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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.

  2. Reproductive success is predicted by social dynamics and kinship in managed animal populations

    PubMed Central

    Newman, Saul J.; Eyre, Simon; Kimble, Catherine H.; Arcos-Burgos, Mauricio; Hogg, Carolyn; Easteal, Simon

    2016-01-01

    Kin and group interactions are important determinants of reproductive success in many species. Their optimization could, therefore, potentially improve the productivity and breeding success of managed populations used for agricultural and conservation purposes. Here we demonstrate this potential using a novel approach to measure and predict the effect of kin and group dynamics on reproductive output in a well-known species, the meerkat Suricata suricatta. Variation in social dynamics predicts 30% of the individual variation in reproductive success of this species in managed populations, and accurately forecasts reproductive output at least two years into the future. Optimization of social dynamics in captive meerkat populations doubles their projected reproductive output. These results demonstrate the utility of a quantitative approach to breeding programs informed by social and kinship dynamics. They suggest that this approach has great potential for improvements in the management of social endangered and agricultural species. PMID:27990255

  3. Reproductive success is predicted by social dynamics and kinship in managed animal populations.

    PubMed

    Newman, Saul J; Eyre, Simon; Kimble, Catherine H; Arcos-Burgos, Mauricio; Hogg, Carolyn; Easteal, Simon

    2016-01-01

    Kin and group interactions are important determinants of reproductive success in many species. Their optimization could, therefore, potentially improve the productivity and breeding success of managed populations used for agricultural and conservation purposes. Here we demonstrate this potential using a novel approach to measure and predict the effect of kin and group dynamics on reproductive output in a well-known species, the meerkat Suricata suricatta. Variation in social dynamics predicts 30% of the individual variation in reproductive success of this species in managed populations, and accurately forecasts reproductive output at least two years into the future. Optimization of social dynamics in captive meerkat populations doubles their projected reproductive output. These results demonstrate the utility of a quantitative approach to breeding programs informed by social and kinship dynamics. They suggest that this approach has great potential for improvements in the management of social endangered and agricultural species.

  4. Linking traits to energetics and population dynamics to predict lizard ranges in changing environments.

    PubMed

    Buckley, Lauren B

    2008-01-01

    I present a dynamic bioenergetic model that couples individual energetics and population dynamics to predict current lizard ranges and those following climate warming. The model predictions are uniquely based on first principles of morphology, life history, and thermal physiology. I apply the model to five populations of a widespread North American lizard, Sceloporus undulatus, to examine how geographic variation in traits and life histories influences ranges. This geographic variation reflects the potential for species to adapt to environmental change. I then consider the range dynamics of the closely related Sceloporus graciosus. Comparing predicted ranges and actual current ranges reveals how dispersal limitations, species interactions, and habitat requirements influence the occupied portions of thermally suitable ranges. The dynamic model predicts individualistic responses to a uniform 3 degrees C warming but a northward shift in the northern range boundary for all populations and species. In contrast to standard correlative climate envelope models, the extent of the predicted northward shift depends on organism traits and life histories. The results highlight the limitations of correlative models and the need for more dynamic models of species' ranges.

  5. 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

  6. 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.

  7. 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.

  8. 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

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

    PubMed

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

    2015-04-01

    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.

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

    PubMed Central

    2013-01-01

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

  11. 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

  12. 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.

  13. 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)

  14. 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.

  15. EVALUATION OF THE EFFICACY OF EXTRAPOLATION POPULATION MODELING TO PREDICT THE DYNAMICS OF AMERICAMYSIS BAHIA POPULATIONS IN THE LABORATORY

    EPA Science Inventory

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

  16. Horn fly population dynamics as prediction tool for the fixation of pesticide resistance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This research project was conducted to establish the population dynamics of the horn fly. Two cattle herds were monitored to establish if contrasting climatic regional conditions, in addition to temperature and precipitation, related to the number of rainy days as a factor influencing horn fly infes...

  17. 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

  18. 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.

  19. High predictability of the seasonal dynamics of a species-like Polynucleobacter population in a freshwater lake.

    PubMed

    Wu, Qinglong L; Hahn, Martin W

    2006-09-01

    One of the key questions in microbial ecology is if seasonal patterns of bacterial community composition (BCC) observed in one year repeat in the following years. We have investigated if the recorded annual dynamics of a species-like Polynucleobacter (subcluster PnecB) population allowed the prediction of the population dynamics in another year. The abundance of PnecB bacteria in the pelagic of temperate Lake Mondsee was investigated by fluorescence in situ hybridization (FISH) over three consecutive years. The PnecB bacteria formed a persistent population, and were present in the entire water body of the lake. Two of the three investigated years differed strongly in summer temperatures and precipitation, which resulted in markedly different growth conditions. But despite of these different environmental conditions, the PnecB population demonstrated remarkably similar seasonal dynamics in the three investigated years. Water temperature was the best predictor of the population dynamics during the first half of the annual cycles. Statistical analysis also indicated influences of phytoplankton and metazooplankton successions on the PnecB population dynamics. Furthermore, 65 lakes and ponds were investigated for the presence of PnecB bacteria. They were detected in the majority (78%) of circum-neutral and alkaline freshwater habitats, but not in any investigated acidic or saline habitat.

  20. 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.

  1. 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.

  2. Predicting prey population dynamics from kill rate, predation rate and predator-prey ratios in three wolf-ungulate systems.

    PubMed

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

    2011-11-01

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

  3. Using Dynamical Models to Predict the Terrestrial-Mass Free-Floating Planet Population

    NASA Astrophysics Data System (ADS)

    Barclay, Thomas; Quintana, Elisa V.

    2016-10-01

    In the classical picture of planet formation, planets form within circumstellar disks as a product of star formation. The material in the disk either forms into a planet, remains bound to the star, falls into the star, or is ejected from the system. We explore the properties of this ejected material using N-body simulations of the late stages of terrestrial planet formation. We find that in planetary systems like ours (with Jupiter and Saturn) about half the ejected material is in bodies less massive than the Moon and half is in bodies more massive than Mars. No planets more massive than half an Earth-mass, however, were ejected, primarily because most of the ejections occur before the timescales needed to grow an Earth-mass body. Without giant planets present in the system, very little material is ever ejected. We predict that future space-borne microlensing searches for free-floating terrestrial-mass planets, such as WFIRST, will discover large numbers of Mars-mass planets but will not make significant detections of Earth-mass planets.

  4. 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

  5. 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%.

  6. 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.

  7. 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

  8. Evolutionary dynamics of diploid populations

    NASA Astrophysics Data System (ADS)

    Desimone, Ralph; Newman, Timothy

    2003-10-01

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

  9. Natural selection and population dynamics.

    PubMed

    Saccheri, Ilik; Hanski, Ilkka

    2006-06-01

    To what extent, and under which circumstances, are population dynamics influenced by concurrent natural selection? Density dependence and environmental stochasticity are generally expected to subsume any selective modulation of population growth rate, but theoretical considerations point to conditions under which selection can have an appreciable impact on population dynamics. By contrast, empirical research has barely scratched the surface of this fundamental question in population biology. Here, we present a diverse body of mostly empirical evidence that demonstrates how selection can influence population dynamics, including studies of small populations, metapopulations, cyclical populations and host-pathogen interactions. We also discuss the utility, in this context, of inferences from molecular genetic data, placing them within the broader framework of quantitative genetics and life-history evolution.

  10. Sustainability of culture-driven population dynamics.

    PubMed

    Ghirlanda, Stefano; Enquist, Magnus; Perc, Matjaz

    2010-05-01

    We consider models of the interactions between human population dynamics and cultural evolution, asking whether they predict sustainable or unsustainable patterns of growth. Phenomenological models predict either unsustainable population growth or stabilization in the near future. The latter prediction, however, is based on extrapolation of current demographic trends and does not take into account causal processes of demographic and cultural dynamics. Most existing causal models assume (or derive from simplified models of the economy) a positive feedback between cultural evolution and demographic growth, and predict unlimited growth in both culture and population. We augment these models taking into account that: (1) cultural transmission is not perfect, i.e., culture can be lost; (2) culture does not always promote population growth. We show that taking these factors into account can cause radically different model behavior, such as population extinction rather than stability, and extinction rather than growth. We conclude that all models agree that a population capable of maintaining a large amount of culture, including a powerful technology, runs a high risk of being unsustainable. We suggest that future work must address more explicitly both the dynamics of resource consumption and the cultural evolution of beliefs implicated in reproductive behavior (e.g., ideas about the preferred family size) and in resource use (e.g., environmentalist stances).

  11. 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...

  12. 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.

