrow time window as a function of the relative location of the active neurons. We applied these metrics to investigate the properties of these transitions in excitatory-only and excitatory-and-inhibitory networks and elucidate how network topology, noise level, and cellular heterogeneity affect both the reliability and the timeliness of the predictions. The developed measures can be calculated in real time and therefore potentially applied in clinical situations. PMID:25855975
Brannon, Anna Margaret
1985-01-01
VICTIMS OF CHILD ABUSE AND PREDICIED ABUSIVE DISCIPIINARY STYLES IN A MIDDLE TO UPPER CLASS POPULATION A Thesis ANNA MARGAREl' BRANNON Subnitted to the Graduate College of Texas A&M University in partial fulfillment of the requirements... for the degree of MASTER OF SCIENCE May 1985 Major Subject: Psychology VICTIMS OF CHILD ABUSE AND PREDICTED ABUSIVE DISCIPLINARY STYLES IN A MIDDLE 'IO UPPER CLASS POPULATION A 'Ihesis by ANNA ~ BRANNON Approved as to style and content by: (harlene Mu...
Yang, Jiue-in; Benecke, Scott; Jeske, Daniel R.; Rocha, Fernando S.; Smith Becker, Jennifer; Timper, Patricia; Ole Becker, J.
2012-01-01
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. PMID:23481664
Effects of the infectious period distribution on predicted transitions in childhood disease dynamics
Krylova, Olga; Earn, David J. D.
2013-01-01
The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced ‘susceptible–exposed–infectious–removed’ (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible–infectious–removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions. PMID:23676892
PSO-BP Neural Network in Reservoir Parameter Dynamic Prediction
Liumei Zhang; Jianfeng Ma; Yichuan Wang; Shaowei Pan
2011-01-01
In compare with the traditional Artificial Neural Network, PSO-BP neutral network has fast convergence and is immune to local minimum. This paper presents an application of PSO-BP neural network for dynamic predicting small layer reservoir parameters of fault block E1f11-1 in well ZHuang 2. By defining input and output neuron number, our method firstly realizes quantization of input neuron. Then
Robust Model Predictive Control for Controlling Fast Vehicle Dynamics
T. Peni; J. Bokor
2006-01-01
This paper proposes a simple robust model predictive algorithm for discrete time uncertain systems having relatively fast dynamics, i.e. the time required to compute the next control action is the multiple of the sampling time. The method is based on the following concept: at time k the set of all possible k+N-th states is determined, and in the next N
Wang, Yao; Bronshtein, Tomer; Sarig, Udi; Nguyen, Evelyne Bao-Vi; Boey, Freddy Yin Chiang; Venkatraman, Subbu S; Machluf, Marcelle
2013-05-01
In most tissue engineering applications, understanding the factors affecting the growth dynamics of coculture systems is crucial for directing the population toward a desirable regenerative process. Yet, no comprehensive analysis method exists to quantify coculture population dynamics, let alone, a unifying model addressing the "environmental" factors influencing cell growth, all together. Here we suggest a modification of the Lotka-Volterra model to analyze the population dynamics of cocultured cells and predict their growth profiles for tissue engineering applications. This model, commonly used to describe the population dynamics of a prey and predator sharing a closed ecological niche, was found to fit our empirical data on cocultures of endothelial cells (ECs) and mesenchymal stem cells (MSCs) that have been widely investigated for their regenerative potential. Applying this model to cocultures of this sort allows us to quantify the effect that culturing conditions have on the way cell growth is affected by the same cells or by the other cells in the coculture. We found that in most cases, EC growth was inhibited by the same cells but promoted by MSCs. The principles resulting from this analysis can be used in various applications to guide the population toward a desired direction while shedding new light on the fundamental interactions between ECs and MSCs. Similar results were also demonstrated on complex substrates made from decellularized porcine cardiac extracellular matrix, where growth occurred only after coculturing ECs and MSCs together. Finally, this unique implementation of the Lotka-Volterra model may also be regarded as a roadmap for using such models with other potentially regenerative cocultures in various applications. PMID:23216214
Phylogenetic prediction of the maximum per capita rate of population growth
Fagan, William F.; Pearson, Yanthe E.; Larsen, Elise A.; Lynch, Heather J.; Turner, Jessica B.; Staver, Hilary; Noble, Andrew E.; Bewick, Sharon; Goldberg, Emma E.
2013-01-01
The maximum per capita rate of population growth, r, is a central measure of population biology. However, researchers can only directly calculate r when adequate time series, life tables and similar datasets are available. We instead view r as an evolvable, synthetic life-history trait and use comparative phylogenetic approaches to predict r for poorly known species. Combining molecular phylogenies, life-history trait data and stochastic macroevolutionary models, we predicted r for mammals of the Caniformia and Cervidae. Cross-validation analyses demonstrated that, even with sparse life-history data, comparative methods estimated r well and outperformed models based on body mass. Values of r predicted via comparative methods were in strong rank agreement with observed values and reduced mean prediction errors by approximately 68 per cent compared with two null models. We demonstrate the utility of our method by estimating r for 102 extant species in these mammal groups with unknown life-history traits. PMID:23720545
Whiteley, Andrew R; Spruell, Paul; Allendorf, Fred W
2004-12-01
Ecological and life history characteristics such as population size, dispersal pattern, and mating system mediate the influence of genetic drift and gene flow on population subdivision. Bull trout (Salvelinus confluentus) and mountain whitefish (Prosopium williamsoni) differ markedly in spawning location, population size and mating system. Based on these differences, we predicted that bull trout would have reduced genetic variation within and greater differentiation among populations compared with mountain whitefish. To test this hypothesis, we used microsatellite markers to determine patterns of genetic divergence for each species in the Clark Fork River, Montana, USA. As predicted, bull trout had a much greater proportion of genetic variation partitioned among populations than mountain whitefish. Among all sites, FST was seven times greater for bull trout (FST = 0.304 for bull trout, 0.042 for mountain whitefish. After removing genetically differentiated high mountain lake sites for each species FST, was 10 times greater for bull trout (FST = 0.176 for bull trout; FST = 0.018 for mountain whitefish). The same characteristics that affect dispersal patterns in these species also lead to predictions about the amount and scale of adaptive divergence among populations. We provide a theoretical framework that incorporates variation in ecological and life history factors, neutral divergence, and adaptive divergence to interpret how neutral and adaptive divergence might be correlates of ecological and life history factors. PMID:15548282
Decadal prediction of Sahel rainfall using dynamics-based indices
NASA Astrophysics Data System (ADS)
Otero, Noelia; Mohino, Elsa; Gaetani, Marco
2015-07-01
At decadal time scales, the capability of state-of-the-art atmosphere-ocean coupled climate models in predicting the precipitation in Sahel is assessed. A set of 14 models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) is selected and two experiments are analysed, namely initialized decadal hindcasts and forced historical simulations. Considering the strong linkage of the atmospheric circulation signatures over West Africa with the rainfall variability, this study aims to investigate the potential of using wind fields for decadal predictions. Namely, a West African monsoon index (WAMI) is defined, based on the coherence of low (925 hPa) and high (200 hPa) troposphere wind fields, which accounts for the intensity of the monsoonal circulation. A combined empirical orthogonal functions analysis is applied to explore the wind fields' covariance modes, and a set of indices is defined on the basis of the identified patterns. The WAMI predictive skill is assessed by comparing WAMI from coupled models with WAMI from reanalysis products and with a standardized precipitation index (SPI) from observations. Results suggest that the predictive skill is highly model dependent and it is strongly related to the WAMI definition. In addition, hindcasts are more skilful than historical simulations in both deterministic and probability forecasts, which suggests an added value of initialization for decadal predictability. Moreover, coupled models are more skilful in predicting the observed SPI than the WAMI obtained from reanalysis. WAMI performance is also compared with decadal predictions from CMIP5 models based on a Sahelian precipitation index, and an improvement in predictive skill is observed in some models when WAMI is used. Therefore, we conclude that dynamics-based indices are potentially more effective for decadal prediction of precipitation in Sahel than precipitation-based indices for those models in which Sahel rainfall variability is not well simulated. We thus recommend a two-fold approach when testing the performance of models in predicting Sahel rainfall, based not only on rainfall but also on the dynamics of the West African monsoon.
Juliano, Steven A.
