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Sample records for predicting population dynamics

  1. Predicting when climate-driven phenotypic change affects population dynamics.

    PubMed

    McLean, Nina; Lawson, Callum R; Leech, Dave I; van de Pol, Martijn

    2016-06-01

    Species' responses to climate change are variable and diverse, yet our understanding of how different responses (e.g. physiological, behavioural, demographic) relate and how they affect the parameters most relevant for conservation (e.g. population persistence) is lacking. Despite this, studies that observe changes in one type of response typically assume that effects on population dynamics will occur, perhaps fallaciously. We use a hierarchical framework to explain and test when impacts of climate on traits (e.g. phenology) affect demographic rates (e.g. reproduction) and in turn population dynamics. Using this conceptual framework, we distinguish four mechanisms that can prevent lower-level responses from impacting population dynamics. Testable hypotheses were identified from the literature that suggest life-history and ecological characteristics which could predict when these mechanisms are likely to be important. A quantitative example on birds illustrates how, even with limited data and without fully-parameterized population models, new insights can be gained; differences among species in the impacts of climate-driven phenological changes on population growth were not explained by the number of broods or density dependence. Our approach helps to predict the types of species in which climate sensitivities of phenotypic traits have strong demographic and population consequences, which is crucial for conservation prioritization of data-deficient species. PMID:27062059

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

    PubMed

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

    2004-12-01

    The occurrence of qualitative shifts in population dynamical regimes has long been the focus of population biologists. Nonlinear ecological models predict that these shifts in dynamical regimes may occur as a result of parameter shifts, but unambiguous empirical evidence is largely restricted to laboratory populations. We used an individual-based modelling approach to predict dynamical shifts in field fish populations where the capacity to cannibalize differed between species. Model-generated individual growth trajectories that reflect different population dynamics were confronted with empirically observed growth trajectories, showing that our ordering and quantitative estimates of the different cannibalistic species in terms of life-history characteristics led to correct qualitative predictions of their dynamics. PMID:15590600

  3. Tuning stochastic matrix models with hydrologic data to predict the population dynamics of a riverine fish

    USGS Publications Warehouse

    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

  4. Assessing spatial coupling in complex population dynamics using mutual prediction and continuity statistics

    USGS Publications Warehouse

    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.

  5. Combining a weed traits database with a population dynamics model predicts shifts in weed communities

    PubMed Central

    Storkey, J; Holst, N; Bøjer, O Q; Bigongiali, F; Bocci, G; Colbach, N; Dorner, Z; Riemens, M M; Sartorato, I; Sønderskov, 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

  6. Predicting evolutionary dynamics

    NASA Astrophysics Data System (ADS)

    Balazsi, Gabor

    We developed an ordinary differential equation-based model to predict the evolutionary dynamics of yeast cells carrying a synthetic gene circuit. The predicted aspects included the speed at which the ancestral genotype disappears from the population; as well as the types of mutant alleles that establish in each environmental condition. We validated these predictions by experimental evolution. The agreement between our predictions and experimental findings suggests that cellular and population fitness landscapes can be useful to predict short-term evolution.

  7. Dynamics of Population Activity in Rat Sensory Cortex: Network Correlations Predict Anatomical Arrangement and Information Content

    PubMed Central

    Sabri, Mohammad Mahdi; Adibi, Mehdi; Arabzadeh, Ehsan

    2016-01-01

    To study the spatiotemporal dynamics of neural activity in a cortical population, we implanted a 10 × 10 microelectrode array in the vibrissal cortex of urethane-anesthetized rats. We recorded spontaneous neuronal activity as well as activity evoked in response to sustained and brief sensory stimulation. To quantify the temporal dynamics of activity, we computed the probability distribution function (PDF) of spiking on one electrode given the observation of a spike on another. The spike-triggered PDFs quantified the strength, temporal delay, and temporal precision of correlated activity across electrodes. Nearby cells showed higher levels of correlation at short delays, whereas distant cells showed lower levels of correlation, which tended to occur at longer delays. We found that functional space built based on the strength of pairwise correlations predicted the anatomical arrangement of electrodes. Moreover, the correlation profile of electrode pairs during spontaneous activity predicted the “signal” and “noise” correlations during sensory stimulation. Finally, mutual information analyses revealed that neurons with stronger correlations to the network during spontaneous activity, conveyed higher information about the sensory stimuli in their evoked response. Given the 400-μm-distance between adjacent electrodes, our functional quantifications unravel the spatiotemporal dynamics of activity among nearby and distant cortical columns. PMID:27458347

  8. Dynamics of Population Activity in Rat Sensory Cortex: Network Correlations Predict Anatomical Arrangement and Information Content.

    PubMed

    Sabri, Mohammad Mahdi; Adibi, Mehdi; Arabzadeh, Ehsan

    2016-01-01

    To study the spatiotemporal dynamics of neural activity in a cortical population, we implanted a 10 × 10 microelectrode array in the vibrissal cortex of urethane-anesthetized rats. We recorded spontaneous neuronal activity as well as activity evoked in response to sustained and brief sensory stimulation. To quantify the temporal dynamics of activity, we computed the probability distribution function (PDF) of spiking on one electrode given the observation of a spike on another. The spike-triggered PDFs quantified the strength, temporal delay, and temporal precision of correlated activity across electrodes. Nearby cells showed higher levels of correlation at short delays, whereas distant cells showed lower levels of correlation, which tended to occur at longer delays. We found that functional space built based on the strength of pairwise correlations predicted the anatomical arrangement of electrodes. Moreover, the correlation profile of electrode pairs during spontaneous activity predicted the "signal" and "noise" correlations during sensory stimulation. Finally, mutual information analyses revealed that neurons with stronger correlations to the network during spontaneous activity, conveyed higher information about the sensory stimuli in their evoked response. Given the 400-μm-distance between adjacent electrodes, our functional quantifications unravel the spatiotemporal dynamics of activity among nearby and distant cortical columns. PMID:27458347

  9. Prediction of population with Alzheimer’s disease in the European Union using a system dynamics model

    PubMed Central

    Tomaskova, Hana; Kuhnova, Jitka; Cimler, Richard; Dolezal, Ondrej; Kuca, Kamil

    2016-01-01

    Introduction Alzheimer’s disease (AD) is a slowly progressing neurodegenerative brain disease with irreversible brain effects; it is the most common cause of dementia. With increasing age, the probability of suffering from AD increases. In this research, population growth of the European Union (EU) until the year 2080 and the number of patients with AD are modeled. Aim The aim of this research is to predict the spread of AD in the EU population until year 2080 using a computer simulation. Methods For the simulation of the EU population and the occurrence of AD in this population, a system dynamics modeling approach has been used. System dynamics is a useful and effective method for the investigation of complex social systems. Over the past decades, its applicability has been demonstrated in a wide variety of applications. In this research, this method has been used to investigate the growth of the EU population and predict the number of patients with AD. The model has been calibrated on the population prediction data created by Eurostat. Results Based on data from Eurostat, the EU population until year 2080 has been modeled. In 2013, the population of the EU was 508 million and the number of patients with AD was 7.5 million. Based on the prediction, in 2040, the population of the EU will be 524 million and the number of patients with AD will be 13.1 million. By the year 2080, the EU population will be 520 million and the number of patients with AD will be 13.7 million. Conclusion System dynamics modeling approach has been used for the prediction of the number of patients with AD in the EU population till the year 2080. These results can be used to determine the economic burden of the treatment of these patients. With different input data, the simulation can be used also for the different regions as well as for different noncontagious disease predictions. PMID:27418826

  10. Predicting Population Curves.

    ERIC Educational Resources Information Center

    Bunton, Matt

    2003-01-01

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

  11. Spatial variation in water loss predicts terrestrial salamander distribution and population dynamics.

    PubMed

    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

  12. Ecological change predicts population dynamics and genetic diversity over 120 000 years.

    PubMed

    Horreo, Jose Luis; Jiménez-Valverde, Alberto; Fitze, Patrick S

    2016-05-01

    While ecological effects on short-term population dynamics are well understood, their effects over millennia are difficult to demonstrate and convincing evidence is scant. Using coalescent methods, we analysed past population dynamics of three lizard species (Psammodromus hispanicus, P. edwardsianus, P. occidentalis) and linked the results with climate change data covering the same temporal horizon (120 000 years). An increase in population size over time was observed in two species, and in P. occidentalis, no change was observed. Temporal changes in temperature seasonality and the maximum temperature of the warmest month were congruent with changes in population dynamics observed for the three species and both variables affected population density, either directly or indirectly (via a life-history trait). These results constitute the first solid link between ecological change and long-term population dynamics. The results moreover suggest that ecological change leaves genetic signatures that can be retrospectively traced, providing evidence that ecological change is a crucial driver of genetic diversity and speciation. PMID:26666533

  13. Climate-Based Models for Pulsed Resources Improve Predictability of Consumer Population Dynamics: Outbreaks of House Mice in Forest Ecosystems

    PubMed Central

    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 (ΔT) 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 ΔT method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ΔT 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

  14. Climate-based models for pulsed resources improve predictability of consumer population dynamics: outbreaks of house mice in forest ecosystems.

    PubMed

    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 (ΔT) 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 ΔT method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ΔT 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

  15. Application of intelligent modeling to predict the population dynamics of Pseudomonas aeruginosa in Frankfurter sausage containing Satureja bachtiarica extracts.

    PubMed

    Alghooneh, Ali; Behbahani, Behrooz Alizadeh; Noorbakhsh, Hamid; Yazdi, Farideh Tabatabaei

    2015-08-01

    Stepwise regression, Genetic Algorithm-Artificial Neural Network (GA-ANN) and Co-Active Neuro Fuzzy Inference System (CANFIS) were used to predict the effect of Satureja extracts (water and ethanol) on the population dynamics of Pseudomonas aeruginosa in a complex food system (Frankfurter sausage). The stepwise regression, GA-ANN and CANFIS were fed with four inputs: concentration (at five levels 0, 2000, 4000, 6000 and 8000 ppm), type of extract (water and ethanol), temperature (at three levels 5, 15 and 25°С) and time (1-20 days). The results showed that the stepwise regression was good for modeling the population dynamics of P. aeruginosa (R(2) = 0.92). It was found that ANN with one hidden layer comprising 14 neurons gave the best fitting with the experimental data, so that made it possible to predict with a high determination coefficient (R(2) = 0.98). Also, an excellent agreement between CANFIS predictions and experimental data was observed (R(2) = 0.96). In this research, GA-ANN was the best approach to simulate the population dynamics of P. aeruginosa. Furthermore, Satureja bachtiarica ethanol extract was able to reduce P. aeruginosa population, showing stronger effect at 5 °C and the concentration of 8000 ppm. PMID:26079732

  16. Interaction Assessment: A modeling tool for predicting population dynamics from field data

    USGS Publications Warehouse

    Emlen, John M.; Duda, Jeffrey J.; Kirchhoff, Matt D.; Freeman, D. Carl

    2006-01-01

    Interaction Assessment (INTASS) is a field and analytic methodology for constructing population dynamics models. Because data collected in generating a model for one species comprise much of the information needed for other species, a small increase in effort can result in simultaneous expressions for the dynamics of multiple species. These expressions can be used to simulate whole community responses to environmental change, including management actions. Since publication of the most recent paper in this series, the INTASS methodology has undergone a large number of developments. These include the use of conceptual models to direct field and modeling efforts and incorporation of an information theoretic approach to model selection. We review these modifications and additions, applying them to a population of Sitka black-tailed deer (Odocoilius hemionis) in Alaska and to cheatgrass (Bromus tectorum) at the Desert Experimental Range in Utah. In both cases, useful information about the species’ ecology and population trends was ascertained. INTASS is portable across a wide range of taxa, habitats and management situations.

  17. Model-based prediction of nephropathia epidemica outbreaks based on climatological and vegetation data and bank vole population dynamics.

    PubMed

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

    2013-11-01

    Wildlife-originated zoonotic diseases in general are a major contributor to emerging infectious diseases. Hantaviruses more specifically cause thousands of human disease cases annually worldwide, while understanding and predicting human hantavirus epidemics pose numerous unsolved challenges. Nephropathia epidemica (NE) is a human infection caused by Puumala virus, which is naturally carried and shed by bank voles (Myodes glareolus). The objective of this study was to develop a method that allows model-based predicting 3 months ahead of the occurrence of NE epidemics. Two data sets were utilized to develop and test the models. These data sets were concerned with NE cases in Finland and Belgium. In this study, we selected the most relevant inputs from all the available data for use in a dynamic linear regression (DLR) model. The number of NE cases in Finland were modelled using data from 1996 to 2008. The NE cases were predicted based on the time series data of average monthly air temperature (°C) and bank voles' trapping index using a DLR model. The bank voles' trapping index data were interpolated using a related dynamic harmonic regression model (DHR). Here, the DLR and DHR models used time-varying parameters. Both the DHR and DLR models were based on a unified state-space estimation framework. For the Belgium case, no time series of the bank voles' population dynamics were available. Several studies, however, have suggested that the population of bank voles is related to the variation in seed production of beech and oak trees in Northern Europe. Therefore, the NE occurrence pattern in Belgium was predicted based on a DLR model by using remotely sensed phenology parameters of broad-leaved forests, together with the oak and beech seed categories and average monthly air temperature (°C) using data from 2001 to 2009. Our results suggest that even without any knowledge about hantavirus dynamics in the host population, the time variation in NE outbreaks in Finland

  18. PREDICTION OF PEROMYSCUS MANICULATUS (DEER MOUSE) POPULATION DYNAMICS IN MONTANA, USA, USING SATELLITE-DRIVEN VEGETATION PRODUCTIVITY AND WEATHER DATA

    PubMed Central

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

    2013-01-01

    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

  19. Prediction of Peromyscus maniculatus (deer mouse) population dynamics in Montana, USA, using satellite-driven vegetation productivity and weather data.

    PubMed

    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

  20. A generic weather-driven model to predict mosquito population dynamics applied to species of Anopheles, Culex and Aedes genera of southern France.

    PubMed

    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 Carbonnière) 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

  1. Population Dynamics of an Insect Herbivore over 32 Years are Driven by Precipitation and Host-Plant Effects: Testing Model Predictions.

    PubMed

    Price, Peter W; Hunter, Mark D

    2015-06-01

    The interaction between the arroyo willow, Salix lasiolepis Bentham, and its specialist herbivore, the arroyo willow stem-galling sawfly, Euura lasiolepis Smith (Hymenoptera: Tenthredinidae), was studied for 32 yr in Flagstaff, AZ, emphasizing a mechanistic understanding of insect population dynamics. Long-term weather records were evaluated to provide a climatic context for this study. Previously, predictive models of sawfly dynamics were developed from estimates of sawfly gall density made between 1981 and 2002; one model each for drier and wetter sites. Predictor variables in these models included winter precipitation and the Palmer Drought Severity Index, which impact the willow growth, with strong bottom-up effects on sawflies. We now evaluate original model predictions of sawfly population dynamics using new data (from 2003-2012). Additionally, willow resources were evaluated in 1986 and in 2012, using as criteria clone area, shoot density, and shoot length. The dry site model accounted for 40% of gall population density variation between 2003 and 2012 (69% over the 32 yr), providing strong support for the bottom-up, mechanistic hypothesis that water supply to willow hosts impacts sawfly populations. The current drying trend stressed willow clones: in drier sites, willow resources declined and gall density decreased by 98%. The wet site model accounted for 23% of variation in gall population density between 2003 and 2012 (48% over 30 yr), consistent with less water limitation. Nonetheless, gall populations were reduced by 72%. PMID:26313951

  2. Comparing models of Red Knot population dynamics

    USGS Publications Warehouse

    McGowan, Conor

    2015-01-01

    Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab (Limulus polyphemus) harvests and protect Red Knot (Calidris canutus rufa) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.

  3. Integrating physiology, population dynamics and climate to make multi-scale predictions for the spread of an invasive insect: the Argentine ant at Haleakala National Park, Hawaii

    USGS Publications Warehouse

    Hartley, Stephen; Krushelnycky, Paul D.; Lester, Philip J.

    2010-01-01

    Mechanistic models for predicting species’ distribution patterns present particular advantages and challenges relative to models developed from statistical correlations between distribution and climate. They can be especially useful for predicting the range of invasive species whose distribution has not yet reached equilibrium. Here, we illustrate how a physiological model of development for the invasive Argentine ant can be connected to differences in micro-site suitability, population dynamics and climatic gradients; processes operating at quite different spatial scales. Our study is located in the subalpine shrubland of Haleakala National Park, Hawaii, where the spread of Argentine ants Linepithema humile has been documented for the past twenty-five years. We report four main results. First, at a microsite level, the accumulation of degree-days recorded in potential ant nest sites under bare ground or rocks was significantly greater than under a groundcover of grassy vegetation. Second, annual degree-days measured where population boundaries have not expanded (456-521 degree-days), were just above the developmental requirements identified from earlier laboratory studies (445 degree-days above 15.98C). Third, rates of population expansion showed a strong linear relationship with annual degree-days. Finally, an empirical relationship between soil degree-days and climate variables mapped at a broader scale predicts the potential for future range expansion of Argentine ants at Haleakala, particularly to the west of the lower colony and the east of the upper colony. Variation in the availability of suitable microsites, driven by changes in vegetation cover and ultimately climate, provide a hierarchical understanding of the distribution of Argentine ants close to their cold-wet limit of climatic tolerances. We conclude that the integration of physiology, population dynamics and climate mapping holds much promise for making more robust predictions about

  4. AMPHIBIAN POPULATION DYNAMICS

    EPA Science Inventory

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

  5. Discreteness effects in population dynamics

    NASA Astrophysics Data System (ADS)

    Guevara Hidalgo, Esteban; Lecomte, Vivien

    2016-05-01

    We analyse numerically the effects of small population size in the initial transient regime of a simple example population dynamics. These effects play an important role for the numerical determination of large deviation functions of additive observables for stochastic processes. A method commonly used in order to determine such functions is the so-called cloning algorithm which in its non-constant population version essentially reduces to the determination of the growth rate of a population, averaged over many realizations of the dynamics. However, the averaging of populations is highly dependent not only on the number of realizations of the population dynamics, and on the initial population size but also on the cut-off time (or population) considered to stop their numerical evolution. This may result in an over-influence of discreteness effects at initial times, caused by small population size. We overcome these effects by introducing a (realization-dependent) time delay in the evolution of populations, additional to the discarding of the initial transient regime of the population growth where these discreteness effects are strong. We show that the improvement in the estimation of the large deviation function comes precisely from these two main contributions.

  6. Development of a predictive model for the growth kinetics of aerobic microbial population on pomegranate marinated chicken breast fillets under isothermal and dynamic temperature conditions.

    PubMed

    Lytou, Anastasia; Panagou, Efstathios Z; Nychas, George-John E

    2016-05-01

    The aim of this study was the development of a model to describe the growth kinetics of aerobic microbial population of chicken breast fillets marinated in pomegranate juice under isothermal and dynamic temperature conditions. Moreover, the effect of pomegranate juice on the extension of the shelf life of the product was investigated. Samples (10 g) of chicken breast fillets were immersed in marinades containing pomegranate juice for 3 h at 4 °C following storage under aerobic conditions at 4, 10, and 15 °C for 10 days. Total Viable Counts (TVC), Pseudomonas spp and lactic acid bacteria (LAB) were enumerated, in parallel with sensory assessment (odor and overall appearance) of marinated and non-marinated samples. The Baranyi model was fitted to the growth data of TVC to calculate the maximum specific growth rate (μmax) that was further modeled as a function of temperature using a square root-type model. The validation of the model was conducted under dynamic temperature conditions based on two fluctuating temperature scenarios with periodic changes from 6 to 13 °C. The shelf life was determined both mathematically and with sensory assessment and its temperature dependence was modeled by an Arrhenius type equation. Results showed that the μmax of TVC of marinated samples was significantly lower compared to control samples regardless temperature, while under dynamic temperature conditions the model satisfactorily predicted the growth of TVC in both control and marinated samples. The shelf-life of marinated samples was significantly extended compared to the control (5 days extension at 4 °C). The calculated activation energies (Ea), 82 and 52 kJ/mol for control and marinated samples, respectively, indicated higher temperature dependence of the shelf life of control samples compared to marinated ones. The present results indicated that pomegranate juice could be used as an alternative ingredient in marinades to prolong the shelf life of chicken. PMID:26742613

  7. Predicting protein dynamics from structural ensembles

    NASA Astrophysics Data System (ADS)

    Copperman, J.; Guenza, M. G.

    2015-12-01

    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 experimental NMR conformers as the input structural ensembles, LE4PD predicts quantitatively accurate results, with correlation coefficient ρ = 0.93 to NMR backbone relaxation measurements for the seven proteins. The NMR solution structure derived ensemble and predicted dynamical relaxation is compared with molecular dynamics simulation-derived structural ensembles and LE4PD predictions and is consistent in the time scale of the simulations. The use of the experimental NMR conformers frees the approach from computationally demanding simulations.

  8. Modeling sandhill crane population dynamics

    USGS Publications Warehouse

    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.

  9. Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

    PubMed

    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

  10. Evolutionary dynamics in structured populations

    PubMed Central

    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

  11. Animal population dynamics: Identification of critical components

    USGS Publications Warehouse

    Emlen, J.M.; Pikitch, E.K.

    1989-01-01

    There is a growing interest in the use of population dynamics models in environmental risk assessment and the promulgation of environmental regulatory policies. Unfortunately, because of species and areal differences in the physical and biotic influences on population dynamics, such models must almost inevitably be both complex and species- or site-specific. Given the emormous variety of species and sites of potential concern, this fact presents a problem; it simply is not possible to construct models for all species and circumstances. Therefore, it is useful, before building predictive population models, to discover what input parameters are of critical importance to the desired output. This information should enable the construction of simpler and more generalizable models. As a first step, it is useful to consider population models as composed to two, partly separable classes, one comprising the purely mechanical descriptors of dynamics from given demographic parameter values, and the other describing the modulation of the demographic parameters by environmental factors (changes in physical environment, species interactions, pathogens, xenobiotic chemicals). This division permits sensitivity analyses to be run on the first of these classes, providing guidance for subsequent model simplification. We here apply such a sensitivity analysis to network models of mammalian and avian population dynamics.

  12. Predicting earth's dynamic changes

    NASA Technical Reports Server (NTRS)

    Rasool, S. I.

    1986-01-01

    Given a suitable strategy for conducting measurements, satellite-based remote sensing of the earth can furnish valuable information on the dynamic changes of such planetary characteristics as ocean surface temperatures and atmospheric CO2. Observations must be global and synoptic, quantitatively validated, and consistent over the long term. A program spanning 20 years will study such critical variables as solar flux, stratospheric temperature, aerosols and ozone, cloud cover, tropospheric gases and aerosols, radiation balance, surface temperature, albedo, precipitation, vegetation cover, moisture, snow and ice, as well as oceanic color, topography, and wind stress.

  13. 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.

  14. Evolutionary dynamics on interdependent populations

    NASA Astrophysics Data System (ADS)

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

    2012-11-01

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

  15. Total Ozone Prediction: Stratospheric Dynamics

    NASA Technical Reports Server (NTRS)

    Jackman, Charles H.; Kawa, S. Ramdy; Douglass, Anne R.

    2003-01-01

    The correct prediction of total ozone as a function of latitude and season is extremely important for global models. This exercise tests the ability of a particular model to simulate ozone. The ozone production (P) and loss (L) will be specified from a well- established global model and will be used in all GCMs for subsequent prediction of ozone. This is the "B-3 Constrained Run" from M&MII. The exercise mostly tests a model stratospheric dynamics in the prediction of total ozone. The GCM predictions will be compared and contrasted with TOMS measurements.

  16. Predicting fish population response to instream flows

    SciTech Connect

    Studley, T.K.; Baldridge, J.E.; Railsback, S.F.

    1996-10-01

    A cooperative research program initiated by Pacific Gas and Electric is described. The goals of the project are to determine if trout populations respond to changes in base streamflows in a predictible manner, and to evaluate and improve the methods used to predict rainbow and brown trout population responses under altered flow regimes. Predictive methods based on computer models of the Physical Habitat Simulation System are described, and predictions generated for four diversions and creeks are tabulated. Baseline data indicates that instream flow assessments can be improved by using guild criteria in streams with competing species and including additional limiting factors (low recruitment, high winter flow, and high stream temperatures) in the analyses.

  17. 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.

  18. Dynamic clustering of bacterial population

    NASA Astrophysics Data System (ADS)

    Ko, Elizabeth P.; Yomo, Tetsuya; Urabe, Itaru

    1994-08-01

    Bacterial cells having the same genotype were observed to split into a few clusters of phenotypes with various levels of enzyme activity. When the mixture of these phenotypically heterogeneous but genotypically homogeneous cells was cultivated in a liquid medium, the distribution of the population size of each cluster of phenotypes showed various kinds of dynamic oscillations. In addition, when this dynamic behavior was examined for the cells of the single colony, various patterns of shifting of homogeneous to heterogeneous lineage and vice versa were observed in the population. The results imply that differentiation of the cells with the same genotype can occur without spatial information and even under the same environment where the cells interact globally without spatial constrait. This interesting phenomenon totally contradicts the conventional biology that the genotype of a cell uniquely determines the phenotype of the cell and its progeny, but is consistent with the theoretical model of cell differentiation presented in the following paper. The sources of discrepancy between the existing theory in molecular biology and our results were discussed and it is concluded that in understanding a complex living system, a simple model consisting of the essence of the complex system can be constructed justifying the observed properties of the molecules in the system which provide free interactions.

  19. 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.

  20. Modeling population dynamics: A quantile approach.

    PubMed

    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

  1. Local extinction synchronizes population dynamics in spatial networks.

    PubMed

    Matter, Stephen F; Roland, Jens

    2010-03-01

    Spatial population theory predicts that synchrony in the dynamics of local populations should decrease as dispersal among populations decreases. Thus, it would be expected that the extinction of local populations and the attendant loss of immigrants to surrounding populations would reduce synchrony. We tested this hypothesis through a large-scale experiment, simulation of the experimental system and general models. Experimental removal of two adjacent subpopulations of the Rocky Mountain Apollo butterfly, Parnassius smintheus within a network consisting of 15 other local populations resulted in a decrease in immigration to surrounding populations that was proportional to their connectivity to the removal populations. These populations also showed a significant increase in synchrony during population removal. The spatial extent of the synchrony showed good agreement with the predicted loss of immigrants owing to the removals. Simulation of the Parnassius system showed a similar short-term result and also indicated that permanent loss of populations produces structural changes increasing synchrony. General models indicate that an increase in synchrony following extinction occurs when populations undergoing extinction have different carrying capacities than surrounding populations. The result is not owing to biased migration per se, but rather is because of the number of immigrants relative to the carrying capacity. Synchrony following extinction should be most common for patchy populations, but can occur in any situation where carrying capacities differ. Overall, our results indicate that local extinction can create a positive feedback for extinction risk, increasing the probability of extinction for population networks by synchronizing their dynamics. PMID:19889700

  2. An Individual-Based Model of Zebrafish Population Dynamics Accounting for Energy Dynamics

    PubMed Central

    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

  3. A Quantitative Model of Honey Bee Colony Population Dynamics

    PubMed Central

    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

  4. Predicting stochastic gene expression dynamics in single cells.

    PubMed

    Mettetal, Jerome T; Muzzey, Dale; Pedraza, Juan M; Ozbudak, Ertugrul M; van Oudenaarden, Alexander

    2006-05-01

    Fluctuations in protein numbers (noise) due to inherent stochastic effects in single cells can have large effects on the dynamic behavior of gene regulatory networks. Although deterministic models can predict the average network behavior, they fail to incorporate the stochasticity characteristic of gene expression, thereby limiting their relevance when single cell behaviors deviate from the population average. Recently, stochastic models have been used to predict distributions of steady-state protein levels within a population but not to predict the dynamic, presteady-state distributions. In the present work, we experimentally examine a system whose dynamics are heavily influenced by stochastic effects. We measure population distributions of protein numbers as a function of time in the Escherichia coli lactose uptake network (lac operon). We then introduce a dynamic stochastic model and show that prediction of dynamic distributions requires only a few noise parameters in addition to the rates that characterize a deterministic model. Whereas the deterministic model cannot fully capture the observed behavior, our stochastic model correctly predicts the experimental dynamics without any fit parameters. Our results provide a proof of principle for the possibility of faithfully predicting dynamic population distributions from deterministic models supplemented by a stochastic component that captures the major noise sources. PMID:16648266

  5. Predictive Bayesian inference and dynamic treatment regimes.

    PubMed

    Saarela, Olli; Arjas, Elja; Stephens, David A; Moodie, Erica E M

    2015-11-01

    While optimal dynamic treatment regimes (DTRs) can be estimated without specification of a predictive model, a model-based approach, combined with dynamic programming and Monte Carlo integration, enables direct probabilistic comparisons between the outcomes under the optimal DTR and alternative (dynamic or static) treatment regimes. The Bayesian predictive approach also circumvents problems related to frequentist estimators under the nonregular estimation problem. However, the model-based approach is susceptible to misspecification, in particular of the "null-paradox" type, which is due to the model parameters not having a direct causal interpretation in the presence of latent individual-level characteristics. Because it is reasonable to insist on correct inferences under the null of no difference between the alternative treatment regimes, we discuss how to achieve this through a "null-robust" reparametrization of the problem in a longitudinal setting. Since we argue that causal inference can be entirely understood as posterior predictive inference in a hypothetical population without covariate imbalances, we also discuss how controlling for confounding through inverse probability of treatment weighting can be justified and incorporated in the Bayesian setting. PMID:26259996

  6. Population Dynamics of Viral Inactivation

    NASA Astrophysics Data System (ADS)

    Freeman, Krista; Li, Dong; Behrens, Manja; Streletzky, Kiril; Olsson, Ulf; Evilevitch, Alex

    We have investigated the population dynamics of viral inactivation in vitrousing time-resolved cryo electron microscopy combined with light and X-ray scattering techniques. Using bacteriophage λ as a model system for pressurized double-stranded DNA viruses, we found that virions incubated with their cell receptor eject their genome in a stochastic triggering process. The triggering of DNA ejection occurs in a non synchronized manner after the receptor addition, resulting in an exponential decay of the number of genome-filled viruses with time. We have explored the characteristic time constant of this triggering process at different temperatures, salt conditions, and packaged genome lengths. Furthermore, using the temperature dependence we determined an activation energy for DNA ejections. The dependences of the time constant and activation energy on internal DNA pressure, affected by salt conditions and encapsidated genome length, suggest that the triggering process is directly dependent on the conformational state of the encapsidated DNA. The results of this work provide insight into how the in vivo kinetics of the spread of viral infection are influenced by intra- and extra cellular environmental conditions. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1252522.

  7. Co-infection alters population dynamics of infectious disease.

    PubMed

    Susi, Hanna; Barrès, 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

  8. Evolutionary dynamics in set structured populations

    PubMed Central

    Tarnita, Corina E.; Antal, Tibor; Ohtsuki, Hisashi; Nowak, Martin A.

    2009-01-01

    Evolutionary dynamics are strongly affected by population structure. The outcome of an evolutionary process in a well-mixed population can be very different from that in a structured population. We introduce a powerful method to study dynamical population structure: evolutionary set theory. The individuals of a population are distributed over sets. Individuals interact with others who are in the same set. Any 2 individuals can have several sets in common. Some sets can be empty, whereas others have many members. Interactions occur in terms of an evolutionary game. The payoff of the game is interpreted as fitness. Both the strategy and the set memberships change under evolutionary updating. Therefore, the population structure itself is a consequence of evolutionary dynamics. We construct a general mathematical approach for studying any evolutionary game in set structured populations. As a particular example, we study the evolution of cooperation and derive precise conditions for cooperators to be selected over defectors. PMID:19433793

  9. Population Dynamics of Genetic Regulatory Networks

    NASA Astrophysics Data System (ADS)

    Braun, Erez

    2005-03-01

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

  10. 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 ν(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 ν 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 ν 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.

  11. Dynamic Random Networks in Dynamic Populations

    NASA Astrophysics Data System (ADS)

    Britton, Tom; Lindholm, Mathias

    2010-05-01

    We consider a random network evolving in continuous time in which new nodes are born and old may die, and where undirected edges between nodes are created randomly and may also disappear. The node population is Markovian and so is the creation and deletion of edges, given the node population. Each node is equipped with a random social index and the intensity at which a node creates new edges is proportional to the social index, and the neighbour is either chosen uniformly or proportional to its social index in a modification of the model. We derive properties of the network as time and the node population tends to infinity. In particular, the degree-distribution is shown to be a mixed Poisson distribution which may exhibit a heavy tail (e.g. power-law) if the social index distribution has a heavy tail. The limiting results are verified by means of simulations, and the model is fitted to a network of sexual contacts.

  12. 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.

  13. Population dynamics with and without selection

    NASA Astrophysics Data System (ADS)

    Pȩkalski, Andrzej; Sznajd-Weron, Katarzyna

    2001-03-01

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

  14. Population dynamics on heterogeneous bacterial substrates

    NASA Astrophysics Data System (ADS)

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

    2012-02-01

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

  15. Travelling waves in vole population dynamics

    NASA Astrophysics Data System (ADS)

    Ranta, Esa; Kaitala, Veijo

    1997-12-01

    Spatial self-organization patterns in population dynamics have been anticipated, but demonstrating their existence requires sampling over long periods of time at a range of sites. Voles cause severe economic damage and are therefore extensively monitored, providing a source of the required data. Using two long-term data sets we now report the existence of travelling waves in vole population numbers.

  16. Predictive Dynamic Security Assessment through Advanced Computing

    SciTech Connect

    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.

  17. How Resource Phenology Affects Consumer Population Dynamics.

    PubMed

    Bewick, Sharon; Cantrell, R Stephen; Cosner, Chris; Fagan, William F

    2016-02-01

    Climate change drives uneven phenology shifts across taxa, and this can result in changes to the phenological match between interacting species. Shifts in the relative phenology of partner species are well documented, but few studies have addressed the effects of such changes on population dynamics. To explore this, we develop a phenologically explicit model describing consumer-resource interactions. Focusing on scenarios for univoltine insects, we show how changes in resource phenology can be reinterpreted as transformations in the year-to-year recursion relationships defining consumer population dynamics. This perspective provides a straightforward path for interpreting the long-term population consequences of phenology change. Specifically, by relating the outcome of phenological shifts to species traits governing recursion relationships (e.g., consumer fecundity or competitive scenario), we demonstrate how changes in relative phenology can force systems into different dynamical regimes, with major implications for resource management, conservation, and other areas of applied dynamics. PMID:26807744

  18. Deterministic evolutionary game dynamics in finite populations.

    PubMed

    Altrock, Philipp M; Traulsen, Arne

    2009-07-01

    Evolutionary game dynamics describes the spreading of successful strategies in a population of reproducing individuals. Typically, the microscopic definition of strategy spreading is stochastic such that the dynamics becomes deterministic only in infinitely large populations. Here, we present a microscopic birth-death process that has a fully deterministic strong selection limit in well-mixed populations of any size. Additionally, under weak selection, from this process the frequency-dependent Moran process is recovered. This makes it a natural extension of the usual evolutionary dynamics under weak selection. We find simple expressions for the fixation probabilities and average fixation times of the process in evolutionary games with two players and two strategies. For cyclic games with two players and three strategies, we show that the resulting deterministic dynamics crucially depends on the initial condition in a nontrivial way. PMID:19658731

  19. Dynamics of Sequence -Discrete Bacterial Populations Inferred Using Metagenomes

    SciTech Connect

    Stevens, Sarah; Bendall, Matthew; Kang, Dongwan; Froula, Jeff; Egan, Rob; Chan, Leong-Keat; Tringe, Susannah; McMahon, Katherine; Malmstrom, Rex

    2014-03-14

    From a multi-year metagenomic time series of two dissimilar Wisconsin lakes we have assembled dozens of genomes using a novel approach that bins contigs into distinct genome based on sequence composition, e.g. kmer frequencies, and contig coverage patterns at various times points. Next, we investigated how these genomes, which represent sequence-discrete bacterial populations, evolved over time and used the time series to discover the population dynamics. For example, we explored changes in single nucleotide polymorphism (SNP) frequencies as well as patterns of gene gain and loss in multiple populations. Interestingly, SNP diversity was purged at nearly every genome position in some populations during the course of this study, suggesting these populations may have experienced genome-wide selective sweeps. This represents the first direct, time-resolved observations of periodic selection in natural populations, a key process predicted by the ecotype model of bacterial diversification.