  13. Two complementary paradigms for analysing population dynamics.

    PubMed Central

    Krebs, Charles J

    2002-01-01

    To understand why population growth rate is sometimes positive and sometimes negative, ecologists have adopted two main approaches. The most common approach is through the density paradigm by plotting population growth rate against population density. The second approach is through the mechanistic paradigm by plotting population growth rate against the relevant ecological processes affecting the population. The density paradigm is applied a posteriori, works sometimes but not always and is remarkably useless in solving management problems or in providing an understanding of why populations change in size. The mechanistic paradigm investigates the factors that supposedly drive density changes and is identical to Caughley's declining population paradigm of conservation biology. The assumption that we can uncover invariant relationships between population growth rate and some other variables is an article of faith. Numerous commercial fishery applications have failed to find the invariant relationships between stock and recruitment that are predicted by the density paradigm. Environmental variation is the rule, and non-equilibrial dynamics should force us to look for the mechanisms of population change. If multiple factors determine changes in population density, there can be no predictability in either of these paradigms and we will become environmental historians rather than scientists with useful generalizations for the population problems of this century. Defining our questions clearly and adopting an experimental approach with crisp alternative hypotheses and adequate controls will be essential to building useful generalizations for solving the practical problems of population management in fisheries, wildlife and conservation. PMID:12396513

  14. Evolutionary dynamics in finite populations

    NASA Astrophysics Data System (ADS)

    Hauert, Christoph

    2013-03-01

    Traditionally, evolutionary dynamics has been studied based on infinite populations and deterministic frameworks such as the replicator equation. Only more recently the focus has shifted to the stochastic dynamics arising in finite populations. Over the past years new concepts have been developed to describe such dynamics and has lead to interesting results that arise from the stochastic, microscopic updates, which drive the evolutionary process. Here we discuss a transparent link between the dynamics in finite and infinite populations. The focus on microscopic processes reveals interesting insights into (sometimes implicit) assumptions in terms of biological interactions that provide the basis for deterministic frameworks and the replicator equation in particular. More specifically, we demonstrate that stochastic differential equations can provide an efficient approach to model evolutionary dynamics in finite populations and we use the rock-scissors-paper game with mutations as an example. For sufficiently large populations the agreement with individual based simulations is excellent, with the interesting caveat that mutation events may not be too rare. In the absence of mutations, the excellent agreement extends to small population sizes.

  15. Dose-structured population dynamics.

    PubMed

    Ginn, Timothy R; Loge, Frank J

    2007-07-01

    Applied population dynamics modeling is relied upon with increasing frequency to quantify how human activities affect human and non-human populations. Current techniques include variously the population's spatial transport, age, size, and physiology, but typically not the life-histories of exposure to other important things occurring in the ambient environment, such as chemicals, heat, or radiation. Consequently, the effects of such 'abiotic' aspects of an ecosystem on populations are only currently addressed through individual-based modeling approaches that despite broad utility are limited in their applicability to realistic ecosystems [V. Grimm, Ten years of individual-based modeling in ecology: what have we learned and what could we learn in the future? Ecol. Model. 115 (1999) 129-148][1]. We describe a new category of population dynamics modeling, wherein population dynamical states of the biotic phases are structured on dose, and apply this framework to demonstrate how chemical species or other ambient aspects can be included in population dynamics in three separate examples involving growth suppression in fish, inactivation of microorganisms with ultraviolet irradiation, and metabolic lag in population growth. Dose-structuring is based on a kinematic approach that is a simple generalization of age-structuring, views the ecosystem as a multi-component mixture with reacting biotic/abiotic components. The resulting model framework accommodates (a) different memories of exposure as in recovery from toxic ambient conditions, (b) differentiation between exogenous and endogenous sources of variation in population response, and (c) quantification of acute or sub-acute effects on populations arising from life-history exposures to abiotic species. Classical models do not easily address the very important fact that organisms differ and have different experiences over their life cycle. The dose structuring is one approach to incorporate some of these elements into the

  16. 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.

  17. 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.

  18. Predictive dynamic digital holography

    NASA Astrophysics Data System (ADS)

    Sulaiman, Sennan; Gibson, Steve; Spencer, Mark

    2016-09-01

    Digital holography has received recent attention for many imaging and sensing applications, including imaging through turbulent and turbid media, adaptive optics, three dimensional projective display technology and optical tweezing. A significant obstacle for digital holography in real-time applications, such as wavefront sensing for high energy laser systems and high speed imaging for target tracking, is the fact that digital holography is computationally intensive; it requires iterative virtual wavefront propagation and hill-climbing to optimize some sharpness criteria. This paper demonstrates real-time methods for digital holography based on approaches developed recently at UCLA for optimal and adaptive identification, prediction, and control of optical wavefronts. The methods presented integrate minimum variance wavefront prediction into digital holography schemes to short-circuit the computationally intensive algorithms for iterative propagation of virtual wavefronts and hill climbing for sharpness optimization.

  19. Predictive models of forest dynamics.

    PubMed

    Purves, Drew; Pacala, Stephen

    2008-06-13

    Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.

  20. Decadal predictability without ocean dynamics.

    PubMed

    Srivastava, Abhishekh; DelSole, Timothy

    2017-02-28

    This paper shows that the most predictable components of internal variability in coupled atmosphere-ocean models are remarkably similar to the most predictable components of climate models without interactive ocean dynamics (i.e., models whose ocean is represented by a 50-m-deep slab ocean mixed layer with no interactive currents). Furthermore, a linear regression model derived solely from dynamical model output can skillfully predict observed anomalies in these components at least a year or two in advance, indicating that these model-derived components and associated linear dynamics are realistic. These results suggest that interactive ocean circulation is not essential for the existence of multiyear predictability previously identified in coupled models and observations.

  1. 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.

  2. 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.

  3. 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.

  4. Exploring Dynamic Risk Prediction for Dialysis Patients

    PubMed Central

    Ganssauge, Malte; Padman, Rema; Teredesai, Pradip; Karambelkar, Ameet

    2016-01-01

    Despite substantial advances in the treatment of end-stage renal disease, mortality of hemodialysis patients remains high. Several models exist that predict mortality for this population and identify patients at risk. However, they mostly focus on patients at a particular stage of dialysis treatment, such as start of dialysis, and only use the most recent patient data. Generalization of such models for predictions in later periods can be challenging since disease characteristics change over time and the evolution of biomarkers is not adequately incorporated. In this research, we explore dynamic methods which allow updates of initial predictions when patients progress in time and new data is observed. We compare a Dynamic Bayesian Network (DBN) to regularized logistic regression models and a Cox model with landmarking. Our preliminary results indicate that the DBN achieves satisfactory performance for short term prediction horizons, but needs further refinement and parameter tuning for longer horizons. PMID:28269937

  5. Stochastic Gain in Population Dynamics

    NASA Astrophysics Data System (ADS)

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

    2004-07-01

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

  6. 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.

  7. Relating individual behaviour to population dynamics.

    PubMed

    Sumpter, D J; Broomhead, D S

    2001-05-07

    How do the behavioural interactions between individuals in an ecological system produce the global population dynamics of that system? We present a stochastic individual-based model of the reproductive cycle of the mite Varroa jacobsoni, a parasite of honeybees. The model has the interesting property in that its population level behaviour is approximated extremely accurately by the exponential logistic equation or Ricker map. We demonstrated how this approximation is obtained mathematically and how the parameters of the exponential logistic equation can be written in terms of the parameters of the individual-based model. Our procedure demonstrates, in at least one case, how study of animal ecology at an individual level can be used to derive global models which predict population change over time.

  8. Predictive models of battle dynamics

    NASA Astrophysics Data System (ADS)

    Jelinek, Jan

    2001-09-01

    The application of control and game theories to improve battle planning and execution requires models, which allow military strategists and commanders to reliably predict the expected outcomes of various alternatives over a long horizon into the future. We have developed probabilistic battle dynamics models, whose building blocks in the form of Markov chains are derived from the first principles, and applied them successfully in the design of the Model Predictive Task Commander package. This paper introduces basic concepts of our modeling approach and explains the probability distributions needed to compute the transition probabilities of the Markov chains.