ARTICLE Temperature Effects on the Dynamics of Aedes albopictus (Diptera: Culicidae) Populations the dynamics of caged populations of Aedes albopictus (Skuse). All cages were equipped with plastic beakers and by enhancing colonization due to rapid population growth. KEY WORDS Aedes albopictus, rate of increase
Holyoak, Marcel
. Advances in Ecological Research, Vol. 37: Population Dynamics and Laboratory Ecology 37:245- 271. 1 Several breakthroughs in ecological understanding of population dynamics have arisen through use in population ecology. We review these roles and also highlight new areas where protist model systems could
Evolutionary behaviour in ecological systems with trade-offs and non-equilibrium population dynamics
White, Andrew
Evolutionary behaviour in ecological systems with trade-offs and non-equilibrium population-history traits have assumed equilibrium underlying population dynamics. It is known that ecological systems can of Sheffield, Sheffield S10 2TN, UK ABSTRACT Question: Do non-equilibrium (cycles or chaos) population dynamics
Cutter, Asher D.
vol. 159, no. 2 the american naturalist february 2002 Population Ecology, Nonlinear Dynamics- ulation model, we explore the evolution of sociality within a population-ecology and nonlinear), the principles of population ecology can be applied to understand their growth and dynamics. In particular
Gao, Jianbo
partially capable of this has been introduced into population ecology. In fact, Hastings et al. [2] haveDirect characterization of chaotic and stochastic dynamics in a population model with strong have comparable but different influences on population dynamics. However, no simple analysis methods
2002 Blackwell Science Ltd Population dynamics of type I and II methanotrophic
Macalady, Jenn
© 2002 Blackwell Science Ltd Population dynamics of type I and II methanotrophic bacteria in rice. Temporal and spatial dynamics of methan- otroph populations in California rice paddies were quantified than methanotrophs. The lack of quantitative information about type I and type II populations
DISCRETE.:rIME DIFFERENCE MODEL FOR SIMULATING INTERACTING FISH POPULATION DYNAMICS
DISCRETE.:rIME DIFFERENCE MODEL FOR SIMULATING INTERACTING FISH POPULATION DYNAMICS C. ALLEN ATKINSON' ABSTRACI' The dynamics of interacting fish populations are modeled using a coupled set relationships analagous to the first-order expressions used in standard differential equation models. Population
BIO 320 Project on Population Dynamics 1. Due Friday, 8 December 2008, the last class meeting.
Caraco, Thomas
BIO 320 Project on Population Dynamics 1. Due Friday, 8 December 2008, the last class meeting. 2, infectious disease, or other population-dynamic process. You may choose to write your own equations basis of population biology. Project should examine a quantitative question (or questions) about
Periodically varying externally imposed environmental effects on population dynamics M. Ballard,1,2
Kenkre, V.M.
Periodically varying externally imposed environmental effects on population dynamics M. Ballard,1. INTRODUCTION The mathematical study of population dynamics has been a subject of great interest in recent years; published 28 September 2004) Effects of externally imposed periodic changes in the environment on population
A Cellular Model for Spatial Population Dynamics Chu Yue (Stella) Donga
Reiter, Clifford A.
1 A Cellular Model for Spatial Population Dynamics Chu Yue (Stella) Donga , James T. Longb in population dynamics. Cellular models classically consist of a regular, discrete arrangement of cells taking 9486, Easton, PA 18042, USA Abstract Interacting populations exhibit complex behavior in nature
Cocco, Simona
2013-01-01
fluctuations around the average dynamics. Here we do so for population time-series data from replicate replicate population dynamics experiments could be designed to optimize the acquired information of interestPHYSICAL REVIEW E 88, 062714 (2013) Trend and fluctuations: Analysis and design of population
Uncertainty estimation and prediction for interdisciplinary ocean dynamics
Lermusiaux, Pierre F.J. . E-mail: pierrel@pacific.harvard.edu
2006-09-01
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.
Accelerometry-based prediction of movement dynamics for balance monitoring.
Fuschillo, Valeria Lucia; Bagalŕ, Fabio; Chiari, Lorenzo; Cappello, Angelo
2012-09-01
This paper proposes a 2D functional evaluation tool for estimating subject-specific body segment parameters, which uses a simple motor task (repeated sit-to-stand, rSTS), recorded with one single-axis accelerometer (SAA) per segment and a force plate (FP). After this preliminary estimation, the accelerometer alone is used to make quasi-real-time predictions of ground reaction force (anterior/posterior, F ( X ), and vertical, F ( Z ), components), center of pressure (CoP) and center of mass (CoM), during rSTS and postural oscillation in the sagittal plane. These predicted dynamic variables, as well as those obtained using anthropometric parameters derived from De Leva, were compared to actual FP outputs in terms of root mean-squared errors (RMSEs). Using De Leva's parameters in place of those estimated, RMSEs increase from 12 to 21 N (F ( X )), from 21 to 24 N (F ( Z )), and from 21.1 to 55.6 mm (CoP) in rSTS; similarly, RMSEs increase from 3.1 to 3.3 N (F ( X )) and from 5.5 to 6.6 mm (CoP) in oscillatory trials. A telescopic inverted pendulum model was adopted to analyze the balance control in rSTS using only predicted CoP and CoM. Results suggest that one SAA per segment is sufficient to predict the dynamics of a biomechanical model of any degrees of freedom. PMID:22802142
Two-Speed Gearbox Dynamic Simulation Predictions and Test Validation
NASA Technical Reports Server (NTRS)
Lewicki, David G.; DeSmidt, Hans; Smith, Edward C.; Bauman, Steven W.
2010-01-01
Dynamic simulations and experimental validation tests were performed on a two-stage, two-speed gearbox as part of the drive system research activities of the NASA Fundamental Aeronautics Subsonics Rotary Wing Project. The gearbox was driven by two electromagnetic motors and had two electromagnetic, multi-disk clutches to control output speed. A dynamic model of the system was created which included a direct current electric motor with proportional-integral-derivative (PID) speed control, a two-speed gearbox with dual electromagnetically actuated clutches, and an eddy current dynamometer. A six degree-of-freedom model of the gearbox accounted for the system torsional dynamics and included gear, clutch, shaft, and load inertias as well as shaft flexibilities and a dry clutch stick-slip friction model. Experimental validation tests were performed on the gearbox in the NASA Glenn gear noise test facility. Gearbox output speed and torque as well as drive motor speed and current were compared to those from the analytical predictions. The experiments correlate very well with the predictions, thus validating the dynamic simulation methodologies.
Swallow, John G; Wallace, Lisa E; Christianson, Sarah J; Johns, Philip M; Wilkinson, Gerald S
2005-10-01
Stalk-eyed flies (Diptera: Diopsidae) possess eyes at the ends of elongated peduncles, and exhibit dramatic variation in eye span, relative to body length, among species. In some sexually dimorphic species, evidence indicates that eye span is under both intra- and intersexual selection. Theory predicts that isolated populations should evolve differences in sexually selected traits due to drift. To determine if eye span changes as a function of divergence time, 1370 flies from 10 populations of the sexually dimorphic species, Cyrtodiopsis dalmanni and Cyrtodiopsis whitei, and one population of the sexually monomorphic congener, Cyrtodiopsis quinqueguttata, were collected from Southeast Asia and measured. Genetic differentiation was used to assess divergence time by comparing mitochondrial (cytochrome oxidase II and 16S ribosomal RNA gene fragments) and nuclear (wingless gene fragment) DNA sequences for c. five individuals per population. Phylogenetic analyses indicate that most populations cluster as monophyletic units with up to 9% nucleotide substitutions between populations within a species. Analyses of molecular variance suggest a high degree of genetic structure within and among the populations; > 97% of the genetic variance occurs between populations and species while < 3% is distributed within populations, indicating that most populations have been isolated for thousands of years. Nevertheless, significant change in the allometric slope of male eye span on body length was detected for only one population of either dimorphic species. These results are not consistent with genetic drift. Rather, relative eye span appears to be under net stabilizing selection in most populations of stalk-eyed flies. Given that one population exhibited dramatic evolutionary change, selection, rather than genetic variation, appears to constrain eye span evolution. PMID:16202096
Coulson, Tim; MacNulty, Daniel R; Stahler, Daniel R; vonHoldt, Bridgett; Wayne, Robert K; Smith, Douglas W
2011-12-01
Environmental change has been observed to generate simultaneous responses in population dynamics, life history, gene frequencies, and morphology in a number of species. But how common are such eco-evolutionary responses to environmental change likely to be? Are they inevitable, or do they require a specific type of change? Can we accurately predict eco-evolutionary responses? We address these questions using theory and data from the study of Yellowstone wolves. We show that environmental change is expected to generate eco-evolutionary change, that changes in the average environment will affect wolves to a greater extent than changes in how variable it is, and that accurate prediction of the consequences of environmental change will probably prove elusive. PMID:22144626
Modeling community population dynamics with the open-source language R.
Green, Robin; Shou, Wenying
2014-01-01
The ability to explain biological phenomena with mathematics and to generate predictions from mathematical models is critical for understanding and controlling natural systems. Concurrently, the rise in open-source software has greatly increased the ease at which researchers can implement their own mathematical models. With a reasonably sound understanding of mathematics and programming skills, a researcher can quickly and easily use such tools for their own work. The purpose of this chapter is to expose the reader to one such tool, the open-source programming language R, and to demonstrate its practical application to studying population dynamics. We use the Lotka-Volterra predator-prey dynamics as an example. PMID:24838889
Population-level reinforcement learning resulting in smooth best response dynamics
Collins, Sean
Population-level reinforcement learning resulting in smooth best response dynamics David S. Leslie dynamics of evolutionary game theory. In contrast, we describe a population-level model which is characterised by the smooth best response dynamics, a system which is intrinsic to the theory of adaptive
Dynamic connectivity at rest predicts attention task performance.