  20. Structural dynamics and ecology of flatfish populations

    NASA Astrophysics Data System (ADS)

    Bailey, Kevin M.

    1997-11-01

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

  1. Multispecies population dynamics of prebiotic compositional assemblies.

    PubMed

    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

  2. Bacterial associations reveal spatial population dynamics in Anopheles gambiae mosquitoes.

    PubMed

    Buck, Moritz; Nilsson, Louise K J; Brunius, Carl; Dabiré, Roch K; Hopkins, Richard; Terenius, Olle

    2016-01-01

    The intolerable burden of malaria has for too long plagued humanity and the prospect of eradicating malaria is an optimistic, but reachable, target in the 21(st) century. However, extensive knowledge is needed about the spatial structure of mosquito populations in order to develop effective interventions against malaria transmission. We hypothesized that the microbiota associated with a mosquito reflects acquisition of bacteria in different environments. By analyzing the whole-body bacterial flora of An. gambiae mosquitoes from Burkina Faso by 16 S amplicon sequencing, we found that the different environments gave each mosquito a specific bacterial profile. In addition, the bacterial profiles provided precise and predicting information on the spatial dynamics of the mosquito population as a whole and showed that the mosquitoes formed clear local populations within a meta-population network. We believe that using microbiotas as proxies for population structures will greatly aid improving the performance of vector interventions around the world. PMID:26960555

  3. Bacterial associations reveal spatial population dynamics in Anopheles gambiae mosquitoes

    PubMed Central

    Buck, Moritz; Nilsson, Louise K. J.; Brunius, Carl; Dabiré, Roch K.; Hopkins, Richard; Terenius, Olle

    2016-01-01

    The intolerable burden of malaria has for too long plagued humanity and the prospect of eradicating malaria is an optimistic, but reachable, target in the 21st century. However, extensive knowledge is needed about the spatial structure of mosquito populations in order to develop effective interventions against malaria transmission. We hypothesized that the microbiota associated with a mosquito reflects acquisition of bacteria in different environments. By analyzing the whole-body bacterial flora of An. gambiae mosquitoes from Burkina Faso by 16 S amplicon sequencing, we found that the different environments gave each mosquito a specific bacterial profile. In addition, the bacterial profiles provided precise and predicting information on the spatial dynamics of the mosquito population as a whole and showed that the mosquitoes formed clear local populations within a meta-population network. We believe that using microbiotas as proxies for population structures will greatly aid improving the performance of vector interventions around the world. PMID:26960555

  4. Stability, complexity and robustness in population dynamics.

    PubMed

    Demongeot, J; Hazgui, H; Ben Amor, H; Waku, J

    2014-09-01

    The problem of stability in population dynamics concerns many domains of application in demography, biology, mechanics and mathematics. The problem is highly generic and independent of the population considered (human, animals, molecules,…). We give in this paper some examples of population dynamics concerning nucleic acids interacting through direct nucleic binding with small or cyclic RNAs acting on mRNAs or tRNAs as translation factors or through protein complexes expressed by genes and linked to DNA as transcription factors. The networks made of these interactions between nucleic acids (considered respectively as edges and nodes of their interaction graph) are complex, but exhibit simple emergent asymptotic behaviours, when time tends to infinity, called attractors. We show that the quantity called attractor entropy plays a crucial role in the study of the stability and robustness of such genetic networks. PMID:25107273

  5. Dynamical inference of hidden biological populations

    NASA Astrophysics Data System (ADS)

    Luchinsky, D. G.; Smelyanskiy, V. N.; Millonas, M.; McClintock, P. V. E.

    2008-10-01

    Population fluctuations in a predator-prey system are analyzed for the case where the number of prey could be determined, subject to measurement noise, but the number of predators was unknown. The problem of how to infer the unmeasured predator dynamics, as well as the model parameters, is addressed. Two solutions are suggested. In the first of these, measurement noise and the dynamical noise in the equation for predator population are neglected; the problem is reduced to a one-dimensional case, and a Bayesian dynamical inference algorithm is employed to reconstruct the model parameters. In the second solution a full-scale Markov Chain Monte Carlo simulation is used to infer both the unknown predator trajectory, and also the model parameters, using the one-dimensional solution as an initial guess.

  6. Seismicity dynamics and earthquake predictability

    NASA Astrophysics Data System (ADS)

    Sobolev, G. A.

    2011-02-01

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

  7. Dynamics of newly established elk populations

    USGS Publications Warehouse

    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.

  8. Signal prediction by anticipatory relaxation dynamics

    NASA Astrophysics Data System (ADS)

    Voss, Henning U.

    2016-03-01

    Real-time prediction of signals is a task often encountered in control problems as well as by living systems. Here, a parsimonious prediction approach based on the coupling of a linear relaxation-delay system to a smooth, stationary signal is described. The resulting anticipatory relaxation dynamics (ARD) is a frequency-dependent predictor of future signal values. ARD not only approximately predicts signals on average but can anticipate the occurrence of signal peaks, too. This can be explained by recognizing ARD as an input-output system with negative group delay. It is characterized, including its prediction horizon, by its analytically given frequency response function.

  9. Stochastic population dynamics under resource constraints

    NASA Astrophysics Data System (ADS)

    Gavane, Ajinkya S.; Nigam, Rahul

    2016-06-01

    This paper investigates the population growth of a certain species in which every generation reproduces thrice over a period of predefined time, under certain constraints of resources needed for survival of population. We study the survival period of a species by randomizing the reproduction probabilities within a window at same predefined ages and the resources are being produced by the working force of the population at a variable rate. This randomness in the reproduction rate makes the population growth stochastic in nature and one cannot predict the exact form of evolution. Hence we study the growth by running simulations for such a population and taking an ensemble averaged over 500 to 5000 such simulations as per the need. While the population reproduces in a stochastic manner, we have implemented a constraint on the amount of resources available for the population. This is important to make the simulations more realistic. The rate of resource production then is tuned to find the rate which suits the survival of the species. We also compute the mean life time of the species corresponding to different resource production rate. Study for these outcomes in the parameter space defined by the reproduction probabilities and rate of resource production is carried out.

  10. Predictive information in a sensory population.

    PubMed

    Palmer, Stephanie E; Marre, Olivier; Berry, Michael J; Bialek, William

    2015-06-01

    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

  11. 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.

  12. 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.

  13. Learning to Estimate Dynamical State with Probabilistic Population Codes

    PubMed Central

    Sabes, Philip N.

    2015-01-01

    Tracking moving objects, including one’s own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is known that this process of state estimation can be learned purely from the statistics of noisy observations. When the dynamics are simply linear with additive Gaussian noise, the optimal solution is the well known Kalman filter (KF), the parameters of which can be learned via latent-variable density estimation (the EM algorithm). The brain does not, however, directly manipulate matrices and vectors, but instead appears to represent probability distributions with the firing rates of population of neurons, “probabilistic population codes.” We show that a recurrent neural network—a modified form of an exponential family harmonium (EFH)—that takes a linear probabilistic population code as input can learn, without supervision, to estimate the state of a linear dynamical system. After observing a series of population responses (spike counts) to the position of a moving object, the network learns to represent the velocity of the object and forms nearly optimal predictions about the position at the next time-step. This result builds on our previous work showing that a similar network can learn to perform multisensory integration and coordinate transformations for static stimuli. The receptive fields of the trained network also make qualitative predictions about the developing and learning brain: tuning gradually emerges for higher-order dynamical states not explicitly present in the inputs, appearing as delayed tuning for the lower-order states. PMID:26540152

  14. Learning to Estimate Dynamical State with Probabilistic Population Codes.

    PubMed

    Makin, Joseph G; Dichter, Benjamin K; Sabes, Philip N

    2015-11-01

    Tracking moving objects, including one's own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is known that this process of state estimation can be learned purely from the statistics of noisy observations. When the dynamics are simply linear with additive Gaussian noise, the optimal solution is the well known Kalman filter (KF), the parameters of which can be learned via latent-variable density estimation (the EM algorithm). The brain does not, however, directly manipulate matrices and vectors, but instead appears to represent probability distributions with the firing rates of population of neurons, "probabilistic population codes." We show that a recurrent neural network-a modified form of an exponential family harmonium (EFH)-that takes a linear probabilistic population code as input can learn, without supervision, to estimate the state of a linear dynamical system. After observing a series of population responses (spike counts) to the position of a moving object, the network learns to represent the velocity of the object and forms nearly optimal predictions about the position at the next time-step. This result builds on our previous work showing that a similar network can learn to perform multisensory integration and coordinate transformations for static stimuli. The receptive fields of the trained network also make qualitative predictions about the developing and learning brain: tuning gradually emerges for higher-order dynamical states not explicitly present in the inputs, appearing as delayed tuning for the lower-order states. PMID:26540152

  15. Population clocks: motor timing with neural dynamics

    PubMed Central

    Buonomano, Dean V.; Laje, Rodrigo

    2010-01-01

    An understanding of sensory and motor processing will require elucidation of the mechanisms by which the brain tells time. Open questions relate to whether timing relies on dedicated or intrinsic mechanisms and whether distinct mechanisms underlie timing across scales and modalities. Although experimental and theoretical studies support the notion that neural circuits are intrinsically capable of sensory timing on short scales, few general models of motor timing have been proposed. For one class of models, population clocks, it is proposed that time is encoded in the time-varying patterns of activity of a population of neurons. We argue that population clocks emerge from the internal dynamics of recurrently connected networks, are biologically realistic and account for many aspects of motor timing. PMID:20889368

  16. Combined CFD/Population Balance Model for Gas Hydrate Particle Size Prediction in Turbulent Pipeline Flow

    NASA Astrophysics Data System (ADS)

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

    2010-09-01

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

  17. Computer Assisted Instruction of Population Dynamics: A New Approach to Population Education. Report No. T-19.

    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…

  18. Adaptive dynamics for physiologically structured population models.

    PubMed

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

    2008-05-01

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

  19. Predictability of threshold exceedances in dynamical systems

    NASA Astrophysics Data System (ADS)

    Bódai, Tamás

    2015-12-01

    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 exceedances-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 suggest that exceedances of higher thresholds are more predictable; or in other words: rare large magnitude, i.e., extreme, events 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. This can be viewed as a confirmation of a counterintuitive (and seemingly contrafactual) statement that was previously formulated for more simple autoregressive stochastic processes. However, we argue that for dynamical systems in general it may be typical only, but not universally true. We argue that when there is a sufficient amount of data depending on the precision of observation, the skill of a class of data-driven categoric predictions of threshold exceedances approximates the skill of the analogous model-driven 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

  20. Price dynamics in political prediction markets

    PubMed Central

    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

  1. API Requirements for Dynamic Graph Prediction

    SciTech Connect

    Gallagher, B; Eliassi-Rad, T

    2006-10-13

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

  2. Price dynamics in political prediction markets.

    PubMed

    Majumder, Saikat Ray; Diermeier, Daniel; Rietz, Thomas A; Amaral, Luís A Nunes

    2009-01-20

    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

  3. Population dynamics of epiphytic orchids in a metapopulation context

    PubMed Central

    Winkler, Manuela; Hülber, Karl; Hietz, Peter

    2009-01-01

    Background and Aims Populations of many epiphytes show a patchy distribution where clusters of plants growing on individual trees are spatially separated and may thus function as metapopulations. Seed dispersal is necessary to (re)colonize unoccupied habitats, and to transfer seeds from high- to low-competition patches. Increasing dispersal distances, however, reduces local fecundity and the probability that seeds will find a safe site outside the original patch. Thus, there is a conflict between seed survival and colonization. Methods Populations of three epiphytic orchids were monitored over three years in a Mexican humid montane forest and analysed with spatially averaged and with spatially explicit matrix metapopulation models. In the latter, population dynamics at the scale of the subpopulations (epiphytes on individual host trees) are based on detailed stage-structured observations of transition probabilities and trees are connected by a dispersal function. Key Results Population growth rates differed among trees and years. While ignoring these differences, and averaging the population matrices over trees, yields negative population growth, metapopulation models predict stable or growing populations because the trees that support growing subpopulations determine the growth of the metapopulation. Stochastic models which account for the differences among years differed only marginally from deterministic models. Population growth rates were significantly lower, and extinctions of local patches more frequent in models where higher dispersal results in reduced local fecundity compared with hypothetical models where this is not the case. The difference between the two models increased with increasing mean dispersal distance. Though recolonization events increased with dispersal distance, this could not compensate the losses due to reduced local fecundity. Conclusions For epiphytes, metapopulation models are useful to capture processes beyond the level of the single

  4. Population Code Dynamics in Categorical Perception

    PubMed Central

    Tajima, Chihiro I.; Tajima, Satohiro; Koida, Kowa; Komatsu, Hidehiko; Aihara, Kazuyuki; Suzuki, Hideyuki

    2016-01-01

    Categorical perception is a ubiquitous function in sensory information processing, and is reported to have important influences on the recognition of presented and/or memorized stimuli. However, such complex interactions among categorical perception and other aspects of sensory processing have not been explained well in a unified manner. Here, we propose a recurrent neural network model to process categorical information of stimuli, which approximately realizes a hierarchical Bayesian estimation on stimuli. The model accounts for a wide variety of neurophysiological and cognitive phenomena in a consistent framework. In particular, the reported complexity of categorical effects, including (i) task-dependent modulation of neural response, (ii) clustering of neural population representation, (iii) temporal evolution of perceptual color memory, and (iv) a non-uniform discrimination threshold, are explained as different aspects of a single model. Moreover, we directly examine key model behaviors in the monkey visual cortex by analyzing neural population dynamics during categorization and discrimination of color stimuli. We find that the categorical task causes temporally-evolving biases in the neuronal population representations toward the focal colors, which supports the proposed model. These results suggest that categorical perception can be achieved by recurrent neural dynamics that approximates optimal probabilistic inference in the changing environment. PMID:26935275

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

    USGS Publications Warehouse

    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.

  6. The impact of population structure on genomic prediction in stratified populations.

    PubMed

    Guo, Zhigang; Tucker, Dominic M; Basten, Christopher J; Gandhi, Harish; Ersoz, Elhan; Guo, Baohong; Xu, Zhanyou; Wang, Daolong; Gay, Gilles

    2014-03-01

    Impacts of population structure on the evaluation of genomic heritability and prediction were investigated and quantified using high-density markers in diverse panels in rice and maize. Population structure is an important factor affecting estimation of genomic heritability and assessment of genomic prediction in stratified populations. In this study, our first objective was to assess effects of population structure on estimations of genomic heritability using the diversity panels in rice and maize. Results indicate population structure explained 33 and 7.5% of genomic heritability for rice and maize, respectively, depending on traits, with the remaining heritability explained by within-subpopulation variation. Estimates of within-subpopulation heritability were higher than that derived from quantitative trait loci identified in genome-wide association studies, suggesting 65% improvement in genetic gains. The second objective was to evaluate effects of population structure on genomic prediction using cross-validation experiments. When population structure exists in both training and validation sets, correcting for population structure led to a significant decrease in accuracy with genomic prediction. In contrast, when prediction was limited to a specific subpopulation, population structure showed little effect on accuracy and within-subpopulation genetic variance dominated predictions. Finally, effects of genomic heritability on genomic prediction were investigated. Accuracies with genomic prediction increased with genomic heritability in both training and validation sets, with the former showing a slightly greater impact. In summary, our results suggest that the population structure contribution to genomic prediction varies based on prediction strategies, and is also affected by the genetic architectures of traits and populations. In practical breeding, these conclusions may be helpful to better understand and utilize the different genetic resources in genomic

  7. Evolutionary dynamics in finite populations with zealots.

    PubMed

    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

  8. Assessing the dynamics of wild populations

    SciTech Connect

    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.

  9. Noise-induced effects in population dynamics

    NASA Astrophysics Data System (ADS)

    Spagnolo, Bernardo; Cirone, Markus; La Barbera, Antonino; de Pasquale, Ferdinando

    2002-03-01

    We investigate the role of noise in the nonlinear relaxation of two ecosystems described by generalized Lotka-Volterra equations in the presence of multiplicative noise. Specifically we study two cases: (i) an ecosystem with two interacting species in the presence of periodic driving; (ii) an ecosystem with a great number of interacting species with random interaction matrix. We analyse the interplay between noise and periodic modulation for case (i) and the role of the noise in the transient dynamics of the ecosystem in the presence of an absorbing barrier in case (ii). We find that the presence of noise is responsible for the generation of temporal oscillations and for the appearance of spatial patterns in the first case. In the other case we obtain the asymptotic behaviour of the time average of the ith population and discuss the effect of the noise on the probability distributions of the population and of the local field.

  10. Migratory diversity predicts population declines in birds.

    PubMed

    Gilroy, James J; Gill, Jennifer A; Butchart, Stuart H M; Jones, Victoria R; Franco, Aldina M A

    2016-03-01

    Declines in migratory species are a pressing concern worldwide, but the mechanisms underpinning these declines are not fully understood. We hypothesised that species with greater within-population variability in migratory movements and destinations, here termed 'migratory diversity', might be more resilient to environmental change. To test this, we related map-based metrics of migratory diversity to recent population trends for 340 European breeding birds. Species that occupy larger non-breeding ranges relative to breeding, a characteristic we term 'migratory dispersion', were less likely to be declining than those with more restricted non-breeding ranges. Species with partial migration strategies (i.e. overlapping breeding and non-breeding ranges) were also less likely to be declining than full migrants or full residents, an effect that was independent of migration distance. Recent rates of advancement in Europe-wide spring arrival date were greater for partial migrants than full migrants, suggesting that migratory diversity may also help facilitate species responses to climate change. PMID:26807694

  11. 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.

  12. Effects of culling on mesopredator population dynamics.

    PubMed

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

    2013-01-01

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

  13. Effects of Culling on Mesopredator Population Dynamics

    PubMed Central

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

    2013-01-01

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

  14. Patterns and localized structures in population dynamics

    NASA Astrophysics Data System (ADS)

    Clerc, M. G.; Escaff, D.; Kenkre, V. M.

    2005-11-01

    Patterns, fronts, and localized structures of a prototypical model for population dynamics interaction are studied. The physical content of the model is the coexistence of a simple random walk for the motion of the individuals with a nonlinearity in the competitive struggle for resources which simultaneously stresses the Allee effect and interaction at a distance. Mathematically, the model is variational and exhibits coexistence between different stable extended states. Solutions are obtained, the phase diagram is constructed, and the emergence of localized structures is investigated.

  15. A population dynamics approach to biological aging

    NASA Astrophysics Data System (ADS)

    de Almeida, R. M. C.

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

  16. Implementation of Genomic Prediction in Lolium perenne (L.) Breeding Populations

    PubMed Central

    Grinberg, Nastasiya F.; Lovatt, Alan; Hegarty, Matt; Lovatt, Andi; Skøt, Kirsten P.; Kelly, Rhys; Blackmore, Tina; Thorogood, Danny; King, Ross D.; Armstead, Ian; Powell, Wayne; Skøt, Leif

    2016-01-01

    Perennial ryegrass (Lolium perenne L.) is one of the most widely grown forage grasses in temperate agriculture. In order to maintain and increase its usage as forage in livestock agriculture, there is a continued need for improvement in biomass yield, quality, disease resistance, and seed yield. Genetic gain for traits such as biomass yield has been relatively modest. This has been attributed to its long breeding cycle, and the necessity to use population based breeding methods. Thanks to recent advances in genotyping techniques there is increasing interest in genomic selection from which genomically estimated breeding values are derived. In this paper we compare the classical RRBLUP model with state-of-the-art machine learning techniques that should yield themselves easily to use in GS and demonstrate their application to predicting quantitative traits in a breeding population of L. perenne. Prediction accuracies varied from 0 to 0.59 depending on trait, prediction model and composition of the training population. The BLUP model produced the highest prediction accuracies for most traits and training populations. Forage quality traits had the highest accuracies compared to yield related traits. There appeared to be no clear pattern to the effect of the training population composition on the prediction accuracies. The heritability of the forage quality traits was generally higher than for the yield related traits, and could partly explain the difference in accuracy. Some population structure was evident in the breeding populations, and probably contributed to the varying effects of training population on the predictions. The average linkage disequilibrium between adjacent markers ranged from 0.121 to 0.215. Higher marker density and larger training population closely related with the test population are likely to improve the prediction accuracy. PMID:26904088

  17. Dynamics of a feline retrovirus (FeLV) in host populations with variable spatial structure.

    PubMed Central

    Fromont, E; Pontier, D; Langlais, M

    1998-01-01

    The predictions of epidemic models are remarkably affected by the underlying assumptions concerning host population dynamics and the relation between host density and disease transmission. Furthermore, hypotheses underlying distinct models are rarely tested. Domestic cats (Felis catus) can be used to compare models and test their predictions, because cat populations show variable spatial structure that probably results in variability in the relation between density and disease transmission. Cat populations also exhibit various dynamics. We compare four epidemiological models of Feline Leukaemia Virus (FeLV). We use two different incidence terms, i.e. proportionate mixing and pseudo-mass action. Population dynamics are modelled as logistic or exponential growth. Compared with proportionate mixing, mass action incidence with logistic growth results in a threshold population size under which the virus cannot persist in the population. Exponential growth of host populations results in systems where FeLV persistence at a steady prevalence and depression of host population growth are biologically unlikely to occur. Predictions of our models account for presently available data on FeLV dynamics in various populations of cats. Thus, host population dynamics and spatial structure can be determinant parameters in parasite transmission, host population depression, and disease control. PMID:9684375

  18. Prediction of dynamical systems by symbolic regression

    NASA Astrophysics Data System (ADS)

    Quade, Markus; Abel, Markus; Shafi, Kamran; Niven, Robert K.; Noack, Bernd R.

    2016-07-01

    We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or simplified models need to be found. We focus on symbolic regression methods as a part of machine learning. These algorithms are capable of learning an analytically tractable model from data, a highly valuable property. Symbolic regression methods can be considered as generalized regression methods. We investigate two particular algorithms, the so-called fast function extraction which is a generalized linear regression algorithm, and genetic programming which is a very general method. Both are able to combine functions in a certain way such that a good model for the prediction of the temporal evolution of a dynamical system can be identified. We illustrate the algorithms by finding a prediction for the evolution of a harmonic oscillator based on measurements, by detecting an arriving front in an excitable system, and as a real-world application, the prediction of solar power production based on energy production observations at a given site together with the weather forecast.

  19. Prediction of dynamical systems by symbolic regression.

    PubMed

    Quade, Markus; Abel, Markus; Shafi, Kamran; Niven, Robert K; Noack, Bernd R

    2016-07-01

    We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or simplified models need to be found. We focus on symbolic regression methods as a part of machine learning. These algorithms are capable of learning an analytically tractable model from data, a highly valuable property. Symbolic regression methods can be considered as generalized regression methods. We investigate two particular algorithms, the so-called fast function extraction which is a generalized linear regression algorithm, and genetic programming which is a very general method. Both are able to combine functions in a certain way such that a good model for the prediction of the temporal evolution of a dynamical system can be identified. We illustrate the algorithms by finding a prediction for the evolution of a harmonic oscillator based on measurements, by detecting an arriving front in an excitable system, and as a real-world application, the prediction of solar power production based on energy production observations at a given site together with the weather forecast. PMID:27575130

  20. Predictable nonlinear dynamics: Advances and limitations

    SciTech Connect

    Anosov, L.A.; Butkovskii, O.Y.; Kravtsov, Y.A.; Surovyatkina, E.D.

    1996-06-01

    Methods for reconstruction chaotic dynamical system structure directly from experimental time series are described. Effectiveness of general methods is illustrated with the results of numerical simulation. It is of common interest that from the single time series it is possible to reconstruct a set of interconnected variables. Predictive power of dynamical models, provided by the nonlinear dynamics inverse problem solution, is limited firstly by the noise level in the system under study and is characterized by the horizon of predictability. New physical results are presented, concerning nonstationary and bifurcation nonlinear systems: (1) algorithms for revealing of nonstationarity in random-like chaotic time-series are suggested based on discriminant analysis with nonlinear discriminant function; (2) an opportunity is established to predict the final state in bifurcation system with quickly varying control parameters; (3) hysteresis is founded out in bifurcation system with quickly varying parameters; (4) delayed correlation {l_angle}noise-prediction error{r_angle} in chaotic systems is revealed. {copyright} {ital 1996 American Institute of Physics.}

  1. Application of optimal prediction to molecular dynamics

    SciTech Connect

    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.

  2. Predictive dynamics of human pain perception.

    PubMed

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

    2012-01-01

    While the static magnitude of thermal pain perception has been shown to follow a power-law function of the temperature, its dynamical features have been largely overlooked. Due to the slow temporal experience of pain, multiple studies now show that the time evolution of its magnitude can be captured with continuous online ratings. Here we use such ratings to model quantitatively the temporal dynamics of thermal pain perception. We show that a differential equation captures the details of the temporal evolution in pain ratings in individual subjects for different stimulus pattern complexities, and also demonstrates strong predictive power to infer pain ratings, including readouts based only on brain functional images. PMID:23133342

  3. [Population dynamics and development in the Caribbean].

    PubMed

    Boland, B

    1995-12-01

    The impact is examined of socioeconomic factors on Caribbean population dynamics. This work begins by describing the socioeconomic context of the late 1980s and early 1990s, under the influence of the economic changes and crises of the 1980s. The small size, openness, dependency, and lack of diversification of the Caribbean economies have made them vulnerable to external pressures. The Bahamas and Belize had economic growth rates exceeding 5% annually during 1981-90, but most of the countries had low or negative growth. Unemployment, poverty, the structural adjustment measures adopted in the mid-1980s, and declines in social spending exacerbated general economic conditions. In broad terms, the population situation of the Caribbean is marked by diversity of sizes and growth rates. A few countries oriented toward services and tourism had demographic growth rates exceeding 3%, while at least 7 had almost no growth or negative growth. Population growth rates reflected different combinations of natural increase and migration. Crude death rates ranged from around 5/1000 to 11/1000, except in Haiti, and all countries of the region except Haiti had life expectancies of 70 years or higher. Despite fertility decline, the average crude birth rate was still relatively high at 26/1000, and the rate of natural increase was 1.8% annually for the region. Nearly half of the regional population was under 15 or over 65 years old. The body of this work provides greater detail on mortality patterns, variations by sex, infant mortality, causes of death, and implications for policy. The discussion of fertility includes general patterns and trends, age specific fertility rates, contraceptive prevalence, levels of adolescent fertility and age factors in adolescent sexual behavior, characteristics of adolescent unions, contraceptive usage, health and social consequences of adolescent childbearing, and the search for solutions. The final section describes the magnitude and causes of

  4. 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

  5. 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.

  6. Building the bridge between animal movement and population dynamics

    PubMed Central

    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

  7. Assessing tiger population dynamics using photographic capture-recapture sampling

    USGS Publications Warehouse

    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

  8. Long-term dynamics of Typha populations

    USGS Publications Warehouse

    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.

  9. Stochasticity and universal dynamics in communicating cellular populations

    NASA Astrophysics Data System (ADS)

    Noorbakhsh, Javad; Mehta, Pankaj; Allyson Sgro Collaboration; David Schwab Collaboration; Troy Mestler Collaboration; Thomas Gregor Collaboration

    2014-03-01

    A fundamental problem in biology is to understand how biochemical networks within individual cells coordinate and control population-level behaviors. Our knowledge of these biochemical networks is often incomplete, with little known about the underlying kinetic parameters. Here, we present a general modeling approach for overcoming these challenges based on universality. We apply our approach to study the emergence of collective oscillations of the signaling molecule cAMP in populations of the social amoebae Dictyostelium discoideum and show that a simple two-dimensional dynamical system can reproduce signaling dynamics of single cells and successfully predict novel population-level behaviors. We reduce all the important parameters of our model to only two and will study its behavior through a phase diagram. This phase diagram determines conditions under which cells are quiet or oscillating either coherently or incoherently. Furthermore it allows us to study the effect of different model components such as stochasticity, multicellularity and signal preprocessing. A central finding of our model is that Dictyostelium exploit stochasticity within biochemical networks to control population level behaviors.

  10. Predicting the dynamics of protein abundance.

    PubMed

    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

  11. Predicting the Dynamics of Protein Abundance

    PubMed Central

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

    2014-01-01

    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

  12. The island syndrome and population dynamics of introduced rats.

    PubMed

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

    2011-11-01

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

  13. Predicting the response of populations to environmental change

    SciTech Connect

    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.

  14. 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.

  15. When Should Harvest Evolution Matter to Population Dynamics?

    PubMed

    Nusslé, Sébastien; Hendry, Andrew P; Carlson, Stephanie M

    2016-07-01

    The potential for evolution to influence fishery sustainability remains a controversial topic. We highlight new modeling research from Dunlop et al. that explores when and how fisheries-induced evolution matters for population dynamics, while also emphasizing transient dynamics in population growth and life history-dependent responses that influence population stability and resiliency. PMID:27095380

  16. Dynamics of adaptive immunity against phage in bacterial populations

    NASA Astrophysics Data System (ADS)

    Bradde, Serena; Vucelja, Marija; Tesileanu, Tiberiu; Balasubramanian, Vijay

    The CRISPR (clustered regularly interspaced short palindromic repeats) mechanism allows bacteria to adaptively defend against phages by acquiring short genomic sequences (spacers) that target specific sequences in the viral genome. We propose a population dynamical model where immunity can be both acquired and lost. The model predicts regimes where bacterial and phage populations can co-exist, others where the populations oscillate, and still others where one population is driven to extinction. Our model considers two key parameters: (1) ease of acquisition and (2) spacer effectiveness in conferring immunity. Analytical calculations and numerical simulations show that if spacers differ mainly in ease of acquisition, or if the probability of acquiring them is sufficiently high, bacteria develop a diverse population of spacers. On the other hand, if spacers differ mainly in their effectiveness, their final distribution will be highly peaked, akin to a ``winner-take-all'' scenario, leading to a specialized spacer distribution. Bacteria can interpolate between these limiting behaviors by actively tuning their overall acquisition rate.

  17. Extreme events: dynamics, statistics and prediction

    NASA Astrophysics Data System (ADS)

    Ghil, M.

    2011-12-01

    In this talk, I will review work on extreme events, their causes and consequences, by a group of European and American researchers involved in a three-year project on these topics. 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.

  18. Extreme events: dynamics, statistics and prediction

    NASA Astrophysics Data System (ADS)

    Ghil, M.; Yiou, P.; Hallegatte, S.; Malamud, B. D.; Naveau, P.; Soloviev, A.; Friederichs, P.; Keilis-Borok, V.; Kondrashov, D.; Kossobokov, V.; Mestre, O.; Nicolis, C.; Rust, H. W.; Shebalin, P.; Vrac, M.; Witt, A.; Zaliapin, I.

    2011-05-01

    We review work on extreme events, their causes and consequences, by a group of European and American researchers involved in a three-year project on these topics. 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.

  19. Effects of temporal variation in temperature and density dependence on insect population dynamics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Understanding effects of environmental variation on insect populations is important in light of predictions about increasing future climatic variability. In order to understand the effects of changing environmental variation on population dynamics and life history evolution in insects one would need...

  20. The influence of historical climate on the population dynamics of three dominant sagebrush steppe plants.

    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...

  1. Population Dynamics of Early Human Migration in Britain

    PubMed Central

    Vahia, Mayank N.; Ladiwala, Uma; Mahathe, Pavan; Mathur, Deepak

    2016-01-01

    Background Early human migration is largely determined by geography and human needs. These are both deterministic parameters when small populations move into unoccupied areas where conflicts and large group dynamics are not important. The early period of human migration into the British Isles provides such a laboratory which, because of its relative geographical isolation, may allow some insights into the complex dynamics of early human migration and interaction. Method and Results We developed a simulation code based on human affinity to habitable land, as defined by availability of water sources, altitude, and flatness of land, in choosing the path of migration. Movement of people on the British island over the prehistoric period from their initial entry points was simulated on the basis of data from the megalithic period. Topographical and hydro-shed data from satellite databases was used to define habitability, based on distance from water bodies, flatness of the terrain, and altitude above sea level. We simulated population movement based on assumptions of affinity for more habitable places, with the rate of movement tempered by existing populations. We compared results of our computer simulations with genetic data and show that our simulation can predict fairly accurately the points of contacts between different migratory paths. Such comparison also provides more detailed information about the path of peoples’ movement over ~2000 years before the present era. Conclusions We demonstrate an accurate method to simulate prehistoric movements of people based upon current topographical satellite data. Our findings are validated by recently-available genetic data. Our method may prove useful in determining early human population dynamics even when no genetic information is available. PMID:27148959

  2. Dynamics of Genome Rearrangement in Bacterial Populations

    PubMed Central

    Darling, Aaron E.; Miklós, István; Ragan, Mark A.

    2008-01-01

    first characterization of genome arrangement evolution in a bacterial population evolving outside laboratory conditions. Insight into the process of genomic rearrangement may further the understanding of pathogen population dynamics and selection on the architecture of circular bacterial chromosomes. PMID:18650965

  3. Population dynamics of Yellowstone grizzly bears

    USGS Publications Warehouse

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

    1985-01-01

    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 and 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.

  4. Predictive accuracy of population viability analysis in conservation biology.

    PubMed

    Brook, B W; O'Grady, J J; Chapman, A P; Burgman, M A; Akçakaya, H R; Frankham, R

    2000-03-23

    Population viability analysis (PVA) is widely applied in conservation biology to predict extinction risks for threatened species and to compare alternative options for their management. It can also be used as a basis for listing species as endangered under World Conservation Union criteria. However, there is considerable scepticism regarding the predictive accuracy of PVA, mainly because of a lack of validation in real systems. Here we conducted a retrospective test of PVA based on 21 long-term ecological studies--the first comprehensive and replicated evaluation of the predictive powers of PVA. Parameters were estimated from the first half of each data set and the second half was used to evaluate the performance of the model. Contrary to recent criticisms, we found that PVA predictions were surprisingly accurate. The risk of population decline closely matched observed outcomes, there was no significant bias, and population size projections did not differ significantly from reality. Furthermore, the predictions of the five PVA software packages were highly concordant. We conclude that PVA is a valid and sufficiently accurate tool for categorizing and managing endangered species. PMID:10746724

  5. DEMOGRAPHIC PROCESSES: POPULATION DYNAMICS IN HETEROGENEOUS LANDSCAPES

    EPA Science Inventory

    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 ...

  6. Consequences of parental care on population dynamics

    NASA Astrophysics Data System (ADS)

    de Oliveira, S. Moss

    1999-12-01

    We review the results obtained using the Penna model for biological ageing (T.J.P. Penna, J. Stat. Phys. 78 (1995) 1629) when different strategies of parental care are introduced into evolving populations. These results concern to: longevity of semelparous populations; self-organization of female menopause; the spatial distribution of the populations and finally, sexual fidelity.