  9. The population dynamics of antimicrobial chemotherapy.

    PubMed Central

    Lipsitch, M; Levin, B R

    1997-01-01

    We present and analyze a series of mathematical models for the emergence of resistance during antibiotic treatment of an infected host. The models consider the population dynamics of antibiotic-sensitive and -resistant bacteria during the course of treatment and addresses the following problems: (i) the probability of obtaining a resistant mutant during the course of treatment as a function of antibiotic exposure; (ii) the conditions under which high, infrequent doses of an antibiotic are predicted to succeed in preventing the emergence of resistance; (iii) the conditions for the success of multiple drug treatment in suppressing the emergence of resistance and the relationship between antibiotic synergism and suppression of resistance; and (iv) the conditions under which nonadherence to the prescribed treatment regimen is predicted to result in treatment failure due to resistance. We analyze the predictions of the model for interpreting and extrapolating existing experimental studies of treatment efficacy and for optimizing treatment protocols to prevent the emergence of resistance. PMID:9021193

  10. Mosquito populations dynamics associated with climate variations.

    PubMed

    Wilke, André Barretto Bruno; Medeiros-Sousa, Antônio Ralph; Ceretti-Junior, Walter; Marrelli, Mauro Toledo

    2017-02-01

    Mosquitoes are responsible for the transmission of numerous serious pathogens. Members of the Aedes and Culex genera, which include many important vectors of mosquito-borne diseases, are highly invasive and adapted to man-made environments. They are spread around the world involuntarily by humans and are highly adapted to urbanized environments, where they are exposed to climate-related abundance drivers. We investigated Culicidae fauna in two urban parks in the city of São Paulo to analyze the correlations between climatic variables and the population dynamics of mosquitoes in these urban areas. Mosquitoes were collected monthly over one year, and sampling sufficiency was evaluated after morphological identification of the specimens. The average monthly temperature and accumulated rainfall for the collection month and previous month were used to explain climate-related abundance drivers for the six most abundant species (Aedes aegypti, Aedes albopictus, Aedes fluviatilis, Aedes scapularis, Culex nigripalpus and Culex quinquefasciatus) and then analyzed using generalized linear statistical models and the Akaike Information Criteria corrected for small samples (AICc). The strength of evidence in favor of each model was evaluated using Akaike weights, and the explanatory model power was measured by McFadden's Pseudo-R(2). Associations between climate and mosquito abundance were found in both parks, indicating that predictive models based on climate variables can provide important information on mosquito population dynamics. We also found that this association is species-dependent. Urbanization processes increase the abundance of a few mosquito species that are well adapted to man-made environments and some of which are important vectors of pathogens. Predictive models for abundance based on climate variables may help elucidate the population dynamics of urban mosquitoes and their impact on the risk of disease transmission, allowing better predictive scenarios to be

  11. 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.

  12. Genomic Predictability of Interconnected Biparental Maize Populations

    PubMed Central

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

    2013-01-01

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

  13. 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

  14. A quantitative model of honey bee colony population dynamics.

    PubMed

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

    2011-04-18

    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.

  15. Predicting how populations decline to extinction

    PubMed Central

    Collen, Ben; McRae, Louise; Deinet, Stefanie; De Palma, Adriana; Carranza, Tharsila; Cooper, Natalie; Loh, Jonathan; Baillie, Jonathan E. M.

    2011-01-01

    Global species extinction typically represents the endpoint in a long sequence of population declines and local extinctions. In comparative studies of extinction risk of contemporary mammalian species, there appear to be some universal traits that may predispose taxa to an elevated risk of extinction. In local population-level studies, there are limited insights into the process of population decline and extinction. Moreover, there is still little appreciation of how local processes scale up to global patterns. Advancing the understanding of factors which predispose populations to rapid declines will benefit proactive conservation and may allow us to target at-risk populations as well as at-risk species. Here, we take mammalian population trend data from the largest repository of population abundance trends, and combine it with the PanTHERIA database on mammal traits to answer the question: what factors can be used to predict decline in mammalian abundance? We find in general that environmental variables are better determinants of cross-species population-level decline than intrinsic biological traits. For effective conservation, we must not only describe which species are at risk and why, but also prescribe ways to counteract this. PMID:21807738

  16. 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.

  17. Encroaching forests decouple alpine butterfly population dynamics.

    PubMed

    Roland, Jens; Matter, Stephen F

    2007-08-21

    Over the past 50 years, the rising tree line along Jumpingpound Ridge in the Rocky Mountains of Alberta, Canada, has reduced the area of alpine meadows and isolated populations that reside within them. By analyzing an 11-year data set of butterfly population sizes for 17 subpopulations along the ridge, we show that forest habitat separating alpine meadows decouples the dynamics of populations of the alpine butterfly Parnassius smintheus. Although the distance between populations is often negatively correlated with synchrony of dynamics, here we show that distance through forest, not Euclidean distance, determines the degree of synchrony. This effect is consistent with previous results demonstrating that encroaching forest reduces dispersal among populations and reduces gene flow. Decoupling dynamics produces more smaller independent populations, each with greater risk of local extinction, but decoupling may produce a lower risk of regional extinction in this capricious environment.

  18. Population dynamics and rural poverty.

    PubMed

    Fong, M S

    1985-01-01

    An overview of the relationship between demographic factors and rural poverty in developing countries is presented. The author examines both the micro- and macro-level perspectives of this relationship and the determinants and consequences of population growth. The author notes the prospects for a rapid increase in the rural labor force and considers its implications for the agricultural production structure and the need for institutional change. Consideration is also given to the continuing demand for high fertility at the family level and the role of infant and child mortality in the poverty cycle. "The paper concludes by drawing attention to the need for developing the mechanism for reconciliation of social and individual optima with respect to family size and population growth." The need for rural development projects that take demographic factors into account is stressed as is the need for effective population programs. (summary in FRE, ITA)

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Model complexity affects transient population dynamics following a dispersal event: a case study with pea aphids.

    PubMed

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

    2009-07-01

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

  5. Detection, Diversity, and Population Dynamics of Waterborne Phytophthora ramorum Populations.

    PubMed

    Eyre, C A; Garbelotto, M

    2015-01-01

    Sudden oak death, the tree disease caused by Phytophthora ramorum, has significant environmental and economic impacts on natural forests on the U.S. west coast, plantations in the United Kingdom, and in the worldwide nursery trade. Stream baiting is vital for monitoring and early detection of the pathogen in high-risk areas and is performed routinely; however, little is known about the nature of water-borne P. ramorum populations. Two drainages in an infested California forest were monitored intensively using stream-baiting for 2 years between 2009 and 2011. Pathogen presence was determined both by isolation and polymerase chain reaction (PCR) from symptomatic bait leaves. Isolates were analyzed using simple sequence repeats to study population dynamics and genetic structure through time. Isolation was successful primarily only during spring conditions, while PCR extended the period of pathogen detection to most of the year. Water populations were extremely diverse, and changed between seasons and years. A few abundant genotypes dominated the water during conditions considered optimal for aerial populations, and matched those dominant in aerial populations. Temporal patterns of genotypic diversification and evenness were identical among aerial, soil, and water populations, indicating that all three substrates are part of the same epidemiological cycle, strongly influenced by rainfall and sporulation on leaves. However, there was structuring between substrates, likely arising due to reduced selection pressure in the water. Additionally, water populations showed wholesale mixing of genotypes without the evident spatial autocorrelation present in leaf and soil populations.

  6. Harvest and dynamics of duck populations

    USGS Publications Warehouse

    Sedinger, James S.; Herzog, Mark P.

    2012-01-01

    The role of harvest in the dynamics of waterfowl populations continues to be debated among scientists and managers. Our perception is that interested members of the public and some managers believe that harvest influences North American duck populations based on calls for more conservative harvest regulations. A recent review of harvest and population dynamics of North American mallard (Anas platyrhynchos) populations (Pöysä et al. 2004) reached similar conclusions. Because of the importance of this issue, we reviewed the evidence for an impact of harvest on duck populations. Our understanding of the effects of harvest is limited because harvest effects are typically confounded with those of population density; regulations are typically most liberal when populations are greatest. This problem also exists in the current Adaptive Harvest Management Program (Conn and Kendall 2004). Consequently, even where harvest appears additive to other mortality, this may be an artifact of ignoring effects of population density. Overall, we found no compelling evidence for strong additive effects of harvest on survival in duck populations that could not be explained by other factors.

  7. 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.

  8. Population dynamics in an intermittent refuge

    NASA Astrophysics Data System (ADS)

    Colombo, E. H.; Anteneodo, C.

    2016-10-01

    Population dynamics is constrained by the environment, which needs to obey certain conditions to support population growth. We consider a standard model for the evolution of a single species population density, which includes reproduction, competition for resources, and spatial spreading, while subject to an external harmful effect. The habitat is spatially heterogeneous, there existing a refuge where the population can be protected. Temporal variability is introduced by the intermittent character of the refuge. This scenario can apply to a wide range of situations, from a laboratory setting where bacteria can be protected by a blinking mask from ultraviolet radiation, to large-scale ecosystems, like a marine reserve where there can be seasonal fishing prohibitions. Using analytical and numerical tools, we investigate the asymptotic behavior of the total population as a function of the size and characteristic time scales of the refuge. We obtain expressions for the minimal size required for population survival, in the slow and fast time scale limits.