Madhyastha, Tara M; Askren, Mary K; Boord, Peter; Grabowski, Thomas J
2015-02-01
Consistent spatial patterns of coherent activity, representing large-scale networks, have been reliably identified in multiple populations. Most often, these studies have examined "stationary" connectivity. However, there is a growing recognition that there is a wealth of information in the time-varying dynamics of networks which has neural underpinnings, which changes with age and disease and that supports behavior. Using factor analysis of overlapping sliding windows across 25 participants with Parkinson disease (PD) and 21 controls (ages 41-86), we identify factors describing the covarying correlations of regions (dynamic connectivity) within attention networks and the default mode network, during two baseline resting-state and task runs. Cortical regions that support attention networks are affected early in PD, motivating the potential utility of dynamic connectivity as a sensitive way to characterize physiological disruption to these networks. We show that measures of dynamic connectivity are more reliable than comparable measures of stationary connectivity. Factors in the dorsal attention network (DAN) and fronto-parietal task control network, obtained at rest, are consistently related to the alerting and orienting reaction time effects in the subsequent Attention Network Task. In addition, the same relationship between the same DAN factor and the alerting effect was present during tasks. Although reliable, dynamic connectivity was not invariant, and changes between factor scores across sessions were related to changes in accuracy. In summary, patterns of time-varying correlations among nodes in an intrinsic network have a stability that has functional relevance. PMID:25014419
Population dynamics of a meiotic/mitotic expansion model for the fragile X syndrome
Ashley, A.E.; Sherman, S.L.
1995-12-01
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 multi-pathway, 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, {open_quotes}contractions{close_quotes} 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. 42 refs., 4 figs., 4 tabs.
Maza-Márquez, P; Gómez-Silván, C; Gómez, M A; González-López, J; Martínez-Toledo, M V; Rodelas, B
2015-03-01
The community structure and population dynamics of Mycolata were monitored in a full-scale membrane bioreactor during four experimental phases under changing operating and environmental conditions, by means of temperature-gradient gel electrophoresis of partial 16S-rRNA genes amplified from community DNA and RNA templates (total and active populations). Non-metric multidimensional scaling and BIO-ENV analyses demonstrated that population dynamics were mostly explained (30-32%) by changes in the input of nutrients in the influent water and the accumulation of biomass in the bioreactors, while the influence of hydraulic and solid retention times, temperature and F/M ratio was minor. Significant correlations were observed between particular Mycolata phylotypes and one or more variables, contributing information for the prediction of their abundance and activity under changing conditions. Fingerprinting and multivariate analyses demonstrated that two foaming episodes, recorded at temperatures <20°C, were connected to the increase of the relative abundance of Mycolata unrelated to Gordonia amarae. PMID:25621724
Zooplankton population dynamics in experimentally toxified pond ecosystems
Sierszen, M.E.; Boston, H.L.; Horn, M.J.
1989-01-01
To evaluate ecosystem response to and recovery from toxic contamination, we added phenolic compounds to a series of experimental ponds. Toxicants were added repeatedly in a temporally staggered sequence to evaluate the influence of seasonal factors and previous exposure history on the responses to toxicant stress. We hypothesized that seasonal changes in ecosystem structure, e.g. shifts in the relative importance of ''top-down'' and ''bottom-up'' controls on energy flow, would influence the system-level responses to the toxicant. Information from these experiments is being incorporated into models that predict ecological risk and system-level behavior under toxicant stress. Here we focus on the responses of zooplankton populations to toxicants, and factors which may affect the apparent severity of toxic effects. 9 refs., 4 figs.
Modelling Lipid Competition Dynamics in Heterogeneous Protocell Populations
Shirt-Ediss, Ben; Ruiz-Mirazo, Kepa; Mavelli, Fabio; Solé, Ricard V.
2014-01-01
Recent experimental work in the field of synthetic protocell biology has shown that prebiotic vesicles are able to ‘steal’ lipids from each other. This phenomenon is driven purely by asymmetries in the physical state or composition of the vesicle membranes, and, when lipid resource is limited, translates directly into competition amongst the vesicles. Such a scenario is interesting from an origins of life perspective because a rudimentary form of cell-level selection emerges. To sharpen intuition about possible mechanisms underlying this behaviour, experimental work must be complemented with theoretical modelling. The aim of this paper is to provide a coarse-grain mathematical model of protocell lipid competition. Our model is capable of reproducing, often quantitatively, results from core experimental papers that reported distinct types vesicle competition. Additionally, we make some predictions untested in the lab, and develop a general numerical method for quickly solving the equilibrium point of a model vesicle population. PMID:25024020
Modelling Lipid Competition Dynamics in Heterogeneous Protocell Populations
NASA Astrophysics Data System (ADS)
Shirt-Ediss, Ben; Ruiz-Mirazo, Kepa; Mavelli, Fabio; Solé, Ricard V.
2014-07-01
Recent experimental work in the field of synthetic protocell biology has shown that prebiotic vesicles are able to `steal' lipids from each other. This phenomenon is driven purely by asymmetries in the physical state or composition of the vesicle membranes, and, when lipid resource is limited, translates directly into competition amongst the vesicles. Such a scenario is interesting from an origins of life perspective because a rudimentary form of cell-level selection emerges. To sharpen intuition about possible mechanisms underlying this behaviour, experimental work must be complemented with theoretical modelling. The aim of this paper is to provide a coarse-grain mathematical model of protocell lipid competition. Our model is capable of reproducing, often quantitatively, results from core experimental papers that reported distinct types vesicle competition. Additionally, we make some predictions untested in the lab, and develop a general numerical method for quickly solving the equilibrium point of a model vesicle population.
Chambert, Thierry; Rotella, Jay J; Higgs, Megan D
2014-04-01
The investigation of individual heterogeneity in vital rates has recently received growing attention among population ecologists. Individual heterogeneity in wild animal populations has been accounted for and quantified by including individually varying effects in models for mark-recapture data, but the real need for underlying individual effects to account for observed levels of individual variation has recently been questioned by the work of Tuljapurkar et al. (Ecology Letters, 12, 93, 2009) on dynamic heterogeneity. Model-selection approaches based on information criteria or Bayes factors have been used to address this question. Here, we suggest that, in addition to model-selection, model-checking methods can provide additional important insights to tackle this issue, as they allow one to evaluate a model's misfit in terms of ecologically meaningful measures. Specifically, we propose the use of posterior predictive checks to explicitly assess discrepancies between a model and the data, and we explain how to incorporate model checking into the inferential process used to assess the practical implications of ignoring individual heterogeneity. Posterior predictive checking is a straightforward and flexible approach for performing model checks in a Bayesian framework that is based on comparisons of observed data to model-generated replications of the data, where parameter uncertainty is incorporated through use of the posterior distribution. If discrepancy measures are chosen carefully and are relevant to the scientific context, posterior predictive checks can provide important information allowing for more efficient model refinement. We illustrate this approach using analyses of vital rates with long-term mark-recapture data for Weddell seals and emphasize its utility for identifying shortfalls or successes of a model at representing a biological process or pattern of interest. We show how posterior predictive checks can be used to strengthen inferences in ecological studies. We demonstrate the application of this method on analyses dealing with the question of individual reproductive heterogeneity in a population of Antarctic pinnipeds. PMID:24834335
Rhythmic Manipulation of Objects with Complex Dynamics: Predictability over Chaos
Nasseroleslami, Bahman; Hasson, Christopher J.; Sternad, Dagmar
2014-01-01
The study of object manipulation has been largely confined to discrete tasks, where accuracy, mechanical effort, or smoothness were examined to explain subjects' preferred movements. This study investigated a rhythmic manipulation task, which involved continuous interaction with a nonlinear object that led to unpredictable object behavior. Using a simplified virtual version of the task of carrying a cup of coffee, we studied how this unpredictable object behavior affected the selected strategies. The experiment was conducted in a virtual set-up, where subjects moved a cup with a ball inside, modeled by cart-and-pendulum dynamics. Inverse dynamics calculations of the system showed that performing the task with different amplitudes and relative phases required different force profiles and rendered the object's dynamics with different degrees of predictability (quantified by Mutual Information between the applied force and the cup kinematics and its sensitivity). Subjects (n?=?8) oscillated the virtual cup between two targets via a robotic manipulandum, paced by a metronome at 1 Hz for 50 trials, each lasting 45 s. They were free to choose their movement amplitude and relative phase between the ball and cup. Experimental results showed that subjects increased their movement amplitudes, which rendered the interactions with the object more predictable and with lower sensitivity to the execution variables. These solutions were associated with higher average exerted force and lower object smoothness, contradicting common expectations from studies on discrete object manipulation and unrestrained movements. Instead, the findings showed that humans selected strategies with higher predictability of interaction dynamics. This finding expressed that humans seek movement strategies where force and kinematics synchronize to repeatable patterns that may require less sensorimotor information processing. PMID:25340581
Particle tagging and its implications for stellar population dynamics
Bret, Theo Le; Cooper, Andrew P; Frenk, Carlos; Zolotov, Adi; Brooks, Alyson M; Governato, Fabio; Parry, Owen H
2015-01-01
We establish a controlled comparison between the properties of galactic stellar halos obtained with hydrodynamical simulations and with `particle tagging'. Tagging is a fast way to obtain stellar population dynamics: instead of tracking gas and star formation, it `paints' stars directly onto a suitably defined subset of dark matter particles in a collisionless, dark-matter-only simulation.Our study shows that there are conditions under which particle tagging generates good fits to the hydrodynamical stellar density profiles of a central Milky-Way-like galaxy and its most prominent substructure. Phase-space diffusion processes are crucial to reshaping the distribution of stars in infalling spheroidal systems and hence the final stellar halo. We conclude that the success of any particular tagging scheme hinges on this diffusion being taken into account, at a minimum by making use of `live' tagging schemes, in which particles are regularly tagged throughout the evolution of a galaxy.