  7. Experimental evidence of antiphase population dynamics in lasers

    SciTech Connect

    Cabrera, Eduardo; Calderon, Oscar G.; Guerra, J.M.

    2005-10-15

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

  8. Risk prediction models for hepatocellular carcinoma in different populations

    PubMed Central

    Ma, Xiao; Yang, Yang; Tu, Hong; Gao, Jing; Tan, Yu-Ting; Zheng, Jia-Li; Bray, Freddie; Xiang, Yong-Bing

    2016-01-01

    Hepatocellular carcinoma (HCC) is a malignant disease with limited therapeutic options due to its aggressive progression. It places heavy burden on most low and middle income countries to treat HCC patients. Nowadays accurate HCC risk predictions can help making decisions on the need for HCC surveillance and antiviral therapy. HCC risk prediction models based on major risk factors of HCC are useful and helpful in providing adequate surveillance strategies to individuals who have different risk levels. Several risk prediction models among cohorts of different populations for estimating HCC incidence have been presented recently by using simple, efficient, and ready-to-use parameters. Moreover, using predictive scoring systems to assess HCC development can provide suggestions to improve clinical and public health approaches, making them more cost-effective and effort-effective, for inducing personalized surveillance programs according to risk stratification. In this review, the features of risk prediction models of HCC across different populations were summarized, and the perspectives of HCC risk prediction models were discussed as well. PMID:27199512

  9. Risk prediction models for hepatocellular carcinoma in different populations.

    PubMed

    Ma, Xiao; Yang, Yang; Tu, Hong; Gao, Jing; Tan, Yu-Ting; Zheng, Jia-Li; Bray, Freddie; Xiang, Yong-Bing

    2016-04-01

    Hepatocellular carcinoma (HCC) is a malignant disease with limited therapeutic options due to its aggressive progression. It places heavy burden on most low and middle income countries to treat HCC patients. Nowadays accurate HCC risk predictions can help making decisions on the need for HCC surveillance and antiviral therapy. HCC risk prediction models based on major risk factors of HCC are useful and helpful in providing adequate surveillance strategies to individuals who have different risk levels. Several risk prediction models among cohorts of different populations for estimating HCC incidence have been presented recently by using simple, efficient, and ready-to-use parameters. Moreover, using predictive scoring systems to assess HCC development can provide suggestions to improve clinical and public health approaches, making them more cost-effective and effort-effective, for inducing personalized surveillance programs according to risk stratification. In this review, the features of risk prediction models of HCC across different populations were summarized, and the perspectives of HCC risk prediction models were discussed as well. PMID:27199512

  10. Prediction of pancreatic necrosis by dynamic pancreatography.

    PubMed Central

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

    1989-01-01

    Parenchymal necrosis has recently been recognized as the principal determinant of the incidence of secondary infection in acute pancreatitis. Because secondary infection of pancreatic necrosis accounts for more than 80% of all deaths from acute pancreatitis, a method for determining the presence or absence of parenchymal necrosis would offer considerable prognostic and therapeutic information. Thirty seven patients with unequivocal acute pancreatitis and five normal controls were prospectively studied with intravenous bolus, contrast-enhanced computed tomography (dynamic pancreatography). In the absence of pancreatic necrosis, there were no significant differences in parenchymal enhancement between any of the following patient groups: controls (5), uncomplicated pancreatitis (20), pancreatic abscess (7), or peripancreatic necrosis (4)(p less than 0.05). On the other hand, pancreatic parenchymal enhancement was significantly reduced or absent in all six patients with segmental or diffuse pancreatic necrosis (p less than 0.05). Postcontrast pancreatic parenchymal enhancement was also found to be inversely correlated with the number of Ranson signs (p less than 0.001). Dynamic pancreatography offers prognostic information and is a safe and reliable technique for predicting the presence or absence of pancreatic parenchymal necrosis. Images Figs. 1A and B. Figs. 3A and B. Figs. 4A and B. Fig. 5. Figs. 6A and B. Fig. 7. PMID:2802834

  11. 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.

  12. Evolutionary dynamics with fluctuating population sizes and strong mutualism.

    PubMed

    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. PMID:26382443

  13. [The effect of the new technological revolution on population dynamics].

    PubMed

    Wu, K

    1985-01-29

    The impact of modernization on population dynamics in China is examined. The author notes that the industrialization process involves the concentration of the population in urban areas and the mechanization of agriculture. The need to redistribute the urban population from major urban areas to smaller towns is noted. PMID:12314273

  14. Population dynamics of Yellowstone grizzly bears

    SciTech Connect

    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.

  15. [Population dynamics and education in Paraguay].

    PubMed

    1977-01-01

    Formulation of development plans and of demographic policies for Paraguay must take into consideration the national reality as a whole, with its cultural, moral, religious, and political values. Other factors to be considered are: 1) the relatively low density of the population; 2) the low mortality, which influences a rather rapid population growth; 3) the predominance of a population in young age; and, 4) the new tendency to urbanzation. PMID:12309623

  16. Predicting neonatal pharmacokinetics from prior data using population pharmacokinetic modeling.

    PubMed

    Wang, Jian; Edginton, Andrea N; Avant, Debbie; Burckart, Gilbert J

    2015-10-01

    Selection of the first dose for neonates in clinical trials is very challenging. The objective of this analysis was to assess if a population pharmacokinetic (PK) model developed with data from infants to adults is predictive of neonatal clearance and to evaluate what age range of prior PK data is needed for informative modeling to predict neonate exposure. Two sources of pharmacokinetic data from 8 drugs were used to develop population models: (1) data from all patients > 2 years of age, and (2) data from all nonneonatal patients aged > 28 days. The prediction error based on the models using data from subjects > 2 years of age showed bias toward overprediction, with median average fold error (AFE) for CL predicted/CLobserved greater than 1.5. The bias for predicting neonatal PK was improved when using all prior PK data including infants as opposed to an assessment without infant PK data, with the median AFE 0.91. As an increased number of pediatric trials are conducted in neonates under the Food and Drug Administration Safety and Innovation Act, dose selection should be based on the best estimates of neonatal pharmacokinetics and pharmacodynamics prior to conducting efficacy and safety studies in neonates. PMID:25907280

  17. Introducing Dynamic Analysis Using Malthus's Principle of Population.

    ERIC Educational Resources Information Center

    Pingle, Mark

    2003-01-01

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

  18. Predictability of population displacement after the 2010 Haiti earthquake

    PubMed Central

    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

  19. Predictability of population displacement after the 2010 Haiti earthquake.

    PubMed

    Lu, Xin; Bengtsson, Linus; Holme, Petter

    2012-07-17

    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

  20. THE POPULATION OF HELIUM-MERGER PROGENITORS: OBSERVATIONAL PREDICTIONS

    SciTech Connect

    Fryer, Chris L.; Belczynski, Krzysztof; Bulik, Tomasz; Berger, Edo; Thoene, Christina

    2013-02-20

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

  1. Mapping Genes that Predict Treatment Outcome in Admixed Populations

    PubMed Central

    Baye, Tesfaye M.; Wilke, Russell A.

    2010-01-01

    There is great interest in characterizing the genetic architecture underlying drug response. For many drugs, gene-based dosing models explain a considerable amount of the overall variation in treatment outcome. As such, prescription drug labels are increasingly being modified to contain pharmacogenetic information. Genetic data must, however, be interpreted within the context of relevant clinical covariates. Even the most predictive models improve with the addition of data related to biogeographical ancestry. The current review explores analytical strategies that leverage population structure to more fully characterize genetic determinants of outcome in large clinical practice-based cohorts. The success of this approach will depend upon several key factors: (1) the availability of outcome data from groups of admixed individuals (i.e., populations recombined over multiple generations), (2) a measurable difference in treatment outcome (i.e., efficacy and toxicity endpoints), and (3) a measurable difference in allele frequency between the ancestral populations. PMID:20921971

  2. Delay driven spatiotemporal chaos in single species population dynamics models.

    PubMed

    Jankovic, Masha; Petrovskii, Sergei; Banerjee, Malay

    2016-08-01

    Questions surrounding the prevalence of complex population dynamics form one of the central themes in ecology. Limit cycles and spatiotemporal chaos are examples that have been widely recognised theoretically, although their importance and applicability to natural populations remains debatable. The ecological processes underlying such dynamics are thought to be numerous, though there seems to be consent as to delayed density dependence being one of the main driving forces. Indeed, time delay is a common feature of many ecological systems and can significantly influence population dynamics. In general, time delays may arise from inter- and intra-specific trophic interactions or population structure, however in the context of single species populations they are linked to more intrinsic biological phenomena such as gestation or resource regeneration. In this paper, we consider theoretically the spatiotemporal dynamics of a single species population using two different mathematical formulations. Firstly, we revisit the diffusive logistic equation in which the per capita growth is a function of some specified delayed argument. We then modify the model by incorporating a spatial convolution which results in a biologically more viable integro-differential model. Using the combination of analytical and numerical techniques, we investigate the effect of time delay on pattern formation. In particular, we show that for sufficiently large values of time delay the system's dynamics are indicative to spatiotemporal chaos. The chaotic dynamics arising in the wake of a travelling population front can be preceded by either a plateau corresponding to dynamical stabilisation of the unstable equilibrium or by periodic oscillations. PMID:27154920

  3. Modeling the population dynamics of Culex quinquefasciatus (Diptera: Culicidae), along an elevational gradient in Hawaii.

    PubMed

    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

  4. Reconstructing local population dynamics in noisy metapopulations--the role of random catastrophes and Allee effects.

    PubMed

    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

  5. Reconstructing Local Population Dynamics in Noisy Metapopulations—The Role of Random Catastrophes and Allee Effects

    PubMed Central

    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

  6. Evolution of specialization under non-equilibrium population dynamics.

    PubMed

    Nurmi, Tuomas; Parvinen, Kalle

    2013-03-21

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

  7. 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.

  8. Stochastic dynamics and logistic population growth.

    PubMed

    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. PMID:26172687

  9. 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.

  10. From neural responses to population behavior: neural focus group predicts population-level media effects.

    PubMed

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

    2012-05-01

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

  11. When stable-stage equilibrium is unlikely: integrating transient population dynamics improves asymptotic methods

    PubMed Central

    Tremblay, Raymond L.; Raventos, Josep; Ackerman, James D.

    2015-01-01

    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

  12. Understanding and predicting ecological dynamics: are major surprises inevitable?

    PubMed

    Doak, Daniel F; Estes, James A; Halpern, Benjamin S; Jacob, Ute; Lindberg, David R; Lovvorn, James; Monson, Daniel H; Tinker, M Timothy; Williams, Terrie M; Wootton, J Timothy; Carroll, Ian; Emmerson, Mark; Micheli, Fiorenza; Novak, Mark

    2008-04-01

    Ecological surprises, substantial and unanticipated changes in the abundance of one or more species that result from previously unsuspected processes, are a common outcome of both experiments and observations in community and population ecology. Here, we give examples of such surprises along with the results of a survey of well-established field ecologists, most of whom have encountered one or more surprises over the course of their careers. Truly surprising results are common enough to require their consideration in any reasonable effort to characterize nature and manage natural resources. We classify surprises as dynamic-, pattern-, or intervention-based, and we speculate on the common processes that cause ecological systems to so often surprise us. A long-standing and still growing concern in the ecological literature is how best to make predictions of future population and community dynamics. Although most work on this subject involves statistical aspects of data analysis and modeling, the frequency and nature of ecological surprises imply that uncertainty cannot be easily tamed through improved analytical procedures, and that prudent management of both exploited and conserved communities will require precautionary and adaptive management approaches. PMID:18481520

  13. Dynamic population mapping using mobile phone data.

    PubMed

    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

  14. Dynamic population mapping using mobile phone data

    PubMed Central

    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

  15. Modeling seasonal interactions in the population dynamics of migratory birds

    USGS Publications Warehouse

    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.

  16. Indirect effects of primary prey population dynamics on alternative prey.

    PubMed

    Barraquand, Frédéric; New, Leslie F; Redpath, Stephen; Matthiopoulos, Jason

    2015-08-01

    We develop a theory of generalist predation showing how alternative prey species are affected by changes in both mean abundance and variability (coefficient of variation) of their predator's primary prey. The theory is motivated by the indirect effects of cyclic rodent populations on ground-breeding birds, and developed through progressive analytic simplifications of an empirically-based model. It applies nonetheless to many other systems where primary prey have fast life-histories and can become superabundant, thus facilitating impact on alternative prey species and generating highly asymmetric interactions. Our results suggest that predator effects on alternative prey should generally decrease with mean primary prey abundance, and increase with primary prey variability (low to high CV)-unless predators have strong aggregative responses, in which case these results can be reversed. Approximations of models including predator dynamics (general numerical response with possible delays) confirm these results but further suggest that negative temporal correlation between predator and primary prey is harmful to alternative prey. Finally, we find that measurements of predator numerical responses are crucial to predict-even qualitatively-the response of ecosystems to changes in the dynamics of outbreaking prey species. PMID:25930160

  17. Within and between population variation in plant traits predicts ecosystem functions associated with a dominant plant species

    PubMed Central

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

    2012-01-01

    Linking intraspecific variation in plant traits to ecosystem carbon uptake may allow us to better predict how shift in populations shape ecosystem function. We investigated whether plant populations of a dominant old-field plant species (Solidago altissima) differed in carbon dynamics and if variation in plant traits among genotypes and between populations predicted carbon dynamics. We established a common garden experiment with 35 genotypes from three populations of S. altissima from either Tennessee (southern populations) or Connecticut (northern populations) to ask whether: (1) southern and northern Solidago populations will differ in aboveground productivity, leaf area, flowering time and duration, and whole ecosystem carbon uptake, (2) intraspecific trait variation (growth and reproduction) will be related to intraspecific variation in gross ecosystem CO2 exchange (GEE) and net ecosystem CO2 exchange (NEE) within and between northern and southern populations. GEE and NEE were 4.8× and 2× greater in southern relative to northern populations. Moreover, southern populations produced 13× more aboveground biomass and 1.4× more inflorescence mass than did northern populations. Flowering dynamics (first- and last-day flowering and flowering duration) varied significantly among genotypes in both the southern and northern populations, but plant performance and ecosystem function did not. Both productivity and inflorescence mass predicted NEE and GEE between S. altissima southern and northern populations. Taken together, our data demonstrate that variation between S. altissima populations in performance and flowering traits are strong predictors of ecosystem function in a dominant old-field species and suggest that populations of the same species might differ substantially in their response to environmental perturbations. PMID:22833791

  18. PC BEEPOP - A PERSONAL COMPUTER HONEY BEE POPULATION DYNAMICS MODEL

    EPA Science Inventory

    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...

  19. A linear model of population dynamics

    NASA Astrophysics Data System (ADS)

    Lushnikov, A. A.; Kagan, A. I.

    2016-08-01

    The Malthus process of population growth is reformulated in terms of the probability w(n,t) to find exactly n individuals at time t assuming that both the birth and the death rates are linear functions of the population size. The master equation for w(n,t) is solved exactly. It is shown that w(n,t) strongly deviates from the Poisson distribution and is expressed in terms either of Laguerre’s polynomials or a modified Bessel function. The latter expression allows for considerable simplifications of the asymptotic analysis of w(n,t).

  20. Multistability in simplest models of the population dynamics

    NASA Astrophysics Data System (ADS)

    Zhdanova, Oksana L.; Frisman, Efim Ya.

    2016-06-01

    The investigation of dynamics behavior of population number and genetic structure has been conducted for a homogeneous limited population influenced by density-dependent selection in single di-allelic genetic locus. The detailed investigation of the mechanisms of the loss of stability in the considered model is carried out. It is shown that coexistence of several different asymptotic dynamic regimes (with own attraction basins) is possible in numerous enough parametric regions which are meaningful biologically.

  1. Human population dynamics in Europe over the Last Glacial Maximum

    PubMed Central

    Tallavaara, Miikka; Luoto, Miska; Korhonen, Natalia; Järvinen, Heikki; Seppä, Heikki

    2015-01-01

    The severe cooling and the expansion of the ice sheets during the Last Glacial Maximum (LGM), 27,000–19,000 y ago (27–19 ky ago) had a major impact on plant and animal populations, including humans. Changes in human population size and range have affected our genetic evolution, and recent modeling efforts have reaffirmed the importance of population dynamics in cultural and linguistic evolution, as well. However, in the absence of historical records, estimating past population levels has remained difficult. Here we show that it is possible to model spatially explicit human population dynamics from the pre-LGM at 30 ky ago through the LGM to the Late Glacial in Europe by using climate envelope modeling tools and modern ethnographic datasets to construct a population calibration model. The simulated range and size of the human population correspond significantly with spatiotemporal patterns in the archaeological data, suggesting that climate was a major driver of population dynamics 30–13 ky ago. The simulated population size declined from about 330,000 people at 30 ky ago to a minimum of 130,000 people at 23 ky ago. The Late Glacial population growth was fastest during Greenland interstadial 1, and by 13 ky ago, there were almost 410,000 people in Europe. Even during the coldest part of the LGM, the climatically suitable area for human habitation remained unfragmented and covered 36% of Europe. PMID:26100880

  2. Human population dynamics in Europe over the Last Glacial Maximum.

    PubMed

    Tallavaara, Miikka; Luoto, Miska; Korhonen, Natalia; Järvinen, Heikki; Seppä, Heikki

    2015-07-01

    The severe cooling and the expansion of the ice sheets during the Last Glacial Maximum (LGM), 27,000-19,000 y ago (27-19 ky ago) had a major impact on plant and animal populations, including humans. Changes in human population size and range have affected our genetic evolution, and recent modeling efforts have reaffirmed the importance of population dynamics in cultural and linguistic evolution, as well. However, in the absence of historical records, estimating past population levels has remained difficult. Here we show that it is possible to model spatially explicit human population dynamics from the pre-LGM at 30 ky ago through the LGM to the Late Glacial in Europe by using climate envelope modeling tools and modern ethnographic datasets to construct a population calibration model. The simulated range and size of the human population correspond significantly with spatiotemporal patterns in the archaeological data, suggesting that climate was a major driver of population dynamics 30-13 ky ago. The simulated population size declined from about 330,000 people at 30 ky ago to a minimum of 130,000 people at 23 ky ago. The Late Glacial population growth was fastest during Greenland interstadial 1, and by 13 ky ago, there were almost 410,000 people in Europe. Even during the coldest part of the LGM, the climatically suitable area for human habitation remained unfragmented and covered 36% of Europe. PMID:26100880

  3. Developing demographic toxicity data: optimizing effort for predicting population outcomes

    PubMed Central

    Stark, John D.

    2016-01-01

    Mounting evidence suggests that population endpoints in risk assessment are far more accurate than static assessments. Complete demographic toxicity data based on full life tables are eminently useful in predicting population outcomes in many applications because they capture both lethal and sublethal effects; however, developing these life tables is extremely costly. In this study we investigated the efficiency of partial life cycle tests as a substitute for full life cycles in parameterizing population models. Life table data were developed for three species of Daphniids, Ceriodaphnia dubia, Daphnia magna, and D. pulex, weekly throughout the life span of these species. Population growth rates (λ) and a series of other demographic parameters generated from the complete life cycle were compared to those calculated from cumulative weeks of the life cycle in order to determine the minimum number of weeks needed to generate an accurate population projection. Results showed that for C. dubia and D. pulex, λ values developed at >4 weeks (44.4% of the life cycle) were not significantly different from λ developed for the full life cycle (9 weeks) of each species. For D. magna, λ values developed at >7 weeks (70% of the life cycle) were not significantly different from λ developed for the full life cycle (10 weeks). Furthermore, these cutoff points for λ were not the same for other demographic parameters, with no clear pattern emerging. Our results indicate that for C. dubia, D. magna, and D. pulex, partial life tables can be used to generate population growth rates in lieu of full life tables. However, the implications of differences in cutoff points for different demographic parameters need to be investigated further. PMID:27257546

  4. Developing demographic toxicity data: optimizing effort for predicting population outcomes.

    PubMed

    Stark, John D; Banks, John E

    2016-01-01

    Mounting evidence suggests that population endpoints in risk assessment are far more accurate than static assessments. Complete demographic toxicity data based on full life tables are eminently useful in predicting population outcomes in many applications because they capture both lethal and sublethal effects; however, developing these life tables is extremely costly. In this study we investigated the efficiency of partial life cycle tests as a substitute for full life cycles in parameterizing population models. Life table data were developed for three species of Daphniids, Ceriodaphnia dubia, Daphnia magna, and D. pulex, weekly throughout the life span of these species. Population growth rates (λ) and a series of other demographic parameters generated from the complete life cycle were compared to those calculated from cumulative weeks of the life cycle in order to determine the minimum number of weeks needed to generate an accurate population projection. Results showed that for C. dubia and D. pulex, λ values developed at >4 weeks (44.4% of the life cycle) were not significantly different from λ developed for the full life cycle (9 weeks) of each species. For D. magna, λ values developed at >7 weeks (70% of the life cycle) were not significantly different from λ developed for the full life cycle (10 weeks). Furthermore, these cutoff points for λ were not the same for other demographic parameters, with no clear pattern emerging. Our results indicate that for C. dubia, D. magna, and D. pulex, partial life tables can be used to generate population growth rates in lieu of full life tables. However, the implications of differences in cutoff points for different demographic parameters need to be investigated further. PMID:27257546

  5. 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.

  6. Explaining "Noise" as Environmental Variations in Population Dynamics

    SciTech Connect

    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.

  7. 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.

  8. AN INDIVIDUAL-BASED MODEL OF COTTUS POPULATION DYNAMICS

    EPA Science Inventory

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

  9. Multiple Cancer Cell Population Dynamics in a Complex Ecology

    NASA Astrophysics Data System (ADS)

    Lin, Ke-Chih; Targa, Gonzalo; Pienta, Kenneth; Sturm, James; Austin, Robert

    We have developed a technology for study of complex ecology cancer population dynamics. The technology includes complex drug gradients, full bright field/dark field/fluorescence imaging of areas of several square millimeters and thin gas-permable membranes which allow single cell extraction and analysis. We will present results of studies of prostate cancer cell dynamics.

  10. Accuracy of Four Tooth Size Prediction Methods on Malay Population

    PubMed Central

    Mahmoud, Belal Khaled; Abu Asab, Saifeddin Hamed I.; Taib, Haslina

    2012-01-01

    Objective. To examine the accuracy of Moyers 50%, Tanaka and Johnston, Ling and Wong and Jaroontham and Godfrey methods in predicting the mesio-distal crown width of the permanent canines and premolars (C + P1 + P2) in Malay population. Materials and Methods. The study models of 240 Malay children (120 males and 120 females) aged 14 to 18 years, all free of any signs of dental pathology or anomalies, were measured using a digital caliper accurate to 0.01 mm. The predicted widths (C + P1 + P2) in both arches derived from the tested prediction equations were compared with the actual measured widths. Results. Moyers and Tanaka and Johnston methods showed significant difference between the actual and predicted widths of (C + P1 + P2) for both sexes. Ling and Wong method also showed statistically significant difference for males, however, there was no significant difference for females. Jaroontham and Godfrey method showed statistical significant difference for females, but the male values did not show any significant difference. Conclusion. For male Malay, the method proposed by Jaroontham and Godfrey for male Thai proved to be highly accurate. For female Malay, the method proposed by Ling and Wong for southern Chinese females proved to be highly accurate. PMID:23209918

  11. 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.

  12. Dynamics of single-species population growth: stability or chaos

    SciTech Connect

    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.

  13. Long-Term Trends and Role of Climate in the Population Dynamics of Eurasian Reindeer.

    PubMed

    Uboni, Alessia; Horstkotte, Tim; Kaarlejärvi, Elina; Sévêque, Anthony; Stammler, Florian; Olofsson, Johan; Forbes, Bruce C; Moen, Jon

    2016-01-01

    Temperature is increasing in Arctic and sub-Arctic regions at a higher rate than anywhere else in the world. The frequency and nature of precipitation events are also predicted to change in the future. These changes in climate are expected, together with increasing human pressures, to have significant impacts on Arctic and sub-Arctic species and ecosystems. Due to the key role that reindeer play in those ecosystems, it is essential to understand how climate will affect the region's most important species. Our study assesses the role of climate on the dynamics of fourteen Eurasian reindeer (Rangifer tarandus) populations, using for the first time data on reindeer abundance collected over a 70-year period, including both wild and semi-domesticated reindeer, and covering more than half of the species' total range. We analyzed trends in population dynamics, investigated synchrony among population growth rates, and assessed the effects of climate on population growth rates. Trends in the population dynamics were remarkably heterogeneous. Synchrony was apparent only among some populations and was not correlated with distance among population ranges. Proxies of climate variability mostly failed to explain population growth rates and synchrony. For both wild and semi-domesticated populations, local weather, biotic pressures, loss of habitat and human disturbances appear to have been more important drivers of reindeer population dynamics than climate. In semi-domesticated populations, management strategies may have masked the effects of climate. Conservation efforts should aim to mitigate human disturbances, which could exacerbate the potentially negative effects of climate change on reindeer populations in the future. Special protection and support should be granted to those semi-domesticated populations that suffered the most because of the collapse of the Soviet Union, in order to protect the livelihood of indigenous peoples that depend on the species, and the multi

  14. Long-Term Trends and Role of Climate in the Population Dynamics of Eurasian Reindeer

    PubMed Central

    Horstkotte, Tim; Kaarlejärvi, Elina; Sévêque, Anthony; Stammler, Florian; Olofsson, Johan; Forbes, Bruce C.; Moen, Jon

    2016-01-01

    Temperature is increasing in Arctic and sub-Arctic regions at a higher rate than anywhere else in the world. The frequency and nature of precipitation events are also predicted to change in the future. These changes in climate are expected, together with increasing human pressures, to have significant impacts on Arctic and sub-Arctic species and ecosystems. Due to the key role that reindeer play in those ecosystems, it is essential to understand how climate will affect the region’s most important species. Our study assesses the role of climate on the dynamics of fourteen Eurasian reindeer (Rangifer tarandus) populations, using for the first time data on reindeer abundance collected over a 70-year period, including both wild and semi-domesticated reindeer, and covering more than half of the species’ total range. We analyzed trends in population dynamics, investigated synchrony among population growth rates, and assessed the effects of climate on population growth rates. Trends in the population dynamics were remarkably heterogeneous. Synchrony was apparent only among some populations and was not correlated with distance among population ranges. Proxies of climate variability mostly failed to explain population growth rates and synchrony. For both wild and semi-domesticated populations, local weather, biotic pressures, loss of habitat and human disturbances appear to have been more important drivers of reindeer population dynamics than climate. In semi-domesticated populations, management strategies may have masked the effects of climate. Conservation efforts should aim to mitigate human disturbances, which could exacerbate the potentially negative effects of climate change on reindeer populations in the future. Special protection and support should be granted to those semi-domesticated populations that suffered the most because of the collapse of the Soviet Union, in order to protect the livelihood of indigenous peoples that depend on the species, and the multi

  15. 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.

  16. Growth dynamics and the evolution of cooperation in microbial populations

    NASA Astrophysics Data System (ADS)

    Cremer, Jonas; Melbinger, Anna; Frey, Erwin

    2012-02-01

    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 factors determining the regimes and thereby the evolutionary pathway towards cooperation.

  17. Uncovering the transmission dynamics of Plasmodium vivax using population genetics

    PubMed Central

    Barry, Alyssa E.; Waltmann, Andreea; Koepfli, Cristian; Barnadas, Celine; Mueller, Ivo

    2015-01-01

    Population genetic analysis of malaria parasites has the power to reveal key insights into malaria epidemiology and transmission dynamics with the potential to deliver tools to support control and elimination efforts. Analyses of parasite genetic diversity have suggested that Plasmodium vivax populations are more genetically diverse and less structured than those of Plasmodium falciparum indicating that P. vivax may be a more ancient parasite of humans and/or less susceptible to population bottlenecks, as well as more efficient at disseminating its genes. These population genetic insights into P. vivax transmission dynamics provide an explanation for its relative resilience to control efforts. Here, we describe current knowledge on P. vivax population genetic structure, its relevance to understanding transmission patterns and relapse and how this information can inform malaria control and elimination programmes. PMID:25891915

  18. Generational Spreading Speed and the Dynamics of Population Range Expansion.

    PubMed

    Bateman, Andrew W; Neubert, Michael G; Krkošek, Martin; Lewis, Mark A

    2015-09-01

    Some of the most fundamental quantities in population ecology describe the growth and spread of populations. Population dynamics are often characterized by the annual rate of increase, λ, or the generational rate of increase, R0. Analyses involving R0 have deepened our understanding of disease dynamics and life-history complexities beyond that afforded by analysis of annual growth alone. While range expansion is quantified by the annual spreading speed, a spatial analog of λ, an R0-like expression for the rate of spread is missing. Using integrodifference models, we derive the appropriate generational spreading speed for populations with complex (stage-structured) life histories. The resulting measure, relevant to locations near the expanding edge of a (re)colonizing population, incorporates both local population growth and explicit spatial dispersal rather than solely growth across a population, as is the case for R0. The calculations for generational spreading speed are often simpler than those for annual spreading speed, and analytic or partial analytic solutions can yield insight into the processes that facilitate or slow a population's spatial spread. We analyze the spatial dynamics of green crabs, sea otters, and teasel as examples to demonstrate the flexibility of our methods and the intuitive insights that they afford. PMID:26655354

  19. Prediction of X-33 Engine Dynamic Environments

    NASA Technical Reports Server (NTRS)

    Shi, John J.

    1999-01-01

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

  20. Population dynamics and the ecological stability of obligate pollination mutualisms

    USGS Publications Warehouse

    Holland, J. Nathaniel; DeAngelis, Donald L.

    2001-01-01

    Mutualistic interactions almost always produce both costs and benefits for each of the interacting species. It is the difference between gross benefits and costs that determines the net benefit and the per-capita effect on each of the interacting populations. For example, the net benefit of obligate pollinators, such as yucca and senita moths, to plants is determined by the difference between the number of ovules fertilized from moth pollination and the number of ovules eaten by the pollinator's larvae. It is clear that if pollinator populations are large, then, because many eggs are laid, costs to plants are large, whereas, if pollinator populations are small, gross benefits are low due to lack of pollination. Even though the size and dynamics of the pollinator population are likely to be crucial, their importance has been neglected in the investigation of mechanisms, such as selective fruit abortion, that can limit costs and increase net benefits. Here, we suggest that both the population size and dynamics of pollinators are important in determining the net benefits to plants, and that fruit abortion can significantly affect these. We develop a model of mutualism between populations of plants and their pollinating seed-predators to explore the ecological consequences of fruit abortion on pollinator population dynamics and the net effect on plants. We demonstrate that the benefit to a plant population is unimodal as a function of pollinator abundance, relative to the abundance of flowers. Both selective abortion of fruit with eggs and random abortion of fruit, without reference to whether they have eggs or not, can limit pollinator population size. This can increase the net benefits to the plant population by limiting the number of eggs laid, if the pollination rate remains high. However, fruit abortion can possibly destabilize the pollinator population, with negative consequences for the plant population.

  1. Estimating Traveler Populations at Airport and Cruise Terminals for Population Distribution and Dynamics

    SciTech Connect

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

    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.

  2. Strongly Deterministic Population Dynamics in Closed Microbial Communities

    NASA Astrophysics Data System (ADS)

    Frentz, Zak; Kuehn, Seppe; Leibler, Stanislas

    2015-10-01

    Biological systems are influenced by random processes at all scales, including molecular, demographic, and behavioral fluctuations, as well as by their interactions with a fluctuating environment. We previously established microbial closed ecosystems (CES) as model systems for studying the role of random events and the emergent statistical laws governing population dynamics. Here, we present long-term measurements of population dynamics using replicate digital holographic microscopes that maintain CES under precisely controlled external conditions while automatically measuring abundances of three microbial species via single-cell imaging. With this system, we measure spatiotemporal population dynamics in more than 60 replicate CES over periods of months. In contrast to previous studies, we observe strongly deterministic population dynamics in replicate systems. Furthermore, we show that previously discovered statistical structure in abundance fluctuations across replicate CES is driven by variation in external conditions, such as illumination. In particular, we confirm the existence of stable ecomodes governing the correlations in population abundances of three species. The observation of strongly deterministic dynamics, together with stable structure of correlations in response to external perturbations, points towards a possibility of simple macroscopic laws governing microbial systems despite numerous stochastic events present on microscopic levels.

  3. Population dynamics: Social security, markets, and families

    PubMed Central

    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

  4. Inferences about ungulate population dynamics derived from age ratios

    USGS Publications Warehouse

    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.

  5. A general method for modeling population dynamics and its applications.

    PubMed

    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

  6. Evolutionary dynamics of general group interactions in structured populations.

    PubMed

    Li, Aming; Broom, Mark; Du, Jinming; Wang, Long

    2016-02-01

    The evolution of populations is influenced by many factors, and the simple classical models have been developed in a number of important ways. Both population structure and multiplayer interactions have been shown to significantly affect the evolution of important properties, such as the level of cooperation or of aggressive behavior. Here we combine these two key factors and develop the evolutionary dynamics of general group interactions in structured populations represented by regular graphs. The traditional linear and threshold public goods games are adopted as models to address the dynamics. We show that for linear group interactions, population structure can favor the evolution of cooperation compared to the well-mixed case, and we see that the more neighbors there are, the harder it is for cooperators to persist in structured populations. We further show that threshold group interactions could lead to the emergence of cooperation even in well-mixed populations. Here population structure sometimes inhibits cooperation for the threshold public goods game, where depending on the benefit to cost ratio, the outcomes are bistability or a monomorphic population of defectors or cooperators. Our results suggest, counterintuitively, that structured populations are not always beneficial for the evolution of cooperation for nonlinear group interactions. PMID:26986362

  7. Evolutionary dynamics of general group interactions in structured populations

    NASA Astrophysics Data System (ADS)

    Li, Aming; Broom, Mark; Du, Jinming; Wang, Long

    2016-02-01

    The evolution of populations is influenced by many factors, and the simple classical models have been developed in a number of important ways. Both population structure and multiplayer interactions have been shown to significantly affect the evolution of important properties, such as the level of cooperation or of aggressive behavior. Here we combine these two key factors and develop the evolutionary dynamics of general group interactions in structured populations represented by regular graphs. The traditional linear and threshold public goods games are adopted as models to address the dynamics. We show that for linear group interactions, population structure can favor the evolution of cooperation compared to the well-mixed case, and we see that the more neighbors there are, the harder it is for cooperators to persist in structured populations. We further show that threshold group interactions could lead to the emergence of cooperation even in well-mixed populations. Here population structure sometimes inhibits cooperation for the threshold public goods game, where depending on the benefit to cost ratio, the outcomes are bistability or a monomorphic population of defectors or cooperators. Our results suggest, counterintuitively, that structured populations are not always beneficial for the evolution of cooperation for nonlinear group interactions.