  9. Monitoring coyote population dynamics by genotyping faeces.

    PubMed

    Prugh, L R; Ritland, C E; Arthur, S M; Krebs, C J

    2005-04-01

    Reliable population estimates are necessary for effective conservation and management, and faecal genotyping has been used successfully to estimate the population size of several elusive mammalian species. Information such as changes in population size over time and survival rates, however, are often more useful for conservation biology than single population estimates. We evaluated the use of faecal genotyping as a tool for monitoring long-term population dynamics, using coyotes (Canis latrans) in the Alaska Range as a case study. We obtained 544 genotypes from 56 coyotes over 3 years (2000-2002). Tissue samples from all 15 radio-collared coyotes in our study area had > or = 1 matching faecal genotypes. We used flexible maximum-likelihood models to study coyote population dynamics, and we tested model performance against radio telemetry data. The staple prey of coyotes, snowshoe hares (Lepus americanus), dramatically declined during this study, and the coyote population declined nearly two-fold with a 1(1/2)-year time lag. Survival rates declined the year after hares crashed but recovered the following year. We conclude that long-term monitoring of elusive species using faecal genotyping is feasible and can provide data that are useful for wildlife conservation and management. We highlight some drawbacks of standard open-population models, such as low precision and the requirement of discrete sampling intervals, and we suggest that the development of open models designed for continuously collected data would enhance the utility of faecal genotyping as a monitoring tool.

  10. Irruptive population dynamics in Yellowstone pronghorn.

    PubMed

    White, P J; Bruggeman, Jason E; Garrott, Robert A

    2007-09-01

    Irruptive population dynamics appear to be widespread in large herbivore populations, but there are few empirical examples from long time series with small measurement error and minimal harvests. We analyzed an 89-year time series of counts and known removals for pronghorn (Antilocapra americana) in Yellowstone National Park of the western United States during 1918-2006 using a suite of density-dependent, density-independent, and irruptive models to determine if the population exhibited irruptive dynamics. Information-theoretic model comparison techniques strongly supported irruptive population dynamics (Leopold model) and density dependence during 1918-1946, with the growth rate slowing after counts exceeded 600 animals. Concerns about sagebrush (Artemisia spp.) degradation led to removals of >1100 pronghorn during 1947-1966, and counts decreased from approximately 700 to 150. The best models for this period (Gompertz, Ricker) suggested that culls replaced intrinsic density-dependent mechanisms. Contrary to expectations, the population did not exhibit enhanced demographic vigor soon after the termination of the harvest program, with counts remaining between 100 and 190 animals during 1967 1981. However, the population irrupted (Caughley model with a one-year lag) to a peak abundance of approximately 600 pronghorn during 1982-1991, with a slowing in growth rate as counts exceeded 500. Numbers crashed to 235 pronghorn during 1992-1995, perhaps because important food resources (e.g., sagebrush) on the winter range were severely diminished by high densities of browsing elk, mule deer, and pronghorn. Pronghorn numbers remained relatively constant during 1996-2006, at a level (196-235) lower than peak abundance, but higher than numbers following the release from culling. The dynamics of this population supported the paradigm that irruption is a fundamental pattern of growth in many populations of large herbivores with high fecundity and delayed density-dependent effects

  11. Towards a Population Dynamics Theory for Evolutionary Computing: Learning from Biological Population Dynamics in Nature

    NASA Astrophysics Data System (ADS)

    Ma, Zhanshan (Sam)

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

  12. Noise can prevent onset of chaos in spatiotemporal population dynamics

    NASA Astrophysics Data System (ADS)

    Petrovskii, S.; Morozov, A.; Malchow, H.; Sieber, M.

    2010-11-01

    Many theoretical approaches predict the dynamics of interacting populations to be chaotic but that has very rarely been observed in ecological data. It has therefore risen a question about factors that can prevent the onset of chaos by, for instance, making the population fluctuations synchronized over the whole habitat. One such factor is stochasticity. The so-called Moran effect predicts that a spatially correlated noise can synchronize the local population dynamics in a spatially discrete system, thus preventing the onset of spatiotemporal chaos. On the whole, however, the issue of noise has remained controversial and insufficiently understood. In particular, a well-built nonspatial theory infers that noise enhances chaos by making the system more sensitive to the initial conditions. In this paper, we address the problem of the interplay between deterministic dynamics and noise by considering a spatially explicit predator-prey system where some parameters are affected by noise. Our findings are rather counter-intuitive. We show that a small noise (i.e. preserving the deterministic skeleton) can indeed synchronize the population oscillations throughout space and hence keep the dynamics regular, but the dependence of the chaos prevention probability on the noise intensity is of resonance type. Once chaos has developed, it appears to be stable with respect to a small noise but it can be suppressed by a large noise. Finally, we show that our results are in a good qualitative agreement with some available field data.

  13. Dispersive models describing mosquitoes’ population dynamics

    NASA Astrophysics Data System (ADS)

    Yamashita, W. M. S.; Takahashi, L. T.; Chapiro, G.

    2016-08-01

    The global incidences of dengue and, more recently, zica virus have increased the interest in studying and understanding the mosquito population dynamics. Understanding this dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. This work is based on the study of nonlinear mathematical models dealing with the life cycle of the dengue mosquito using partial differential equations. We investigate the existence of traveling wave solutions using semi-analytical method combining dynamical systems techniques and numerical integration. Obtained solutions are validated through numerical simulations using finite difference schemes.

  14. Connecting micro dynamics and population distributions in system dynamics models.

    PubMed

    Fallah-Fini, Saeideh; Rahmandad, Hazhir; Chen, Hsin-Jen; Xue, Hong; Wang, Youfa

    2013-01-01

    Researchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g., people) aggregated in stock variables. Yet, many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g., body weight). This paper presents a new method to connect the micro-level dynamics associated with elements in a population with the macro-level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of Body Mass Index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual-based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual-based model.

  15. Connecting micro dynamics and population distributions in system dynamics models

    PubMed Central

    Rahmandad, Hazhir; Chen, Hsin-Jen; Xue, Hong; Wang, Youfa

    2014-01-01

    Researchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g., people) aggregated in stock variables. Yet, many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g., body weight). This paper presents a new method to connect the micro-level dynamics associated with elements in a population with the macro-level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of Body Mass Index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual-based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual-based model. PMID:25620842

  16. 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

  17. Dynamic control and quantification of bacterial population dynamics in droplets.

    PubMed

    Huang, Shuqiang; Srimani, Jaydeep K; Lee, Anna J; Zhang, Ying; Lopatkin, Allison J; Leong, Kam W; You, Lingchong

    2015-08-01

    Culturing and measuring bacterial population dynamics are critical to develop insights into gene regulation or bacterial physiology. Traditional methods, based on bulk culture to obtain such quantification, have the limitations of higher cost/volume of reagents, non-amendable to small size of population and more laborious manipulation. To this end, droplet-based microfluidics represents a promising alternative that is cost-effective and high-throughput. However, difficulties in manipulating the droplet environment and monitoring encapsulated bacterial population for long-term experiments limit its utilization. To overcome these limitations, we used an electrode-free injection technology to modulate the chemical environment in droplets. This ability is critical for precise control of bacterial dynamics in droplets. Moreover, we developed a trapping device for long-term monitoring of population dynamics in individual droplets for at least 240 h. We demonstrated the utility of this new microfluidic system by quantifying population dynamics of natural and engineered bacteria. Our approach can further improve the analysis for systems and synthetic biology in terms of manipulability and high temporal resolution.

  18. Dynamic control and quantification of bacterial population dynamics in droplets

    PubMed Central

    Huang, Shuqiang; Srimani, Jaydeep K.; Lee, Anna J.; Zhang, Ying; Lopatkin, Allison J.; Leong, Kam W.; You, Lingchong

    2015-01-01

    Culturing and measuring bacterial population dynamics are critical to develop insights into gene regulation or bacterial physiology. Traditional methods, based on bulk culture to obtain such quantification, have the limitations of higher cost/volume of reagents, non-amendable to small size of population and more laborious manipulation. To this end, droplet-based microfluidics represents a promising alternative that is cost-effective and high-throughput. However, difficulties in manipulating the droplet environment and monitoring encapsulated bacterial population for long-term experiments limit its utilization. To overcome these limitations, we used an electrode-free injection technology to modulate the chemical environment in droplets. This ability is critical for precise control of bacterial dynamics in droplets. Moreover, we developed a trapping device for long-term monitoring of population dynamics in individual droplets for at least 240 h. We demonstrated the utility of this new microfluidic system by quantifying population dynamics of natural and engineered bacteria. Our approach can further improve the analysis for systems and synthetic biology in terms of manipulability and high temporal resolution. PMID:26005763

  19. Dynamics of North American breeding bird populations

    NASA Astrophysics Data System (ADS)

    Keitt, Timothy H.; Stanley, H. Eugene

    1998-05-01

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

  20. Dynamics of newly established elk populations

    USGS Publications Warehouse

    Sargeant, G.A.; Oehler, M.W.

    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.