On signals of phase transitions in salmon population dynamics.
Krkošek, Martin; Drake, John M
2014-06-01
Critical slowing down (CSD) reflects the decline in resilience of equilibria near a bifurcation and may reveal early warning signals (EWS) of ecological phase transitions. We studied CSD in the recruitment dynamics of 120 stocks of three Pacific salmon (Oncorhynchus spp.) species in relation to critical transitions in fishery models. Pink salmon (Oncorhynchus gorbuscha) exhibited increased variability and autocorrelation in populations that had a growth parameter, r, close to zero, consistent with EWS of extinction. However, models and data for sockeye salmon (Oncorhynchus nerka) indicate that portfolio effects from heterogeneity in age-at-maturity may obscure EWS. Chum salmon (Oncorhynchus keta) show intermediate results. The data do not reveal EWS of Ricker-type bifurcations that cause oscillations and chaos at high r. These results not only provide empirical support for CSD in some ecological systems, but also indicate that portfolio effects of age structure may conceal EWS of some critical transitions. PMID:24759855
Richards-like two species population dynamics model.
Ribeiro, Fabiano; Cabella, Brenno Caetano Troca; Martinez, Alexandre Souto
2014-12-01
The two-species population dynamics model is the simplest paradigm of inter- and intra-species interaction. Here, we present a generalized Lotka-Volterra model with intraspecific competition, which retrieves as particular cases, some well-known models. The generalization parameter is related to the species habitat dimensionality and their interaction range. Contrary to standard models, the species coupling parameters are general, not restricted to non-negative values. Therefore, they may represent different ecological regimes, which are derived from the asymptotic solution stability analysis and are represented in a phase diagram. In this diagram, we have identified a forbidden region in the mutualism regime, and a survival/extinction transition with dependence on initial conditions for the competition regime. Also, we shed light on two types of predation and competition: weak, if there are species coexistence, or strong, if at least one species is extinguished. PMID:25112794
Prediction of lung function response for populations exposed to a wide range of ozone conditions
Abstract Context: A human exposure-response (E-R) model that has previously been demonstrated to accurately predict population mean FEV1 response to ozone exposure has been proposed as the foundation for future risk assessments for ambient ozone. Objective: Fit the origi...
ERIC Educational Resources Information Center
Goodman, Anna; Goodman, Robert
2011-01-01
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…
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 ...
The Predictive Ability of IQ and Working Memory Scores in Literacy in an Adult Population
ERIC Educational Resources Information Center
Alloway, Tracy Packiam; Gregory, David
2013-01-01
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…
Evolutionary population genetics of promoters: Predicting binding sites and functional phylogenies
Lässig, Michael
Evolutionary population genetics of promoters: Predicting binding sites and functional phylogenies¨ lpicherstrasse 77, 50937 Cologne, Germany Edited by Tomoko Ohta, National Institute of Genetics, Mishima, Japan-binding sites in prokaryotes, using an empirically grounded model with point mutations and genetic drift
Over the next 50 years,the Earth's human population is predicted to increase from the
Aneja, Viney P.
Over the next 50 years,the Earth's human population is predicted to increase from the current 6 have profound envi- ronmental effects.Increased consumption of animal protein in developed of reactive nitrogen has led to deleterious effects on the environment,such as decreased visibility from
White, Douglas R.
Supplementary Material to the article by Peter Turchin and Andrey Korotayev "Population Dynamics and Internal Warfare: A Reconsideration" England 1450-1800: Population data Population numbers for the period of Wrigley et al was resampled at a decadal intervals. For the period 1450-1525 population data were taken
DRAFT VOL. 83, NO. 4, OCTOBER 2010 1 Structured Population Dynamics
Rebarber, Richard
DRAFT VOL. 83, NO. 4, OCTOBER 2010 1 Structured Population Dynamics: An Introduction to Integral territory? What are the best management op- tions to eradicate a population (pest species) or to facilitate population recovery (en- dangered species)? Population modeling helps answer these questions by integrating
610 Habitat quality and population density drive occupancy dynamics of snowshoe hare in variegated and population density. We examined the relative influence of area, structural isolation, habitat quality, local population density, and neighborhood popula- tion density (i.e. population density in the landscape around
Predicting individual brain maturity using dynamic functional connectivity
Qin, Jian; Chen, Shan-Guang; Hu, Dewen; Zeng, Ling-Li; Fan, Yi-Ming; Chen, Xiao-Ping; Shen, Hui
2015-01-01
Neuroimaging-based functional connectivity (FC) analyses have revealed significant developmental trends in specific intrinsic connectivity networks linked to cognitive and behavioral maturation. However, knowledge of how brain functional maturation is associated with FC dynamics at rest is limited. Here, we examined age-related differences in the temporal variability of FC dynamics with data publicly released by the Nathan Kline Institute (NKI; n = 183, ages 7–30) and showed that dynamic inter-region interactions can be used to accurately predict individual brain maturity across development. Furthermore, we identified a significant age-dependent trend underlying dynamic inter-network FC, including increasing variability of the connections between the visual network, default mode network (DMN) and cerebellum as well as within the cerebellum and DMN and decreasing variability within the cerebellum and between the cerebellum and DMN as well as the cingulo-opercular network. Overall, the results suggested significant developmental changes in dynamic inter-network interaction, which may shed new light on the functional organization of typical developmental brains. PMID:26236224
Although earthworms are known to influence agroecosystem processes, there are relatively few long-term studies addressing population dynamics under cropping systems in which earthworm populations were intentionally altered. We assessed earthworm communities from fall 1994 to spr...
[Biology and population dynamics of Porcellionides sexfasciatus (Crustacea, Isopoda, Oniscidea)].
Achouri, Mohamed Sghaďer; Charfi-Cheikhrouha, Faouzia
2002-05-01
The biology and the population dynamics of Porcellionides sexfasciatus Budde-Lund (1879) were studied on a field and carried out at Garat Nâam (Kasserine, Tunisia) from July 1996 to June 1998. The reproduction exhibited a seasonal pattern extending from February/March to October/November. The juveniles appeared in the population from April to November. Size frequency distributions were analysed and 14 cohorts were recognised during the sampling period. Six cohorts were identified at the first sampling and eight new ones on the other samplings. Among these latter cohorts, three were tracked till they disappeared. Minimum average length of new cohorts ranged from 3.07 +/- 0.35 mm to 3.47 +/- 0.2 mm. Maximum average length of cohorts was 10.42 mm. P. sexfasciatus is a semi-annual species (females producing two or three broods per year), with iteroparous and amphogenes females (females reproducing twice or more in their life and producing both males and females), and bivoltine life cycle (two generations per year). The females are able to produce two broods, in the laboratory, without new mating. Fecundity and fertility, corresponding to the number of eggs or embryos per brood, appeared positively correlated with females' size. Although oscillating throughout the year, the sex ratio was often in equilibrium. PMID:12187647
The role of resting cysts in Alexandrium minutum population dynamics
NASA Astrophysics Data System (ADS)
Estrada, Marta; Solé, Jordi; Anglčs, Sílvia; Garcés, Esther
2010-02-01
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.
Rodhouse, Thomas J; Ormsbee, Patricia C; Irvine, Kathryn M; Vierling, Lee A; Szewczak, Joseph M; Vierling, Kerri T
2012-06-01
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
Nevado, B; Mautner, S; Sturmbauer, C; Verheyen, E
2013-08-01
Understanding how genetic variation is generated and maintained in natural populations, and how this process unfolds in a changing environment, remains a central issue in biological research. In this work, we analysed patterns of genetic diversity from several populations of three cichlid species from Lake Tanganyika in parallel, using the mitochondrial DNA control region. We sampled populations inhabiting the littoral rocky habitats in both very deep and very shallow areas of the lake. We hypothesized that the former would constitute relatively older, more stable and genetically more diverse populations, because they should have been less severely affected by the well-documented episodes of dramatic water-level fluctuations. In agreement with our predictions, populations of all three species sampled in very shallow shorelines showed traces of stronger population growth than populations of the same species inhabiting deep shorelines. However, contrary to our working hypothesis, we found a significant trend towards increased genetic diversity in the younger, demographically less stable populations inhabiting shallow areas, in comparison with the older and more stable populations inhabiting the deep shorelines. We interpret this finding as the result of the establishment of metapopulation dynamics in the former shorelines, by the frequent perturbation and reshuffling of individuals between populations due to the lake-level fluctuations. The repeated succession of periods of allopatric separation and secondary contact is likely to have further increased the rapid pace of speciation in lacustrine cichlids. PMID:23837841
Predicting sports scoring dynamics with restoration and anti-persistence
Peel, Leto
2015-01-01
Professional team sports provide an excellent domain for studying the dynamics of social competitions. These games are constructed with simple, well-defined rules and payoffs that admit a high-dimensional set of possible actions and nontrivial scoring dynamics. The resulting gameplay and efforts to predict its evolution are the object of great interest to both sports professionals and enthusiasts. In this paper, we consider two online prediction problems for team sports:~given a partially observed game Who will score next? and ultimately Who will win? We present novel interpretable generative models of within-game scoring that allow for dependence on lead size (restoration) and on the last team to score (anti-persistence). We then apply these models to comprehensive within-game scoring data for four sports leagues over a ten year period. By assessing these models' relative goodness-of-fit we shed new light on the underlying mechanisms driving the observed scoring dynamics of each sport. Furthermore, in both p...