  8. Cryptic Population Dynamics: Rapid Evolution Masks Trophic Interactions

    PubMed Central

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

    2007-01-01

    Trophic relationships, such as those between predator and prey or between pathogen and host, are key interactions linking species in ecological food webs. The structure of these links and their strengths have major consequences for the dynamics and stability of food webs. The existence and strength of particular trophic links has often been assessed using observational data on changes in species abundance through time. Here we show that very strong links can be completely missed by these kinds of analyses when changes in population abundance are accompanied by contemporaneous rapid evolution in the prey or host species. Experimental observations, in rotifer-alga and phage-bacteria chemostats, show that the predator or pathogen can exhibit large-amplitude cycles while the abundance of the prey or host remains essentially constant. We know that the species are tightly linked in these experimental microcosms, but without this knowledge, we would infer from observed patterns in abundance that the species are weakly or not at all linked. Mathematical modeling shows that this kind of cryptic dynamics occurs when there is rapid prey or host evolution for traits conferring defense against attack, and the cost of defense (in terms of tradeoffs with other fitness components) is low. Several predictions of the theory that we developed to explain the rotifer-alga experiments are confirmed in the phage-bacteria experiments, where bacterial evolution could be tracked. Modeling suggests that rapid evolution may also confound experimental approaches to measuring interaction strength, but it identifies certain experimental designs as being more robust against potential confounding by rapid evolution. PMID:17803356

  9. Complex Population Dynamics in Mussels Arising from Density-Linked Stochasticity

    PubMed Central

    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

  10. Improving genomic prediction for Danish Jersey using a joint Danish-US reference population

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Accuracy of genomic prediction depends on the information in the reference population. Achieving an adequate sized reference population is a challenge for genomic prediction in small cattle populations. One way to increase the size of reference population is to combine reference data from different ...

  11. Developing methods to assess and predict the population level effects of environmental contaminants.

    USGS Publications Warehouse

    Emlen, J.M.; Springman, K.R.

    2007-01-01

    The field of ecological toxicity seems largely to have drifted away from what its title implies--assessing and predicting the ecological consequences of environmental contaminants--moving instead toward an emphasis on individual effects and physiologic case studies. This paper elucidates how a relatively new ecological methodology, interaction assessment (INTASS), could be useful in addressing the field's initial goals. Specifically, INTASS is a model platform and methodology, applicable across a broad array of taxa and habitat types, that can be used to construct population dynamics models from field data. Information on environmental contaminants and multiple stressors can be incorporated into these models in a form that bypasses the problems inherent in assessing uptake, chemical interactions in the environment, and synergistic effects in the organism. INTASS can, therefore, be used to evaluate the effects of contaminants and other stressors at the population level and to predict how changes in stressor levels or composition of contaminant mixtures, as well as various mitigation measures, might affect population dynamics.

  12. Real-Time Bioluminescent Tracking of Cellular Population Dynamics

    SciTech Connect

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

    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.

  13. A spatial ecosystem and populations dynamics model (SEAPODYM) Modeling of tuna and tuna-like populations

    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

  14. The DynaMine webserver: predicting protein dynamics from sequence.

    PubMed

    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

  15. Stochastic population dynamics in populations of western terrestrial garter snakes with divergent life histories

    USGS Publications Warehouse

    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

  16. A Hierarchical Approach Embedding Hydrologic and Population Modeling for a West Nile Virus Vector Prediction

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  17. 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.

  18. 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 (κa 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 θ0 = langkabrang/langkbbrang appears to be an integer in the asymptotic limits of the three time regimes. For early times (defined by t < t1 = κb) the total number of links presents a linear evolution, where the two populations are indistinguishable and where θ0 = 1. Interestingly, in the intermediate time regime (defined for t_1\\lt t\\lt t_2\\propto \\kappa_a and for which θ0 = 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 θ0 = 3.

  19. Population Dynamics with Global Regulation: The Conserved Fisher Equation

    NASA Astrophysics Data System (ADS)

    Newman, T. J.; Kolomeisky, E. B.; Antonovics, J.

    2004-06-01

    We introduce and study a conserved version of the Fisher equation. Within a population biology context, this model describes spatially extended populations in which the total number of individuals is fixed due to either biotic or environmental factors. We find a rich spectrum of dynamical phases including a pseudotraveling wave and, in the presence of the Allee effect, a phase transition from a locally constrained high density state to a low density fragmented state.

  20. Evolutionary History and Population Dynamics of Hepatitis E Virus

    PubMed Central

    Purdy, Michael A.; Khudyakov, Yury E.

    2010-01-01

    Background Hepatitis E virus (HEV) is an enterically transmitted hepatropic virus. It segregates as four genotypes. All genotypes infect humans while only genotypes 3 and 4 also infect several animal species. It has been suggested that hepatitis E is zoonotic, but no study has analyzed the evolutionary history of HEV. We present here an analysis of the evolutionary history of HEV. Methods and Findings The times to the most recent common ancestors for all four genotypes of HEV were calculated using BEAST to conduct a Bayesian analysis of HEV. The population dynamics for genotypes 1, 3 and 4 were analyzed using skyline plots. Bayesian analysis showed that the most recent common ancestor for modern HEV existed between 536 and 1344 years ago. The progenitor of HEV appears to have given rise to anthropotropic and enzootic forms of HEV, which evolved into genotypes 1 and 2 and genotypes 3 and 4, respectively. Population dynamics suggest that genotypes 1, 3 and 4 experienced a population expansion during the 20th century. Genotype 1 has increased in infected population size ∼30–35 years ago. Genotype 3 and 4 have experienced an increase in population size starting late in the 19th century until ca.1940-45, with genotype 3 having undergone additional rapid expansion until ca.1960. The effective population size for both genotype 3 and 4 rapidly declined to pre-expansion levels starting in ca.1990. Genotype 4 was further examined as Chinese and Japanese sequences, which exhibited different population dynamics, suggesting that this genotype experienced different evolutionary history in these two countries. Conclusions HEV appears to have evolved through a series of steps, in which the ancestors of HEV may have adapted to a succession of animal hosts leading to humans. Analysis of the population dynamics of HEV suggests a substantial temporal variation in the rate of transmission among HEV genotypes in different geographic regions late in the 20th Century. PMID:21203540

  1. Sexual abuse predicts functional somatic symptoms: an adolescent population study.

    PubMed

    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

  2. Demography of the Early Neolithic Population in Central Balkans: Population Dynamics Reconstruction Using Summed Radiocarbon Probability Distributions

    PubMed Central

    2016-01-01

    The Central Balkans region is of great importance for understanding the spread of the Neolithic in Europe but the Early Neolithic population dynamics of the region is unknown. In this study we apply the method of summed calibrated probability distributions to a set of published radiocarbon dates from the Republic of Serbia in order to reconstruct population dynamics in the Early Neolithic in this part of the Central Balkans. The results indicate that there was a significant population growth after ~6200 calBC, when the Neolithic was introduced into the region, followed by a bust at the end of the Early Neolithic phase (~5400 calBC). These results are broadly consistent with the predictions of the Neolithic Demographic Transition theory and the patterns of population booms and busts detected in other regions of Europe. These results suggest that the cultural process that underlies the patterns observed in Central and Western Europe was also in operation in the Central Balkan Neolithic and that the population increase component of this process can be considered as an important factor for the spread of the Neolithic as envisioned in the demic diffusion hypothesis. PMID:27508413

  3. Demography of the Early Neolithic Population in Central Balkans: Population Dynamics Reconstruction Using Summed Radiocarbon Probability Distributions.

    PubMed

    Porčić, Marko; Blagojević, Tamara; Stefanović, Sofija

    2016-01-01

    The Central Balkans region is of great importance for understanding the spread of the Neolithic in Europe but the Early Neolithic population dynamics of the region is unknown. In this study we apply the method of summed calibrated probability distributions to a set of published radiocarbon dates from the Republic of Serbia in order to reconstruct population dynamics in the Early Neolithic in this part of the Central Balkans. The results indicate that there was a significant population growth after ~6200 calBC, when the Neolithic was introduced into the region, followed by a bust at the end of the Early Neolithic phase (~5400 calBC). These results are broadly consistent with the predictions of the Neolithic Demographic Transition theory and the patterns of population booms and busts detected in other regions of Europe. These results suggest that the cultural process that underlies the patterns observed in Central and Western Europe was also in operation in the Central Balkan Neolithic and that the population increase component of this process can be considered as an important factor for the spread of the Neolithic as envisioned in the demic diffusion hypothesis. PMID:27508413

  4. Optimal population prediction of sandhill crane recruitment based on climate-mediated habitat limitations.

    PubMed

    Gerber, Brian D; Kendall, William L; Hooten, Mevin B; Dubovsky, James A; Drewien, Roderick C

    2015-09-01

    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. 5. 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

  5. Generating a dynamic synthetic population--using an age-structured two-sex model for household dynamics.

    PubMed

    Namazi-Rad, M; Namazi-Rad, Mohammad-Reza; Mokhtarian, P; Mokhtarian, Payam; Perez, P; 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

  6. 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,…

  7. Connectivity structures local population dynamics: a long-term empirical test in a large metapopulation system.

    PubMed

    Castorani, Max C N; Reed, Daniel C; Alberto, Filipe; Bell, Tom W; Simons, Rachel D; Cavanaugh, Kyle C; Siegel, David A; Raimondi, Peter T

    2015-12-01

    Ecological theory predicts that demographic connectivity structures the dynamics of local populations within metapopulation systems, but empirical support has been constrained by major limitations in data and methodology. We tested this prediction for giant kelp Macrocystis pyrifera, a key habitat-forming species in temperate coastal ecosystems worldwide, in southern California, USA. We combined a long-term (22 years), large-scale (~500 km coastline), high-resolution census of abundance with novel patch delineation methods and an innovative connectivity measure incorporating oceanographic transport and source fecundity. Connectivity strongly predicted local dynamics (well-connected patches had lower probabilities of extinction and higher probabilities of colonization, leading to greater likelihoods of occupancy) but this relationship was mediated by patch size. Moreover, the relationship between connectivity and local population dynamics varied over time, possibly due to temporal variation in oceanographic transport processes. Surprisingly, connectivity had a smaller influence on colonization relative to extinction, possibly because local ecological factors differ greatly between extinct and extant patches. Our results provide the first comprehensive evidence that southern California giant kelp populations function as a metapopulation system, challenging the view that populations of this important foundation species are governed exclusively by self-replenishment. PMID:26909421

  8. Dynamic regimes of local homogeneous population model with time lag

    NASA Astrophysics Data System (ADS)

    Neverova, Galina; Frisman, Efim

    2016-06-01

    We investigated Moran - Ricker model with time lag 1. It is made analytical and numerical study of the model. It is shown there is co-existence of various dynamic regimes under the same values of parameters. The model simultaneously possesses several different limit regimes: stable state, periodic fluctuations, and chaotic attractor. The research results show if present population size substantially depends on population number of previous year then it is observed quasi-periodic oscillations. Fluctuations with period 2 occur when the growth of population size is regulated by density dependence in the current year.

  9. Predicting Tenure Dynamics: Models Help Manage Tenure System.

    ERIC Educational Resources Information Center

    Strauss, Jon C.

    1997-01-01

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

  10. Disentangling seasonal bacterioplankton population dynamics by high-frequency sampling.

    PubMed

    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

  11. Modeling the population dynamics of Culex quinquefasciatus (Diptera: Culcidae), along an elevational gradient in Hawaii

    USGS Publications Warehouse

    Ahumada, Jorge A.; LaPointe, Dennis; Samuel, Michael D.

    2004-01-01

    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.

  12. Dynamics of Two Populations with Different Birth Rates

    NASA Astrophysics Data System (ADS)

    Hoffmann, Julia; Pekalski, Andrzej

    We propose a simple model describing the dynamics of a system of two populations — more numerous natives and less numerous immigrants. The immigrants' birth rate is higher than that of the natives. Several modifications of this model taking into account changes of the birth rates due to external factors and/or possibility of contacts between the populations, are also introduced. The model is studied within two approaches — by solving a set of differential equations and through a Monte Carlo simulations. We show that the question of which population will eventually dominate depends on such factors as the probability of producing offsprings of mixed origin, assimilation of the immigrants, the ratio of the birth rates, initial numbers of the populations and the average age of an individual. In all, but two extreme cases, both populations will survive.

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

    PubMed

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

    2013-08-01

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

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

    PubMed Central

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

    2010-01-01

    Background We test whether the phenotypic variance of symbionts (Symbiodinium) in corals is closely related with the capacity of corals to acclimatize to increasing seawater temperatures. Moreover, we assess whether more specialist symbionts will increase within coral hosts under ocean warming. The present study is only applicable to those corals that naturally have the capacity to support more than one type of Symbiodinium within the lifetime of a colony; for example, Montastraea annularis and Montastraea faveolata. Methodology/Principal Findings The population dynamics of competing Symbiodinium symbiont populations were projected through time in coral hosts using a novel, discrete time optimal–resource model. Models were run for two Atlantic Ocean localities. Four symbiont populations, with different environmental optima and phenotypic variances, were modeled to grow, divide, and compete in the corals under seasonal fluctuations in solar insolation and seawater temperature. Elevated seawater temperatures were input into the model 1.5°C above the seasonal summer average, and the symbiont population response was observed for each location. The models showed dynamic fluctuations in Symbiodinium populations densities within corals. Population density predictions for Lee Stocking Island, the Bahamas, where temperatures were relatively homogenous throughout the year, showed a dominance of both type 2, with high phenotypic variance, and type 1, a high-temperature and high-insolation specialist. Whereas the densities of Symbiodinium types 3 and 4, a high-temperature, low-insolation specialist, and a high-temperature, low-insolation generalist, remained consistently low. Predictions for Key Largo, Florida, where environmental conditions were more seasonally variable, showed the coexistence of generalists (types 2 and 4) and low densities of specialists (types 1 and 3). When elevated temperatures were input into the model, population densities in corals at Lee Stocking

  15. 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."

  16. COMPARISON OF SAMPLING TECHNIQUES USED IN STUDYING LEPIDOPTERA POPULATION DYNAMICS

    EPA Science Inventory

    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...

  17. 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, η Car, ζ Pup, γ2 Velorum and WR 140.

  18. Population Dynamics, Demography, Dispersal and Spread of Bemisia tabaci

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Bemisia tabaci is an insect pest of global significance. It attacks multiple crops and causes damage through feeding and transmission of plant viruses. This review focuses on the current state of knowledge of the population dynamics, demography and dispersal of this important pest. Sampling metho...

  19. 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

  20. Population dynamics and mutualism: Functional responses of benefits and costs

    USGS Publications Warehouse

    Holland, J. Nathaniel; DeAngelis, Donald L.; Bronstein, Judith L.

    2002-01-01

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

  1. Evolution of complex dynamics in spatially structured populations

    PubMed Central

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

    1999-01-01

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

  2. Improved Comorbidity Adjustment for Predicting Mortality in Medicare Populations

    PubMed Central

    Schneeweiss, Sebastian; Wang, Philip S; Avorn, Jerry; Glynn, Robert J

    2003-01-01

    Objective To define and improve the performance of existing comorbidity scores in predicting mortality in Medicare enrollees. Data Sources Study participants were two Medicare populations who had complete drug coverage either through Medicaid or a statewide pharmacy assistance program: New Jersey Medicare enrollees (NNJ=235,881) and Pennsylvania Medicare enrollees (NPA=230,913). Study Design Frequently used comorbidity scores were computed for all subjects during the baseline year (January 1, 1994, to December 31, 1994, and one year later in Pennsylvania). The study outcome was one-year mortality during the following year. Performance of scores was measured with the c-statistic derived from multivariate logistic regression models. Empirical weights were derived in the New Jersey population and the performance of scores with new weights was validated in the Pennsylvania population. Principal Findings A score based on ICD-9-diagnoses (Romano) performed 60 percent better than one based on patterns of medication use (Chronic Disease Score, or CDS-1) (c=0.771 vs. c=0.703). The performance of the Romano score was further improved slightly by inclusion of the number of different prescription drugs used during the past year. Modeling the 17 conditions included in the Romano score as separate binary indicators increased its performance by 8 percent (c=0.781). We derived elderly-specific weights for these scores in the New Jersey sample, including negative weights for the use of some drugs, for example, lipid lowering drugs. Applying these weights, the performance of Romano and CDS-1 scores improved in an independent validation sample of Pennsylvania Medicare enrollees by 8.3 percent and 43 percent compared to the scores with the original weights. When we added an indicator of nursing home residency, age, and gender, the Romano score reached a performance of c=0.80. Conclusions We conclude that in epidemiologic studies of the elderly, a modified diagnosis-based score using

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

    PubMed Central

    Perc, Matjaž; Gómez-Gardeñes, 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

  4. 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.

  5. Diversity Waves in Collapse-Driven Population Dynamics

    PubMed Central

    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

  6. Diversity waves in collapse-driven population dynamics

    SciTech Connect

    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. 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.

  7. Diversity waves in collapse-driven population dynamics

    DOE PAGESBeta

    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

  8. Diversity Waves in Collapse-Driven Population Dynamics.

    PubMed

    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

  9. Modeling structured population dynamics using data from unmarked individuals

    USGS Publications Warehouse

    Grant, Evan H. Campbell; 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.

  10. Metamodels for Transdisciplinary Analysis of Wildlife Population Dynamics

    PubMed Central

    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

  11. 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.

  12. Second Cancers After Fractionated Radiotherapy: Stochastic Population Dynamics Effects

    NASA Technical Reports Server (NTRS)

    Sachs, Rainer K.; Shuryak, Igor; Brenner, David; Fakir, Hatim; Hahnfeldt, Philip

    2007-01-01

    When ionizing radiation is used in cancer therapy it can induce second cancers in nearby organs. Mainly due to longer patient survival times, these second cancers have become of increasing concern. Estimating the risk of solid second cancers involves modeling: because of long latency times, available data is usually for older, obsolescent treatment regimens. Moreover, modeling second cancers gives unique insights into human carcinogenesis, since the therapy involves administering well characterized doses of a well studied carcinogen, followed by long-term monitoring. In addition to putative radiation initiation that produces pre-malignant cells, inactivation (i.e. cell killing), and subsequent cell repopulation by proliferation can be important at the doses relevant to second cancer situations. A recent initiation/inactivation/proliferation (IIP) model characterized quantitatively the observed occurrence of second breast and lung cancers, using a deterministic cell population dynamics approach. To analyze ifradiation-initiated pre-malignant clones become extinct before full repopulation can occur, we here give a stochastic version of this I I model. Combining Monte Carlo simulations with standard solutions for time-inhomogeneous birth-death equations, we show that repeated cycles of inactivation and repopulation, as occur during fractionated radiation therapy, can lead to distributions of pre-malignant cells per patient with variance >> mean, even when pre-malignant clones are Poisson-distributed. Thus fewer patients would be affected, but with a higher probability, than a deterministic model, tracking average pre-malignant cell numbers, would predict. Our results are applied to data on breast cancers after radiotherapy for Hodgkin disease. The stochastic IIP analysis, unlike the deterministic one, indicates: a) initiated, pre-malignant cells can have a growth advantage during repopulation, not just during the longer tumor latency period that follows; b) weekend

  13. Aspiration dynamics of multi-player games in finite populations

    PubMed Central

    Du, Jinming; Wu, Bin; Altrock, Philipp M.; Wang, Long

    2014-01-01

    On studying strategy update rules in the framework of evolutionary game theory, one can differentiate between imitation processes and aspiration-driven dynamics. In the former case, individuals imitate the strategy of a more successful peer. In the latter case, individuals adjust their strategies based on a comparison of their pay-offs from the evolutionary game to a value they aspire, called the level of aspiration. Unlike imitation processes of pairwise comparison, aspiration-driven updates do not require additional information about the strategic environment and can thus be interpreted as being more spontaneous. Recent work has mainly focused on understanding how aspiration dynamics alter the evolutionary outcome in structured populations. However, the baseline case for understanding strategy selection is the well-mixed population case, which is still lacking sufficient understanding. We explore how aspiration-driven strategy-update dynamics under imperfect rationality influence the average abundance of a strategy in multi-player evolutionary games with two strategies. We analytically derive a condition under which a strategy is more abundant than the other in the weak selection limiting case. This approach has a long-standing history in evolutionary games and is mostly applied for its mathematical approachability. Hence, we also explore strong selection numerically, which shows that our weak selection condition is a robust predictor of the average abundance of a strategy. The condition turns out to differ from that of a wide class of imitation dynamics, as long as the game is not dyadic. Therefore, a strategy favoured under imitation dynamics can be disfavoured under aspiration dynamics. This does not require any population structure, and thus highlights the intrinsic difference between imitation and aspiration dynamics. PMID:24598208

  14. 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

  15. How Predation and Landscape Fragmentation Affect Vole Population Dynamics

    PubMed Central

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

    2011-01-01

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

  16. 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.

  17. Structural Drift: The Population Dynamics of Sequential Learning

    PubMed Central

    Crutchfield, James P.; Whalen, Sean

    2012-01-01

    We introduce a theory of sequential causal inference in which learners in a chain estimate a structural model from their upstream “teacher” and then pass samples from the model to their downstream “student”. It extends the population dynamics of genetic drift, recasting Kimura's selectively neutral theory as a special case of a generalized drift process using structured populations with memory. We examine the diffusion and fixation properties of several drift processes and propose applications to learning, inference, and evolution. We also demonstrate how the organization of drift process space controls fidelity, facilitates innovations, and leads to information loss in sequential learning with and without memory. PMID:22685387

  18. Evolutionary dynamics of a multigroup fluctuating-population system

    NASA Astrophysics Data System (ADS)

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

    1993-03-01

    We studied the evolutionary dynamics of a population undergoing asexual reproduction in a flat-fitness landscape. The quantity of interest is the distribution of the overlap function q which is a measure of the similarity in the genome structure between two individuals. We obtain analytical expressions for , , and p(q) in a model with the following features: continuous time, fluctuating population divided into many compartments, and a finite number of genes per genome. A few special cases of interest are also discussed.

  19. Dynamics of a population of oscillatory and excitable elements

    NASA Astrophysics Data System (ADS)

    O'Keeffe, Kevin P.; Strogatz, Steven H.

    2016-06-01

    We analyze a variant of a model proposed by Kuramoto, Shinomoto, and Sakaguchi for a large population of coupled oscillatory and excitable elements. Using the Ott-Antonsen ansatz, we reduce the behavior of the population to a two-dimensional dynamical system with three parameters. We present the stability diagram and calculate several of its bifurcation curves analytically, for both excitatory and inhibitory coupling. Our main result is that when the coupling function is broad, the system can display bistability between steady states of constant high and low activity, whereas when the coupling function is narrow and inhibitory, one of the states in the bistable regime can show persistent pulsations in activity.

  20. Optimal control methods for controlling bacterial populations with persister dynamics

    NASA Astrophysics Data System (ADS)

    Cogan, N. G.

    2016-06-01

    Bacterial tolerance to antibiotics is a well-known phenomena; however, only recent studies of bacterial biofilms have shown how multifaceted tolerance really is. By joining into a structured community and offering shared protection and gene transfer, bacterial populations can protect themselves genotypically, phenotypically and physically. In this study, we collect a line of research that focuses on phenotypic (or plastic) tolerance. The dynamics of persister formation are becoming better understood, even though there are major questions that remain. The thrust of our results indicate that even without detailed description of the biological mechanisms, theoretical studies can offer strategies that can eradicate bacterial populations with existing drugs.

  1. The demography of climate-driven and density-regulated population dynamics in a perennial plant.

    PubMed

    Dahlgren, Johan P; Bengtsson, Karin; Ehrlén, Johan

    2016-04-01

    Identifying the internal and external drivers of population dynamics is a key objective in ecology, currently accentuated by the need to forecast the effects of climate change on species distributions and abundances. The interplay between environmental and density effects is one particularly important aspect of such forecasts. We examined the simultaneous impact of climate and intraspecific density on vital rates of the dwarf shrub Fumana procumbens over 20 yr, using generalized additive mixed models. We then analyzed effects on population dynamics using integral projection models. The population projection models accurately captured observed fluctuations in population size. Our analyses suggested the population was intrinsically regulated but with annual fluctuations in response to variation in weather. Simulations showed that implicitly assuming variation in demographic rates to be driven solely by the environment can overestimate extinction risks if there is density dependence. We conclude that density regulation can dampen effects of climate change on Fumana population size, and discuss the need to quantify density dependence in predictions of population responses to environmental changes. PMID:27220206

  2. Gaining insight in the interaction of zinc and population density with a combined dynamic energy budget and population model.

    PubMed

    Klok, Chris

    2008-12-01

    Laboratory tests are typically conducted under optimal conditions testing the single effect of a toxicant In the field, due to suboptimal conditions, density dependence can both diminish and enhance effects of toxicants on populations. A review of the literature indicated that general insight on interaction of density and toxicants is lacking, and therefore no predictions on their combined action can be made. In this paper the influence of zinc was tested at different population densities on the demographic rates: growth, reproduction, and survival in the earthworm Lumbricus rubellus. Changes in these rates were extrapolated with a combined Dynamic energy budget (DEB) and a population model to assess consequences at the population level. Inference from the DEB model indicated that density decreased the assimilation of food whereas zinc increased the maintenance costs. The combined effects of density and zinc resulted in a decrease in the intrinsic rate of population increase which suddenly dropped to zero at combinations of zinc and density where development is so strongly retarded that individuals do not mature. This already happened at zinc levels where zinc induced mortality is low and therefore density enhances zinc effects and density dependent compensation is not expected. PMID:19192801

  3. Dynamical models of a sample of Population II stars

    NASA Astrophysics Data System (ADS)

    Levison, H. F.; Richstone, D. O.

    1986-09-01

    Dynamical models are constructed in order to investigate the implications of recent kinematic data of distant Population II stars on the emissivity distribution of those stars. Models are constructed using a modified Schwarzschild method in two extreme scale-free potentials, spherical and E6 elliptical. Both potentials produce flat rotation curves and velocity dispersion profiles. In all models, the distribution of stars in this sample is flat. Moreover, it is not possible to construct a model with a strictly spheroidal emissivity distribution. Most models have dimples at the poles. The dynamics of the models indicate that the system is supported by both the third integral and z angular momentum.

  4. Dynamic Inlet Distortion Prediction with a Combined Computational Fluid Dynamics and Distortion Synthesis Approach

    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.

  5. 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.

  6. Predicting catastrophes in nonlinear dynamical systems by compressive sensing

    PubMed Central

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

    2013-01-01

    An extremely challenging problem of significant interest is to predict catastrophes in advance of their occurrences. We present a general approach to predicting catastrophes in nonlinear dynamical systems under the assumption that the system equations are completely unknown and only time series reflecting the evolution of the dynamical variables of the system are available. Our idea is to expand the vector field or map of the underlying system into a suitable function series and then to use the compressive-sensing technique to accurately estimate the various terms in the expansion. Examples using paradigmatic chaotic systems are provided to demonstrate our idea and potential challenges are discussed. PMID:21568562

  7. Nonlinear dynamics and predictability in the atmospheric sciences

    SciTech Connect

    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.

  8. Prediction of competitive microbial growth in mixed culture at dynamic temperature patterns.

    PubMed

    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

  9. Effect of temperature on the population dynamics of Aedes aegypti

    NASA Astrophysics Data System (ADS)

    Yusoff, Nuraini; Tokachil, Mohd Najir

    2015-10-01

    Aedes aegypti is one of the main vectors in the transmission of dengue fever. Its abundance may cause the spread of the disease to be more intense. In the study of its biological life cycle, temperature was found to increase the development rate of each stage of this species and thus, accelerate the process of the development from egg to adult. In this paper, a Lefkovitch matrix model will be used to study the stage-structured population dynamics of Aedes aegypti. In constructing the transition matrix, temperature will be taken into account. As a case study, temperature recorded at the Subang Meteorological Station for year 2006 until 2010 will be used. Population dynamics of Aedes aegypti at maximum, average and minimum temperature for each year will be simulated and compared. It is expected that the higher the temperature, the faster the mosquito will breed. The result will be compared to the number of dengue fever incidences to see their relationship.

  10. Seasonal Population Dynamics of Three Potato Pests in Washington State.

    PubMed

    D'Auria, Elizabeth M; Wohleb, Carrie H; Waters, Timothy D; Crowder, David W

    2016-08-01

    Pest phenology models allow producers to anticipate pest outbreaks and deploy integrated pest management (IPM) strategies. Phenology models are particularly useful for cropping systems with multiple economically damaging pests throughout a season. Potato (Solanum tuberosum L.) crops of Washington State, USA, are attacked by many insect pests including the potato tuberworm (Phthorimaea operculella Zeller), the beet leafhopper (Circulifer tenellus Baker), and the green peach aphid (Myzus persicae Sulzer). Each of these pests directly damages potato foliage or tubers; C. tenellus and M. persicae also transmit pathogens that can drastically reduce potato yields. We monitored the seasonal population dynamics of these pests by conducting weekly sampling on a network of commercial farms from 2007 to 2014. Using these data, we developed phenology models to characterize the seasonal population dynamics of each pest based on accumulated degree-days (DD). All three pests exhibited consistent population dynamics across seasons that were mediated by temperature. Of the three pests, C. tenellus was generally the first detected in potato crops, with 90% of adults captured by 936 DD. In contrast, populations of P. operculella and M. persicae built up more slowly over the course of the season, with 90% cumulative catch by 1,590 and 2,634 DD, respectively. Understanding these seasonal patterns could help potato producers plan their IPM strategies while allowing them to move away from calendar-based applications of insecticides. More broadly, our results show how long-term monitoring studies that explore dynamics of multiple pest species can aid in developing IPM strategies in crop systems. PMID:27271946

  11. Development of paradigms for the dynamics of structured populations

    SciTech Connect

    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.

  12. Continuous probabilistic analysis to evolutionary game dynamics in finite populations.

    PubMed

    Gao, Meng

    2009-07-01

    Evolutionary game dynamics of two strategies in finite population is studied by continuous probabilistic approach. Besides frequency dependent selection, mutation was also included in this study. The equilibrium probability density functions of abundance, expected time to extinction or fixation were derived and their numerical solutions are calculated as illustrations. Meanwhile, individual-based computer simulations are also done. A comparison reveals the consistency between theoretical analysis and simulations. PMID:19219510

  13. A Novel Dynamic Update Framework for Epileptic Seizure Prediction

    PubMed Central

    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

  14. A novel dynamic update framework for epileptic seizure prediction.

    PubMed

    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

  15. Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care

    Cancer.gov

    Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care, a 2010 workshop sponsored by the Epidemiology and Genomics Research Program.

  16. Deterministic processes guide long-term synchronised population dynamics in replicate anaerobic digesters

    PubMed Central

    Vanwonterghem, Inka; Jensen, Paul D; Dennis, Paul G; Hugenholtz, Philip; Rabaey, Korneel; Tyson, Gene W

    2014-01-01

    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, α-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

  17. Interacting trophic forcing and the population dynamics of herring.

    PubMed

    Lindegren, Martin; Ostman, Orjan; Gårdmark, 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

  18. Understanding past, contemporary, and future dynamics of plants, populations, and communities using Sonoran Desert winter annuals.

    PubMed

    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

  19. Inferring the Dynamics of Effective Population Size Using Autosomal Genomes.

    PubMed

    Hou, Zheng; Luo, Yin; Wang, Zhisheng; Zheng, Hong-Xiang; Wang, Yi; Zhou, Hang; Wu, Leqin; Jin, Li

    2016-01-01

    Next-generation sequencing technology has provided a great opportunity for inferring human demographic history by investigating changes in the effective population size (Ne). In this report, we introduce a strategy for estimating Ne dynamics, allowing the exploration of large multi-locus SNP datasets. We applied this strategy to the Phase 1 Han Chinese samples from the 1000 Genomes Project. The Han Chinese population has undergone a continuous expansion since 25,000 years ago, at first slowly from about 7,300 to 9,800 (at the end of the last glacial maximum about 15,000 YBP), then more quickly to about 46,000 (at the beginning of the Neolithic about 8,000 YBP), and then even more quickly to reach a population size of about 140,000 (recently). PMID:26832887

  20. Connection between dynamically derived IMF normalisation and stellar populations

    NASA Astrophysics Data System (ADS)

    McDermid, Richard M.

    2015-04-01

    In this contributed talk I present recent results on the connection between stellar population properties and the normalisation of the stellar initial mass function (IMF) measured using stellar dynamics, based on a large sample of 260 early-type galaxies observed as part of the ATLAS3D project. This measure of the IMF normalisation is found to vary non-uniformly with age- and metallicity-sensitive absorption line strengths. Applying single stellar population models, there are weak but measurable trends of the IMF with age and abundance ratio. Accounting for the dependence of stellar population parameters on velocity dispersion effectively removes these trends, but subsequently introduces a trend with metallicity, such that `heavy' IMFs favour lower metallicities. The correlations are weaker than those found from previous studies directly detecting low-mass stars, suggesting some degree of tension between the different approaches of measuring the IMF. Resolving these discrepancies will be the focus of future work.

  1. Inferring the Dynamics of Effective Population Size Using Autosomal Genomes

    PubMed Central

    Hou, Zheng; Luo, Yin; Wang, Zhisheng; Zheng, Hong-Xiang; Wang, Yi; Zhou, Hang; Wu, Leqin; Jin, Li

    2016-01-01

    Next-generation sequencing technology has provided a great opportunity for inferring human demographic history by investigating changes in the effective population size (Ne). In this report, we introduce a strategy for estimating Ne dynamics, allowing the exploration of large multi-locus SNP datasets. We applied this strategy to the Phase 1 Han Chinese samples from the 1000 Genomes Project. The Han Chinese population has undergone a continuous expansion since 25,000 years ago, at first slowly from about 7,300 to 9,800 (at the end of the last glacial maximum about 15,000 YBP), then more quickly to about 46,000 (at the beginning of the Neolithic about 8,000 YBP), and then even more quickly to reach a population size of about 140,000 (recently). PMID:26832887

  2. Evolutionary dynamics of social dilemmas in structured heterogeneous populations

    PubMed Central

    Santos, F. C.; Pacheco, J. M.; Lenaerts, Tom

    2006-01-01

    Real populations have been shown to be heterogeneous, in which some individuals have many more contacts than others. This fact contrasts with the traditional homogeneous setting used in studies of evolutionary game dynamics. We incorporate heterogeneity in the population by studying games on graphs, in which the variability in connectivity ranges from single-scale graphs, for which heterogeneity is small and associated degree distributions exhibit a Gaussian tale, to scale-free graphs, for which heterogeneity is large with degree distributions exhibiting a power-law behavior. We study the evolution of cooperation, modeled in terms of the most popular dilemmas of cooperation. We show that, for all dilemmas, increasing heterogeneity favors the emergence of cooperation, such that long-term cooperative behavior easily resists short-term noncooperative behavior. Moreover, we show how cooperation depends on the intricate ties between individuals in scale-free populations. PMID:16484371

  3. Evolutionary dynamics of social dilemmas in structured heterogeneous populations.

    PubMed

    Santos, F C; Pacheco, J M; Lenaerts, Tom

    2006-02-28

    Real populations have been shown to be heterogeneous, in which some individuals have many more contacts than others. This fact contrasts with the traditional homogeneous setting used in studies of evolutionary game dynamics. We incorporate heterogeneity in the population by studying games on graphs, in which the variability in connectivity ranges from single-scale graphs, for which heterogeneity is small and associated degree distributions exhibit a Gaussian tale, to scale-free graphs, for which heterogeneity is large with degree distributions exhibiting a power-law behavior. We study the evolution of cooperation, modeled in terms of the most popular dilemmas of cooperation. We show that, for all dilemmas, increasing heterogeneity favors the emergence of cooperation, such that long-term cooperative behavior easily resists short-term noncooperative behavior. Moreover, we show how cooperation depends on the intricate ties between individuals in scale-free populations. PMID:16484371

  4. Drivers of waterfowl population dynamics: from teal to swans

    USGS Publications Warehouse

    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.

  5. 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.

  6. Population dynamics of Microtus pennsylvanicus in corridor-linked patches

    USGS Publications Warehouse

    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.

  7. 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...

  8. 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…

  9. Effectiveness of Genomic Prediction of Maize Hybrid Performance in Different Breeding Populations and Environments

    PubMed Central

    Windhausen, Vanessa S.; Atlin, Gary N.; Hickey, John M.; Crossa, Jose; Jannink, Jean-Luc; Sorrells, Mark E.; Raman, Babu; Cairns, Jill E.; Tarekegne, Amsal; Semagn, Kassa; Beyene, Yoseph; Grudloyma, Pichet; Technow, Frank; Riedelsheimer, Christian; Melchinger, Albrecht E.