  1. Spatio-temporal transitions in the dynamics of bacterial populations

    NASA Astrophysics Data System (ADS)

    Lin, Anna; Lincoln, Bryan; Mann, Bernward; Torres, Gelsy; Kas, Josef; Swinney, Harry

    2001-03-01

    We experimentally investigate the population dynamics of a strain of E. coli bacteria living under spatially inhomogeneous growth conditions. A localized perturbation that moves with a well-defined drift velocity is imposed on the system. A reaction-diffusion model of this situation^1 predicts that an abrupt transition between spatial localization and extinction of the colony occurs for a fixed average growth rate when the drift velocity exceeds a critical value. Also, a transition between localized and delocalized populations is predicted to occur at a fixed drift velocity when the spatially averaged growth rate is varied. We create a spatially localized perturbation with UV light and vary the strength and drift velocity of the perturbation to investigate the existence of the different bacterial population distributions and the transitions between them. Numerical simulations of a 250 mm by 20 mm system guide our experiments. ^1K. A. Dahmen, D. R. Nelson, N. M. Shnerb, Jour. Math. Bio., 41 1 (2000).

  2. Population dynamics in non-homogeneous environments

    NASA Astrophysics Data System (ADS)

    Alards, Kim M. J.; Tesser, Francesca; Toschi, Federico

    2014-11-01

    For organisms living in aquatic ecosystems the presence of fluid transport can have a strong influence on the dynamics of populations and on evolution of species. In particular, displacements due to self-propulsion, summed up with turbulent dispersion at larger scales, strongly influence the local densities and thus population and genetic dynamics. Real marine environments are furthermore characterized by a high degree of non-homogeneities. In the case of population fronts propagating in ``fast'' turbulence, with respect to the population duplication time, the flow effect can be studied by replacing the microscopic diffusivity with an effective turbulent diffusivity. In the opposite case of ``slow'' turbulence the advection by the flow has to be considered locally. Here we employ numerical simulations to study the influence of non-homogeneities in the diffusion coefficient of reacting individuals of different species expanding in a 2 dimensional space. Moreover, to explore the influence of advection, we consider a population expanding in the presence of simple velocity fields like cellular flows. The output is analyzed in terms of front roughness, front shape, propagation speed and, concerning the genetics, by means of heterozygosity and local and global extinction probabilities.

  3. 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.

  4. Population dynamics of king eiders breeding in northern Alaska

    USGS Publications Warehouse

    Bentzen, Rebecca L.; Powell, Abby N.

    2012-01-01

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

  5. Dynamic analysis of grinding using the population balance model

    SciTech Connect

    Williams, M.C. |

    1995-12-31

    The dynamic behavior of batch mill, CSTR mill, and a closed grinding network consisting of a mill, sump, and cyclone was analyzed using the dynamic population balance model (PBM). The dynamic solution of the PBM of a batch, CSTR and a closed grinding network consisting of a mill, sump, and cyclone forms the basis of the dynamic analysis presented here. Two numerical dynamic solution approaches were used. These are: (1) providing additional constraints on breakage selection functions or (2) performing the Arbiter-Bhrany (or other) normalization of the selection functions. Actual experimental anthracite batch grinding data was used to obtain the functionality of the batch dynamic mill selection and breakage functions for a real physical system. The Levenberg-Marquardt algorithm for systems of constrained non-linear equations is used to solve the batch dynamic PBM grinding equations to obtain the grinding selection and breakage rate functions. The mill, sump and hydrocyclone were modeled as a CSTR operating at various retention times. Batch dynamic PBM data was used to provide the mill kinetic and breakage selection function data. Different dynamic solutions were obtained depending on the numerical approach used. Each solution approach to a dynamic PBM with transport, while giving the same prediction for a single batch grinding time, gives different solutions or predictions for mill composition for other grinding times. This fact makes dynamic nodal analysis and control problematic. The fact that the constraint solution approach gives a solution may suggest that normalization for closed networks is not necessary. Differences in solutions to the PBM cannot be excused away by inaccuracies in the data used to model the grinding phenomenon.

  6. 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

  7. 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.

  8. Optimization-based Dynamic Human Lifting Prediction

    DTIC Science & Technology

    2008-06-01

    Anith Mathai, Steve Beck,Timothy Marler , Jingzhou Yang, Jasbir S. Arora, Karim Abdel-Malek Virtual Soldier Research Program, Center for Computer Aided...Rahmatalla, S., Kim, J., Marler , T., Beck, S., Yang, J., busek, J., Arora, J.S., and Abdel-Malek, K. Optimization-based dynamic human walking prediction

  9. Modeling Bacterial Population Growth from Stochastic Single-Cell Dynamics

    PubMed Central

    Molina, Ignacio; Theodoropoulos, Constantinos

    2014-01-01

    A few bacterial cells may be sufficient to produce a food-borne illness outbreak, provided that they are capable of adapting and proliferating on a food matrix. This is why any quantitative health risk assessment policy must incorporate methods to accurately predict the growth of bacterial populations from a small number of pathogens. In this aim, mathematical models have become a powerful tool. Unfortunately, at low cell concentrations, standard deterministic models fail to predict the fate of the population, essentially because the heterogeneity between individuals becomes relevant. In this work, a stochastic differential equation (SDE) model is proposed to describe variability within single-cell growth and division and to simulate population growth from a given initial number of individuals. We provide evidence of the model ability to explain the observed distributions of times to division, including the lag time produced by the adaptation to the environment, by comparing model predictions with experiments from the literature for Escherichia coli, Listeria innocua, and Salmonella enterica. The model is shown to accurately predict experimental growth population dynamics for both small and large microbial populations. The use of stochastic models for the estimation of parameters to successfully fit experimental data is a particularly challenging problem. For instance, if Monte Carlo methods are employed to model the required distributions of times to division, the parameter estimation problem can become numerically intractable. We overcame this limitation by converting the stochastic description to a partial differential equation (backward Kolmogorov) instead, which relates to the distribution of division times. Contrary to previous stochastic formulations based on random parameters, the present model is capable of explaining the variability observed in populations that result from the growth of a small number of initial cells as well as the lack of it compared to

  10. Modeling bacterial population growth from stochastic single-cell dynamics.

    PubMed

    Alonso, Antonio A; Molina, Ignacio; Theodoropoulos, Constantinos

    2014-09-01

    A few bacterial cells may be sufficient to produce a food-borne illness outbreak, provided that they are capable of adapting and proliferating on a food matrix. This is why any quantitative health risk assessment policy must incorporate methods to accurately predict the growth of bacterial populations from a small number of pathogens. In this aim, mathematical models have become a powerful tool. Unfortunately, at low cell concentrations, standard deterministic models fail to predict the fate of the population, essentially because the heterogeneity between individuals becomes relevant. In this work, a stochastic differential equation (SDE) model is proposed to describe variability within single-cell growth and division and to simulate population growth from a given initial number of individuals. We provide evidence of the model ability to explain the observed distributions of times to division, including the lag time produced by the adaptation to the environment, by comparing model predictions with experiments from the literature for Escherichia coli, Listeria innocua, and Salmonella enterica. The model is shown to accurately predict experimental growth population dynamics for both small and large microbial populations. The use of stochastic models for the estimation of parameters to successfully fit experimental data is a particularly challenging problem. For instance, if Monte Carlo methods are employed to model the required distributions of times to division, the parameter estimation problem can become numerically intractable. We overcame this limitation by converting the stochastic description to a partial differential equation (backward Kolmogorov) instead, which relates to the distribution of division times. Contrary to previous stochastic formulations based on random parameters, the present model is capable of explaining the variability observed in populations that result from the growth of a small number of initial cells as well as the lack of it compared to

  11. 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.

  12. 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

  13. Predicting Virtual World User Population Fluctuations with Deep Learning.

    PubMed

    Kim, Young Bin; Park, Nuri; Zhang, Qimeng; Kim, Jun Gi; Kang, Shin Jin; Kim, Chang Hun

    2016-01-01

    This paper proposes a system for predicting increases in virtual world user actions. The virtual world user population is a very important aspect of these worlds; however, methods for predicting fluctuations in these populations have not been well documented. Therefore, we attempt to predict changes in virtual world user populations with deep learning, using easily accessible online data, including formal datasets from Google Trends, Wikipedia, and online communities, as well as informal datasets collected from online forums. We use the proposed system to analyze the user population of EVE Online, one of the largest virtual worlds.