Do resting brain dynamics predict oddball evoked-potential?
2011-01-01
Background The oddball paradigm is widely applied to the investigation of cognitive function in neuroscience and in neuropsychiatry. Whether cortical oscillation in the resting state can predict the elicited oddball event-related potential (ERP) is still not clear. This study explored the relationship between resting electroencephalography (EEG) and oddball ERPs. The regional powers of 18 electrodes across delta, theta, alpha and beta frequencies were correlated with the amplitude and latency of N1, P2, N2 and P3 components of oddball ERPs. A multivariate analysis based on partial least squares (PLS) was applied to further examine the spatial pattern revealed by multiple correlations. Results Higher synchronization in the resting state, especially at the alpha spectrum, is associated with higher neural responsiveness and faster neural propagation, as indicated by the higher amplitude change of N1/N2 and shorter latency of P2. None of the resting quantitative EEG indices predict P3 latency and amplitude. The PLS analysis confirms that the resting cortical dynamics which explains N1/N2 amplitude and P2 latency does not show regional specificity, indicating a global property of the brain. Conclusions This study differs from previous approaches by relating dynamics in the resting state to neural responsiveness in the activation state. Our analyses suggest that the neural characteristics carried by resting brain dynamics modulate the earlier/automatic stage of target detection. PMID:22114868
Population dynamics of nitrifying bacteria in an aquatic ecosystem.
Kubo, Y; Takasu, F; Shimura, R; Nagaoka, S; Shigesada, N
1999-12-01
In a space environment such as Space Shuttle or Space Station, animal experiments with aquatic species in a closed system pose a crucial problem in maintaining their water quality for a long term. In nature, ammonia as an animal wastes is converted by nitrifying bacteria to nitrite or nitrate compounds, which usually become nitrogen sources for plants. Thus an application of the biological reactor with such bacteria attached on some filters has been suggested and experimentally studied for efficient waste managements of ammonia. Although some successful results were reported (Kozu et al. 1995, Nagaoka et al. 1998, Nakamura et al. 1997, 1998) in the space applications, purely empirical approaches have so far been taken to develop a biological filter having a stable nitrifying activity. In this study, we constructed a mathematical model to deal with the dynamics of the ammonia nitrifying processes in a biological reactor. The model describes population dynamics of the ammonia-oxidizing bacteria and the nitrite-oxidizing bacteria cultivated on the same filter. We estimated parameters involved in the model using the experimental data. The result shows that these estimated parameters could be applied to general cases and that the two bacteria are in a symbiotic relationship; they can better perform when both coexist, as has been empirically recognized. Based on the model analysis, we discuss how to prepare a high performance biological filter. PMID:11542799
Replication, Communication, and the Population Dynamics of Scientific Discovery
McElreath, Richard; Smaldino, Paul E.
2015-01-01
Many published research results are false (Ioannidis, 2005), and controversy continues over the roles of replication and publication policy in improving the reliability of research. Addressing these problems is frustrated by the lack of a formal framework that jointly represents hypothesis formation, replication, publication bias, and variation in research quality. We develop a mathematical model of scientific discovery that combines all of these elements. This model provides both a dynamic model of research as well as a formal framework for reasoning about the normative structure of science. We show that replication may serve as a ratchet that gradually separates true hypotheses from false, but the same factors that make initial findings unreliable also make replications unreliable. The most important factors in improving the reliability of research are the rate of false positives and the base rate of true hypotheses, and we offer suggestions for addressing each. Our results also bring clarity to verbal debates about the communication of research. Surprisingly, publication bias is not always an obstacle, but instead may have positive impacts—suppression of negative novel findings is often beneficial. We also find that communication of negative replications may aid true discovery even when attempts to replicate have diminished power. The model speaks constructively to ongoing debates about the design and conduct of science, focusing analysis and discussion on precise, internally consistent models, as well as highlighting the importance of population dynamics. PMID:26308448
Replication, Communication, and the Population Dynamics of Scientific Discovery.
McElreath, Richard; Smaldino, Paul E
2015-01-01
Many published research results are false (Ioannidis, 2005), and controversy continues over the roles of replication and publication policy in improving the reliability of research. Addressing these problems is frustrated by the lack of a formal framework that jointly represents hypothesis formation, replication, publication bias, and variation in research quality. We develop a mathematical model of scientific discovery that combines all of these elements. This model provides both a dynamic model of research as well as a formal framework for reasoning about the normative structure of science. We show that replication may serve as a ratchet that gradually separates true hypotheses from false, but the same factors that make initial findings unreliable also make replications unreliable. The most important factors in improving the reliability of research are the rate of false positives and the base rate of true hypotheses, and we offer suggestions for addressing each. Our results also bring clarity to verbal debates about the communication of research. Surprisingly, publication bias is not always an obstacle, but instead may have positive impacts-suppression of negative novel findings is often beneficial. We also find that communication of negative replications may aid true discovery even when attempts to replicate have diminished power. The model speaks constructively to ongoing debates about the design and conduct of science, focusing analysis and discussion on precise, internally consistent models, as well as highlighting the importance of population dynamics. PMID:26308448
The population dynamics of nitrifiers in ammonium-rich systems.
Raszka, Anna; Surmacz-Górska, Joanna; Zabczy?ski, Sebastian; Miksch, Korneliusz
2011-12-01
Non-optimal pH, dissolved oxygen concentration, the presence of toxic substances, or the influence of grazers are known to cause disturbances in nitrification. Because activated sludge is a mixture of different organisms, bacteria, and higher organisms, the stability of processes such as carbon removal, nitrification, denitrification, and dephosphatation depends on a range of interactions. These interactions occur both between and within trophic levels. Understanding of the ecology of microorganisms involved in bioprocesses is essential for effective control of startup and operation of a particular process. The aim of the study was to gain further insight into the dynamics of nitrifiers in activated sludge at various sludge ages while treating higher concentrations of ammonium. The results confirmed the importance of Nitrosococcus mobilis and Nitrobacter sp. as the dominant nitrifiers responsible for nitritation and nitratation, respectively, in the presence of unlimited ammonium. The size of the dominant bacteria colony was larger compared to the other species present and reached 25 microm. Problems with nitrification occurred in all high-ammonium loaded reactors. The dynamics of nitrifier population was monitored by oxygen uptake rate (OUR) using a test enabling the OUR measurement separately for ammonium-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB). The results reveal the hypersensitivity of nitrifiers to the substrate and products of incomplete nitrification. PMID:22368958
Modelling the impact of marine reserves on a population with depensatory dynamics.
Chan, Matthew H; Kim, Peter S
2014-09-01
In this study, we use a spatially implicit, stage-structured model to evaluate marine reserve effectiveness for a fish population exhibiting depensatory (strong Allee) effects in its dynamics. We examine the stability and sensitivity of the equilibria of the modelled system with regards to key system parameters and find that for a reasonable set of parameters, populations can be protected from a collapse if a small percentage of the total area is set aside in reserves. Furthermore, the overall abundance of the population is predicted to achieve a maximum at a certain ratio A of reserve area to fished area, which depends heavily on the other system parameters such as the net export rate of fish from the marine reserves to the fished areas. This finding runs contrary to the contested "equivalence at best" result when comparing fishery management through traditional catch or effort control and management through marine reserves. Lastly, we analyse the problem from a bioeconomics perspective by computing the optimal harvesting policy using Pontryagin's Maximum Principle, which suggests that the value for A which maximizes the optimal equilibrium fishery yield also maximizes population abundance when the cost per unit harvest is constant, but can increase substantially when the cost per unit harvest increases with the area being harvested. PMID:25124763
Dynamical evolution and spatial mixing of multiple population globular clusters
NASA Astrophysics Data System (ADS)
Vesperini, Enrico; McMillan, Stephen L. W.; D'Antona, Francesca; D'Ercole, Annibale
2013-03-01
Numerous spectroscopic and photometric observational studies have provided strong evidence for the widespread presence of multiple stellar populations in globular clusters. In this paper, we study the long-term dynamical evolution of multiple population clusters, focusing on the evolution of the spatial distributions of the first- (FG) and second-generation (SG) stars. In previous studies, we have suggested that SG stars formed from the ejecta of FG AGB stars are expected initially to be concentrated in the cluster inner regions. Here, by means of N-body simulations, we explore the time-scales and the dynamics of the spatial mixing of the FG and the SG populations and their dependence on the SG initial concentration. Our simulations show that, as the evolution proceeds, the radial profile of the SG/FG number ratio, NSG/NFG, is characterized by three regions: (1) a flat inner part; (2) a declining part in which FG stars are increasingly dominant and (3) an outer region where the NSG/NFG profile flattens again (the NSG/NFG profile may rise slightly again in the outermost cluster regions). Until mixing is complete and the NSG/NFG profile is flat over the entire cluster, the radial variation of NSG/NFG implies that the fraction of SG stars determined by observations covering a limited range of radial distances is not, in general, equal to the SG global fraction, (NSG/NFG)glob. The distance at which NSG/NFG equals (NSG/NFG)glob is approximately between 1 and 2 cluster half-mass radii. The time-scale for complete mixing depends on the SG initial concentration, but in all cases complete mixing is expected only for clusters in advanced evolutionary phases, having lost at least 60-70 per cent of their mass due to two-body relaxation (in addition to the early FG loss due to the cluster expansion triggered by SNII ejecta and gas expulsion).The results of our simulations suggest that in many Galactic globular clusters the SG should still be more spatially concentrated than the FG.