    2012-01-01

    Genomic prediction is expected to considerably increase genetic gains by increasing selection intensity and accelerating the breeding cycle. In this study, marker effects estimated in 255 diverse maize (Zea mays L.) hybrids were used to predict grain yield, anthesis date, and anthesis-silking interval within the diversity panel and testcross progenies of 30 F2-derived lines from each of five populations. Although up to 25% of the genetic variance could be explained by cross validation within the diversity panel, the prediction of testcross performance of F2-derived lines using marker effects estimated in the diversity panel was on average zero. Hybrids in the diversity panel could be grouped into eight breeding populations differing in mean performance. When performance was predicted separately for each breeding population on the basis of marker effects estimated in the other populations, predictive ability was low (i.e., 0.12 for grain yield). These results suggest that prediction resulted mostly from differences in mean performance of the breeding populations and less from the relationship between the training and validation sets or linkage disequilibrium with causal variants underlying the predicted traits. Potential uses for genomic prediction in maize hybrid breeding are discussed emphasizing the need of (1) a clear definition of the breeding scenario in which genomic prediction should be applied (i.e., prediction among or within populations), (2) a detailed analysis of the population structure before performing cross validation, and (3) larger training sets with strong genetic relationship to the validation set. PMID:23173094

  10. Deciphering and prediction of plant dynamics under field conditions.

    PubMed

    Izawa, Takeshi

    2015-04-01

    Elucidation of plant dynamics under fluctuating natural environments is a challenging goal in plant physiology. Recently, using a computer statistics integrating a series of transcriptome data of field-grown rice leaves during an entire crop season and several corresponding environmental data such as solar radiation and ambient temperature, most parts of transcriptome have been modeled. This reveals the detailed contributions of developmental timing, circadian clocks and each environmental factor to transcriptome dynamics in the field and can predict transcriptome dynamics under given environments. Furthermore, some traits such as flowering time in natural environments have been shown to be predicted by mathematical models based on gene-networks parameterized with data obtained in the laboratory, and phenology models refined by knowledge of molecular genetics. New molecular physiology is beginning in plant science. PMID:25706440

  11. The effect of temperature on Anopheles mosquito population dynamics and the potential for malaria transmission.

    PubMed

    Beck-Johnson, Lindsay M; Nelson, William A; Paaijmans, Krijn P; Read, Andrew F; Thomas, Matthew B; Bjørnstad, Ottar N

    2013-01-01

    The parasites that cause malaria depend on Anopheles mosquitoes for transmission; because of this, mosquito population dynamics are a key determinant of malaria risk. Development and survival rates of both the Anopheles mosquitoes and the Plasmodium parasites that cause malaria depend on temperature, making this a potential driver of mosquito population dynamics and malaria transmission. We developed a temperature-dependent, stage-structured delayed differential equation model to better understand how climate determines risk. Including the full mosquito life cycle in the model reveals that the mosquito population abundance is more sensitive to temperature than previously thought because it is strongly influenced by the dynamics of the juvenile mosquito stages whose vital rates are also temperature-dependent. Additionally, the model predicts a peak in abundance of mosquitoes old enough to vector malaria at more accurate temperatures than previous models. Our results point to the importance of incorporating detailed vector biology into models for predicting the risk for vector borne diseases. PMID:24244467

  12. Against matching theory: predictions of an evolutionary theory of behavior dynamics.

    PubMed

    McDowell, J J; Calvin, Nicholas T

    2015-05-01

    A selectionist theory of adaptive behavior dynamics instantiates the idea that behavior evolves in response to selection pressure from the environment in the form of resource acquisition or threat escape or avoidance. The theory is implemented by a computer program that creates an artificial organism and animates it with a population of potential behaviors. The population undergoes selection, recombination, and mutation across generations, or ticks of time, which produces a continuous stream of behavior that can be studied as if it were the behavior of a live organism. Novel predictions of the evolutionary theory can be compared to predictions of matching theory in a critical experiment that arranges concurrent schedules with reinforcer magnitudes that vary across conditions in one component of the schedules but not the other. Matching theory and the evolutionary theory make conflicting predictions about the outcome of this critical experiment, such that the results must disconfirm at least one of the theories. PMID:25680328

  13. Population dynamics in Asia and the Pacific: implications for development.

    PubMed

    1994-03-01

    This article is an excerpt from a recently published article on interactions between population and development in the "Economic and Social Survey of Asia and the Pacific, 1993." Topics include the dynamics of change (growth, age structure, sex composition, migration); implications for specific development issues (population and education, population and health, population and employment, and population and the environment); and policy approaches (slowing growth, spatial distribution, and the role of women). The Asian focus is on population policy and fertility declines. Different conditions specific to each country and varying degrees of program success give rise to country-specific differences in rates of growth and declines in fertility. Population compositions and pressures on spatial distribution differ among countries. Development demands differ for education, health, employment, and environmental controls. A common feature is that population is integrated into social and economic development policies. The links between population and the environment are recognized and will be integrated into policy as knowledge emerges. The ESCAP region has about 58% of world population, and fertility has declined to 3.1 children per woman. Fertility declines do not result in demonstrable changes in the rate of population growth, because the proportion of reproductive age women has increased and will continue to do so until 2010. Reductions in fertility are balanced by mortality declines. The annual rate of increase has gradually slowed, however the absolute size is still huge. The goal of the Bali Declaration of 1992 is to reach replacement level fertility of 2.2 children per woman by 2010 in the ESCAP region. The UN median variant projects 2.4 children per woman by 2010. The countries unlikely to reach replacement level fertility are India, the Philippines, Vietnam, Bangladesh, and Pakistan. Age structure will determine the need for services. For example, South Asia will

  14. Spatial structure and chaos in insect population dynamics

    NASA Astrophysics Data System (ADS)

    Hassell, Michael P.; Comins, Hugh N.; Mayt, Robert M.

    1991-09-01

    MOST environments are spatially subdivided, or patchy, and there has been much interest in the relationship between the dynamics of populations at the local and regional (metapopulation) scales1. Here we study mathematical models for host-parasitoid interactions, where in each generation specified fractions (µN and µp, respectively) of the host and parasitoid subpopulations in each patch move to adjacent patches; in most previous work, the movement is not localized but is to any other patch2. These simple and biologically sensible models with limited diffusive dispersal exhibit a remarkable range of dynamic behaviour: the density of the host and parasitoid subpopulations in a two-dimensional array of patches may exhibit complex patterns of spiral waves or spatially chaotic variation, they may show static 'crystal lattice' patterns, or they may become extinct. This range of behaviour is obtained with the local dynamics being deterministically unstable, with a constant host reproductive rate and no density dependence in the movement patterns. The dynamics depend on the host reproductive rate, and on the values of the parameters µN and µp. The results are relatively insensitive to the details of the interactions; we get essentially the same results from the mathematically-explicit Nicholon-Bailey model of host-parasitoid interactions, and from a very general 'cellular automaton' model in which only qualitative rules are specified. We conclude that local movement in a patchy environment can help otherwise unstable host and parasitoid populations to persist together, but that the deterministically generated spatial patterns in population density can be exceedingly complex (and sometimes indistinguishable from random environmental fluctuations).

  15. Context-dependent survival, fecundity and predicted population-level consequences of brucellosis in African buffalo.

    PubMed

    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 (χ(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 λ = 1·11 (95% CI = 1·02-1·21) in herds without brucellosis and λ = 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

  16. Temporal dynamics of Puumala hantavirus infection in cyclic populations of bank voles

    PubMed Central

    Voutilainen, Liina; Kallio, Eva R.; Niemimaa, Jukka; Vapalahti, Olli; Henttonen, Heikki

    2016-01-01

    Understanding the dynamics of zoonotic pathogens in their reservoir host populations is a prerequisite for predicting and preventing human disease epidemics. The human infection risk of Puumala hantavirus (PUUV) is highest in northern Europe, where populations of the rodent host (bank vole, Myodes glareolus) undergo cyclic fluctuations. We conducted a 7-year capture-mark-recapture study to monitor seasonal and multiannual patterns of the PUUV infection rate in bank vole populations exhibiting a 3-year density cycle. Infected bank voles were most abundant in mid-winter months during years of increasing or peak host density. Prevalence of PUUV infection in bank voles exhibited a regular, seasonal pattern reflecting the annual population turnover and accumulation of infections within each year cohort. In autumn, the PUUV transmission rate tracked increasing host abundance, suggesting a density-dependent transmission. However, prevalence of PUUV infection was similar during the increase and peak years of the density cycle despite a twofold difference in host density. This may result from the high proportion of individuals carrying maternal antibodies constraining transmission during the cycle peak years. Our exceptionally intensive and long-term dataset provides a solid basis on which to develop models to predict the dynamic public health threat posed by PUUV in northern Europe. PMID:26887639

  17. Temporal dynamics of Puumala hantavirus infection in cyclic populations of bank voles.

    PubMed

    Voutilainen, Liina; Kallio, Eva R; Niemimaa, Jukka; Vapalahti, Olli; Henttonen, Heikki

    2016-01-01

    Understanding the dynamics of zoonotic pathogens in their reservoir host populations is a prerequisite for predicting and preventing human disease epidemics. The human infection risk of Puumala hantavirus (PUUV) is highest in northern Europe, where populations of the rodent host (bank vole, Myodes glareolus) undergo cyclic fluctuations. We conducted a 7-year capture-mark-recapture study to monitor seasonal and multiannual patterns of the PUUV infection rate in bank vole populations exhibiting a 3-year density cycle. Infected bank voles were most abundant in mid-winter months during years of increasing or peak host density. Prevalence of PUUV infection in bank voles exhibited a regular, seasonal pattern reflecting the annual population turnover and accumulation of infections within each year cohort. In autumn, the PUUV transmission rate tracked increasing host abundance, suggesting a density-dependent transmission. However, prevalence of PUUV infection was similar during the increase and peak years of the density cycle despite a twofold difference in host density. This may result from the high proportion of individuals carrying maternal antibodies constraining transmission during the cycle peak years. Our exceptionally intensive and long-term dataset provides a solid basis on which to develop models to predict the dynamic public health threat posed by PUUV in northern Europe. PMID:26887639

  18. Assessing predictability of a hydrological stochastic-dynamical system

    NASA Astrophysics Data System (ADS)

    Gelfan, Alexander

    2014-05-01

    The water cycle includes the processes with different memory that creates potential for predictability of hydrological system based on separating its long and short memory components and conditioning long-term prediction on slower evolving components (similar to approaches in climate prediction). In the face of the Panta Rhei IAHS Decade questions, it is important to find a conceptual approach to classify hydrological system components with respect to their predictability, define predictable/unpredictable patterns, extend lead-time and improve reliability of hydrological predictions based on the predictable patterns. Representation of hydrological systems as the dynamical systems subjected to the effect of noise (stochastic-dynamical systems) provides possible tool for such conceptualization. A method has been proposed for assessing predictability of hydrological system caused by its sensitivity to both initial and boundary conditions. The predictability is defined through a procedure of convergence of pre-assigned probabilistic measure (e.g. variance) of the system state to stable value. The time interval of the convergence, that is the time interval during which the system losses memory about its initial state, defines limit of the system predictability. The proposed method was applied to assess predictability of soil moisture dynamics in the Nizhnedevitskaya experimental station (51.516N; 38.383E) located in the agricultural zone of the central European Russia. A stochastic-dynamical model combining a deterministic one-dimensional model of hydrothermal regime of soil with a stochastic model of meteorological inputs was developed. The deterministic model describes processes of coupled heat and moisture transfer through unfrozen/frozen soil and accounts for the influence of phase changes on water flow. The stochastic model produces time series of daily meteorological variables (precipitation, air temperature and humidity), whose statistical properties are similar

  19. Identifying consumer-resource population dynamics using paleoecological data.

    PubMed

    Einarsson, Árni; Hauptfleisch, Ulf; Leavitt, Peter R; Ives, Anthony R

    2016-02-01

    Ecologists have long been fascinated by cyclic population fluctuations, because they suggest strong interactions between exploiter and victim species. Nonetheless, even for populations showing high-amplitude fluctuations, it is often hard to identify which species are the key drivers of the dynamics, because data are generally only available for a single species. Here, we use a paleoecological approach to investigate fluctuations in the midge population in Lake Mývatn, Iceland, which ranges over several orders of magnitude in irregular, multigeneration cycles. Previous circumstantial evidence points to consumer-resource interactions between midges and their primary food, diatoms, as the cause of these high-amplitude fluctuations. Using a pair of sediment cores from the lake, we reconstructed 26 years of dynamics of midges using egg remains and of algal groups using diagnostic pigments. We analyzed these data using statistical methods that account for both the autocorrelated nature of paleoecological data and measurement error caused by the mixing of sediment layers. The analyses revealed a signature of consumer-resource interactions in the fluctuations of midges and diatoms: diatom abundance (as inferred from biomarker pigment diatoxanthin) increased when midge abundance was low, and midge abundance (inferred from egg capsules) decreased when diatom abundance was low. Similar patterns were not found for pigments characterizing the other dominant primary producer group in the lake (cyanobacteria), subdominant algae (cryptophytes), or ubiquitous but chemically unstable biomarkers of total algal abundance (chlorophyll a); however, a significant but weaker pattern was found for the chemically stable indicator of total algal populations (β-carotene) to which diatoms are the dominant contributor. These analyses provide the first paleoecological evaluation of specific trophic interactions underlying high amplitude population fluctuations in lakes. PMID:27145611

  20. Linking individual phenotype to density-dependent population growth: the influence of body size on the population dynamics of malaria vectors

    PubMed Central

    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

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

    PubMed Central

    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

  2. Mammal population regulation, keystone processes and ecosystem dynamics.

    PubMed Central

    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

  3. Population pharmacokinetic–pharmacodynamic modelling in oncology: a tool for predicting clinical response

    PubMed Central

    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

  4. Nature versus nurture: Predictability in low-temperature Ising dynamics

    NASA Astrophysics Data System (ADS)

    Ye, J.; Machta, J.; Newman, C. M.; Stein, D. L.

    2013-10-01

    Consider a dynamical many-body system with a random initial state subsequently evolving through stochastic dynamics. What is the relative importance of the initial state (“nature”) versus the realization of the stochastic dynamics (“nurture”) in predicting the final state? We examined this question for the two-dimensional Ising ferromagnet following an initial deep quench from T=∞ to T=0. We performed Monte Carlo studies on the overlap between “identical twins” raised in independent dynamical environments, up to size L=500. Our results suggest an overlap decaying with time as t-θh with θh=0.22±0.02; the same exponent holds for a quench to low but nonzero temperature. This “heritability exponent” may equal the persistence exponent for the two-dimensional Ising ferromagnet, but the two differ more generally.

  5. Nature versus nurture: predictability in low-temperature Ising dynamics.

    PubMed

    Ye, J; Machta, J; Newman, C M; Stein, D L

    2013-10-01

    Consider a dynamical many-body system with a random initial state subsequently evolving through stochastic dynamics. What is the relative importance of the initial state ("nature") versus the realization of the stochastic dynamics ("nurture") in predicting the final state? We examined this question for the two-dimensional Ising ferromagnet following an initial deep quench from T=∞ to T=0. We performed Monte Carlo studies on the overlap between "identical twins" raised in independent dynamical environments, up to size L=500. Our results suggest an overlap decaying with time as t(-θ)(h) with θ(h)=0.22 ± 0.02; the same exponent holds for a quench to low but nonzero temperature. This "heritability exponent" may equal the persistence exponent for the two-dimensional Ising ferromagnet, but the two differ more generally. PMID:24229093

  6. Uncoupling the Effects of Seed Predation and Seed Dispersal by Granivorous Ants on Plant Population Dynamics

    PubMed Central

    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

  7. 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.

  8. Dynamic evidential reasoning algorithm for systems reliability prediction

    NASA Astrophysics Data System (ADS)

    Hu, Chang-Hua; Si, Xiao-Sheng; Yang, Jian-Bo

    2010-07-01

    In this article, dynamic evidential reasoning (DER) algorithm is applied to forecast reliability in turbochargers engine systems and a reliability prediction model is developed. The focus of this study is to examine the feasibility and validity of DER algorithm in systems reliability prediction by comparing it with some existing approaches. To build an effective DER forecasting model, the parameters of prediction model must be set carefully. To solve this problem, a generic nonlinear optimisation model is investigated to search for the optimal parameters of forecasting model, and then the optimal parameters are adopted to construct the DER forecasting model. Finally, a numerical example is provided to demonstrate the detailed implementation procedures and the validity of the proposed approach in the areas of reliability prediction.

  9. Statistical prediction of dynamic distortion of inlet flow using minimum dynamic measurement. An application to the Melick statistical method and inlet flow dynamic distortion prediction without RMS measurements

    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.

  10. Evolutionary dynamics for persistent cooperation in structured populations

    NASA Astrophysics Data System (ADS)

    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.

  11. Chain pooling to minimize prediction error in subset regression. [Monte Carlo studies using population models

    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.

  12. Slicing and dicing globular clusters: dynamically evolved single stellar populations

    NASA Astrophysics Data System (ADS)

    Sippel, Anna C.; Hurley, Jarrod R.

    2016-04-01

    We utilize direct N-body models of globular clusters including stellar evolution to calculate magnitudes for each star in the Hubble Space Telescope Advanced Camera for Surveys 555, 606 and 814 filters. This enables us to analyse the colour of dynamically evolved single stellar populations over time in colour-magnitude diagrams of both, resolved and integrated globular clusters. We find that the change of integrated cluster colour is driven predominantly by the colour of the brightest stars available and hence by stellar evolution, but not by the removal of low-mass stars. We show that even in mass-segregated clusters, different stellar populations are distributed over the entire cluster. This implies that evolved stars also exist within and outside the half-mass radius.

  13. State-dependent neutral delay equations from population dynamics.

    PubMed

    Barbarossa, M V; Hadeler, K P; Kuttler, C

    2014-10-01

    A novel class of state-dependent delay equations is derived from the balance laws of age-structured population dynamics, assuming that birth rates and death rates, as functions of age, are piece-wise constant and that the length of the juvenile phase depends on the total adult population size. The resulting class of equations includes also neutral delay equations. All these equations are very different from the standard delay equations with state-dependent delay since the balance laws require non-linear correction factors. These equations can be written as systems for two variables consisting of an ordinary differential equation (ODE) and a generalized shift, a form suitable for numerical calculations. It is shown that the neutral equation (and the corresponding ODE--shift system) is a limiting case of a system of two standard delay equations. PMID:25117688

  14. Temporal variation in the synchrony of weather and its consequences for spatiotemporal population dynamics.

    PubMed

    Allstadt, Andrew J; Liebhold, Andrew M; Johnson, Derek M; Davis, Robert E; Haynes, Kyle J

    2015-11-01

    Over large areas, synchronous fluctuations in population density are often attributed to environmental stochasticity (e.g., weather) shared among local populations. This concept was first advanced by Patrick Moran who showed, based on several assumptions, that long-term population synchrony will equal the synchrony of environmental stochasticity among locations. We examine the consequences of violating one of Moran's assumptions, namely that environmental synchrony is constant through time. We demonstrate that the synchrony of weather conditions from regions across the United States varied considerably from 1895 to 2010. Using a simulation model modified from Moran's original study, we show that temporal variation in environmental synchrony can cause changes in population synchrony, which in turn can temporarily increase or decrease the amplitude of regional-scale population fluctuations. A case study using the gypsy moth (Lymantria dispar) provides empirical support for these predictions. This study provides theoretical and empirical evidence that temporal variation in environmental synchrony can be used to identify factors that synchronize population fluctuations and highlights a previously underappreciated cause of variability in population dynamics. PMID:27070013

  15. Evolutionary game dynamics in populations with different learners

    PubMed Central

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

    2012-01-01

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

  16. Population Dynamics of Patients with Bacterial Resistance in Hospital Environment.

    PubMed

    Qu, Leilei; Pan, Qiuhui; Gao, Xubin; He, Mingfeng

    2016-01-01

    During the past decades, the increase of antibiotic resistance has become a major concern worldwide. The researchers found that superbugs with new type of resistance genes (NDM-1) have two aspects of transmission characteristics; the first is that the antibiotic resistance genes can horizontally transfer among bacteria, and the other is that the superbugs can spread between humans through direct contact. Based on these two transmission mechanisms, we study the dynamics of population in hospital environment where superbugs exist. In this paper, we build three mathematic models to illustrate the dynamics of patients with bacterial resistance in hospital environment. The models are analyzed using stability theory of differential equations. Positive equilibrium points of the system are investigated and their stability analysis is carried out. Moreover, the numerical simulation of the proposed model is also performed which supports the theoretical findings. PMID:26904150

  17. Population Dynamics of Patients with Bacterial Resistance in Hospital Environment

    PubMed Central

    Qu, Leilei; Pan, Qiuhui; Gao, Xubin; He, Mingfeng

    2016-01-01

    During the past decades, the increase of antibiotic resistance has become a major concern worldwide. The researchers found that superbugs with new type of resistance genes (NDM-1) have two aspects of transmission characteristics; the first is that the antibiotic resistance genes can horizontally transfer among bacteria, and the other is that the superbugs can spread between humans through direct contact. Based on these two transmission mechanisms, we study the dynamics of population in hospital environment where superbugs exist. In this paper, we build three mathematic models to illustrate the dynamics of patients with bacterial resistance in hospital environment. The models are analyzed using stability theory of differential equations. Positive equilibrium points of the system are investigated and their stability analysis is carried out. Moreover, the numerical simulation of the proposed model is also performed which supports the theoretical findings. PMID:26904150

  18. 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.

  19. Mosquito population dynamics from cellular automata-based simulation

    NASA Astrophysics Data System (ADS)

    Syafarina, Inna; Sadikin, Rifki; Nuraini, Nuning

    2016-02-01

    In this paper we present an innovative model for simulating mosquito-vector population dynamics. The simulation consist of two stages: demography and dispersal dynamics. For demography simulation, we follow the existing model for modeling a mosquito life cycles. Moreover, we use cellular automata-based model for simulating dispersal of the vector. In simulation, each individual vector is able to move to other grid based on a random walk. Our model is also capable to represent immunity factor for each grid. We simulate the model to evaluate its correctness. Based on the simulations, we can conclude that our model is correct. However, our model need to be improved to find a realistic parameters to match real data.

  20. Population-dynamics method with a multicanonical feedback control

    NASA Astrophysics Data System (ADS)

    Nemoto, Takahiro; Bouchet, Freddy; Jack, Robert L.; Lecomte, Vivien

    2016-06-01

    We discuss the Giardinà-Kurchan-Peliti population dynamics method for evaluating large deviations of time-averaged quantities in Markov processes [Phys. Rev. Lett. 96, 120603 (2006), 10.1103/PhysRevLett.96.120603]. This method exhibits systematic errors which can be large in some circumstances, particularly for systems with weak noise, with many degrees of freedom, or close to dynamical phase transitions. We show how these errors can be mitigated by introducing control forces within the algorithm. These forces are determined by an iteration-and-feedback scheme, inspired by multicanonical methods in equilibrium sampling. We demonstrate substantially improved results in a simple model, and we discuss potential applications to more complex systems.

  1. Population-dynamics method with a multicanonical feedback control.

    PubMed

    Nemoto, Takahiro; Bouchet, Freddy; Jack, Robert L; Lecomte, Vivien

    2016-06-01

    We discuss the Giardinà-Kurchan-Peliti population dynamics method for evaluating large deviations of time-averaged quantities in Markov processes [Phys. Rev. Lett. 96, 120603 (2006)PRLTAO0031-900710.1103/PhysRevLett.96.120603]. This method exhibits systematic errors which can be large in some circumstances, particularly for systems with weak noise, with many degrees of freedom, or close to dynamical phase transitions. We show how these errors can be mitigated by introducing control forces within the algorithm. These forces are determined by an iteration-and-feedback scheme, inspired by multicanonical methods in equilibrium sampling. We demonstrate substantially improved results in a simple model, and we discuss potential applications to more complex systems. PMID:27415224

  2. Population dynamics and range expansion in nine-banded armadillos.

    PubMed

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

    2013-01-01

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

  3. Population Dynamics and Range Expansion in Nine-Banded Armadillos

    PubMed Central

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

    2013-01-01

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

  4. 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.

  5. 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.

  6. 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.

  7. Monitored and modeled coral population dynamics and the refuge concept.

    PubMed

    Riegl, B; Purkis, S J; Keck, J; Rowlands, G P

    2009-01-01

    With large-scale impacts on coral reefs due to global climatic change projected to increase dramatically, and suitability of many areas for reef growth projected to decrease, the question arises whether particular settings might serve as refugia that can maintain higher coral populations than surrounding areas. We examine this hypothesis on a small, local scale in Honduras, western Caribbean. Dense coral thickets containing high numbers of the endangered coral Acropora cervicornis occur on offshore banks while being rare on the fringing reef on nearby Roatán. Geomorphological setting and community dynamics were evaluated and monitored from 1996 to 2005. A model of population dynamics was developed to test assumptions derived from monitoring. Coral cover on the fringing reef declined in 1998 from >30% to <20%, but the banks maintained areas of very dense coral cover (32% cover by A. cervicornis on the banks but <1% on the fringing reef). Bathymetry from satellite images showed the banks to be well-separated from the fringing reef, making asexual connectivity between banks and fringing reef impossible but protecting the banks from direct land-runoff during storms. Exposure to SE tradewinds also causes good flushing. Only four A. cervicornis recruits were recorded on the fringing reef over 6 years. Runoff associated with hurricanes caused greater mortality than did bleaching in 1998 and 2005 on the fringing reef, but not on the banks. Since 1870, our analysis suggests that corals on the banks may have been favored during 17 runoff events associated with tropical depressions and storms and potentially also during five bleaching events, but this is more uncertain. Our model suggests that under this disturbance regime, the banks will indeed maintain higher coral populations than the fringing reef and supports the assumption that offshore banks could serve as refugia with the capacity to subsidize depleted mainland populations. PMID:19100585

  8. Psychoanalysis and dynamical systems theory: prediction and self similarity.

    PubMed

    Galatzer-Levy, R M

    1995-01-01

    The theory of dynamical systems (sometimes called chaos theory) has emerged in the past two decades as a powerful tool for understanding the evolution of complex systems. Attempts to develop psychoanalysis along the lines of nineteenth century physical science have proven unsatisfactory. The theory of dynamical systems provides another route for development. It suggests that prediction should aim at describing the overall evolution of systems and that the possibilities for such evolution are broader than classical theory suggested. It also shows that complex systems often involve structures that repeat basic features on several different levels of observation. This suggests a method for systematically exploring the overly rich data of psychoanalysis. PMID:8926326

  9. Movement prediction using accelerometers in a human population.

    PubMed

    Xiao, Luo; He, Bing; Koster, Annemarie; Caserotti, Paolo; Lange-Maia, Brittney; Glynn, Nancy W; Harris, Tamara B; Crainiceanu, Ciprian M

    2016-06-01

    We introduce statistical methods for predicting the types of human activity at sub-second resolution using triaxial accelerometry data. The major innovation is that we use labeled activity data from some subjects to predict the activity labels of other subjects. To achieve this, we normalize the data across subjects by matching the standing up and lying down portions of triaxial accelerometry data. This is necessary to account for differences between the variability in the position of the device relative to gravity, which are induced by body shape and size as well as by the ambiguous definition of device placement. We also normalize the data at the device level to ensure that the magnitude of the signal at rest is similar across devices. After normalization we use overlapping movelets (segments of triaxial accelerometry time series) extracted from some of the subjects to predict the movement type of the other subjects. The problem was motivated by and is applied to a laboratory study of 20 older participants who performed different activities while wearing accelerometers at the hip. Prediction results based on other people's labeled dictionaries of activity performed almost as well as those obtained using their own labeled dictionaries. These findings indicate that prediction of activity types for data collected during natural activities of daily living may actually be possible. PMID:26288278

  10. Prediction uncertainty and optimal experimental design for learning dynamical systems

    NASA Astrophysics Data System (ADS)

    Letham, Benjamin; Letham, Portia A.; Rudin, Cynthia; Browne, Edward P.

    2016-06-01

    Dynamical systems are frequently used to model biological systems. When these models are fit to data, it is necessary to ascertain the uncertainty in the model fit. Here, we present prediction deviation, a metric of uncertainty that determines the extent to which observed data have constrained the model's predictions. This is accomplished by solving an optimization problem that searches for a pair of models that each provides a good fit for the observed data, yet has maximally different predictions. We develop a method for estimating a priori the impact that additional experiments would have on the prediction deviation, allowing the experimenter to design a set of experiments that would most reduce uncertainty. We use prediction deviation to assess uncertainty in a model of interferon-alpha inhibition of viral infection, and to select a sequence of experiments that reduces this uncertainty. Finally, we prove a theoretical result which shows that prediction deviation provides bounds on the trajectories of the underlying true model. These results show that prediction deviation is a meaningful metric of uncertainty that can be used for optimal experimental design.

  11. 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.

  12. 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.

  13. Time of day, seasonality, cardinal direction, and xylem sap effects on Homalodisca vitripennis population dynamics and movement in citrus

    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) ...

  14. Evolutionary game theory for physical and biological scientists. I. Training and validating population dynamics equations

    PubMed Central

    Liao, David; Tlsty, Thea D.

    2014-01-01

    Failure to understand evolutionary dynamics has been hypothesized as limiting our ability to control biological systems. An increasing awareness of similarities between macroscopic ecosystems and cellular tissues has inspired optimism that game theory will provide insights into the progression and control of cancer. To realize this potential, the ability to compare game theoretic models and experimental measurements of population dynamics should be broadly disseminated. In this tutorial, we present an analysis method that can be used to train parameters in game theoretic dynamics equations, used to validate the resulting equations, and used to make predictions to challenge these equations and to design treatment strategies. The data analysis techniques in this tutorial are adapted from the analysis of reaction kinetics using the method of initial rates taught in undergraduate general chemistry courses. Reliance on computer programming is avoided to encourage the adoption of these methods as routine bench activities. PMID:25097751

  15. [On the relation between encounter rate and population density: Are classical models of population dynamics justified?].

    PubMed

    Nedorezov, L V

    2015-01-01

    A stochastic model of migrations on a lattice and with discrete time is considered. It is assumed that space is homogenous with respect to its properties and during one time step every individual (independently of local population numbers) can migrate to nearest nodes of lattice with equal probabilities. It is also assumed that population size remains constant during certain time interval of computer experiments. The following variants of estimation of encounter rate between individuals are considered: when for the fixed time moments every individual in every node of lattice interacts with all other individuals in the node; when individuals can stay in nodes independently, or can be involved in groups in two, three or four individuals. For each variant of interactions between individuals, average value (with respect to space and time) is computed for various values of population size. The samples obtained were compared with respective functions of classic models of isolated population dynamics: Verhulst model, Gompertz model, Svirezhev model, and theta-logistic model. Parameters of functions were calculated with least square method. Analyses of deviations were performed using Kolmogorov-Smirnov test, Lilliefors test, Shapiro-Wilk test, and other statistical tests. It is shown that from traditional point of view there are no correspondence between the encounter rate and functions describing effects of self-regulatory mechanisms on population dynamics. Best fitting of samples was obtained with Verhulst and theta-logistic models when using the dataset resulted from the situation when every individual in the node interacts with all other individuals. PMID:26606790

  16. 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…

  17. Population dynamics of minimally cognitive individuals. Part I: Introducing knowledge into the dynamics

    SciTech Connect

    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.

  18. Accuracy of genome-enabled prediction exploring purebred and crossbred pig populations.

    PubMed

    Veroneze, R; Lopes, M S; Hidalgo, A M; Guimarães, S E F; Silva, F F; Harlizius, B; Lopes, P S; Knol, E F; M van Arendonk, J A; Bastiaansen, J W M

    2015-10-01

    Pig breeding companies keep relatively small populations of pure sire and dam lines that are selected to improve the performance of crossbred animals. This design of the pig breeding industry presents challenges to the implementation of genomic selection, which requires large data sets to obtain highly accurate genomic breeding values. The objective of this study was to evaluate the impact of different reference sets (across population and multipopulation) on the accuracy of genomic breeding values in 3 purebred pig populations and to assess the potential of using crossbreed performance in genomic prediction. Data consisted of phenotypes and genotypes on animals from 3 purebred populations (sire line [SL] 1, = 1,146; SL2, = 682; and SL3, = 1,264) and 3 crossbred pig populations (Terminal cross [TER] 1, = 183; TER2, = 106; and TER3, = 177). Animals were genotyped using the Illumina Porcine SNP60 Beadchip. For each purebred population, within-, across-, and multipopulation predictions were considered. In addition, data from the paternal purebred populations were used as a reference set to predict the performance of crossbred animals. Backfat thickness phenotypes were precorrected for fixed effects and subsequently included in the genomic BLUP model. A genomic relationship matrix that accounted for the differences in allele frequencies between lines was implemented. Accuracies of genomic EBV obtained within the 3 different sire lines varied considerably. For within-population prediction, SL1 showed higher values (0.80) than SL2 (0.61) and SL3 (0.67). Multipopulation predictions had accuracies similar to within-population accuracies for the validation in SL1. For SL2 and SL3, the accuracies of multipopulation prediction were similar to the within-population prediction when the reference set was composed by 900 animals (600 of the target line plus 300 of another line). For across-population predictions, the accuracy was mostly close to zero. The accuracies of predicting

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

    SciTech Connect

    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.

  20. Linking populations to landscapes: richness scenarios resulting from changes in the dynamics of an ecosystem engineer.