  14. Predicting Virtual World User Population Fluctuations with Deep Learning

    PubMed Central

    Park, Nuri; Zhang, Qimeng; Kim, Jun Gi; Kang, Shin Jin; Kim, Chang Hun

    2016-01-01

    This paper proposes a system for predicting increases in virtual world user actions. The virtual world user population is a very important aspect of these worlds; however, methods for predicting fluctuations in these populations have not been well documented. Therefore, we attempt to predict changes in virtual world user populations with deep learning, using easily accessible online data, including formal datasets from Google Trends, Wikipedia, and online communities, as well as informal datasets collected from online forums. We use the proposed system to analyze the user population of EVE Online, one of the largest virtual worlds. PMID:27936009

  15. 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…

  16. Hidden hysteresis – population dynamics can obscure gene network dynamics

    PubMed Central

    2013-01-01

    Background Positive feedback is a common motif in gene regulatory networks. It can be used in synthetic networks as an amplifier to increase the level of gene expression, as well as a nonlinear module to create bistable gene networks that display hysteresis in response to a given stimulus. Using a synthetic positive feedback-based tetracycline sensor in E. coli, we show that the population dynamics of a cell culture has a profound effect on the observed hysteretic response of a population of cells with this synthetic gene circuit. Results The amount of observable hysteresis in a cell culture harboring the gene circuit depended on the initial concentration of cells within the culture. The magnitude of the hysteresis observed was inversely related to the dilution procedure used to inoculate the subcultures; the higher the dilution of the cell culture, lower was the observed hysteresis of that culture at steady state. Although the behavior of the gene circuit in individual cells did not change significantly in the different subcultures, the proportion of cells exhibiting high levels of steady-state gene expression did change. Although the interrelated kinetics of gene expression and cell growth are unpredictable at first sight, we were able to resolve the surprising dilution-dependent hysteresis as a result of two interrelated phenomena - the stochastic switching between the ON and OFF phenotypes that led to the cumulative failure of the gene circuit over time, and the nonlinear, logistic growth of the cell in the batch culture. Conclusions These findings reinforce the fact that population dynamics cannot be ignored in analyzing the dynamics of gene networks. Indeed population dynamics may play a significant role in the manifestation of bistability and hysteresis, and is an important consideration when designing synthetic gene circuits intended for long-term application. PMID:23800122

  17. 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

  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.

  20. 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

  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 δ-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. Song Diversity Predicts the Viability of Fragmented Bird Populations

    PubMed Central

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

    2008-01-01

    In the global scenario of increasing habitat fragmentation, finding appropriate indicators of population viability is a priority for conservation. We explored the potential of learned behaviours, specifically acoustic signals, to predict the persistence over time of fragmented bird populations. We found an association between male song diversity and the annual rate of population change, population productivity and population size, resulting in birds singing poor repertoires in populations more prone to extinction. This is the first demonstration that population viability can be predicted by a cultural trait (acquired via social learning). Our results emphasise that cultural attributes can reflect not only individual-level characteristics, but also the emergent population-level properties. This opens the way to the study of animal cultural diversity in the increasingly common human-altered landscapes. PMID:18350158

  3. Dynamically hot galaxies. II - Global stellar populations

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

  4. 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.

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

    PubMed

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

    2013-10-01

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

  6. 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.

  7. 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

  8. Predicting Dynamic Separation Characteristics of General Configurations.

    DTIC Science & Technology

    1987-07-01

    Cebeci et al. (15) and Le Balleur (16), among others. In addition, the method provides a foundation for ap- plying improved modeling techniques ...AD-A196 669 PREDICTING DYNAMIC SEPRATION CHRACTERISTICS OF / GENERAL CONFIGURRTIONS(U) ANALYTICAL METHODS INC REDMOND MA B "ASKEW ET AL. JUL 87 AMI...a NAME Of MONI1TORING ORGANIZATION Analytical Methods , Inc. ItgpabIAir Force Office of Scientific Research 6c. A DD0R ESS (City. S tote and ZIP Code

  9. 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

  10. 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

  11. Lagged effects of ocean climate change on fulmar population dynamics.

    PubMed

    Thompson, P M; Ollason, J C

    2001-09-27

    Environmental variation reflected by the North Atlantic Oscillation affects breeding and survival in terrestrial vertebrates, and climate change is predicted to have an impact on population dynamics by influencing food quality or availability. The North Atlantic Oscillation also affects the abundance of marine fish and zooplankton, but it is unclear whether this filters up trophic levels to long-lived marine top predators. Here we show by analysis of data from a 50-year study of the fulmar that two different indices of ocean climate variation may have lagged effects on population dynamics in this procellariiform seabird. Annual variability in breeding performance is influenced by the North Atlantic Oscillation, whereas cohort differences in recruitment are related to temperature changes in the summer growing season in the year of birth. Because fulmars exhibit delayed reproduction, there is a 5-year lag in the population's response to these effects of environmental change. These data show how interactions between different climatic factors result in complex dynamics, and that the effects of climate change may take many years to become apparent in long-lived marine top predators.

  12. Toward a predictive theory of wetting dynamics.

    PubMed

    Duvivier, Damien; Blake, Terence D; De Coninck, Joël

    2013-08-13

    The molecular kinetic theory (MKT) of dynamic wetting, first proposed nearly 50 years ago, has since been refined to account explicitly for the effects of viscosity and solid-liquid interactions. The MKT asserts that the systematic deviation of the dynamic contact angle from its equilibrium value quantitatively reflects local energy dissipation (friction) at the moving contact line as it traverses sites of solid-liquid interaction. Specifically, it predicts that the coefficient of contact-line friction ζ will be proportional to the viscosity of the liquid ηL and exponentially dependent upon the strength of solid-liquid interactions as measured by the equilibrium work of adhesion Wa(0). Here, we analyze a very large set of dynamic wetting data drawn from more than 20 publications and representative of a very wide range of systems, from molecular-dynamics-simulated Lenard-Jones liquids and substrates, through conventional liquids and solids, to molten glasses and liquid metals on refractory solids. The combined set spans 9 decades of viscosity and 11 decades of contact-line friction. Our analysis confirms the predicted dependence of ζ upon ηL and Wa(0), although the data are scattered. In particular, a plot of ln(ζ/ηL) versus Wa(0)/n (i.e., the work of adhesion per solid-liquid interaction site) is broadly linear, with 85% of the data falling within a triangular envelope defined by Wa(0) and 0.25Wa(0). Various reasons for this divergence are explored, and a semi-empirical approach is proposed to predict ζ. We suggest that the broad agreement between the MKT and such a wide range of data is strong evidence that the local microscopic contact angle is directly dependent upon the velocity of the contact line.

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

    PubMed

    Karanth, K Ullas; Nichols, James D; Kumar, N Samba; Hines, James E

    2006-11-01

    Although wide-ranging, elusive, large carnivore species, such as the tiger, are of scientific and conservation interest, rigorous inferences about their population dynamics are scarce because of methodological problems of sampling populations at the required spatial and temporal scales. We report the application of a rigorous, noninvasive method for assessing tiger population dynamics to test model-based predictions about population viability. We obtained photographic capture histories for 74 individual tigers during a nine-year study involving 5725 trap-nights of effort. These data were modeled under a likelihood-based, "robust design" capture-recapture analytic framework. We explicitly modeled and estimated ecological parameters such as time-specific abundance, density, survival, recruitment, temporary emigration, and transience, using models that incorporated effects of factors such as individual heterogeneity, trap-response, and time on probabilities of photo-capturing tigers. The model estimated a random temporary emigration parameter of gamma" = gamma' = 0.10 +/- 0.069 (values are estimated mean +/- SE). When scaled to an annual basis, tiger survival rates were estimated at S = 0.77 +/- 0.051, and the estimated probability that a newly caught animal was a transient was tau = 0.18 +/- 0.11. During the period when the sampled area was of constant size, the estimated population size N(t) varied from 17 +/- 1.7 to 31 +/- 2.1 tigers, with a geometric mean rate of annual population change estimated as lambda = 1.03 +/- 0.020, representing a 3% annual increase. The estimated recruitment of new animals, B(t), varied from 0 +/- 3.0 to 14 +/- 2.9 tigers. Population density estimates, D, ranged from 7.33 +/- 0.8 tigers/100 km2 to 21.73 +/- 1.7 tigers/100 km2 during the study. Thus, despite substantial annual losses and temporal variation in recruitment, the tiger density remained at relatively high levels in Nagarahole. Our results are consistent with the hypothesis

  14. 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

  15. Prediction with measurement errors in finite populations

    PubMed Central

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

    2011-01-01

    We address the problem of selecting the best linear unbiased predictor (BLUP) of the latent value (e.g., serum glucose fasting level) of sample subjects with heteroskedastic measurement errors. Using a simple example, we compare the usual mixed model BLUP to a similar predictor based on a mixed model framed in a finite population (FPMM) setup with two sources of variability, the first of which corresponds to simple random sampling and the second, to heteroskedastic measurement errors. Under this last approach, we show that when measurement errors are subject-specific, the BLUP shrinkage constants are based on a pooled measurement error variance as opposed to the individual ones generally considered for the usual mixed model BLUP. In contrast, when the heteroskedastic measurement errors are measurement condition-specific, the FPMM BLUP involves different shrinkage constants. We also show that in this setup, when measurement errors are subject-specific, the usual mixed model predictor is biased but has a smaller mean squared error than the FPMM BLUP which point to some difficulties in the interpretation of such predictors. PMID:22162621

  16. 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.