2012-01-01
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. PMID:23174043
Genomic predictions based on a joint reference population for the Nordic Red cattle breeds.
Zhou, L; Heringstad, B; Su, G; Guldbrandtsen, B; Meuwissen, T H E; Svendsen, M; Grove, H; Nielsen, U S; Lund, M S
2014-07-01
The main aim of this study was to compare accuracies of imputation and genomic predictions based on single and joint reference populations for Norwegian Red (NRF) and a composite breed (DFS) consisting of Danish Red, Finnish Ayrshire, and Swedish Red. The single nucleotide polymorphism (SNP) data for NRF consisted of 2 data sets: one including 25,000 markers (NRF25K) and the other including 50,000 markers (NRF50K). The NRF25K data set had 2,572 bulls, and the NRF50K data set had 1,128 bulls. Four hundred forty-two bulls were genotyped in both data sets (double-genotyped bulls). The DFS data set (DSF50K) included 50,000 markers of 13,472 individuals, of which around 4,700 were progeny-tested bulls. The NRF25K data set was imputed to 50,000 density using the software Beagle. The average error rate for the imputation of NRF25K decreased slightly from 0.023 to 0.021, and the correlation between observed and imputed genotypes changed from 0.935 to 0.936 when comparing the NRF50K reference and the NRF50K-DFS50K joint reference imputations. A genomic BLUP (GBLUP) model and a Bayesian 4-component mixture model were used to predict genomic breeding values for the NRF and DFS bulls based on the single and joint NRF and DFS reference populations. In the multiple population predictions, accuracies of genomic breeding values increased for the 3 production traits (milk, fat, and protein yields) for both NRF and DFS. Accuracies increased by 6 and 1.3 percentage points, on average, for the NRF and DFS bulls, respectively, using the GBLUP model, and by 9.3 and 1.3 percentage points, on average, using the Bayesian 4-component mixture model. However, accuracies for health or reproduction traits did not increase from the multiple population predictions. Among the 3 DFS populations, Swedish Red gained most in accuracies from the multiple population predictions, presumably because Swedish Red has a closer genetic relationship with NRF than Danish Red and Finnish Ayrshire. The Bayesian 4-component mixture model performed better than the GBLUP model for most production traits for both NRF and DFS, whereas no advantage was found for health or reproduction traits. In general, combining NRF and DFS reference populations was useful in genomic predictions for both the NRF and DFS bulls. PMID:24792791
Mackenzie, Brian R; Meier, H E Markus; Lindegren, Martin; Neuenfeldt, Stefan; Eero, Margit; Blenckner, Thorsten; Tomczak, Maciej T; Niiranen, Susa
2012-09-01
Understanding how climate change, exploitation and eutrophication will affect populations and ecosystems of the Baltic Sea can be facilitated with models which realistically combine these forcings into common frameworks. Here, we evaluate sensitivity of fish recruitment and population dynamics to past and future environmental forcings provided by three ocean-biogeochemical models of the Baltic Sea. Modeled temperature explained nearly as much variability in reproductive success of sprat (Sprattus sprattus; Clupeidae) as measured temperatures during 1973-2005, and both the spawner biomass and the temperature have influenced recruitment for at least 50 years. The three Baltic Sea models estimate relatively similar developments (increases) in biomass and fishery yield during twenty-first century climate change (ca. 28 % range among models). However, this uncertainty is exceeded by the one associated with the fish population model, and by the source of global climate data used by regional models. Knowledge of processes and biases could reduce these uncertainties. PMID:22926884
Transmembrane Topology and Signal Peptide Prediction Using Dynamic Bayesian Networks
Reynolds, Sheila M.; Käll, Lukas; Riffle, Michael E.; Bilmes, Jeff A.; Noble, William Stafford
2008-01-01
Hidden Markov models (HMMs) have been successfully applied to the tasks of transmembrane protein topology prediction and signal peptide prediction. In this paper we expand upon this work by making use of the more powerful class of dynamic Bayesian networks (DBNs). Our model, Philius, is inspired by a previously published HMM, Phobius, and combines a signal peptide submodel with a transmembrane submodel. We introduce a two-stage DBN decoder that combines the power of posterior decoding with the grammar constraints of Viterbi-style decoding. Philius also provides protein type, segment, and topology confidence metrics to aid in the interpretation of the predictions. We report a relative improvement of 13% over Phobius in full-topology prediction accuracy on transmembrane proteins, and a sensitivity and specificity of 0.96 in detecting signal peptides. We also show that our confidence metrics correlate well with the observed precision. In addition, we have made predictions on all 6.3 million proteins in the Yeast Resource Center (YRC) database. This large-scale study provides an overall picture of the relative numbers of proteins that include a signal-peptide and/or one or more transmembrane segments as well as a valuable resource for the scientific community. All DBNs are implemented using the Graphical Models Toolkit. Source code for the models described here is available at http://noble.gs.washington.edu/proj/philius. A Philius Web server is available at http://www.yeastrc.org/philius, and the predictions on the YRC database are available at http://www.yeastrc.org/pdr. PMID:18989393
A dynamic programming algorithm for RNA structure prediction including pseudoknots.
Rivas, E; Eddy, S R
1999-02-01
We describe a dynamic programming algorithm for predicting optimal RNA secondary structure, including pseudoknots. The algorithm has a worst case complexity of O(N6) in time and O(N4) in storage. The description of the algorithm is complex, which led us to adopt a useful graphical representation (Feynman diagrams) borrowed from quantum field theory. We present an implementation of the algorithm that generates the optimal minimum energy structure for a single RNA sequence, using standard RNA folding thermodynamic parameters augmented by a few parameters describing the thermodynamic stability of pseudoknots. We demonstrate the properties of the algorithm by using it to predict structures for several small pseudoknotted and non-pseudoknotted RNAs. Although the time and memory demands of the algorithm are steep, we believe this is the first algorithm to be able to fold optimal (minimum energy) pseudoknotted RNAs with the accepted RNA thermodynamic model. PMID:9925784
Cooperative Bacterial Growth Dynamics Predict the Evolution of Antibiotic Resistance
NASA Astrophysics Data System (ADS)
Artemova, Tatiana; Gerardin, Ylaine; Hsin-Jung Li, Sophia; Gore, Jeff
2011-03-01
Since the discovery of penicillin, antibiotics have been our primary weapon against bacterial infections. Unfortunately, bacteria can gain resistance to penicillin by acquiring the gene that encodes beta-lactamase, which inactivates the antibiotic. However, mutations in this gene are necessary to degrade the modern antibiotic cefotaxime. Understanding the conditions that favor the spread of these mutations is a challenge. Here we show that bacterial growth in beta-lactam antibiotics is cooperative and that the nature of this growth determines the conditions in which resistance evolves. Quantitative analysis of the growth dynamics predicts a peak in selection at very low antibiotic concentrations; competition between strains confirms this prediction. We also find significant selection at higher antibiotic concentrations, close to the minimum inhibitory concentrations of the strains. Our results argue that an understanding of the evolutionary forces that lead to antibiotic resistance requires a quantitative understanding of the evolution of cooperation in bacteria.
Modified Newtonian dynamics as a prediction of general relativity
Rahman, S
2006-01-01
We treat the physical vacuum as a featureless relativistic continuum in motion, and explore its consequences. Proceeding in a step-by-step manner, we are able to show that the equations of classical electrodynamics follow from the motion of a space-filling fluid of neutral spinors which we identify with neutrinos. The model predicts that antimatter has negative mass, and that neutrinos are matter-antimatter dipoles. Together these suffice to explain the presence of modified Newtonian dynamics as a gravitational polarisation effect. The existence of antigravity could resolve other major outstanding issues in cosmology, including the rate of expansion of the universe and its flatness, the origin of gamma ray bursts, and the smallness of the cosmological constant. If our model is correct then all of these observations are non-trivial predictions of Einstein's general theory of relativity.
Seasonal coastal sea level prediction using a dynamical model
NASA Astrophysics Data System (ADS)
McIntosh, Peter C.; Church, John A.; Miles, Elaine R.; Ridgway, Ken; Spillman, Claire M.
2015-08-01
Sea level varies on a range of time scales from tidal to decadal and centennial change. To date, little attention has been focussed on the prediction of interannual sea level anomalies. Here we demonstrate that forecasts of coastal sea level anomalies from the dynamical Predictive Ocean Atmosphere Model for Australia (POAMA) have significant skill throughout the equatorial Pacific and along the eastern boundaries of the Pacific and Indian Oceans at lead times out to 8 months. POAMA forecasts for the western Pacific generally have greater skill than persistence, particularly at longer lead times. POAMA also has comparable or greater skill than previously published statistical forecasts from both a Markov model and canonical correlation analysis. Our results indicate the capability of physically based models to address the challenge of providing skillful forecasts of seasonal sea level fluctuations for coastal communities over a broad area and at a range of lead times.
Usefulness of multiparental populations of maize (Zea mays L.) for genome-based prediction.