    PubMed

    Wright, Justin P

    2009-12-01

    Predicting the effects of the loss of individual species on diversity represents one of the primary challenges facing community ecology. One pathway by which organisms of one species affect the distribution of species is ecosystem engineering. Changes in the dynamics of ecosystem engineers that lead to changes in the distribution of the patches of altered habitat are likely to lead to changes in diversity. I link data on the distribution of plant species found in the riparian zone of the Adirondacks (New York, USA) in patches modified by beaver and in unmodified forest patches to a model connecting the dynamics of ecosystem engineers to the dynamics of the patches that they create. These analyses demonstrate that changes in key parameters of the model, such as decreases in beaver colonization rates and rate of patch abandonment, lead to changes in species richness of up to 45% at the landscape scale, and that these changes are likely to occur over long time scales. This general approach of linking the population dynamics or behavior of a single species to changes in species richness at the landscape scale provides a means for both testing the importance of ecosystem engineering in different systems and developing scenarios to predict how changes in the dynamics of a single species are likely to affect species richness. PMID:20120810

  1. Impact of simian immunodeficiency virus infection on chimpanzee population dynamics.

    PubMed

    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

  2. Rational Prediction with Molecular Dynamics for Hit Identification

    PubMed Central

    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

  3. The contribution of germination functional traits to population dynamics of a desert plant community.

    PubMed

    Huang, Zhenying; Liu, Shuangshuang; Bradford, Kent J; Huxman, Travis E; Venable, D Lawrence

    2016-01-01

    Early life-cycle events play critical roles in determining the population and community dynamics of plants. The ecology of seeds and their germination patterns can determine range limits, adaptation to environmental variation, species diversity, and community responses to climate change. Understanding the adaptive consequences and environmental filtering of such functional traits will allow us to explain and predict ecological dynamics. Here we quantify key functional aspects of germination physiology and relate them to an existing functional ecology framework to explain long-term population dynamics for 13 species of desert annuals near Tucson, Arizona, USA. Our goal was to assess the extent to which germination functional biology contributes to long-term population processes in nature. Some of the species differences in base, optimum, and maximum temperatures for germination, thermal times to germination, and base water potentials for germination were strongly related to 20-yr mean germination fractions, 25-yr average germination dates, seed size, and long-term demographic variation. Comparisons of germination fraction, survival, and fecundity vs. yearly changes in population size found significant roles for all three factors, although in varying proportions for different species. Relationships between species' germination physiologies and relative germination fractions varied across years, with fast-germinating species being favored in years with warm temperatures during rainfall events in the germination season. Species with low germination fractions and high demographic variance have low integrated water-use efficiency, higher vegetative growth rates, and smaller, slower-germinating seeds. We have identified and quantified a number of functional traits associated with germination biology that play critical roles in ecological population dynamics. PMID:27008793

  4. Long-term disease dynamics in lakes: causes and consequences of chytrid infections in Daphnia populations.

    PubMed

    Johnson, Pieter T J; Ives, Anthony R; Lathrop, Richard C; Carpenter, Stephen R

    2009-01-01

    Understanding the drivers and consequences of disease epidemics is an important frontier in ecology. However, long-term data on hosts, their parasites, and the corresponding environmental conditions necessary to explore these interactions are often unavailable. We examined the dynamics of Daphnia pulicaria, a keystone zooplankter in lake ecosystems, to explore the long-term causes and consequences of infection by a chytridiomycete parasitoid (Polycaryum laeve). After quantifying host-pathogen dynamics from vouchered samples collected over 15 years, we used autoregressive models to evaluate (1) hypothesized drivers of infection, including host density, water temperature, dissolved oxygen, host-food availability, and lake mixing; and (2) the effects of epidemics on host populations. Infection was present in most years but varied widely in prevalence, from < 1% to 34%, with seasonal peaks in early spring and late fall. Within years, lake stratification strongly inhibited P. laeve transmission, such that epidemics occurred primarily during periods of water mixing. Development of the thermocline likely reduced transmission by spatially separating susceptible hosts from infectious zoospores. Among years, ice duration and cumulative snowfall correlated negatively with infection prevalence, likely because of reductions in spring phytoplankton and D. pulicaria density in years with extended winters. Epidemics also influenced dynamics of the host population. Infected D. pulicaria rarely (< 1%) contained eggs, and P. laeve prevalence was positively correlated with sexual reproduction in D. pulicaria. Analyses of D. pulicaria density-dependent population dynamics predicted that, in the absence of P. laeve infection, host abundance would be 11-50% higher than what was observed. By underscoring the importance of complex physical processes in controlling host-parasite interactions and of epidemic disease in influencing host populations, our results highlight the value of long

  5. Effects of spatial structure of population size on the population dynamics of barnacles across their elevational range.

    PubMed

    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

  6. 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...

  7. [Population dynamics of thrushes and seasonal resource partition].

    PubMed

    Burskiĭ, O V; Demidova, E Iu; Morkovin, A A

    2014-01-01

    We studied seasonal population dynamics in birds using four thrush species from the Yenisei middle taiga region as an example. Long-term data on bird route censuses, capture-mark-recapture, and nest observa- tions were incorporated in the analysis. Particularly, methodological problems that complicate a direct comparison between assessed numbers at different phases of the annual cycle are considered. The integrated analysis of the results allowed comparing changes in numbers, energy expenditure, age structure, migrating status, and density distribution of selected populations during the snowless period and relating them to seasonal changes in food resource abundance. Thrush population numbers within the breeding range, and their energy consumption in the Yenisei middle taiga proportionately reflect the seasonal change in abundance of food resources. The compliance between resource intake and carrying capacity of the environment is attained by: timing of arrival and departure regarding to the species' range of tolerance; change in numbers as a result of reproduction and mortality; change in numbers due to habitat changes and long-distance movements; increasing energetic expenditures during reproduction and molt; timing, intensity and replication of nesting attempts; timing of molt and proportion of molting individuals in a population; individual variations of the annual cycle. Reproductive growth of local bird populations is not fast enough to catch up with seasonal growth of ecosystems productivity. Superabundance of invertebrates at the peak of the season offers a temporal niche which, on the one hand, is suitable for species capable of diet switching, while, on the other hand, may be used by specialized consumers, namely tropical migrants for whom, at high resource level, a shortened breeding period suffices. PMID:25786310

  8. Cycles, stochasticity and density dependence in pink salmon population dynamics.

    PubMed

    Krkosek, Martin; Hilborn, Ray; Peterman, Randall M; Quinn, Thomas P

    2011-07-01

    Complex dynamics of animal populations often involve deterministic and stochastic components. A fascinating example is the variation in magnitude of 2-year cycles in abundances of pink salmon (Oncorhynchus gorbuscha) stocks along the North Pacific rim. Pink salmon have a 2-year anadromous and semelparous life cycle, resulting in odd- and even-year lineages that occupy the same habitats but are reproductively isolated in time. One lineage is often much more abundant than the other in a given river, and there are phase switches in dominance between odd- and even-year lines. In some regions, the weak line is absent and in others both lines are abundant. Our analysis of 33 stocks indicates that these patterns probably result from stochastic perturbations of damped oscillations owing to density-dependent mortality caused by interactions between lineages. Possible mechanisms are cannibalism, disease transmission, food depletion and habitat degradation by which one lineage affects the other, although no mechanism has been well-studied. Our results provide comprehensive empirical estimates of lagged density-dependent mortality in salmon populations and suggest that a combination of stochasticity and density dependence drives cyclical dynamics of pink salmon stocks. PMID:21147806

  9. 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

  10. 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.

  11. 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.

  12. Inferring Network Dynamics and Neuron Properties from Population Recordings

    PubMed Central

    Linaro, Daniele; Storace, Marco; Mattia, Maurizio

    2011-01-01

    Understanding the computational capabilities of the nervous system means to “identify” its emergent multiscale dynamics. For this purpose, we propose a novel model-driven identification procedure and apply it to sparsely connected populations of excitatory integrate-and-fire neurons with spike frequency adaptation (SFA). Our method does not characterize the system from its microscopic elements in a bottom-up fashion, and does not resort to any linearization. We investigate networks as a whole, inferring their properties from the response dynamics of the instantaneous discharge rate to brief and aspecific supra-threshold stimulations. While several available methods assume generic expressions for the system as a black box, we adopt a mean-field theory for the evolution of the network transparently parameterized by identified elements (such as dynamic timescales), which are in turn non-trivially related to single-neuron properties. In particular, from the elicited transient responses, the input–output gain function of the neurons in the network is extracted and direct links to the microscopic level are made available: indeed, we show how to extract the decay time constant of the SFA, the absolute refractory period and the average synaptic efficacy. In addition and contrary to previous attempts, our method captures the system dynamics across bifurcations separating qualitatively different dynamical regimes. The robustness and the generality of the methodology is tested on controlled simulations, reporting a good agreement between theoretically expected and identified values. The assumptions behind the underlying theoretical framework make the method readily applicable to biological preparations like cultured neuron networks and in vitro brain slices. PMID:22016731

  13. Predicting the effects of human developments on individual dolphins to understand potential long-term population consequences.

    PubMed

    Pirotta, Enrico; Harwood, John; Thompson, Paul M; New, Leslie; Cheney, Barbara; Arso, Monica; Hammond, Philip S; Donovan, Carl; Lusseau, David

    2015-11-01

    Human activities that impact wildlife do not necessarily remove individuals from populations. They may also change individual behaviour in ways that have sublethal effects. This has driven interest in developing analytical tools that predict the population consequences of short-term behavioural responses. In this study, we incorporate empirical information on the ecology of a population of bottlenose dolphins into an individual-based model that predicts how individuals' behavioural dynamics arise from their underlying motivational states, as well as their interaction with boat traffic and dredging activities. We simulate the potential effects of proposed coastal developments on this population and predict that the operational phase may affect animals' motivational states. For such results to be relevant for management, the effects on individuals' vital rates also need to be quantified. We investigate whether the relationship between an individual's exposure and the survival of its calves can be directly estimated using a Bayesian multi-stage model for calf survival. The results suggest that any effect on calf survival is probably small and that a significant relationship could only be detected in large, closely studied populations. Our work can be used to guide management decisions, accelerate the consenting process for coastal and offshore developments and design targeted monitoring. PMID:26511044

  14. Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival.

    PubMed

    Christiansen-Jucht, Céline; Erguler, Kamil; Shek, Chee Yan; Basáñez, María-Gloria; Parham, Paul E

    2015-06-01

    Climate change and global warming are emerging as important threats to human health, particularly through the potential increase in vector- and water-borne diseases. Environmental variables are known to affect substantially the population dynamics and abundance of the poikilothermic vectors of disease, but the exact extent of this sensitivity is not well established. Focusing on malaria and its main vector in Africa, Anopheles gambiae sensu stricto, we present a set of novel mathematical models of climate-driven mosquito population dynamics motivated by experimental data suggesting that in An. gambiae, mortality is temperature and age dependent. We compared the performance of these models to that of a "standard" model ignoring age dependence. We used a longitudinal dataset of vector abundance over 36 months in sub-Saharan Africa for comparison between models that incorporate age dependence and one that does not, and observe that age-dependent models consistently fitted the data better than the reference model. This highlights that including age dependence in the vector component of mosquito-borne disease models may be important to predict more reliably disease transmission dynamics. Further data and studies are needed to enable improved fitting, leading to more accurate and informative model predictions for the An. gambiae malaria vector as well as for other disease vectors. PMID:26030468

  15. Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival

    PubMed Central

    Christiansen-Jucht, Céline; Erguler, Kamil; Shek, Chee Yan; Basáñez, María-Gloria; Parham, Paul E.

    2015-01-01

    Climate change and global warming are emerging as important threats to human health, particularly through the potential increase in vector- and water-borne diseases. Environmental variables are known to affect substantially the population dynamics and abundance of the poikilothermic vectors of disease, but the exact extent of this sensitivity is not well established. Focusing on malaria and its main vector in Africa, Anopheles gambiae sensu stricto, we present a set of novel mathematical models of climate-driven mosquito population dynamics motivated by experimental data suggesting that in An. gambiae, mortality is temperature and age dependent. We compared the performance of these models to that of a “standard” model ignoring age dependence. We used a longitudinal dataset of vector abundance over 36 months in sub-Saharan Africa for comparison between models that incorporate age dependence and one that does not, and observe that age-dependent models consistently fitted the data better than the reference model. This highlights that including age dependence in the vector component of mosquito-borne disease models may be important to predict more reliably disease transmission dynamics. Further data and studies are needed to enable improved fitting, leading to more accurate and informative model predictions for the An. gambiae malaria vector as well as for other disease vectors. PMID:26030468

  16. 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.

  17. [Gypsy moth Lymantria dispar L. in the South Urals: Patterns in population dynamics and modelling].

    PubMed

    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

  18. Review: How to improve genomic predictions in small dairy cattle populations.

    PubMed

    Lund, M S; van den Berg, I; Ma, P; Brøndum, R F; Su, G

    2016-06-01

    This paper reviews strategies and methods to improve accuracies of genomic predictions from the perspective of a numerically small population. Improvements are realized by influencing one or both of the main factors: (1) improve or increase genomic connections to phenotypic records in training data. (2) Models and strategies to focus genomic predictions on markers closer to the causative variants. Combining populations into a joint reference population results in high improvements when combining populations of the same breed and diminishes as the genetic distance between populations increases. For distantly related breeds sophisticated Bayesian variable selection models in combination with denser markers sets or functional subsets of markers is needed. This is expected to be further improved by the efficient use of sequence information. In addition predictions can be improved by the use of phenotypes of genotyped and non-genotyped cows directly. For a small population the optimal approach will combine the above components. PMID:26781646

  19. Parsimonious snow model explains reindeer population dynamics and ranging behavior

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  20. Uncertainty estimation and prediction for interdisciplinary ocean dynamics

    SciTech Connect

    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.

  1. [The population of Latin America: population dynamics from 1990 to 2050].

    PubMed

    Chackiel, J

    1992-01-01

    Past population projections have proven deficient in predicting demographic changes and their intensity. Projections did not envision a decline of nearly 40% in Latin American fertility in two decades. The projections in this work are cautious and based primarily on past trends and the expected continuation of a process leading eventually to replacement level fertility. The economic crisis of the 1980s has generated pessimism regarding the continuation of fertility declines based on economic progress. For the projection, the Latin American countries were classified into four stages of demographic transition. Most Latin American countries, including the three most populated, were considered to be in the third stage, characterized by fertility and mortality in full transition. A table of demographic indicators contains projections for the years 2010, 2025, and 2050 for all of Latin America and for Bolivia, Guatemala, Mexico, Brazil, and Argentina, which are considered to represent the four stages of transition. Latin America as a whole in 1990 had a population of 430,182,000, with a total fertility rate of 3.1, life expectancy at birth of 69 years, and natural increase rate of 2.1%. 36% of the population was under 15 years old. In 2010, 2025, and 2050, respectively, the population is projected to increase to 587 million, 686 million, and 785 million; the total fertility rate to decline to 2.3, 2.1, and 2.1; life expectancy at birth to increase to 72 years, 74 years, and 74 years, and the natural increase rate to decline to 1.2, 0.8, and 0.3%. The proportion of the population under 15 will decline to 28% in 2010, 24% in 2025, and 21% in 2050. PMID:12158077

  2. Predicting and understanding forest dynamics using a simple tractable model

    PubMed Central

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

    2008-01-01

    The perfect-plasticity approximation (PPA) is an analytically tractable model of forest dynamics, defined in terms of parameters for individual trees, including allometry, growth, and mortality. We estimated these parameters for the eight most common species on each of four soil types in the US Lake states (Michigan, Wisconsin, and Minnesota) by using short-term (≤15-year) inventory data from individual trees. We implemented 100-year PPA simulations given these parameters and compared these predictions to chronosequences of stand development. Predictions for the timing and magnitude of basal area dynamics and ecological succession on each soil were accurate, and predictions for the diameter distribution of 100-year-old stands were correct in form and slope. For a given species, the PPA provides analytical metrics for early-successional performance (H20, height of a 20-year-old open-grown tree) and late-successional performance (Ẑ*, equilibrium canopy height in monoculture). These metrics predicted which species were early or late successional on each soil type. Decomposing Ẑ* showed that (i) succession is driven both by superior understory performance and superior canopy performance of late-successional species, and (ii) performance differences primarily reflect differences in mortality rather than growth. The predicted late-successional dominants matched chronosequences on xeromesic (Quercus rubra) and mesic (codominance by Acer rubrum and Acer saccharum) soil. On hydromesic and hydric soils, the literature reports that the current dominant species in old stands (Thuja occidentalis) is now failing to regenerate. Consistent with this, the PPA predicted that, on these soils, stands are now succeeding to dominance by other late-successional species (e.g., Fraxinus nigra, A. rubrum). PMID:18971335

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

    USGS Publications Warehouse

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

    2009-01-01

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

  4. Fitness costs of an insecticide resistance and their population dynamical consequences in the oriental fruit fly.

    PubMed

    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

  5. Phonon-Induced Population Dynamics and Intersystem Crossing in Nitrogen-Vacancy Centers

    NASA Astrophysics Data System (ADS)

    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.

    2015-04-01

    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.

  6. Genomic Prediction in Pea: Effect of Marker Density and Training Population Size and Composition on Prediction Accuracy

    PubMed Central

    Tayeh, Nadim; Klein, Anthony; Le Paslier, Marie-Christine; Jacquin, Françoise; Houtin, Hervé; Rond, Céline; Chabert-Martinello, Marianne; Magnin-Robert, Jean-Bernard; Marget, Pascal; Aubert, Grégoire; Burstin, Judith

    2015-01-01

    Pea is an important food and feed crop and a valuable component of low-input farming systems. Improving resistance to biotic and abiotic stresses is a major breeding target to enhance yield potential and regularity. Genomic selection (GS) has lately emerged as a promising technique to increase the accuracy and gain of marker-based selection. It uses genome-wide molecular marker data to predict the breeding values of candidate lines to selection. A collection of 339 genetic resource accessions (CRB339) was subjected to high-density genotyping using the GenoPea 13.2K SNP Array. Genomic prediction accuracy was evaluated for thousand seed weight (TSW), the number of seeds per plant (NSeed), and the date of flowering (BegFlo). Mean cross-environment prediction accuracies reached 0.83 for TSW, 0.68 for NSeed, and 0.65 for BegFlo. For each trait, the statistical method, the marker density, and/or the training population size and composition used for prediction were varied to investigate their effects on prediction accuracy: the effect was large for the size and composition of the training population but limited for the statistical method and marker density. Maximizing the relatedness between individuals in the training and test sets, through the CDmean-based method, significantly improved prediction accuracies. A cross-population cross-validation experiment was further conducted using the CRB339 collection as a training population set and nine recombinant inbred lines populations as test set. Prediction quality was high with mean Q2 of 0.44 for TSW and 0.59 for BegFlo. Results are discussed in the light of current efforts to develop GS strategies in pea. PMID:26635819

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

    PubMed

    Boggs, Carol L; Inouye, David W

    2012-05-01

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

  8. Rhythmic Manipulation of Objects with Complex Dynamics: Predictability over Chaos

    PubMed Central

    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

  9. Predicting individual brain maturity using dynamic functional connectivity

    PubMed Central

    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

  10. Population dynamics of a northern-adapted mammal: disentangling the influence of predation and climate change.

    PubMed

    Pokallus, John W; Pauli, Jonathan N

    2015-09-01

    Community structure and interspecific interactions are particularly vulnerable to rapidly changing climatic regimes. Recent changes in both climate and vertebrate community assemblages have created a unique opportunity to examine the impacts of two dynamic forces on population regulation. We examined the effects of warming winter conditions and the reestablishment of a previously extirpated predator, the fisher (Martes pennanti), on regulatory mechanisms in a northern-adapted mammal, the porcupine (Erethizon dorsatum), along their southern range boundary. Using a long-term (17-year) capture-recapture data set, we (1) quantified the impacts of climate change and increased fisher predation on the survival of adult porcupines at their regional southern terminus, (2) assessed recruitment (via both adult fecundity and juvenile survival) of porcupines, and (3) modeled the relative importance of predation and winter conditions on the demography and population growth rate (λ). Severe winters and abundant predators interacted synergistically to reduce adult survivorship by as much as 44%, while expanding predator populations led to near reproductive failure among porcupines. Increasing predatory pressure, disruptions in this community module, and more frequent extreme winter weather events led to predicted extirpation within 50 years, whereas in the absence of predators, the population was viable. Our results provide a mechanistic understanding behind distributional shifts resulting from climate change and may be broadly relevant for predicting future distributional shifts in other northern-adapted mammalian species. PMID:26552263

  11. Exploring iris colour prediction and ancestry inference in admixed populations of South America.

    PubMed

    Freire-Aradas, A; Ruiz, Y; Phillips, C; Maroñas, 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

  12. Population dynamics and potential of fisheries stock enhancement: practical theory for assessment and policy analysis

    PubMed Central

    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

  13. Population dynamics can be more important than physiological limits for determining range shifts under climate change.

    PubMed

    Fordham, Damien A; Mellin, Camille; Russell, Bayden D; Akçakaya, Reşit H; Bradshaw, Corey J A; Aiello-Lammens, Matthew E; Caley, Julian M; Connell, Sean D; Mayfield, Stephen; Shepherd, Scoresby A; Brook, Barry W

    2013-10-01

    Evidence is accumulating that species' responses to climate changes are best predicted by modelling the interaction of physiological limits, biotic processes and the effects of dispersal-limitation. Using commercially harvested blacklip (Haliotis rubra) and greenlip abalone (Haliotis laevigata) as case studies, we determine the relative importance of accounting for interactions among physiology, metapopulation dynamics and exploitation in predictions of range (geographical occupancy) and abundance (spatially explicit density) under various climate change scenarios. Traditional correlative ecological niche models (ENM) predict that climate change will benefit the commercial exploitation of abalone by promoting increased abundances without any reduction in range size. However, models that account simultaneously for demographic processes and physiological responses to climate-related factors result in future (and present) estimates of area of occupancy (AOO) and abundance that differ from those generated by ENMs alone. Range expansion and population growth are unlikely for blacklip abalone because of important interactions between climate-dependent mortality and metapopulation processes; in contrast, greenlip abalone should increase in abundance despite a contraction in AOO. The strongly non-linear relationship between abalone population size and AOO has important ramifications for the use of ENM predictions that rely on metrics describing change in habitat area as proxies for extinction risk. These results show that predicting species' responses to climate change often require physiological information to understand climatic range determinants, and a metapopulation model that can make full use of this data to more realistically account for processes such as local extirpation, demographic rescue, source-sink dynamics and dispersal-limitation. PMID:23907833

  14. Do resting brain dynamics predict oddball evoked-potential?

    PubMed Central

    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

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

    EPA Science Inventory

    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...

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

    EPA Science Inventory

    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...

  17. Prediction of muscle performance during dynamic repetitive movement

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

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

  18. Dispersal, niche breadth and population extinction: colonization ratios predict range size in North American dragonflies.

    PubMed

    McCauley, Shannon J; Davis, Christopher J; Werner, Earl E; Robeson, Michael S

    2014-07-01

    Species' range sizes are shaped by fundamental differences in species' ecological and evolutionary characteristics, and understanding the mechanisms determining range size can shed light on the factors responsible for generating and structuring biological diversity. Moreover, because geographic range size is associated with a species' risk of extinction and their ability to respond to global changes in climate and land use, understanding these mechanisms has important conservation implications. Despite the hypotheses that dispersal behaviour is a strong determinant of species range areas, few data are available to directly compare the relationship between dispersal behaviour and range size. Here, we overcome this limitation by combining data from a multispecies dispersal experiment with additional species-level trait data that are commonly hypothesized to affect range size (e.g. niche breadth, local abundance and body size.). This enables us to examine the relationship between these species-level traits and range size across North America for fifteen dragonfly species. Ten models based on a priori predictions about the relationship between species traits and range size were evaluated and two models were identified as good predictors of species range size. These models indicated that only two species' level traits, dispersal behaviour and niche breadth were strongly related to range size. The evidence from these two models indicated that dragonfly species that disperse more often and further had larger North American ranges. Extinction and colonization dynamics are expected to be a key linkage between dispersal behaviour and range size in dragonflies. To evaluate how extinction and colonization dynamics among dragonflies were related to range size we used an independent data set of extinction and colonization rates for eleven dragonfly species and assessed the relationship between these populations rates and North American range areas for these species. We found a

  19. Wave trains in a model of gypsy moth population dynamics

    NASA Astrophysics Data System (ADS)

    Wilder, J. W.; Vasquez, D. A.; Christie, I.; Colbert, J. J.

    1995-12-01

    A recent model of gypsy moth [Lymantria dispar (Lepidoptera: Lymantriidae)] populations led to the observation of traveling waves in a one-dimensional spatial model. In this work, these waves are studied in more detail and their nature investigated. It was observed that when there are no spatial effects the model behaves chaotically under certain conditions. Under the same conditions, when diffusion is allowed, traveling waves develop. The biomass densities involved in the model, when examined at one point in the spatial domain, are found to correspond to a limit cycle lying on the surface of the chaotic attractor of the spatially homogeneous model. Also observed are wave trains that have modulating maxima, and which when examined at one point in the spatial domain show a quasiperiodic temporal behavior. This complex behavior is determined to be due to the interaction of the traveling wave and the chaotic background dynamics.

  20. On signals of phase transitions in salmon population dynamics.

    PubMed

    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

  1. Richards-like two species population dynamics model.

    PubMed

    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

  2. Urban aerosols harbor diverse and dynamic bacterial populations

    PubMed Central

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

    2007-01-01

    Considering the importance of its potential implications for human health, agricultural productivity, and ecosystem stability, surprisingly little is known regarding the composition or dynamics of the atmosphere's microbial inhabitants. Using a custom high-density DNA microarray, we detected and monitored bacterial populations in two U.S. cities over 17 weeks. These urban aerosols contained at least 1,800 diverse bacterial types, a richness approaching that of some soil bacterial communities. We also reveal the consistent presence of bacterial families with pathogenic members including environmental relatives of select agents of bioterrorism significance. Finally, using multivariate regression techniques, we demonstrate that temporal and meteorological influences can be stronger factors than location in shaping the biological composition of the air we breathe. PMID:17182744

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

    PubMed

    Buhay, Jennifer E

    2011-10-01

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

  4. Neural Population Dynamics Modeled by Mean-Field Graphs

    NASA Astrophysics Data System (ADS)

    Kozma, Robert; Puljic, Marko

    2011-09-01

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

  5. Dynamical criticality in the collective activity of a neural population

    NASA Astrophysics Data System (ADS)

    Mora, Thierry

    The past decade has seen a wealth of physiological data suggesting that neural networks may behave like critical branching processes. Concurrently, the collective activity of neurons has been studied using explicit mappings to classic statistical mechanics models such as disordered Ising models, allowing for the study of their thermodynamics, but these efforts have ignored the dynamical nature of neural activity. I will show how to reconcile these two approaches by learning effective statistical mechanics models of the full history of the collective activity of a neuron population directly from physiological data, treating time as an additional dimension. Applying this technique to multi-electrode recordings from retinal ganglion cells, and studying the thermodynamics of the inferred model, reveals a peak in specific heat reminiscent of a second-order phase transition.

  6. [Phlebotomines of Senegal (Diptera: Psychodidae): population and population dynamics of the Mont-Rolland region].

    PubMed

    Ba, Y; Trouillet, J; Thonnon, J; Fontenille, D

    1998-06-01

    Phlebotomine sandflies were captured on a monthly basis from May 1995 to April 1996 in the Mont-Rolland district in Western Senegal. The objectives were to study the population dynamics of sandflies and to make an inventory of the viruses they transmit. Among 10,315 specimens captured, belonging to 14 species, Sergentomyia dubia (35.9%), S. schwetzi (27.7%) and S. buxtoni (24.5%) were the most abundant. Species from the genus Sergentomyia accounted for 99.6% versus 0.4% for the genus Phlebotomus. The sandflies population was observed to peak in February. The most populated resting sites of the captured insects were in decreasing order tree-holes, termite-hills and burrows. S. dubia was the most abundant species captured in tree-holes. It was S. buxtoni in termite-hills, while S. schwetzi was found to dwell most often in burrows. No virus was isolated from 2,114 specimens tested. PMID:9754310

  7. 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.

  8. Modelling lipid competition dynamics in heterogeneous protocell populations.

    PubMed

    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

  9. Modelling Lipid Competition Dynamics in Heterogeneous Protocell Populations

    PubMed Central

    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

  10. Far from random: dynamical groupings among the NEO population

    NASA Astrophysics Data System (ADS)

    de la Fuente Marcos, C.; de la Fuente Marcos, R.

    2016-03-01

    Among the near-Earth object (NEO) population, there are comets and active asteroids which are sources of fragments that initially move together; in addition, some NEOs follow orbits temporarily trapped in a web of secular resonances. These facts contribute to increasing the risk of meteoroid strikes on Earth, making its proper quantification difficult. The identification and subsequent study of groups of small NEOs that appear to move in similar trajectories are necessary steps in improving our understanding of the impact risk associated with meteoroids. Here, we present results of a search for statistically significant dynamical groupings among the NEO population. Our Monte Carlo-based methodology recovers well-documented groupings like the Taurid Complex or the one resulting from the split comet 73P/Schwassmann-Wachmann 3, and new ones that may have been the source of past impacts. Among the most conspicuous are the Mjolnir and Ptah groups, perhaps the source of recent impact events like Almahata Sitta and Chelyabinsk, respectively. Meteoroid 2014 AA, that hit the Earth on 2014 January 2, could have its origin in a marginally significant grouping associated with Bennu. We find that most of the substructure present within the orbital domain of the NEOs is of resonant nature, probably induced by secular resonances and the Kozai mechanism that confine these objects into specific paths with well-defined perihelia.

  11. Population dynamics in a metastable neon magneto-optical trap

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

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

  12. Replication, Communication, and the Population Dynamics of Scientific Discovery

    PubMed Central

    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

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

    PubMed Central

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

    2011-01-01

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

  14. Modelling Multi-Pulse Population Dynamics from Ultrafast Spectroscopy

    PubMed Central

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

    2011-01-01

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

  15. Population Dynamics of Dactylella oviparasitica and Heterodera schachtii: Toward a Decision Model for Sugar Beet Planting

    PubMed Central

    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

  16. Population dynamics of an Ac-like transposable element in self- and cross-pollinating arabidopsis.

    PubMed Central

    Wright, S I; Le, Q H; Schoen, D J; Bureau, T E

    2001-01-01

    Theoretical models predict that the mating system should be an important factor driving the dynamics of transposable elements in natural populations due to differences in selective pressure on both element and host. We used a PCR-based approach to examine the abundance and levels of insertion polymorphism of Ac-III, a recently identified Ac-like transposon family, in natural populations of the selfing plant Arabidopsis thaliana and its close outcrossing relative, Arabidopsis lyrata. Although several insertions appeared to be ancient and shared between species, there is strong evidence for recent activity of this element family in both species. Sequences of the regions flanking insertions indicate that all Ac-III transposons segregating in natural populations are in noncoding regions and provide no evidence for local transposition events. Transposon display analysis suggests the presence of slightly higher numbers of insertion sites per individual but fewer total polymorphic insertions in the self-pollinating A. thaliana than A. lyrata. Element insertions appear to be segregating at significantly lower frequencies in A. lyrata than A. thaliana, which is consistent with a reduction in transposition rate, reduction in effective population size, or reduced efficacy of natural selection against element insertions in selfing populations. PMID:11454774

  17. 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.

  18. 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.

  19. A dynamic programming algorithm for RNA structure prediction including pseudoknots.

    PubMed

    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

  20. PREDICTING POPULATION EXPOSURES TO PM: THE IMPORTANCE OF MICROENVIRONMENTAL CONCENTRATIONS AND HUMAN ACTIVITIES

    EPA Science Inventory

    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...

  1. Recent range expansion of a terrestrial orchid corresponds with climate-driven variation in its population dynamics.

    PubMed

    van der Meer, Sascha; Jacquemyn, Hans; Carey, Peter D; Jongejans, Eelke

    2016-06-01

    The population dynamics and distribution limits of plant species are predicted to change as the climate changes. However, it remains unclear to what extent climate variables affect population dynamics, which vital rates are most sensitive to climate change, and whether the same vital rates drive population dynamics in different populations. In this study, we used long-term demographic data from two populations of the terrestrial orchid Himantoglossum hircinum growing at the northern edge of their geographic range to quantify the influence of climate change on demographic vital rates. Integral projection models were constructed to study how climate conditions between 1991 and 2006 affected population dynamics and to assess how projected future climate change will affect the long-term viability of this species. Based on the parameterised vital rate functions and the observed climatic conditions, one of the studied populations had an average population growth rate above 1 (λ = 1.04), while the other was declining at ca. 3 % year(-1) (λ = 0.97). Variation in temperature and precipitation mainly affected population growth through their effect on survival and fecundity. Based on UK Climate Projection 2009 estimates of future climate conditions for three greenhouse gas emission scenarios, population growth rates are expected to increase in one of the studied populations. Overall, our results indicate that the observed changes in climatic conditions appeared to be beneficial to the long-term survival of the species in the UK and suggest that they may have been the driving force behind the current range expansion of H. hircinum in England. PMID:26932468

  2. Prediction and measurement of human pilot dynamic characteristics

    NASA Technical Reports Server (NTRS)

    Hess, Ronald A.; Reedy, James T.

    1988-01-01

    An analytical and experimental study of human pilot control strategies in a manned rotorcraft simulation is described. The task simulated involves a low-speed, constant-altitude maneuvering task in which a head-down display is utilized to allow the pilot to track a moving hover point. The efficacy of the display law driving an 'acceleration symbol' is determined and the manner in which the prediction and measurement of pilot/vehicle dynamics can be made part of man/machine system evaluations is demonstrated.

  3. Differences in male coloration are predicted by divergent sexual selection between populations of a cichlid fish.

    PubMed

    Selz, O M; Thommen, R; Pierotti, M E R; Anaya-Rojas, J M; Seehausen, O

    2016-05-11

    Female mating preferences can influence both intraspecific sexual selection and interspecific reproductive isolation, and have therefore been proposed to play a central role in speciation. Here, we investigate experimentally in the African cichlid fish Pundamilia nyererei if differences in male coloration between three para-allopatric populations (i.e. island populations with gene flow) of P. nyererei are predicted by differences in sexual selection by female mate choice between populations. Second, we investigate if female mating preferences are based on the same components of male coloration and go in the same direction when females choose among males of their own population, their own and other conspecific populations and a closely related para-allopatric sister-species, P. igneopinnis Mate-choice experiments revealed that females of the three populations mated species-assortatively, that populations varied in their extent of population-assortative mating and that females chose among males of their own population based on different male colours. Females of different populations exerted directional intrapopulation sexual selection on different male colours, and these differences corresponded in two of the populations to the observed differences in male coloration between the populations. Our results suggest that differences in male coloration between populations of P. nyererei can be explained by divergent sexual selection and that population-assortative mating may directly result from intrapopulation sexual selection. PMID:27147097

  4. 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

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

    PubMed

    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

  6. Coral population dynamics across consecutive mass mortality events.

    PubMed

    Riegl, Bernhard; Purkis, Sam

    2015-11-01

    Annual coral mortality events due to increased atmospheric heat may occur regularly from the middle of the century and are considered apocalyptic for coral reefs. In the Arabian/Persian Gulf, this situation has already occurred and population dynamics of four widespread corals (Acropora downingi, Porites harrisoni, Dipsastrea pallida, Cyphastrea micropthalma) were examined across the first-ever occurrence of four back-to-back mass mortality events (2009-2012). Mortality was driven by diseases in 2009, bleaching and subsequent diseases in 2010/2011/2012. 2009 reduced P. harrisoni cover and size, the other events increasingly reduced overall cover (2009: -10%; 2010: -20%; 2011: -20%; 2012: -15%) and affected all examined species. Regeneration was only observed after the first disturbance. P. harrisoni and A. downingi severely declined from 2010 due to bleaching and subsequent white syndromes, while D. pallida and P. daedalea declined from 2011 due to bleaching and black-band disease. C. microphthalma cover was not affected. In all species, most large corals were lost while fission due to partial tissue mortality bolstered small size classes. This general shrinkage led to a decrease of coral cover and a dramatic reduction of fecundity. Transition matrices for disturbed and undisturbed conditions were evaluated as Life Table Response Experiment and showed that C. microphthalma changed the least in size-class dynamics and fecundity, suggesting they were 'winners'. In an ordered 'degradation cascade', impacts decreased from the most common to the least common species, leading to step-wise removal of previously dominant species. A potentially permanent shift from high- to low-coral cover with different coral community and size structure can be expected due to the demographic dynamics resultant from the disturbances. Similarities to degradation of other Caribbean and Pacific reefs are discussed. As comparable environmental conditions and mortality patterns must be

  7. Predicting physical time series using dynamic ridge polynomial neural networks.

    PubMed

    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

  8. Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks

    PubMed Central

    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

  9. The contribution of dominance to phenotype prediction in a pine breeding and simulated population

    PubMed Central

    de Almeida Filho, J E; Guimarães, J F R; e Silva, F F; de Resende, M D V; Muñoz, P; Kirst, M; Resende, M F R

    2016-01-01

    Pedigrees and dense marker panels have been used to predict the genetic merit of individuals in plant and animal breeding, accounting primarily for the contribution of additive effects. However, nonadditive effects may also affect trait variation in many breeding systems, particularly when specific combining ability is explored. Here we used models with different priors, and including additive-only and additive plus dominance effects, to predict polygenic (height) and oligogenic (fusiform rust resistance) traits in a structured breeding population of loblolly pine (Pinus taeda L.). Models were largely similar in predictive ability, and the inclusion of dominance only improved modestly the predictions for tree height. Next, we simulated a genetically similar population to assess the ability of predicting polygenic and oligogenic traits controlled by different levels of dominance. The simulation showed an overall decrease in the accuracy of total genomic predictions as dominance increases, regardless of the method used for prediction. Thus, dominance effects may not be accounted for as effectively in prediction models compared with traits controlled by additive alleles only. When the ratio of dominance to total phenotypic variance reached 0.2, the additive–dominance prediction models were significantly better than the additive-only models. However, in the prediction of the subsequent progeny population, this accuracy increase was only observed for the oligogenic trait. PMID:27118156

  10. The contribution of dominance to phenotype prediction in a pine breeding and simulated population.

    PubMed

    de Almeida Filho, J E; Guimarães, J F R; E Silva, F F; de Resende, M D V; Muñoz, P; Kirst, M; Resende, M F R

    2016-07-01

    Pedigrees and dense marker panels have been used to predict the genetic merit of individuals in plant and animal breeding, accounting primarily for the contribution of additive effects. However, nonadditive effects may also affect trait variation in many breeding systems, particularly when specific combining ability is explored. Here we used models with different priors, and including additive-only and additive plus dominance effects, to predict polygenic (height) and oligogenic (fusiform rust resistance) traits in a structured breeding population of loblolly pine (Pinus taeda L.). Models were largely similar in predictive ability, and the inclusion of dominance only improved modestly the predictions for tree height. Next, we simulated a genetically similar population to assess the ability of predicting polygenic and oligogenic traits controlled by different levels of dominance. The simulation showed an overall decrease in the accuracy of total genomic predictions as dominance increases, regardless of the method used for prediction. Thus, dominance effects may not be accounted for as effectively in prediction models compared with traits controlled by additive alleles only. When the ratio of dominance to total phenotypic variance reached 0.2, the additive-dominance prediction models were significantly better than the additive-only models. However, in the prediction of the subsequent progeny population, this accuracy increase was only observed for the oligogenic trait. PMID:27118156

  11. Modeling responses of large-river fish populations to global climate change through downscaling and incorporation of predictive uncertainty

    USGS Publications Warehouse

    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.