  17. 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.

  18. 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.

  19. Clinical prediction and the idea of a population.

    PubMed

    Armstrong, David

    2017-01-01

    Using an analysis of the British Medical Journal over the past 170 years, this article describes how changes in the idea of a population have informed new technologies of medical prediction. These approaches have largely replaced older ideas of clinical prognosis based on understanding the natural histories of the underlying pathologies. The 19(th)-century idea of a population, which provided a denominator for medical events such as births and deaths, was constrained in its predictive power by its method of enumerating individual bodies. During the 20(th) century, populations were increasingly constructed through inferential techniques based on patient groups and samples seen to possess variable characteristics. The emergence of these new virtual populations created the conditions for the emergence of predictive algorithms that are used to foretell our medical futures.

  20. 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.

  1. Biotic Population Dynamics: Creative Biotic Patterns

    NASA Astrophysics Data System (ADS)

    Sabelli, Hector; Kovacevic, Lazar

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

  2. 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.

  3. 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...

  4. 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...

  5. Effects of rainfall on Culex mosquito population dynamics.

    PubMed

    Valdez, L D; Sibona, G J; Diaz, L A; Contigiani, M S; Condat, C A

    2017-03-27

    The dynamics of a mosquito population depends heavily on climatic variables such as temperature and precipitation. Since climate change models predict that global warming will impact on the frequency and intensity of rainfall, it is important to understand how these variables affect the mosquito populations. We present a model of the dynamics of a Culex quinquefasciatus mosquito population that incorporates the effect of rainfall and use it to study the influence of the number of rainy days and the mean monthly precipitation on the maximum yearly abundance of mosquitoes Mmax. Additionally, using a fracturing process, we investigate the influence of the variability in daily rainfall on Mmax. We find that, given a constant value of monthly precipitation, there is an optimum number of rainy days for which Mmax is a maximum. On the other hand, we show that increasing daily rainfall variability reduces the dependence of Mmax on the number of rainy days, leading also to a higher abundance of mosquitoes for the case of low mean monthly precipitation. Finally, we explore the effect of the rainfall in the months preceding the wettest season, and we obtain that a regimen with high precipitations throughout the year and a higher variability tends to advance slightly the time at which the peak mosquito abundance occurs, but could significantly change the total mosquito abundance in a year.

  6. 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

  7. Predicting the Future Impact of Droughts on Ungulate Populations in Arid and Semi-Arid Environments

    PubMed Central

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

    2012-01-01

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

  8. Dynamics of genome rearrangement in bacterial populations.

    PubMed

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

    2008-07-18

    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.

  9. 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.

    2015-12-01

    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

  10. Evaluation of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Populations

    PubMed Central

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

    2011-01-01

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

  11. Dynamic situation assessment and prediction (DSAP)

    NASA Astrophysics Data System (ADS)

    Sisti, Alex F.

    2003-09-01

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

  12. The role of population inertia in predicting the outcome of stage-structured biological invasions.

    PubMed

    Guiver, Chris; Dreiwi, Hanan; Filannino, Donna-Maria; Hodgson, Dave; Lloyd, Stephanie; Townley, Stuart

    2015-07-01

    Deterministic dynamic models for coupled resident and invader populations are considered with the purpose of finding quantities that are effective at predicting when the invasive population will become established asymptotically. A key feature of the models considered is the stage-structure, meaning that the populations are described by vectors of discrete developmental stage- or age-classes. The vector structure permits exotic transient behaviour-phenomena not encountered in scalar models. Analysis using a linear Lyapunov function demonstrates that for the class of population models considered, a large so-called population inertia is indicative of successful invasion. Population inertia is an indicator of transient growth or decline. Furthermore, for the class of models considered, we find that the so-called invasion exponent, an existing index used in models for invasion, is not always a reliable comparative indicator of successful invasion. We highlight these findings through numerical examples and a biological interpretation of why this might be the case is discussed.

  13. Dynamic distributions and population declines of Golden-winged Warblers

    USGS Publications Warehouse

    Rosenberg, Kenneth V.; Will, Tom; Buehler, David A.; Barker Swarthout, Sara; Thogmartin, Wayne E.; Chandler, Richard

    2016-01-01

    With an estimated breeding population in 2010 of 383,000 pairs, the Golden-winged Warbler (Vermivora chrysoptera) is among the most vulnerable and steeply declining of North American passerines. This species also has exhibited among the most dynamic breeding distributions, with populations expanding and then contracting over the past 150 years in response to regional habitat changes, interactions with closely related Blue-winged Warblers (V. cyanoptera), and possibly climate change. Since 1966, the rangewide population has declined by >70% (-2.3% per year; latest North American Breeding Bird Survey data), with much steeper declines in the Appalachian Mountains bird conservation region (-8.3% per year, 98% overall decline). Despite apparently stable or increasing populations in the northwestern part of the range (Minnesota, Manitoba), population estimates for Golden-winged Warbler have continued to decline by 18% from the decade of the 1990s to the 2000s. Population modeling predicts a further decline to roughly 37,000 individuals by 2100, with the species likely to persist only in Manitoba, Minnesota, and possibly Ontario. To delineate the present-day distribution and to identify population concentrations that could serve as conservation focus areas, we compiled rangewide survey data collected in 2000-2006 in 21 states and 3 Canadian provinces, as part of the Golden-winged Warbler Atlas Project (GOWAP), supplemented by state and provincial Breeding Bird Atlas data and more recent observations in eBird. Based on >8,000 GOWAP surveys for Golden-winged and Blue-winged warblers and their hybrids, we mapped occurrence of phenotypically pure and mixed populations in a roughly 0.5-degree grid across the species’ ranges. Hybrids and mixed Golden-winged-Blue-winged populations occurred in a relatively narrow zone across Minnesota, Wisconsin, Michigan, southern Ontario, and northern New York. Phenotypically pure Golden-winged Warbler populations occurred north of this

  14. Dynamic Model Predicting Overweight, Obesity, and Extreme Obesity Prevalence Trends

    PubMed Central

    Thomas, Diana M.; Weedermann, Marion; Fuemmeler, Bernard F.; Martin, Corby K.; Dhurandhar, Nikhil V.; Bredlau, Carl; Heymsfield, Steven B.; Ravussin, Eric; Bouchard, Claude

    2013-01-01

    Objective Obesity prevalence in the United States (US) appears to be leveling, but the reasons behind the plateau remain unknown. Mechanistic insights can be provided from a mathematical model. The objective of this study is to model known multiple population parameters associated with changes in body mass index (BMI) classes and to establish conditions under which obesity prevalence will plateau. Design and Methods A differential equation system was developed that predicts population-wide obesity prevalence trends. The model considers both social and non-social influences on weight gain, incorporates other known parameters affecting obesity trends, and allows for country specific population growth. Results The dynamic model predicts that: obesity prevalence is a function of birth rate and the probability of being born in an obesogenic environment; obesity prevalence will plateau independent of current prevention strategies; and the US prevalence of obesity, overweight, and extreme obesity will plateau by about 2030 at 28%, 32%, and 9%, respectively. Conclusions The US prevalence of obesity is stabilizing and will plateau, independent of current preventative strategies. This trend has important implications in accurately evaluating the impact of various anti-obesity strategies aimed at reducing obesity prevalence. PMID:23804487

  15. 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.

  16. 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.

  17. Temperature-driven regime shifts in the dynamics of size-structured populations.

    PubMed

    Ohlberger, Jan; Edeline, Eric; Vøllestad, Leif Asbjørn; Stenseth, Nils C; Claessen, David

    2011-02-01

    Global warming impacts virtually all biota and ecosystems. Many of these impacts are mediated through direct effects of temperature on individual vital rates. Yet how this translates from the individual to the population level is still poorly understood, hampering the assessment of global warming impacts on population structure and dynamics. Here, we study the effects of temperature on intraspecific competition and cannibalism and the population dynamical consequences in a size-structured fish population. We use a physiologically structured consumer-resource model in which we explicitly model the temperature dependencies of the consumer vital rates and the resource population growth rate. Our model predicts that increased temperature decreases resource density despite higher resource growth rates, reflecting stronger intraspecific competition among consumers. At a critical temperature, the consumer population dynamics destabilize and shift from a stable equilibrium to competition-driven generation cycles that are dominated by recruits. As a consequence, maximum age decreases and the proportion of younger and smaller-sized fish increases. These model predictions support the hypothesis of decreasing mean body sizes due to increased temperatures. We conclude that in size-structured fish populations, global warming may increase competition, favor smaller size classes, and induce regime shifts that destabilize population and community dynamics.