Lehermeier, Christina; Krämer, Nicole; Bauer, Eva; Bauland, Cyril; Camisan, Christian; Campo, Laura; Flament, Pascal; Melchinger, Albrecht E; Menz, Monica; Meyer, Nina; Moreau, Laurence; Moreno-González, Jesús; Ouzunova, Milena; Pausch, Hubert; Ranc, Nicolas; Schipprack, Wolfgang; Schönleben, Manfred; Walter, Hildrun; Charcosset, Alain; Schön, Chris-Carolin
2014-09-01
The efficiency of marker-assisted prediction of phenotypes has been studied intensively for different types of plant breeding populations. However, one remaining question is how to incorporate and counterbalance information from biparental and multiparental populations into model training for genome-wide prediction. To address this question, we evaluated testcross performance of 1652 doubled-haploid maize (Zea mays L.) lines that were genotyped with 56,110 single nucleotide polymorphism markers and phenotyped for five agronomic traits in four to six European environments. The lines are arranged in two diverse half-sib panels representing two major European heterotic germplasm pools. The data set contains 10 related biparental dent families and 11 related biparental flint families generated from crosses of maize lines important for European maize breeding. With this new data set we analyzed genome-based best linear unbiased prediction in different validation schemes and compositions of estimation and test sets. Further, we theoretically and empirically investigated marker linkage phases across multiparental populations. In general, predictive abilities similar to or higher than those within biparental families could be achieved by combining several half-sib families in the estimation set. For the majority of families, 375 half-sib lines in the estimation set were sufficient to reach the same predictive performance of biomass yield as an estimation set of 50 full-sib lines. In contrast, prediction across heterotic pools was not possible for most cases. Our findings are important for experimental design in genome-based prediction as they provide guidelines for the genetic structure and required sample size of data sets used for model training. PMID:25236445
Nonlinearities Lead to Qualitative Differences in Population Dynamics of Predator-Prey Systems
Ameixa, Olga M. C. C.; Messelink, Gerben J.; Kindlmann, Pavel
2013-01-01
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
Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks
Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir
2014-01-01
Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques. PMID:25157950
Meng, Ran; Chang, Silvia D.; Jones, Edward C.; Goldenberg, S. Larry; Kozlowski, Piotr
2010-01-01
Rationale and objective To test whether individually measured Arterial Input Function (AIF) provides more accurate prostate cancer diagnosis then population average AIF when DCE MRI data are acquired with limited temporal resolution. Material and methods 26 patients with a high clinical suspicion for prostate caner and no prior treatment underwent Dynamic Contrast Enhanced (DCE) MRI examination at 3.0 T prior to biopsy. DCE MRI data were fitted to a pharmacokinetic model using three forms of AIF: an individually measured, a local population average, and a literature double exponential population average. Receiver Operating Characteristic (ROC) analysis was used to correlate MRI with the biopsy results. Goodness of fit (?2) for the three AIFs was compared using non-parametric Mann-Whitney test. Results Average Ktrans values were significantly higher in tumour than in normal peripheral zone for all three AIFs. The individually measured and the local population average AIFs had the highest sensitivity (76%), while the double exponential AIF had the highest specificity (82%). The areas under the ROC curves were not significantly different between any of the AIFs (0.81, 0.76, and 0.81 for the individually measured, local population average and double exponential AIFs respectively). ?2 was not significantly different for the 3 AIFs, however, it was significantly higher in enhancing than in non-enhancing regions for all 3 AIFs. Conclusions These results suggest that, when DCE MRI data are acquired with limited temporal resolution, experimentally measured individual AIF is not significantly better than population average AIF in predicting the biopsy results in prostate cancer. PMID:20074982
Local predictability and information flow in complex dynamical systems
NASA Astrophysics Data System (ADS)
Liang, X. San
2013-04-01
Predictability is by observation a local notion in complex dynamical systems. Its spatiotemporal structure implies a flow, or transfer in discrete cases, of information that redistributes the local predictability within the state space of concern. Information flow is a fundamental concept in general physics which has applications in a wide variety of disciplines such as neuroscience, material science, atmosphere-ocean science, and turbulence research, to name but a few. In this study, it is rigorously formulated with respect to relative entropy within the framework of a system with many components, each signifying a location or a structure. Given a component, the mechanism governing the evolution of its predictability can be classified into two groups, one due to the component itself, another due to a transfer of information from its peers. A measure of the transfer is rigorously derived, and an explicit expression obtained. This measure possesses a form reminiscent of that we have obtained before with respect to absolute entropy in [X.S. Liang and R. Kleeman, A rigorous formalism of information transfer between dynamical system components, Physica D 227 (2007) 173-182]; in particular, when the system is of dimensionality 2, there is no difference between the formalisms with respect to absolute entropy and relative entropy, except for a minus sign. Properties have been explored and discussed; particularly discussed is the property of asymmetry or causality, which states that information transfer from one component to another carries no hint about the transfer in the other direction, in contrast to the transfer of other quantities such as energy. This formalism has been applied to the study of the scale-scale interaction and information transfer between the first two modes of the truncated Burgers equation. It is found that all 12 transfers are essentially zero or negligible, save for a strong transfer between the sine components from the low-frequency mode to the high-frequency mode. That is to say, the predictability of the high-frequency mode is controlled by the knowledge of the low-frequency mode. This result, though from a highly idealized system, has interesting implications about the dynamical closure problem in turbulence research and atmosphere-ocean science, i.e., the subgrid processes may to some extent be parameterized by the large-scale dynamics. This study can be adopted to investigate the propagation of uncertainties in fluid flows, which has important applications in problems such as atmospheric observing platform design, and may be utilized to identify the route of information flowing within a complex network.
Dynamics of Populations of Planetary Systems (IAU C197)
NASA Astrophysics Data System (ADS)
Knezevic, Zoran; Milani, Andrea
2005-05-01
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
Population structure in the native range predicts the spread of introduced marine species
Gaither, Michelle R.; Bowen, Brian W.; Toonen, Robert J.
2013-01-01
Forecasting invasion success remains a fundamental challenge in invasion biology. The effort to identify universal characteristics that predict which species become invasive has faltered in part because of the diversity of taxa and systems considered. Here, we use an alternative approach focused on the spread stage of invasions. FST, a measure of alternative fixation of alleles, is a common proxy for realized dispersal among natural populations, summarizing the combined influences of life history, behaviour, habitat requirements, population size, history and ecology. We test the hypothesis that population structure in the native range (FST) is negatively correlated with the geographical extent of spread of marine species in an introduced range. An analysis of the available data (29 species, nine phyla) revealed a significant negative correlation (R2 = 0.245–0.464) between FST and the extent of spread of non-native species. Mode FST among pairwise comparisons between populations in the native range demonstrated the highest predictive power (R2 = 0.464, p < 0.001). There was significant improvement when marker type was considered, with mtDNA datasets providing the strongest relationship (n = 21, R2 = 0.333–0.516). This study shows that FST can be used to make qualitative predictions concerning the geographical extent to which a non-native marine species will spread once established in a new area. PMID:23595272
Population structure in the native range predicts the spread of introduced marine species.
Gaither, Michelle R; Bowen, Brian W; Toonen, Robert J
2013-06-01
Forecasting invasion success remains a fundamental challenge in invasion biology. The effort to identify universal characteristics that predict which species become invasive has faltered in part because of the diversity of taxa and systems considered. Here, we use an alternative approach focused on the spread stage of invasions. FST, a measure of alternative fixation of alleles, is a common proxy for realized dispersal among natural populations, summarizing the combined influences of life history, behaviour, habitat requirements, population size, history and ecology. We test the hypothesis that population structure in the native range (FST) is negatively correlated with the geographical extent of spread of marine species in an introduced range. An analysis of the available data (29 species, nine phyla) revealed a significant negative correlation (R(2) = 0.245-0.464) between FST and the extent of spread of non-native species. Mode FST among pairwise comparisons between populations in the native range demonstrated the highest predictive power (R(2) = 0.464, p < 0.001). There was significant improvement when marker type was considered, with mtDNA datasets providing the strongest relationship (n = 21, R(2) = 0.333-0.516). This study shows that FST can be used to make qualitative predictions concerning the geographical extent to which a non-native marine species will spread once established in a new area. PMID:23595272
Satellite Microwave Remote Sensing for Environmental Modeling of Mosquito Population Dynamics.
Chuang, Ting-Wu; Henebry, Geoffrey M; Kimball, John S; Vanroekel-Patton, Denise L; Hildreth, Michael B; Wimberly, Michael C
2012-10-01
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. PMID:23049143
Cetinba?, Murat; Shakhnovich, Eugene I
2013-01-01
Although molecular chaperones are essential components of protein homeostatic machinery, their mechanism of action and impact on adaptation and evolutionary dynamics remain controversial. Here we developed a physics-based ab initio multi-scale model of a living cell for population dynamics simulations to elucidate the effect of chaperones on adaptive evolution. The 6-loci genomes of model cells encode model proteins, whose folding and interactions in cellular milieu can be evaluated exactly from their genome sequences. A genotype-phenotype relationship that is based on a simple yet non-trivially postulated protein-protein interaction (PPI) network determines the cell division rate. Model proteins can exist in native and molten globule states and participate in functional and all possible promiscuous non-functional PPIs. We find that an active chaperone mechanism, whereby chaperones directly catalyze protein folding, has a significant impact on the cellular fitness and the rate of evolutionary dynamics, while passive chaperones, which just maintain misfolded proteins in soluble complexes have a negligible effect on the fitness. We find that by partially releasing the constraint on protein stability, active chaperones promote a deeper exploration of sequence space to strengthen functional PPIs, and diminish the non-functional PPIs. A key experimentally testable prediction emerging from our analysis is that down-regulation of chaperones that catalyze protein folding significantly slows down the adaptation dynamics. PMID:24244114
Effects of plant genotype and insect dispersal rate on the population dynamics of a forest pest.