  12. Accelerometry-based prediction of movement dynamics for balance monitoring.

    PubMed

    Fuschillo, Valeria Lucia; Bagalà, 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

  13. Role of seasonality on predator-prey-subsidy population dynamics.

    PubMed

    Levy, Dorian; Harrington, Heather A; Van Gorder, Robert A

    2016-05-01

    The role of seasonality on predator-prey interactions in the presence of a resource subsidy is examined using a system of non-autonomous ordinary differential equations (ODEs). The problem is motivated by the Arctic, inhabited by the ecological system of arctic foxes (predator), lemmings (prey), and seal carrion (subsidy). We construct two nonlinear, nonautonomous systems of ODEs named the Primary Model, and the n-Patch Model. The Primary Model considers spatial factors implicitly, and the n-Patch Model considers space explicitly as a "Stepping Stone" system. We establish the boundedness of the dynamics, as well as the necessity of sufficiently nutritional food for the survival of the predator. We investigate the importance of including the resource subsidy explicitly in the model, and the importance of accounting for predator mortality during migration. We find a variety of non-equilibrium dynamics for both systems, obtaining both limit cycles and chaotic oscillations. We were then able to discuss relevant implications for biologically interesting predator-prey systems including subsidy under seasonal effects. Notably, we can observe the extinction or persistence of a species when the corresponding autonomous system might predict the opposite. PMID:26916622

  14. Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana.

    PubMed

    Fournier-Level, Alexandre; Perry, Emily O; Wang, Jonathan A; Braun, Peter T; Migneault, Andrew; Cooper, Martha D; Metcalf, C Jessica E; Schmitt, Johanna

    2016-05-17

    Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico "resurrection experiments" showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation. PMID:27140640

  15. Local competition and metapopulation processes drive long-term seagrass-epiphyte population dynamics.

    PubMed

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

    2013-01-01

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

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

    PubMed Central

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

    2013-01-01

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

  17. Dynamics of Populations of Planetary Systems (IAU C197)

    NASA Astrophysics Data System (ADS)

    Knezevic, Zoran; Milani, Andrea

    2005-05-01

    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

  18. PCI-SS: MISO dynamic nonlinear protein secondary structure prediction

    PubMed Central

    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 α-helices, β-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

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

    SciTech Connect

    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.

  20. The effects of population density and malnutrition on the dynamics of whooping cough.

    PubMed Central

    Duncan, C. J.; Duncan, S. R.; Scott, S.

    1998-01-01

    Liverpool, a seaport in NW England, suffered severely from lethal infectious diseases in the second half of the 19th century: the population was densely crowded and malnourished and life expectancy was low. Time-series analysis shows that the epidemics of whooping cough (i) had an interepidemic interval of 2.9 years, 1863-85, which lengthened to 3.4 years, 1885-1900 (ii) were strongly coherent with wheat prices (P < 0.001) and (iii) also correlated with cycles of seasonal weather conditions. It is suggested from mathematical modelling that the epidemics in this compromised population were maintained (i.e. the system was driven) by an oscillation of malnutrition and by seasonal weather conditions. A model that incorporates both the dynamics of whooping cough and the demographic characteristics of the population is presented. It has been shown to replicate the dynamics of the epidemics and has been used to predict the changes with time of (i) the force of the infection and (ii) the proportion of those infected with whooping cough who died. PMID:9825783

  1. Dynamics and forecasting of population growth and urban expansion in Srinagar City - A Geospatial Approach

    NASA Astrophysics Data System (ADS)

    Farooq, M.; Muslim, M.

    2014-11-01

    The urban areas of developing countries are densely populated and need the use of sophisticated monitoring systems, such as remote sensing and geographical information systems (GIS). The urban sprawl of a city is best understood by studying the dynamics of LULC change which can be easily generated by using sequential satellite images, required for the prediction of urban growth. Multivariate statistical techniques and regression models have been used to establish the relationship between the urban growth and its causative factors and for forecast of the population growth and urban expansion. In Srinagar city, one of the fastest growing metropolitan cities situated in Jammu and Kashmir State of India, sprawl is taking its toll on the natural resources at an alarming pace. The present study was carried over a period of 40 years (1971-2011), to understand the dynamics of spatial and temporal variability of urban sprawl. The results reveal that built-up area has increased by 585.08 % while as the population has increased by 214.75 %. The forecast showed an increase of 246.84 km2 in built-up area which exceeds the overall carrying capacity of the city. The most common conversions were also evaluated.

  2. Linking operation parameters and environmental variables to population dynamics of Mycolata in a membrane bioreactor.

    PubMed

    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

  3. Individual predictions of eye-movements with dynamic scenes

    NASA Astrophysics Data System (ADS)

    Barth, Erhardt; Drewes, Jan; Martinetz, Thomas

    2003-06-01

    We present a model that predicts saccadic eye-movements and can be tuned to a particular human observer who is viewing a dynamic sequence of images. Our work is motivated by applications that involve gaze-contingent interactive displays on which information is displayed as a function of gaze direction. The approach therefore differs from standard approaches in two ways: (1) we deal with dynamic scenes, and (2) we provide means of adapting the model to a particular observer. As an indicator for the degree of saliency we evaluate the intrinsic dimension of the image sequence within a geometric approach implemented by using the structure tensor. Out of these candidate saliency-based locations, the currently attended location is selected according to a strategy found by supervised learning. The data are obtained with an eye-tracker and subjects who view video sequences. The selection algorithm receives candidate locations of current and past frames and a limited history of locations attended in the past. We use a linear mapping that is obtained by minimizing the quadratic difference between the predicted and the actually attended location by gradient descent. Being linear, the learned mapping can be quickly adapted to the individual observer.

  4. Transcriptome dynamics-based operon prediction in prokaryotes

    PubMed Central

    2014-01-01

    Background Inferring operon maps is crucial to understanding the regulatory networks of prokaryotic genomes. Recently, RNA-seq based transcriptome studies revealed that in many bacterial species the operon structure vary with the change of environmental conditions. Therefore, new computational solutions that use both static and dynamic data are necessary to create condition specific operon predictions. Results In this work, we propose a novel classification method that integrates RNA-seq based transcriptome profiles with genomic sequence features to accurately identify the operons that are expressed under a measured condition. The classifiers are trained on a small set of confirmed operons and then used to classify the remaining gene pairs of the organism studied. Finally, by linking consecutive gene pairs classified as operons, our computational approach produces condition-dependent operon maps. We evaluated our approach on various RNA-seq expression profiles of the bacteria Haemophilus somni, Porphyromonas gingivalis, Escherichia coli and Salmonella enterica. Our results demonstrate that, using features depending on both transcriptome dynamics and genome sequence characteristics, we can identify operon pairs with high accuracy. Moreover, the combination of DNA sequence and expression data results in more accurate predictions than each one alone. Conclusion We present a computational strategy for the comprehensive analysis of condition-dependent operon maps in prokaryotes. Our method can be used to generate condition specific operon maps of many bacterial organisms for which high-resolution transcriptome data is available. PMID:24884724

  5. Repeatable and Predictable Dynamics of the Outer Radiation Belt

    NASA Astrophysics Data System (ADS)

    Murphy, K. R.; Mann, I. R.; Sibeck, D. G.; Ozeke, L.; Rae, J.; Watt, C.

    2015-12-01

    Many believe that the response of energetic electrons in the outer radiation belt to each geomagnetic storm is unique, such that the response to any two storms in never the same. This has coined the popular phrase "If you've seen one storm, you've seen one storm". Here we investigate the response of energetic electrons in the outer radiation belt to geomagnetic storms driven by Coronal Mass Ejections (CMEs) and Co-rotating Interaction Regions (CIRs) during the SAMPEX era through solar cycle 23 (1994-2004). We demonstrate that the outer radiation belt responds consistently and predictably to external solar wind energy input and magnetospheric wave dynamics such that larger geomagnetic storms are associated with both increased loss and acceleration. In particular, we demonstrate that the amount of electron loss in the outer radiation belt and subsequent acceleration during a geomagnetic storms is very well characterised by the total energy input from the solar wind, the minimum location of the magnetopause, minimum Dst, and ULF wave power within the inner magnetosphere. Finally we demonstrate that CMEs and CIRs have different external and internal driving conditions that produce distinct belt morphologies. However, a simple ULF wave diffusion model can reproduce both morphologies. This demonstrates how the radiation belts respond predictably for different storm drivers and magnetospheric dynamics.

  6. Prediction of the size of unerupted canines and premolars in a Saudi Arab population.

    PubMed

    al-Khadra, B H

    1993-10-01

    The estimation of the size of unerupted permanent teeth is an essential aspect in treatment planning in the mixed dentition. The commonly used prediction methods of Moyers and Tanaka and Johnston are based on data from a sample of children of Northern European descent. The accuracy of these methods when applied to a different population is questionable. When we applied the Moyers probability tables to a limited sample of a Saudi Arab population, we found that the 35% level was a more accurate determinant than the commonly used 75% confidence level. Likewise, the prediction equations of Tanaka and Johnston overestimated the size of buccal segments in this population. The data illustrate the limitations of these methods when applied to a sample population of other than European descent. From this data, two linear regression equations were developed for tooth size prediction in Saudi Arab children. PMID:8213659

  7. POPULATION DYNAMICS OF AMBIENT AND ALTERED EARTHWORM COMMUNITIES IN ROW-CROP AGROECOSYSTEMS IN OHIO, USA

    EPA Science Inventory

    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...

  8. Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks

    PubMed Central

    Podobnik, Boris; Lipic, Tomislav; Horvatic, Davor; Majdandzic, Antonio; Bishop, Steven R.; Eugene Stanley, H.

    2015-01-01

    Estimating the critical points at which complex systems abruptly flip from one state to another is one of the remaining challenges in network science. Due to lack of knowledge about the underlying stochastic processes controlling critical transitions, it is widely considered difficult to determine the location of critical points for real-world networks, and it is even more difficult to predict the time at which these potentially catastrophic failures occur. We analyse a class of decaying dynamic networks experiencing persistent failures in which the magnitude of the overall failure is quantified by the probability that a potentially permanent internal failure will occur. When the fraction of active neighbours is reduced to a critical threshold, cascading failures can trigger a total network failure. For this class of network we find that the time to network failure, which is equivalent to network lifetime, is inversely dependent upon the magnitude of the failure and logarithmically dependent on the threshold. We analyse how permanent failures affect network robustness using network lifetime as a measure. These findings provide new methodological insight into system dynamics and, in particular, of the dynamic processes of networks. We illustrate the network model by selected examples from biology, and social science. PMID:26387609

  9. Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks

    NASA Astrophysics Data System (ADS)

    Podobnik, Boris; Lipic, Tomislav; Horvatic, Davor; Majdandzic, Antonio; Bishop, Steven R.; Eugene Stanley, H.

    2015-09-01

    Estimating the critical points at which complex systems abruptly flip from one state to another is one of the remaining challenges in network science. Due to lack of knowledge about the underlying stochastic processes controlling critical transitions, it is widely considered difficult to determine the location of critical points for real-world networks, and it is even more difficult to predict the time at which these potentially catastrophic failures occur. We analyse a class of decaying dynamic networks experiencing persistent failures in which the magnitude of the overall failure is quantified by the probability that a potentially permanent internal failure will occur. When the fraction of active neighbours is reduced to a critical threshold, cascading failures can trigger a total network failure. For this class of network we find that the time to network failure, which is equivalent to network lifetime, is inversely dependent upon the magnitude of the failure and logarithmically dependent on the threshold. We analyse how permanent failures affect network robustness using network lifetime as a measure. These findings provide new methodological insight into system dynamics and, in particular, of the dynamic processes of networks. We illustrate the network model by selected examples from biology, and social science.

  10. Large-Scale Modelling of the Environmentally-Driven Population Dynamics of Temperate Aedes albopictus (Skuse)

    PubMed Central

    Erguler, Kamil; Smith-Unna, Stephanie E.; Waldock, Joanna; Proestos, Yiannis; Christophides, George K.; Lelieveld, Jos; Parham, Paul E.

    2016-01-01

    The Asian tiger mosquito, Aedes albopictus, is a highly invasive vector species. It is a proven vector of dengue and chikungunya viruses, with the potential to host a further 24 arboviruses. It has recently expanded its geographical range, threatening many countries in the Middle East, Mediterranean, Europe and North America. Here, we investigate the theoretical limitations of its range expansion by developing an environmentally-driven mathematical model of its population dynamics. We focus on the temperate strain of Ae. albopictus and compile a comprehensive literature-based database of physiological parameters. As a novel approach, we link its population dynamics to globally-available environmental datasets by performing inference on all parameters. We adopt a Bayesian approach using experimental data as prior knowledge and the surveillance dataset of Emilia-Romagna, Italy, as evidence. The model accounts for temperature, precipitation, human population density and photoperiod as the main environmental drivers, and, in addition, incorporates the mechanism of diapause and a simple breeding site model. The model demonstrates high predictive skill over the reference region and beyond, confirming most of the current reports of vector presence in Europe. One of the main hypotheses derived from the model is the survival of Ae. albopictus populations through harsh winter conditions. The model, constrained by the environmental datasets, requires that either diapausing eggs or adult vectors have increased cold resistance. The model also suggests that temperature and photoperiod control diapause initiation and termination differentially. We demonstrate that it is possible to account for unobserved properties and constraints, such as differences between laboratory and field conditions, to derive reliable inferences on the environmental dependence of Ae. albopictus populations. PMID:26871447

  11. Large-Scale Modelling of the Environmentally-Driven Population Dynamics of Temperate Aedes albopictus (Skuse).

    PubMed

    Erguler, Kamil; Smith-Unna, Stephanie E; Waldock, Joanna; Proestos, Yiannis; Christophides, George K; Lelieveld, Jos; Parham, Paul E

    2016-01-01

    The Asian tiger mosquito, Aedes albopictus, is a highly invasive vector species. It is a proven vector of dengue and chikungunya viruses, with the potential to host a further 24 arboviruses. It has recently expanded its geographical range, threatening many countries in the Middle East, Mediterranean, Europe and North America. Here, we investigate the theoretical limitations of its range expansion by developing an environmentally-driven mathematical model of its population dynamics. We focus on the temperate strain of Ae. albopictus and compile a comprehensive literature-based database of physiological parameters. As a novel approach, we link its population dynamics to globally-available environmental datasets by performing inference on all parameters. We adopt a Bayesian approach using experimental data as prior knowledge and the surveillance dataset of Emilia-Romagna, Italy, as evidence. The model accounts for temperature, precipitation, human population density and photoperiod as the main environmental drivers, and, in addition, incorporates the mechanism of diapause and a simple breeding site model. The model demonstrates high predictive skill over the reference region and beyond, confirming most of the current reports of vector presence in Europe. One of the main hypotheses derived from the model is the survival of Ae. albopictus populations through harsh winter conditions. The model, constrained by the environmental datasets, requires that either diapausing eggs or adult vectors have increased cold resistance. The model also suggests that temperature and photoperiod control diapause initiation and termination differentially. We demonstrate that it is possible to account for unobserved properties and constraints, such as differences between laboratory and field conditions, to derive reliable inferences on the environmental dependence of Ae. albopictus populations. PMID:26871447

  12. Exploring Gravity Wave Predictability and Dynamics in Deepwave

    NASA Astrophysics Data System (ADS)

    Doyle, J. D.; Fritts, D. C.; Smith, R. B.; Eckermann, S. D.; Taylor, M. J.; Dörnbrack, A.; Uddstrom, M.; Reynolds, C. A.; Reinecke, A.; Jiang, Q.

    2014-12-01

    The DEEP propagating gravity WAVE program (DEEPWAVE) is a comprehensive, airborne and ground-based measurement and modeling program centered on New Zealand and focused on providing a new understanding of gravity wave dynamics and impacts from the troposphere through the mesosphere and lower thermosphere (MLT). This program employed the NSF/NCAR GV (NGV) research aircraft from a base in New Zealand in a 6-week field measurement campaign in June-July 2014. During the field phase, the NGV was equipped with new lidar and airglow instruments, as well as dropwindsondes and a full suite of flight level instruments including the microwave temperature profiler (MTP), providing temperatures and vertical winds spanning altitudes from immediately above the NGV flight altitude (~13 km) to ~100 km. The region near New Zealand was chosen since all the relevant GW sources (e.g., mountains, cyclones, jet streams) occur strongly here, and upper-level winds in austral winter permit gravity waves to propagate to very high altitudes. The COAMPS adjoint modeling system provided forecast sensitivity in real time during the six-week DEEPWAVE field phase. Five missions were conducted using the NGV to observe regions of high forecast sensitivity, as diagnosed using the COAMPS adjoint model. In this presentation, we provide a summary of the sensitivity characteristics and explore the implications for predictability of low-level winds crucial for gravity wave launching, as well as predictability of gravity wave characteristics in the stratosphere. In general, the sensitive regions were characterized by localized strong dynamics, often involving intense baroclinic systems with deep convection. The results of the adjoint modeling system suggest that gravity wave launching and the characteristics of the gravity waves can be linked to these sensitive regions near frontal zones within baroclinic systems. The predictability links between the tropospheric fronts, cyclones, jet regions, and gravity

  13. Assessing the status and trend of bat populations across broad geographic regions with dynamic distribution models.

    PubMed

    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

  14. Prediction of Plate Motions and Stresses from Global Dynamic Models

    NASA Astrophysics Data System (ADS)

    Ghosh, A.; Holt, W. E.

    2011-12-01

    Predicting plate motions correctly has been a challenge for global dynamic models. In addition to predicting plate motions, a successful model must also explain the following features: plate rigidity, plate boundary zone deformation, as well as intraplate stress patterns and deformation. In this study we show that, given constraints from shallow lithosphere structure, history of subduction, and first order features from whole mantle tomography, it is possible to achieve a high level of accuracy in predicting plate motions and lithosphere deformation within plate boundary zones. Best-fit dynamic models presently provide an RMS velocity misfit of global surface motions (compared at 63,000 spaced points in the GSRM NNR model [Kreemer et al., 2006]) of order 1 cm/yr. We explore the relative contribution of shallow lithosphere structure vs. whole mantle convection in affecting surface deformation as well as plate motions. We show that shallow lithosphere structure that includes topography and lateral density variations in the lithosphere is an integral part of global force balance. Its inclusion in geodynamic models is essential in order to match observations of surface motions and stresses, particularly within continental zones of deformation. We also argue that stiff slabs may not be as important as has been previously claimed in controlling plate motion and lithosphere deformation. An important result of this study is the calibration of absolute stress magnitudes in the lithosphere, verified through benchmarking using whole mantle convection models. Given additional constraints of the matching of surface motions, we also calibrate the absolute effective lithosphere viscosities. Best-fit models require plates with effective viscosities of order 1023 Pa-s, with plate boundary zones possessing effective viscosities 1-3 orders of magnitude weaker. Given deviatoric stress magnitudes within the lithosphere of order 10 - 60 MPa, our global models predict less than 2 mm

  15. Dynamic wake prediction and visualization with uncertainty analysis

    NASA Technical Reports Server (NTRS)

    Holforty, Wendy L. (Inventor); Powell, J. David (Inventor)

    2005-01-01

    A dynamic wake avoidance system utilizes aircraft and atmospheric parameters readily available in flight to model and predict airborne wake vortices in real time. A novel combination of algorithms allows for a relatively simple yet robust wake model to be constructed based on information extracted from a broadcast. The system predicts the location and movement of the wake based on the nominal wake model and correspondingly performs an uncertainty analysis on the wake model to determine a wake hazard zone (no fly zone), which comprises a plurality of wake planes, each moving independently from another. The system selectively adjusts dimensions of each wake plane to minimize spatial and temporal uncertainty, thereby ensuring that the actual wake is within the wake hazard zone. The predicted wake hazard zone is communicated in real time directly to a user via a realistic visual representation. In an example, the wake hazard zone is visualized on a 3-D flight deck display to enable a pilot to visualize or see a neighboring aircraft as well as its wake. The system substantially enhances the pilot's situational awareness and allows for a further safe decrease in spacing, which could alleviate airport and airspace congestion.

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

    PubMed Central

    Černá, Lucie; Münzbergová, Zuzana

    2013-01-01

    Background Many studies compare the population dynamics of single species within multiple habitat types, while much less is known about the differences in population dynamics in closely related species in the same habitat. Additionally, comparisons of the effect of habitat types and species are largely missing. Methodology and Principal Findings We estimated the importance of the habitat type and species for population dynamics of plants. Specifically, we compared the dynamics of two closely related species, the allotetraploid species Anthericum liliago and the diploid species Anthericum ramosum, occurring in the same habitat type. We also compared the dynamics of A. ramosum in two contrasting habitats. We examined three populations per species and habitat type. The results showed that single life history traits as well as the mean population dynamics of A. liliago and A. ramosum from the same habitat type were more similar than the population dynamics of A. ramosum from the two contrasting habitats. Conclusions Our findings suggest that when transferring knowledge regarding population dynamics between populations, we need to take habitat conditions into account, as these conditions appear to be more important than the species involved (ploidy level). However, the two species differ significantly in their overall population growth rates, indicating that the ploidy level has an effect on species performance. In contrast to what has been suggested by previous studies, we observed a higher population growth rate in the diploid species. This is in agreement with the wider range of habitats occupied by the diploid species. PMID:24116057

  17. Prediction of human population responses to toxic compounds by a collaborative competition

    PubMed Central

    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; Friend, Stephen; Dearry, Allen; Simeonov, Anton; Tice, Raymond; Rusyn, Ivan; Wright, Fred A.; Stolovitzky, Gustavo; Xie, Yang; Saez-Rodriguez, Julio

    2015-01-01

    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 inter-individual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against a blinded experimental dataset. 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

  18. Prediction of human population responses to toxic compounds by a collaborative competition.

    PubMed

    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; Friend, Stephen; Dearry, Allen; Simeonov, Anton; Tice, Raymond R; Rusyn, Ivan; Wright, Fred A; Stolovitzky, Gustavo; Xie, Yang; Saez-Rodriguez, Julio

    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

  19. Extrapolating toxic effects on individuals to the population level: the role of dynamic energy budgets.

    PubMed

    Jager, Tjalling; Klok, Chris

    2010-11-12

    The interest of environmental management is in the long-term health of populations and ecosystems. However, toxicity is usually assessed in short-term experiments with individuals. Modelling based on dynamic energy budget (DEB) theory aids the extraction of mechanistic information from the data, which in turn supports educated extrapolation to the population level. To illustrate the use of DEB models in this extrapolation, we analyse a dataset for life cycle toxicity of copper in the earthworm Dendrobaena octaedra. We compare four approaches for the analysis of the toxicity data: no model, a simple DEB model without reserves and maturation (the Kooijman-Metz formulation), a more complex one with static reserves and simplified maturation (as used in the DEBtox software) and a full-scale DEB model (DEB3) with explicit calculation of reserves and maturation. For the population prediction, we compare two simple demographic approaches (discrete time matrix model and continuous time Euler-Lotka equation). In our case, the difference between DEB approaches and population models turned out to be small. However, differences between DEB models increased when extrapolating to more field-relevant conditions. The DEB3 model allows for a completely consistent assessment of toxic effects and therefore greater confidence in extrapolating, but poses greater demands on the available data. PMID:20921051

  20. Finite-time singularity in the dynamics of the world population, economic and financial indices

    NASA Astrophysics Data System (ADS)

    Johansen, Anders; Sornette, Didier

    2001-05-01

    Contrary to common belief, both the Earth's human population and its economic output have grown faster than exponential, i.e., in a super-Malthusian mode, for most of the known history. These growth rates are compatible with a spontaneous singularity occurring at the same critical time 2052±10 signaling an abrupt transition to a new regime. The degree of abruptness can be infered from the fact that the maximum of the world population growth rate was reached in 1970, i.e., about 80 years before the predicted singular time, corresponding to approximately 4% of the studied time interval over which the acceleration is documented. This rounding-off of the finite-time singularity is probably due to a combination of well-known finite-size effects and friction and suggests that we have already entered the transition region to a new regime. As theoretical support, a multivariate analysis coupling population, capital, R&D and technology shows that a dramatic acceleration in the population growth during most of the timespan can occur even though the isolated dynamics do not exhibit it. Possible scenarios for the cross-over and the new regime are discussed.

  1. Population dynamics of a pathogen: the conundrum of vivax malaria.

    PubMed

    McQueen, Philip G

    2010-08-01

    Building a mathematical model of population dynamics of pathogens within their host involves considerations of factors similar to those in ecology, as pathogens can prey on cells in the host. But within the multicellular host, attacked cell types are integrated with other cellular systems, which in turn intervene in the infection. For example, immune responses attempt to sense and then eliminate or contain pathogens, and homeostatic mechanisms try to compensate for cell loss. This review focuses on modeling applied to malarias, diseases caused by single-cell eukaryote parasites that infect red blood cells, with special concern given to vivax malaria, a disease often thought to be benign (if sometimes incapacitating) because the parasite only attacks a small proportion of red blood cells, the very youngest ones. However, I will use mathematical modeling to argue that depletion of this pool of red blood cells can be disastrous to the host if growth of the parasite is not vigorously check by host immune responses. Also, modeling can elucidate aspects of new field observations that indicate that vivax malaria is more dangerous than previously thought. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12551-010-0034-3) contains supplementary material, which is available to authorized users. PMID:20730124

  2. Spatiotemporal dynamics of insect pest population under viral infection.

    PubMed

    Ghosh, Suma; Bhattacharyya, Samit

    2013-07-01

    The interrelationship between pathogen infection and host mobility is of great importance for successful spread of disease in spatial pest population. As spread of infection depends on horizontal transmission of pathogen, there are numerous factors like susceptibility, latent period, host movement that influence overall effectiveness of the control policy. Initiation of new infection cycle depends on density of infected inoculum in the site. So, spatial movement of infected hosts during the course of infection influence the dynamics. Also, infected individuals are more vulnerable to predators and hence production of virus particles in the site depends on predation to some extent. We derive a four dimensional delayed reaction-diffusion model in one spatial dimension and compute the minimum travelling speed of transmission of infection. We show that the minimum speed is sensitive to several parameters of the system. For example, the minimum speed decreases only with increase in delay in lysis process, but otherwise it increases with increase in force of infection, diffusivity of infectives or per capita virus production. A concluding discussion with numerical simulation is presented in the end. PMID:23562890

  3. Fluctuation Relations of Fitness and Information in Population Dynamics

    NASA Astrophysics Data System (ADS)

    Kobayashi, Tetsuya J.; Sughiyama, Yuki

    2015-12-01

    Phenotype switching with and without sensing environment is a common strategy of organisms to survive in a fluctuating environment. Understanding the evolutionary advantages of switching and sensing requires a quantitative evaluation of their fitness gain and its fluctuation together with the conditions for the switching and sensing strategies being adapted to a given environment. In this work, by using a pathwise formulation of the population dynamics, we show that the optimal switching strategy is characterized by a consistency condition for time-forward and backward path probabilities. The formulation also clarifies the underlying information-theoretic aspect of selection as a passive information compression. The loss of fitness by a suboptimal strategy is also shown to satisfy a fluctuation relation, which provides us with the information on how environmental fluctuation impacts the advantages of the optimal strategy. These results are naturally extended to the situation that organisms can use an environmental signal by actively sensing the environment. The fluctuation relations of the fitness gain by sensing are derived in which the multivariate mutual information among the phenotype, the environment, and the signal plays the role to quantify the relevant information in the signal for the fitness gain.

  4. Dynamics and Predictability of Deep Propagating Atmospheric Gravity Waves

    NASA Astrophysics Data System (ADS)

    Doyle, J.; Fritts, D. C.; Smith, R.; Eckermann, S. D.

    2012-12-01

    An overview will be provided of the first field campaign that attempts to follow deeply propagating gravity waves (GWs) from their tropospheric sources to their mesospheric breakdown. The DEEP propagating gravity WAVE experiment over New Zealand (DEEPWAVE-NZ) is a comprehensive, airborne and ground-based measurement and modeling program focused on providing a new understanding of GW dynamics and impacts from the troposphere through the mesosphere and lower thermosphere (MLT). This program will employ the new NSF/NCAR GV (NGV) research aircraft from a base in New Zealand in a 6-week field measurement campaign in June-July 2014. The NGV will be equipped with new lidar and airglow instruments for the DEEPWAVE measurement program, providing temperatures and vertical winds spanning altitudes from immediately above the NGV flight altitude (~13 km) to ~100 km. The region near New Zealand is chosen since all the relevant GW sources occur strongly here, and upper-level winds in austral winter permit GWs to propagate to very high altitudes. Given large-amplitude GWs that propagate routinely into the MLT, the New Zealand region offers an ideal natural laboratory for studying these important GW dynamics and effects impacting weather and climate over a much deeper atmospheric layer than previous campaigns have attempted (0-100 km altitude). The logistics of making measurements in the vicinity of New Zealand are potentially easier than from the Andes and Drake Passage region. A suite of GW-focused modeling and predictability tools will be used to guide NGV flight planning to GW events of greatest scientific significance. These models will also drive scientific interpretation of the GW measurements, together providing answers to the key science questions posed by DEEPWAVE about GW dynamics, morphology, predictability and impacts from 0-100 km. Preliminary results will be presented from high-resolution and adjoint models applied over areas featuring deep wave propagation. The high

  5. Labour-efficient in vitro lymphocyte population tracking and fate prediction using automation and manual review.

    PubMed

    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

  6. Effects of plant genotype and insect dispersal rate on the population dynamics of a forest pest.

    PubMed

    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

  7. Catalysis of protein folding by chaperones accelerates evolutionary dynamics in adapting cell populations.

    PubMed

    Cetinbaş, 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

  8. POPULATION PHARMACOKINETIC/DYNAMIC MODEL OF LYMPHOSUPPRESSION AFTER FLUDARABINE ADMINISTRATION

    PubMed Central

    McCune, Jeannine S.; Vicini, Paolo; Salinger, David H.; O’Donnell, Paul V.; Sandmaier, Brenda M.; Anasetti, Claudio; Mager, Donald E.

    2014-01-01

    Purpose Quantitative relationships between 9-β-D-arabinofuranosyl-2-fluoroadenine (F-ara-A) concentrations and lymphosuppression have not been reported, but would be useful for regimen design. A population pharmacokinetic/pharmacodynamic model was constructed in this study using data from 41 hematopoietic cell transplant (HCT) recipients conditioned with busulfan in combination with fludarabine (total dose 120 mg/m2, Protocol 1519) or with fludarabine (total dose 250 mg/m2) with rabbit antithymocyte globulin (rATG, Protocol 2041). Methods Individual pharmacokinetic parameters were fixed to post-hoc Bayesian estimates, and circulating absolute lymphocyte counts (ALC) were obtained during the three weeks prior to graft infusion. A semi-physiological cell kill model with three lymphocyte transit compartments was applied and aptly characterized the time-course of suppression of circulating ALC by fludarabine administration. Drug and system-specific parameters were estimated using a maximum likelihood expectation maximization algorithm, and the final model was qualified using an internal visual predictive check. Results The final model successfully characterized the time-course and variability in ALC. Pharmacodynamic parameters exhibited considerable between subject variability (38.9-211%). The HCT protocol was the only covariate associated with the pharmacodynamic parameters, specifically the lymphocyte kill rate, the transit rate between lymphocyte compartments, and the baseline ALC. Conclusions This model can be used to simulate the degree of lymphosuppression for design of future fludarabine-based conditioning regimens. PMID:25374408

  9. Individual and population pharmacokinetic compartment analysis: a graphic procedure for quantification of predictive performance

    PubMed Central

    Eksborg, Staffan

    2013-01-01

    Objectives Pharmacokinetic studies are important for optimizing of drug dosing, but requires proper validation of the used pharmacokinetic procedures. However, simple and reliable statistical methods suitable for evaluation of the predictive performance of pharmacokinetic analysis are essentially lacking. The aim of the present study was to construct and evaluate a graphic procedure for quantification of predictive performance of individual and population pharmacokinetic compartment analysis. Methods Original data from previously published pharmacokinetic compartment analyses after intravenous, oral, and epidural administration, and digitized data, obtained from published scatter plots of observed vs predicted drug concentrations from population pharmacokinetic studies using the NPEM algorithm and NONMEM computer program and Bayesian forecasting procedures, were used for estimating the predictive performance according to the proposed graphical method and by the method of Sheiner and Beal. Results The graphical plot proposed in the present paper proved to be a useful tool for evaluation of predictive performance of both individual and population compartment pharmacokinetic analysis. Conclusion The proposed method is simple to use and gives valuable information concerning time- and concentration-dependent inaccuracies that might occur in individual and population pharmacokinetic compartment analysis. Predictive performance can be quantified by the fraction of concentration ratios within arbitrarily specified ranges, e.g. within the range 0.8–1.2.

  10. Evolutionary Game Dynamics in Finite Populations with Strong Selection and Weak Mutation

    PubMed Central

    Fudenberg, Drew; Nowak, Martin A.; Taylor, Christine

    2011-01-01

    We study stochastic game dynamics in finite populations. To this end we extend the classical Moran process to incorporate frequency-dependent selection and mutation. For 2 × 2 games, we give a complete analysis of the long-run behavior when mutation rates are small. For 3 × 3 coordination games, we provide a simple rule to determine which strategy will be selected in large populations. The expected motion in our model resembles the standard replicator dynamics when the population is large, but is qualitatively different when the population is small. Our analysis shows that even in large finite populations the behavior of a replicator-like system can be different from that of the standard replicator dynamics. As an application, we consider selective language dynamics. We determine which language will be spoken in finite large populations. The results have an intuitive interpretation but would not be expected from an analysis of the replicator dynamics. PMID:16987535

  11. Differences in the dynamics and potential production of impounded and unimpounded white sturgeon populations in the lower Columbia River

    SciTech Connect

    Beamesderfer, R.C.P.; Rien, T.A.; Nigro, A.A.