Moran, Emily V; Bewick, Sharon; Cobbold, Christina A
2013-12-01
It has been shown that plant genotype can strongly affect not only individual herbivore performance, but also community composition and ecosystem function. Few studies, however, have addressed how plant genotype affects herbivore population dynamics. In this paper, we used a simulation modeling approach to ask how the genetic composition of a forest influences pest outbreak dynamics, using the example of aspen (Populus tremuloides) and forest tent caterpillars (FTC; Malacosoma disstria). Specifically, we examined how plant genotype, the relative size of genotypic patches, and the rate of insect dispersal between them, affect the frequency, amplitude, and duration of outbreaks. We found that coupling two different genotypes does not necessarily result in an averaging of insect dynamics. Instead, depending on the ratio of patch sizes, when dispersal rates are moderate, outbreaks in the two-genotype case may be more or less severe than in forests of either genotype alone. Thresholds for different dynamic behaviors were similar for all genotypic combinations. Thus, the qualitative behavior of a stand of two different genotypes can be predicted based on the response of the insect to each genotype, the relative sizes of the two patches, and the scale of insect dispersal. PMID:24597225
Montane refugia predict population genetic structure in the Large-blotched Ensatina salamander.
Devitt, Thomas J; Devitt, Susan E Cameron; Hollingsworth, Bradford D; McGuire, Jimmy A; Moritz, Craig
2013-03-01
Understanding the biotic consequences of Pleistocene range shifts and fragmentation remains a fundamental goal in historical biogeography and evolutionary biology. Here, we combine species distribution models (SDM) from the present and two late Quaternary time periods with multilocus genetic data (mitochondrial DNA and microsatellites) to evaluate the effect of climate-induced habitat shifts on population genetic structure in the Large-blotched Ensatina (Ensatina eschscholtzii klauberi), a plethodontid salamander endemic to middle and high-elevation conifer forest in the Transverse and Peninsular Ranges of southern California and northern Baja California. A composite SDM representing the range through time predicts two disjunct refugia, one in southern California encompassing the core of the species range and the other in the Sierra San Pedro Mártir of northern Baja California at the southern limit of the species range. Based on our spatial model, we would expect a pattern of high connectivity among populations within the northern refugium and, conversely, a pattern of isolation due to long-term persistence of the Sierra San Pedro Mártir population. Our genetic results are consistent with these predictions based on the hypothetical refugia in that (i) historical measures of population connectivity among stable areas are correlated with gene flow estimates; and (ii) there is strong geographical structure between separate refugia. These results provide evidence for the role of recent climatic change in shaping patterns of population persistence and connectivity within the Transverse and Peninsular Ranges, an evolutionary hotspot. PMID:23379992
Augustin, Jean-Christophe; Ferrier, Rachel; Hezard, Bernard; Lintz, Adrienne; Stahl, Valérie
2015-02-01
Individual-based modeling (IBM) approach combined with the microenvironment modeling of vacuum-packed cold-smoked salmon was more effective to describe the variability of the growth of a few Listeria monocytogenes cells contaminating irradiated salmon slices than the traditional population models. The IBM approach was particularly relevant to predict the absence of growth in 25% (5 among 20) of artificially contaminated cold-smoked salmon samples stored at 8 °C. These results confirmed similar observations obtained with smear soft cheese (Ferrier et al., 2013). These two different food models were used to compare the IBM/microscale and population/macroscale modeling approaches in more global exposure and risk assessment frameworks taking into account the variability and/or the uncertainty of the factors influencing the growth of L. monocytogenes. We observed that the traditional population models significantly overestimate exposure and risk estimates in comparison to IBM approach when contamination of foods occurs with a low number of cells (<100 per serving). Moreover, the exposure estimates obtained with the population model were characterized by a great uncertainty. The overestimation was mainly linked to the ability of IBM to predict no growth situations rather than the consideration of microscale environment. On the other hand, when the aim of quantitative risk assessment studies is only to assess the relative impact of changes in control measures affecting the growth of foodborne bacteria, the two modeling approach gave similar results and the simplest population approach was suitable. PMID:25500386
PCI-SS: MISO dynamic nonlinear protein secondary structure prediction
Green, James R; Korenberg, Michael J; Aboul-Magd, Mohammed O
2009-01-01
Background Since the function of a protein is largely dictated by its three dimensional configuration, determining a protein's structure is of fundamental importance to biology. Here we report on a novel approach to determining the one dimensional secondary structure of proteins (distinguishing ?-helices, ?-strands, and non-regular structures) from primary sequence data which makes use of Parallel Cascade Identification (PCI), a powerful technique from the field of nonlinear system identification. Results Using PSI-BLAST divergent evolutionary profiles as input data, dynamic nonlinear systems are built through a black-box approach to model the process of protein folding. Genetic algorithms (GAs) are applied in order to optimize the architectural parameters of the PCI models. The three-state prediction problem is broken down into a combination of three binary sub-problems and protein structure classifiers are built using 2 layers of PCI classifiers. Careful construction of the optimization, training, and test datasets ensures that no homology exists between any training and testing data. A detailed comparison between PCI and 9 contemporary methods is provided over a set of 125 new protein chains guaranteed to be dissimilar to all training data. Unlike other secondary structure prediction methods, here a web service is developed to provide both human- and machine-readable interfaces to PCI-based protein secondary structure prediction. This server, called PCI-SS, is available at . In addition to a dynamic PHP-generated web interface for humans, a Simple Object Access Protocol (SOAP) interface is added to permit invocation of the PCI-SS service remotely. This machine-readable interface facilitates incorporation of PCI-SS into multi-faceted systems biology analysis pipelines requiring protein secondary structure information, and greatly simplifies high-throughput analyses. XML is used to represent the input protein sequence data and also to encode the resulting structure prediction in a machine-readable format. To our knowledge, this represents the only publicly available SOAP-interface for a protein secondary structure prediction service with published WSDL interface definition. Conclusion Relative to the 9 contemporary methods included in the comparison cascaded PCI classifiers perform well, however PCI finds greatest application as a consensus classifier. When PCI is used to combine a sequence-to-structure PCI-based classifier with the current leading ANN-based method, PSIPRED, the overall error rate (Q3) is maintained while the rate of occurrence of a particularly detrimental error is reduced by up to 25%. This improvement in BAD score, combined with the machine-readable SOAP web service interface makes PCI-SS particularly useful for inclusion in a tertiary structure prediction pipeline. PMID:19615046
Kumar, Vikas; de Barros, Felipe P J; Schuhmacher, Marta; Fernŕndez-Garcia, Daniel; Sanchez-Vila, Xavier
2013-12-15
We study the time dependent interaction between hydrogeological and exposure parameters in daily dose predictions due to exposure of humans to groundwater contamination. Dose predictions are treated stochastically to account for an incomplete hydrogeological and geochemical field characterization, and an incomplete knowledge of the physiological response. We used a nested Monte Carlo framework to account for uncertainty and variability arising from both hydrogeological and exposure variables. Our interest is in the temporal dynamics of the total dose and their effects on parametric uncertainty reduction. We illustrate the approach to a HCH (lindane) pollution problem at the Ebro River, Spain. The temporal distribution of lindane in the river water can have a strong impact in the evaluation of risk. The total dose displays a non-linear effect on different population cohorts, indicating the need to account for population variability. We then expand the concept of Comparative Information Yield Curves developed earlier (see de Barros et al. [29]) to evaluate parametric uncertainty reduction under temporally variable exposure dose. Results show that the importance of parametric uncertainty reduction varies according to the temporal dynamics of the lindane plume. The approach could be used for any chemical to aid decision makers to better allocate resources towards reducing uncertainty. PMID:24011618
Santos, Sílvio B.; Carvalho, Carla; Azeredo, Joana; Ferreira, Eugénio C.
2014-01-01
The prevalence and impact of bacteriophages in the ecology of bacterial communities coupled with their ability to control pathogens turn essential to understand and predict the dynamics between phage and bacteria populations. To achieve this knowledge it is essential to develop mathematical models able to explain and simulate the population dynamics of phage and bacteria. We have developed an unstructured mathematical model using delay-differential equations to predict the interactions between a broad-host-range Salmonella phage and its pathogenic host. The model takes into consideration the main biological parameters that rule phage-bacteria interactions likewise the adsorption rate, latent period, burst size, bacterial growth rate, and substrate uptake rate, among others. The experimental validation of the model was performed with data from phage-interaction studies in a 5 L bioreactor. The key and innovative aspect of the model was the introduction of variations in the latent period and adsorption rate values that are considered as constants in previous developed models. By modelling the latent period as a normal distribution of values and the adsorption rate as a function of the bacterial growth rate it was possible to accurately predict the behaviour of the phage-bacteria population. The model was shown to predict simulated data with a good agreement with the experimental observations and explains how a lytic phage and its host bacteria are able to coexist. PMID:25051248