    1995-11-01

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

  12. Satellite Microwave Remote Sensing for Environmental Modeling of Mosquito Population Dynamics.

    PubMed

    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

  13. Satellite Microwave Remote Sensing for Environmental Modeling of Mosquito Population Dynamics

    PubMed Central

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

    2012-01-01

    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

  14. Effects of Lead Exposure, Environmental Conditions, and Metapopulation Processes on Population Dynamics of Spectacled Eiders.

    USGS Publications Warehouse

    Flint, Paul L.; Grand, James B.; Petersen, Margaret; Robert Rockwell

    2016-01-01

    Spectacled eider Somateria fischeri numbers have declined and they are considered threatened in accordance with the US Endangered Species Act throughout their range. We synthesized the available information for spectacled eiders to construct deterministic, stochastic, and metapopulation models for this species that incorporated current estimates of vital rates such as nest success, adult survival, and the impact of lead poisoning on survival. Elasticities of our deterministic models suggested that the populations would respond most dramatically to changes in adult female survival and that the reductions in adult female survival related to lead poisoning were locally important. We also examined the sensitivity of the population to changes in lead exposure rates. With the knowledge that some vital rates vary with environmental conditions, we cast stochastic models that mimicked observed variation in productivity. We also used the stochastic model to examine the probability that a specific population will persist for periods of up to 50 y. Elasticity analysis of these models was consistent with that for the deterministic models, with perturbations to adult female survival having the greatest effect on population projections. When used in single population models, demographic data for some localities predicted rapid declines that were inconsistent with our observations in the field. Thus, we constructed a metapopulation model and examined the predictions for local subpopulations and the metapopulation over a wide range of dispersal rates. Using the metapopulation model, we were able to simulate the observed stability of local subpopulations as well as that of the metapopulation. Finally, we developed a global metapopulation model that simulates periodic winter habitat limitation, similar to that which might be experienced in years of heavy sea ice in the core wintering area of spectacled eiders in the central Bering Sea. Our metapopulation analyses suggested that no

  15. Dynamic interactions between hydrogeological and exposure parameters in daily dose prediction under uncertainty and temporal variability.

    PubMed

    Kumar, Vikas; de Barros, Felipe P J; Schuhmacher, Marta; Fernàndez-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

  16. Sharing reference data and including cows in the reference population improve genomic predictions in Danish Jersey.

    PubMed

    Su, G; Ma, P; Nielsen, U S; Aamand, G P; Wiggans, G; Guldbrandtsen, B; Lund, M S

    2016-06-01

    Small reference populations limit the accuracy of genomic prediction in numerically small breeds, such like Danish Jersey. The objective of this study was to investigate two approaches to improve genomic prediction by increasing size of reference population in Danish Jersey. The first approach was to include North American Jersey bulls in Danish Jersey reference population. The second was to genotype cows and use them as reference animals. The validation of genomic prediction was carried out on bulls and cows, respectively. In validation on bulls, about 300 Danish bulls (depending on traits) born in 2005 and later were used as validation data, and the reference populations were: (1) about 1050 Danish bulls, (2) about 1050 Danish bulls and about 1150 US bulls. In validation on cows, about 3000 Danish cows from 87 young half-sib families were used as validation data, and the reference populations were: (1) about 1250 Danish bulls, (2) about 1250 Danish bulls and about 1150 US bulls, (3) about 1250 Danish bulls and about 4800 cows, (4) about 1250 Danish bulls, 1150 US bulls and 4800 Danish cows. Genomic best linear unbiased prediction model was used to predict breeding values. De-regressed proofs were used as response variables. In the validation on bulls for eight traits, the joint DK-US bull reference population led to higher reliability of genomic prediction than the DK bull reference population for six traits, but not for fertility and longevity. Averaged over the eight traits, the gain was 3 percentage points. In the validation on cows for six traits (fertility and longevity were not available), the gain from inclusion of US bull in reference population was 6.6 percentage points in average over the six traits, and the gain from inclusion of cows was 8.2 percentage points. However, the gains from cows and US bulls were not accumulative. The total gain of including both US bulls and Danish cows was 10.5 percentage points. The results indicate that sharing reference

  17. Methods for evaluating the predictive accuracy of structural dynamic models

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  18. Parsimonious description for predicting high-dimensional dynamics

    PubMed Central

    Hirata, Yoshito; Takeuchi, Tomoya; Horai, Shunsuke; Suzuki, Hideyuki; Aihara, Kazuyuki

    2015-01-01

    When we observe a system, we often cannot observe all its variables and may have some of its limited measurements. Under such a circumstance, delay coordinates, vectors made of successive measurements, are useful to reconstruct the states of the whole system. Although the method of delay coordinates is theoretically supported for high-dimensional dynamical systems, practically there is a limitation because the calculation for higher-dimensional delay coordinates becomes more expensive. Here, we propose a parsimonious description of virtually infinite-dimensional delay coordinates by evaluating their distances with exponentially decaying weights. This description enables us to predict the future values of the measurements faster because we can reuse the calculated distances, and more accurately because the description naturally reduces the bias of the classical delay coordinates toward the stable directions. We demonstrate the proposed method with toy models of the atmosphere and real datasets related to renewable energy. PMID:26510518

  19. Nonlinear Dynamic Inversion Baseline Control Law: Architecture and Performance Predictions

    NASA Technical Reports Server (NTRS)

    Miller, Christopher J.

    2011-01-01

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

  20. Prediction of dynamic blade loading of the Francis-99 turbine

    NASA Astrophysics Data System (ADS)

    Nicolle, J.; Cupillard, S.

    2015-01-01

    CFD simulations focusing on capturing dynamic fluctuations of the flow for three operating points were performed for a scale model of a high head Francis turbine. A mesh sensitivity study showed an influence of the near wall resolution, consequently a low Reynolds mesh with a SST turbulence model was used. Rotor/stator fluctuations are well reproduced with the full turbine simulation at all operating points. Velocity contours and average velocity profiles from LDV measurements in the draft tube confirm that the flow physics is generally well reproduced. Simplified approaches such as profile transform and Fourier transform underestimated the measured fluctuations. As full turbine simulations were time-consuming, a simulation with only the draft tube was performed at part load to predict the fluctuations in the draft tube cone. The SAS-SST turbulence model was able to capture the vortex rope behavior.

  1. Dynamical recurrent neural networks--towards environmental time series prediction.

    PubMed

    Aussem, A; Murtagh, F; Sarazin, M

    1995-06-01

    Dynamical Recurrent Neural Networks (DRNN) (Aussem 1995a) are a class of fully recurrent networks obtained by modeling synapses as autoregressive filters. By virtue of their internal dynamic, these networks approximate the underlying law governing the time series by a system of nonlinear difference equations of internal variables. They therefore provide history-sensitive forecasts without having to be explicitly fed with external memory. The model is trained by a local and recursive error propagation algorithm called temporal-recurrent-backpropagation. The efficiency of the procedure benefits from the exponential decay of the gradient terms backpropagated through the adjoint network. We assess the predictive ability of the DRNN model with meterological and astronomical time series recorded around the candidate observation sites for the future VLT telescope. The hope is that reliable environmental forecasts provided with the model will allow the modern telescopes to be preset, a few hours in advance, in the most suited instrumental mode. In this perspective, the model is first appraised on precipitation measurements with traditional nonlinear AR and ARMA techniques using feedforward networks. Then we tackle a complex problem, namely the prediction of astronomical seeing, known to be a very erratic time series. A fuzzy coding approach is used to reduce the complexity of the underlying laws governing the seeing. Then, a fuzzy correspondence analysis is carried out to explore the internal relationships in the data. Based on a carefully selected set of meteorological variables at the same time-point, a nonlinear multiple regression, termed nowcasting (Murtagh et al. 1993, 1995), is carried out on the fuzzily coded seeing records. The DRNN is shown to outperform the fuzzy k-nearest neighbors method. PMID:7496587

  2. Ongoing dynamics in large-scale functional connectivity predict perception

    PubMed Central

    Sadaghiani, Sepideh; Poline, Jean-Baptiste; Kleinschmidt, Andreas; D’Esposito, Mark

    2015-01-01

    Most brain activity occurs in an ongoing manner not directly locked to external events or stimuli. Regional ongoing activity fluctuates in unison with some brain regions but not others, and the degree of long-range coupling is called functional connectivity, often measured with correlation. Strength and spatial distributions of functional connectivity dynamically change in an ongoing manner over seconds to minutes, even when the external environment is held constant. Direct evidence for any behavioral relevance of these continuous large-scale dynamics has been limited. Here, we investigated whether ongoing changes in baseline functional connectivity correlate with perception. In a continuous auditory detection task, participants perceived the target sound in roughly one-half of the trials. Very long (22–40 s) interstimulus intervals permitted investigation of baseline connectivity unaffected by preceding evoked responses. Using multivariate classification, we observed that functional connectivity before the target predicted whether it was heard or missed. Using graph theoretical measures, we characterized the difference in functional connectivity between states that lead to hits vs. misses. Before misses compared with hits and task-free rest, connectivity showed reduced modularity, a measure of integrity of modular network structure. This effect was strongest in the default mode and visual networks and caused by both reduced within-network connectivity and enhanced across-network connections before misses. The relation of behavior to prestimulus connectivity was dissociable from that of prestimulus activity amplitudes. In conclusion, moment to moment dynamic changes in baseline functional connectivity may shape subsequent behavioral performance. A highly modular network structure seems beneficial to perceptual efficiency. PMID:26106164

  3. The more the merrier? How a few SNPs predict pigmentation phenotypes in the Northern German population.

    PubMed

    Caliebe, Amke; Harder, Melanie; Schuett, Rebecca; Krawczak, Michael; Nebel, Almut; von Wurmb-Schwark, Nicole

    2016-05-01

    Human pigmentation traits are of great interest to many research areas, from ancient DNA analysis to forensic science. We developed a gene-based predictive model for pigmentation phenotypes in a realistic target population for forensic case work from Northern Germany and compared our model with those brought forth by previous studies of genetically more heterogeneous populations. In doing so, we aimed at answering the following research questions: (1) do existing models allow good prediction of high-quality phenotypes in a genetically similar albeit more homogeneous population? (2) Would a model specifically set up for the more homogeneous population perform notably better than existing models? (3) Can the number of markers included in existing models be reduced without compromising their predictive capability in the more homogenous population? We investigated the association between eye, hair and skin colour and 12 candidate single-nucleotide polymorphisms (SNPs) from six genes. Our study comprised two samples of 300 and 100 individuals from Northern Germany. SNP rs12913832 in HERC2 was found to be strongly associated with blue eye colour (odds ratio=40.0, P<1.2 × 10(-4)) and to yield moderate predictive power (AUC: 77%; sensitivity: 90%, specificity: 63%, both at a 0.5 threshold for blue eye colour probability). SNP associations with hair and skin colour were weaker and genotypes less predictive. A comparison with two recently published sets of markers to predict eye and hair colour revealed that the consideration of additional SNPs with weak-to-moderate effect increased the predictive power for eye colour, but not for hair colour. PMID:26286644

  4. Association of Climatic Variability, Vector Population and Malarial Disease in District of Visakhapatnam, India: A Modeling and Prediction Analysis

    PubMed Central

    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

  5. The Dynamics of Nestedness Predicts the Evolution of Industrial Ecosystems

    PubMed Central

    Bustos, Sebastián; Gomez, Charles; Hausmann, Ricardo; Hidalgo, César A.

    2012-01-01

    In economic systems, the mix of products that countries make or export has been shown to be a strong leading indicator of economic growth. Hence, methods to characterize and predict the structure of the network connecting countries to the products that they export are relevant for understanding the dynamics of economic development. Here we study the presence and absence of industries in international and domestic economies and show that these networks are significantly nested. This means that the less filled rows and columns of these networks' adjacency matrices tend to be subsets of the fuller rows and columns. Moreover, we show that their nestedness remains constant over time and that it is sustained by both, a bias for industries that deviate from the networks' nestedness to disappear, and a bias for the industries that are missing according to nestedness to appear. This makes the appearance and disappearance of individual industries in each location predictable. We interpret the high level of nestedness observed in these networks in the context of the neutral model of development introduced by Hidalgo and Hausmann (2009). We show that the model can reproduce the high level of nestedness observed in these networks only when we assume a high level of heterogeneity in the distribution of capabilities available in countries and required by products. In the context of the neutral model, this implies that the high level of nestedness observed in these economic networks emerges as a combination of both, the complementarity of inputs and heterogeneity in the number of capabilities available in countries and required by products. The stability of nestedness in industrial ecosystems, and the predictability implied by it, demonstrates the importance of the study of network properties in the evolution of economic networks. PMID:23185326

  6. Phylogenetic prediction of the maximum per capita rate of population growth

    PubMed Central

    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

  7. Behavioural models of population growth rates: implications for conservation and prediction.

    PubMed Central

    Sutherland, William J; Norris, Ken

    2002-01-01

    Conservation biologists often wish to predict how vertebrate populations will respond to local or global changes in conditions such as those resulting from sea-level rise, deforestation, exploitation, genetically modified crops, global warming, human disturbance or from conservation activities. Predicting the consequences of such changes almost always requires understanding the population growth rate and the density dependence. Traditional means of directly measuring density dependence are often extremely difficult and have the problem that if the environment changes then it is necessary to remeasure the density dependence. We describe an alternative approach that does not require such long datasets and can be used to predict the density dependence under novel conditions. Game theory can be used to describe behavioural decisions that individuals make in response to interference, prey depletion, territorial behaviour or social dominance, and the resultant fitness consequences. It is then possible to predict how survival or reproductive output changes with population size. From this we can then make predictions about the responses of populations to environmental changes. We will illustrate how this can be applied to a range of species and a range of applied problems. PMID:12396518

  8. Discrete Molecular Dynamics Can Predict Helical Prestructured Motifs in Disordered Proteins

    PubMed Central

    Han, Kyou-Hoon; Dokholyan, Nikolay V.; Tompa, Péter; Kalmár, Lajos; Hegedűs, Tamás

    2014-01-01

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

  9. DYNAMICS OF NEMATODE POPULATIONS IN CACAO GROWN UNDER TRADIONALLY SYSTEM OF MANAGEMENT IN PERUVIAN AMAZON

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Nature of crops and management systems greatly influences population dynamics of parasitic and nonparasitic nematodes in soil. An experiment was undertaken at Tropical Crop Research institute (ICT), Tarapoto, Peru to assess the population dynamics of nematodes in a Cocoa (Theobroma cacao L.)-Banana ...

  10. Environmental controls, oceanography and population dynamics of pathogens and harmful algal blooms: connecting sources to human exposure

    PubMed Central

    Dyble, Julianne; Bienfang, Paul; Dusek, Eva; Hitchcock, Gary; Holland, Fred; Laws, Ed; Lerczak, James; McGillicuddy, Dennis J; Minnett, Peter; Moore, Stephanie K; O'Kelly, Charles; Solo-Gabriele, Helena; Wang, John D

    2008-01-01

    Coupled physical-biological models are capable of linking the complex interactions between environmental factors and physical hydrodynamics to simulate the growth, toxicity and transport of infectious pathogens and harmful algal blooms (HABs). Such simulations can be used to assess and predict the impact of pathogens and HABs on human health. Given the widespread and increasing reliance of coastal communities on aquatic systems for drinking water, seafood and recreation, such predictions are critical for making informed resource management decisions. Here we identify three challenges to making this connection between pathogens/HABs and human health: predicting concentrations and toxicity; identifying the spatial and temporal scales of population and ecosystem interactions; and applying the understanding of population dynamics of pathogens/HABs to management strategies. We elaborate on the need to meet each of these challenges, describe how modeling approaches can be used and discuss strategies for moving forward in addressing these challenges. PMID:19025676

  11. Inverse modeling of pesticide degradation and pesticide-degrading population size dynamics in a bioremediation system: parameterizing the Monod model.

    PubMed

    Sniegowski, Kristel; Mertens, Jan; Diels, Jan; Smolders, Erik; Springael, Dirk

    2009-05-01

    Pesticide degradation models are compared which simulate the response of biofilters for treatment of pesticide-contaminated waste water to time-irregular pesticide supply in which the pesticide is used for growth and mineralized. Biofilter microcosms containing a mixture of straw, peat and soil and harboring micropopulations which uses the herbicide linuron for growth, were irrigated with linuron for 28 weeks with a stop in its supply between week 12 and 17. Matrix samples were regularly taken to assay linuron mineralization. A first-order approximation of the Monod model was used to simulate the observed mineralization data, while an inverse modeling framework combining a sensitivity analysis (Morris Sensitivity Analysis) with an inverse modeling approach (Shuffled Complex Evolution Metropolis) adopted to parameterize the model. Lag times in linuron mineralization decreased during the initial weeks of linuron irrigation but increased after supply of linuron ceased. The model well-simulated the lag time dynamics which were related to the dynamics of the predicted linuron-degrading population size in the microcosms. It was predicted that the population size decreased at a rate of 0.031 d(-1) after pesticide supply ceased to reach its initial population size after 25 weeks. We conclude that modeling pesticide degradation in biofilters should incorporate biomass dynamics in case the pesticide is used as C-source. First-order approaches without incorporating biomass dynamics could lead to underestimation of the risk of pesticide leaching. PMID:19232428

  12. Rabies disease dynamics in naïve dog populations in Australia.

    PubMed

    Sparkes, Jessica; McLeod, Steven; Ballard, Guy; Fleming, Peter J S; Körtner, Gerhard; Brown, Wendy Y

    2016-09-01

    Currently, Australia is free from terrestrial rabies but an incursion from nearby Indonesia, where the virus is endemic, is a feasible threat. Here, we aimed to determine whether the response to a simulated rabies incursion would vary between three extant Australian dog populations; free-roaming domestic dogs from a remote indigenous community in northern Australia, and free-roaming domestic and wild dogs in peri-urban areas of north-east New South Wales. We further sought to predict how different management strategies impacted disease dynamics in these populations. We used simple stochastic state-transition models and dog demographic and contact rate data from the three dog populations to simulate rabies spread, and used global and local sensitivity analyses to determine effects of model parameters. To identify the most effective control options, dog removal and vaccination strategies were also simulated. Responses to simulated rabies incursions varied between the dog populations. Free-roaming domestic dogs from north-east New South Wales exhibited the lowest risk for rabies maintenance and spread. Due to low containment and high contact rates, rabies progressed rapidly through free-roaming dogs from the remote indigenous community in northern Australia. In contrast, rabies remained at relatively low levels within the north-east New South Wales wild dog population for over a year prior to an epidemic. Across all scenarios, sensitivity analyses revealed that contact rates and the probability of transmission were the most important drivers of the number of infectious individuals within a population. The number of infectious individuals was less sensitive to birth and death rates. Removal of dogs as a control strategy was not effective for any population modelled, while vaccination rates in excess of 70% of the population resulted in significant reductions in disease progression. The variability in response between these distinct dog groups to a rabies incursion

  13. Population dynamics of a Salmonella lytic phage and its host: implications of the host bacterial growth rate in modelling.

    PubMed

    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

  14. Population Dynamics of a Salmonella Lytic Phage and Its Host: Implications of the Host Bacterial Growth Rate in Modelling

    PubMed Central

    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

  15. Evolution of virulence driven by predator-prey interaction: Possible consequences for population dynamics.

    PubMed

    Morozov, A Yu; Adamson, M W

    2011-05-01

    The evolution of pathogen virulence in natural populations has conventionally been considered as a result of selection caused by the interactions of the host with its pathogen(s). The host population, however, is generally embedded in complex trophic interactions with other populations in the community, in particular, intensive predation on the infected host can increase its mortality, and this can affect the course of virulence evolution. Reciprocally, in the long run, the evolution of virulence within an infected host can affect the patterns of population dynamics of a predator consuming the host (e.g. resulting in large amplitude oscillations, causing a severe drop in the population size, etc.). Surprisingly, neither the effect of predation on the evolution of virulence within a host, nor the influence of the evolution of virulence upon the consumer's dynamics has been addressed in the literature yet. In this paper, we consider a classical S-I ecoepidemiological model in which the infected host is consumed by a predator. We are particularly interested in the evolutionarily stable virulence of the pathogen in the model and its dependence upon ecologically relevant parameters. We show that predation can prominently shift the evolutionarily stable virulence towards more severe strains as compared to the same system without predation. We demonstrate that the evolution of virulence can result in a succession of dynamical regimes and can even lead to the extinction of the predator in the long run. The presence of a predator can indirectly affect the evolution within its prey since the evolutionarily stable virulence becomes a function of the prey growth rate, which would not be the case in a predator-free system. We find that the evolutionarily stable virulence largely depends on the carrying capacity K of the prey in a non-monotonous way. The model also predicts that in an eutrophic environment the shift of virulence towards evolutionarily stable benign strains can

  16. Dynamics of coastal cod populations: intra- and intercohort density dependence and stochastic processes

    PubMed Central

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

    1999-01-01

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

  17. Quantifying seasonal population fluxes driving rubella transmission dynamics using mobile phone data.

    PubMed

    Wesolowski, Amy; Metcalf, C J E; Eagle, Nathan; Kombich, Janeth; Grenfell, Bryan T; Bjørnstad, Ottar N; Lessler, Justin; Tatem, Andrew J; Buckee, Caroline O

    2015-09-01

    Changing patterns of human aggregation are thought to drive annual and multiannual outbreaks of infectious diseases, but the paucity of data about travel behavior and population flux over time has made this idea difficult to test quantitatively. Current measures of human mobility, especially in low-income settings, are often static, relying on approximate travel times, road networks, or cross-sectional surveys. Mobile phone data provide a unique source of information about human travel, but the power of these data to describe epidemiologically relevant changes in population density remains unclear. Here we quantify seasonal travel patterns using mobile phone data from nearly 15 million anonymous subscribers in Kenya. Using a rich data source of rubella incidence, we show that patterns of population travel (fluxes) inferred from mobile phone data are predictive of disease transmission and improve significantly on standard school term time and weather covariates. Further, combining seasonal and spatial data on travel from mobile phone data allows us to characterize seasonal fluctuations in risk across Kenya and produce dynamic importation risk maps for rubella. Mobile phone data therefore offer a valuable previously unidentified source of data for measuring key drivers of seasonal epidemics. PMID:26283349

  18. Effects of Nano-Titanium Dioxide on Freshwater Algal Population Dynamics

    PubMed Central

    Kulacki, Konrad J.; Cardinale, Bradley J.

    2012-01-01

    To make predictions about the possible effects of nanomaterials across environments and taxa, toxicity testing must incorporate not only a variety of organisms and endpoints, but also an understanding of the mechanisms that underlie nanoparticle toxicity. Here, we report the results of a laboratory experiment in which we examined how titanium dioxide nanoparticles impact the population dynamics and production of biomass across a range of freshwater algae. We exposed 10 of the most common species of North American freshwater pelagic algae (phytoplankton) to five increasing concentrations of n-TiO2 (ranging from controls to 300 mg n-TiO2 L−1). We then examined the effects of n-TiO2 on the population growth rates and biomass production of each algal species over a period of 25 days. On average, increasing concentrations of n-TiO2 had no significant effects on algal growth rates (p = 0.376), even though there was considerable species-specific variation in responses. In contrast, exposure to n-TiO2 tended to increase maximum biomass achieved by species in culture (p = 0.06). Results suggest that titanium dioxide nanoparticles could influence certain aspects of population growth of freshwater phytoplankton, though effects are unlikely at environmentally relevant concentrations. PMID:23071735

  19. Quantifying seasonal population fluxes driving rubella transmission dynamics using mobile phone data

    PubMed Central

    Wesolowski, Amy; Metcalf, C. J. E.; Eagle, Nathan; Kombich, Janeth; Grenfell, Bryan T.; Bjørnstad, Ottar N.; Lessler, Justin; Tatem, Andrew J.; Buckee, Caroline O.

    2015-01-01

    Changing patterns of human aggregation are thought to drive annual and multiannual outbreaks of infectious diseases, but the paucity of data about travel behavior and population flux over time has made this idea difficult to test quantitatively. Current measures of human mobility, especially in low-income settings, are often static, relying on approximate travel times, road networks, or cross-sectional surveys. Mobile phone data provide a unique source of information about human travel, but the power of these data to describe epidemiologically relevant changes in population density remains unclear. Here we quantify seasonal travel patterns using mobile phone data from nearly 15 million anonymous subscribers in Kenya. Using a rich data source of rubella incidence, we show that patterns of population travel (fluxes) inferred from mobile phone data are predictive of disease transmission and improve significantly on standard school term time and weather covariates. Further, combining seasonal and spatial data on travel from mobile phone data allows us to characterize seasonal fluctuations in risk across Kenya and produce dynamic importation risk maps for rubella. Mobile phone data therefore offer a valuable previously unidentified source of data for measuring key drivers of seasonal epidemics. PMID:26283349

  20. Seasonal Synechococcus and Thaumarchaeal population dynamics examined with high resolution with remote in situ instrumentation

    PubMed Central

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

    2012-01-01

    Monterey Bay, CA is an Eastern boundary upwelling system that is nitrogen limited much of the year. In order to resolve population dynamics of microorganisms important for nutrient cycling in this region, we deployed the Environmental Sample Processor with quantitative PCR assays targeting both ribosomal RNA genes and functional genes for subclades of cyanobacteria (Synechococcus) and ammonia-oxidizing Archaea (Thaumarchaeota) populations. Results showed a strong correlation between Thaumarchaea abundances and nitrate during the spring upwelling but not the fall sampling period. In relatively stratified fall waters, the Thaumarchaeota community reached higher numbers than in the spring, and an unexpected positive correlation with chlorophyll concentration was observed. Further, we detected drops in Synechococcus abundance that occurred on short (that is, daily) time scales. Upwelling intensity and blooms of eukaryotic phytoplankton strongly influenced Synechococcus distributions in the spring and fall, revealing what appear to be the environmental limitations of Synechococcus populations in this region. Each of these findings has implications for Monterey Bay biogeochemistry. High-resolution sampling provides a better-resolved framework within which to observe changes in the plankton community. We conclude that controls on these ecosystems change on smaller scales than are routinely assessed, and that more predictable trends will be uncovered if they are evaluated within seasonal (monthly), rather than on annual or interannual scales. PMID:21975596

  1. Motional timescale predictions by molecular dynamics simulations: Case study using proline and hydroxyproline sidechain dynamics

    PubMed Central

    Aliev, Abil E; Kulke, Martin; Khaneja, Harmeet S; Chudasama, Vijay; Sheppard, Tom D; Lanigan, Rachel M

    2014-01-01

    We propose a new approach for force field optimizations which aims at reproducing dynamics characteristics using biomolecular MD simulations, in addition to improved prediction of motionally averaged structural properties available from experiment. As the source of experimental data for dynamics fittings, we use 13C NMR spin-lattice relaxation times T1 of backbone and sidechain carbons, which allow to determine correlation times of both overall molecular and intramolecular motions. For structural fittings, we use motionally averaged experimental values of NMR J couplings. The proline residue and its derivative 4-hydroxyproline with relatively simple cyclic structure and sidechain dynamics were chosen for the assessment of the new approach in this work. Initially, grid search and simplexed MD simulations identified large number of parameter sets which fit equally well experimental J couplings. Using the Arrhenius-type relationship between the force constant and the correlation time, the available MD data for a series of parameter sets were analyzed to predict the value of the force constant that best reproduces experimental timescale of the sidechain dynamics. Verification of the new force-field (termed as AMBER99SB-ILDNP) against NMR J couplings and correlation times showed consistent and significant improvements compared to the original force field in reproducing both structural and dynamics properties. The results suggest that matching experimental timescales of motions together with motionally averaged characteristics is the valid approach for force field parameter optimization. Such a comprehensive approach is not restricted to cyclic residues and can be extended to other amino acid residues, as well as to the backbone. Proteins 2014; 82:195–215. © 2013 Wiley Periodicals, Inc. PMID:23818175

  2. A new ODE tumor growth modeling based on tumor population dynamics

    SciTech Connect

    Oroji, Amin; Omar, Mohd bin; Yarahmadian, Shantia

    2015-10-22

    In this paper a new mathematical model for the population of tumor growth treated by radiation is proposed. The cells dynamics population in each state and the dynamics of whole tumor population are studied. Furthermore, a new definition of tumor lifespan is presented. Finally, the effects of two main parameters, treatment parameter (q), and repair mechanism parameter (r) on tumor lifespan are probed, and it is showed that the change in treatment parameter (q) highly affects the tumor lifespan.

  3. [Nonlinear effects on population dynamics related to age structure and fishery impact].

    PubMed

    Frisman, E Ia; Last, E V

    2005-01-01

    Population dynamics of commercial fish populations with an age structure was studied by the example of salmons. The relationship between the amount of catch on fishing efforts and total abundance of a stock fished is described by a nonlinear "trophic" function. Special attention is given to the analysis of population dynamics stability under conditions for maximum profit. Simulation results are compared to statistical data on the catch of Pacific salmon species in the Bering Sea. PMID:16240747

  4. A new ODE tumor growth modeling based on tumor population dynamics

    NASA Astrophysics Data System (ADS)

    Oroji, Amin; Omar, Mohd bin; Yarahmadian, Shantia

    2015-10-01

    In this paper a new mathematical model for the population of tumor growth treated by radiation is proposed. The cells dynamics population in each state and the dynamics of whole tumor population are studied. Furthermore, a new definition of tumor lifespan is presented. Finally, the effects of two main parameters, treatment parameter (q), and repair mechanism parameter (r) on tumor lifespan are probed, and it is showed that the change in treatment parameter (q) highly affects the tumor lifespan.

  5. Deciphering DNA replication dynamics in eukaryotic cell populations in relation with their averaged chromatin conformations

    PubMed Central

    Goldar, A.; Arneodo, A.; Audit, B.; Argoul, F.; Rappailles, A.; Guilbaud, G.; Petryk, N.; Kahli, M.; Hyrien, O.

    2016-01-01

    We propose a non-local model of DNA replication that takes into account the observed uncertainty on the position and time of replication initiation in eukaryote cell populations. By picturing replication initiation as a two-state system and considering all possible transition configurations, and by taking into account the chromatin’s fractal dimension, we derive an analytical expression for the rate of replication initiation. This model predicts with no free parameter the temporal profiles of initiation rate, replication fork density and fraction of replicated DNA, in quantitative agreement with corresponding experimental data from both S. cerevisiae and human cells and provides a quantitative estimate of initiation site redundancy. This study shows that, to a large extent, the program that regulates the dynamics of eukaryotic DNA replication is a collective phenomenon that emerges from the stochastic nature of replication origins initiation. PMID:26935043

  6. Deciphering DNA replication dynamics in eukaryotic cell populations in relation with their averaged chromatin conformations

    NASA Astrophysics Data System (ADS)

    Goldar, A.; Arneodo, A.; Audit, B.; Argoul, F.; Rappailles, A.; Guilbaud, G.; Petryk, N.; Kahli, M.; Hyrien, O.

    2016-03-01

    We propose a non-local model of DNA replication that takes into account the observed uncertainty on the position and time of replication initiation in eukaryote cell populations. By picturing replication initiation as a two-state system and considering all possible transition configurations, and by taking into account the chromatin’s fractal dimension, we derive an analytical expression for the rate of replication initiation. This model predicts with no free parameter the temporal profiles of initiation rate, replication fork density and fraction of replicated DNA, in quantitative agreement with corresponding experimental data from both S. cerevisiae and human cells and provides a quantitative estimate of initiation site redundancy. This study shows that, to a large extent, the program that regulates the dynamics of eukaryotic DNA replication is a collective phenomenon that emerges from the stochastic nature of replication origins initiation.

  7. The influence of climatic variability on local population dynamics of Cercidium microphyllum (foothill paloverde)

    USGS Publications Warehouse

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

    2002-01-01

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

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

    PubMed Central

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

    1996-01-01

    Population sizes of two ice nucleation-active strains of Pseudomonas syringae were compared on leaves in controlled environments and in the field to determine the ability of microcosm studies to predict plant habitat preferences in the field. The P. syringae strains investigated were the parental strains of recombinant deletion mutant strains deficient in ice nucleation activity that had been field tested for their ability to control plant frost injury. The population size of the P. syringae strains was measured after inoculation at three field locations on up to 40 of the same plant species that were studied in the growth chamber. There was seldom a significant relationship between the mean population size of a given P. syringae strain incubated under either wet or dry conditions in microcosms and the mean population size which could be recovered from the same species when inoculated in the field. Specifically, on some plant species, the population size recovered from leaves in the field was substantially greater than from that species in a controlled environment, while for other plant species field populations were significantly smaller than those observed under controlled conditions. Population sizes of inoculated P. syringae strains, however, were frequently highly positively correlated with the indigenous bacterial population size on the same plant species in the field, suggesting that the ability of a particular plant species to support introduced bacterial strains is correlated with its ability to support large bacterial populations or that indigenous bacteria enhance the survival of introduced strains. Microcosm studies therefore seem most effective at assessing possible differences between parental and recombinant strains under a given environmental regime but are limited in their ability to predict the specific population sizes or plant habitat preferences of bacteria on leaves under field conditions. PMID:16535405

  9. Data Driven Approach for High Resolution Population Distribution and Dynamics Models

    SciTech Connect

    Bhaduri, Budhendra L; Bright, Eddie A; Rose, Amy N; Liu, Cheng; Urban, Marie L; Stewart, Robert N

    2014-01-01

    High resolution population distribution data are vital for successfully addressing critical issues ranging from energy and socio-environmental research to public health to human security. Commonly available population data from Census is constrained both in space and time and does not capture population dynamics as functions of space and time. This imposes a significant limitation on the fidelity of event-based simulation models with sensitive space-time resolution. This paper describes ongoing development of high-resolution population distribution and dynamics models, at Oak Ridge National Laboratory, through spatial data integration and modeling with behavioral or activity-based mobility datasets for representing temporal dynamics of population. The model is resolved at 1 km resolution globally and describes the U.S. population for nighttime and daytime at 90m. Integration of such population data provides the opportunity to develop simulations and applications in critical infrastructure management from local to global scales.

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

    PubMed

    Franzén, Markus; Nilsson, Sven G

    2013-06-01

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

  11. Population dynamics of the estuarine isopod Sphaeroma rugicauda

    NASA Astrophysics Data System (ADS)

    Heath, David J.; Khazaeli, Aziz A.

    1985-01-01

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

  12. Intraspecific Competition and Population Dynamics of Aedes aegypti

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  13. Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates

    PubMed Central

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

    2014-01-01

    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

  14. Synconset waves and chains: spiking onsets in synchronous populations predict and are predicted by network structure.

    PubMed

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

    2013-01-01

    framework to several aspects of network physiology including cell assemblies, population codes, and oscillatory synchrony. PMID:24116018

  15. POPULATION EXPOSURES TO PARTICULATE MATTER: A COMPARISON OF EXPOSURE MODEL PREDICTIONS AND MEASUREMENT DATA

    EPA Science Inventory

    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 ...

  16. Population Mean Scores Predict Child Mental Disorder Rates: Validating SDQ Prevalence Estimators in Britain

    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…

  17. Prediction of lung function response for populations exposed to a wide range of ozone conditions

    EPA Science Inventory

    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...

  18. 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