  18. Role of finite populations in determining evolutionary dynamics

    NASA Astrophysics Data System (ADS)

    Ray, Tane S.; Payne, Karl A.; Moseley, L. Leo

    2008-02-01

    The connection between the finite size of an evolving population and its dynamical behavior is examined through analytical and computational studies of a simple model of evolution. The infinite population limit of the model is shown to be governed by a special case of the quasispecies equations. A flat fitness landscape yields identical results for the dynamics of infinite and finite populations. On the other hand, a monotonically increasing fitness landscape shows “epochs” in the dynamics of finite populations that become more pronounced as the rate of mutation decreases. The details of the dynamics are profoundly different for any two simulation runs in that events arising from the stochastic noise in the pseudorandom number sequence are amplified. As the population size is increased or, equivalently, the mutation rate is increased, these epochs become smaller but do not entirely disappear.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Modelling food and population dynamics in honey bee colonies.

    PubMed

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

    2013-01-01

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

  6. 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.

  7. 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.

  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.

  9. 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

  10. 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

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

    USGS Publications Warehouse

    Runge, M.C.; Marra, P.P.; Greenberg, Russell; Marra, Peter 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.

  12. Population dynamics of cancer cells with cell state conversions

    PubMed Central

    Zhou, Da; Wu, Dingming; Li, Zhe; Qian, Minping; Zhang, Michael Q.

    2015-01-01

    Cancer stem cell (CSC) theory suggests a cell-lineage structure in tumor cells in which CSCs are capable of giving rise to the other non-stem cancer cells (NSCCs) but not vice versa. However, an alternative scenario of bidirectional interconversions between CSCs and NSCCs was proposed very recently. Here we present a general population model of cancer cells by integrating conventional cell divisions with direct conversions between different cell states, namely, not only can CSCs differentiate into NSCCs by asymmetric cell division, NSCCs can also dedifferentiate into CSCs by cell state conversion. Our theoretical model is validated when applying the model to recent experimental data. It is also found that the transient increase in CSCs proportion initiated from the purified NSCCs subpopulation cannot be well predicted by the conventional CSC model where the conversion from NSCCs to CSCs is forbidden, implying that the cell state conversion is required especially for the transient dynamics. The theoretical analysis also gives the condition such that our general model can be equivalently reduced into a simple Markov chain with only cell state transitions keeping the same cell proportion dynamics. PMID:26085954

  13. Complex population dynamics and the coalescent under neutrality.

    PubMed

    Volz, Erik M

    2012-01-01

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

  14. Africa's population and family planning dynamics.

    PubMed

    Segal, A

    1993-01-01

    The historical and current demography of Africa in this discussion focuses on the context of population policy, contraceptive use, reproductive behavior, polygamy, and economic impacts. Sub-Saharan Africa countries have the highest rate of population growth in the world. 50% are aged under 20 years, and 20% are aged under five years. Urban areas are growing at the fastest rates in the world (5-6% annually). Population density remains low, except for areas where there is high soil fertility. Many African countries recognize the need for population policies. The most important donor to Africa, the World Bank, has pressured African governments to adopt family planning (FP) programs. A major World Bank study has shown that more FP services are desired by African women. Family expenditures for the 1980s for FP were estimated at $100 million annually, of which $53 million was provided by donors. Further expansion in the program is needed. The World Bank targeted contraceptive use at 25% of African married couples. Except for Egypt and North African countries, contraceptive use is around 3-4%. Another perspective on population reduction is to expand programs for child spacing and postnatal nutrition of mothers and infants. There has been a failure to turn health systems around to low-cost preventive health, particularly in rural areas. Infant mortality must be reduced before fertility will decline. Population growth can be slowed by changing the status of African women (high social status and recognition are associated with high fertility), age of marriage, child spacing, agricultural productivity, and nutrition. Demographic data on Africa have only become available during the past 25 years. African demographers are in short supply and require training abroad. Demographic data gaps and reliability problems are offset by the recent availability and quantity of survey data. Historical demography has produced conflicting results. Although some investigators, such as Ester

  15. 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.

  16. Synchronization and stability in noisy population dynamics.

    PubMed

    Araujo, Sabrina B L; de Aguiar, M A M

    2008-02-01

    We study the stability and synchronization of predator-prey populations subjected to noise. The system is described by patches of local populations coupled by migration and predation over a neighborhood. When a single patch is considered, random perturbations tend to destabilize the populations, leading to extinction. If the number of patches is small, stabilization in the presence of noise is maintained at the expense of synchronization. As the number of patches increases, both the stability and the synchrony among patches increase. However, a residual asynchrony, large compared with the noise amplitude, seems to persist even in the limit of an infinite number of patches. Therefore, the mechanism of stabilization by asynchrony recently proposed by Abta [Phys. Rev. Lett. 98, 098104 (2007)], combining noise, diffusion, and nonlinearities, seems to be more general than first proposed.

  17. Workshop on Populations & Crowds: Dynamics, Disruptions and their Computational Models

    DTIC Science & Technology

    2015-01-01

    Aug-2012 9-Aug-2013 Approved for Public Release; Distribution Unlimited Final Report: Workshop on Populations & Crowds: Dynamics, Disruptions and... Disruptions , Social networks REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 10. SPONSOR/MONITOR’S ACRONYM(S) ARO 8. PERFORMING...Number of Papers published in non peer-reviewed journals: Final Report: Workshop on Populations & Crowds: Dynamics, Disruptions and their Computational

  18. Noise-induced stabilization in population dynamics.

    PubMed

    Parker, Matthew; Kamenev, Alex; Meerson, Baruch

    2011-10-28

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

  19. 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

  20. 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

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

    PubMed

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

    2015-07-07

    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.

  2. A framework for studying transient dynamics of population projection matrix models.

    PubMed

    Stott, Iain; Townley, Stuart; Hodgson, David James

    2011-09-01

    Empirical models are central to effective conservation and population management, and should be predictive of real-world dynamics. Available modelling methods are diverse, but analysis usually focuses on long-term dynamics that are unable to describe the complicated short-term time series that can arise even from simple models following ecological disturbances or perturbations. Recent interest in such transient dynamics has led to diverse methodologies for their quantification in density-independent, time-invariant population projection matrix (PPM) models, but the fragmented nature of this literature has stifled the widespread analysis of transients. We review the literature on transient analyses of linear PPM models and synthesise a coherent framework. We promote the use of standardised indices, and categorise indices according to their focus on either convergence times or transient population density, and on either transient bounds or case-specific transient dynamics. We use a large database of empirical PPM models to explore relationships between indices of transient dynamics. This analysis promotes the use of population inertia as a simple, versatile and informative predictor of transient population density, but criticises the utility of established indices of convergence times. Our findings should guide further development of analyses of transient population dynamics using PPMs or other empirical modelling techniques.

  3. 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.

  4. 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.

  5. 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...

  6. Optimal birth control of population dynamics.

    PubMed

    Chan, W L; Guo, B Z

    1989-11-01

    The authors studied optimal birth control policies for an age-structured population of McKendrick type which is a distributed parameter system involving 1st order partial differential equations with nonlocal bilinear boundary control. The functional analytic approach of Dubovitskii and Milyutin is adopted in the investigation. Maximum principles for problems with a free end condition and fixed final horizon are developed, and the time optimal control problems, the problem with target sets, and infinite planning horizon case are investigated.

  7. Reconstruction of cell population dynamics using CFSE

    PubMed Central

    Yates, Andrew; Chan, Cliburn; Strid, Jessica; Moon, Simon; Callard, Robin; George, Andrew JT; Stark, Jaroslav

    2007-01-01

    Background Quantifying cell division and death is central to many studies in the biological sciences. The fluorescent dye CFSE allows the tracking of cell division in vitro and in vivo and provides a rich source of information with which to test models of cell kinetics. Cell division and death have a stochastic component at the single-cell level, and the probabilities of these occurring in any given time interval may also undergo systematic variation at a population level. This gives rise to heterogeneity in proliferating cell populations. Branching processes provide a natural means of describing this behaviour. Results We present a likelihood-based method for estimating the parameters of branching process models of cell kinetics using CFSE-labeling experiments, and demonstrate its validity using synthetic and experimental datasets. Performing inference and model comparison with real CFSE data presents some statistical problems and we suggest methods of dealing with them. Conclusion The approach we describe here can be used to recover the (potentially variable) division and death rates of any cell population for which division tracking information is available. PMID:17565685

  8. Experimental test of an eco-evolutionary dynamic feedback loop between evolution and population density in the green peach aphid.

    PubMed

    Turcotte, Martin M; Reznick, David N; Daniel Hare, J

    2013-05-01

    An eco-evolutionary feedback loop is defined as the reciprocal impacts of ecology on evolutionary dynamics and evolution on ecological dynamics on contemporary timescales. We experimentally tested for an eco-evolutionary feedback loop in the green peach aphid, Myzus persicae, by manipulating initial densities and evolution. We found strong evidence that initial aphid density alters the rate and direction of evolution, as measured by changes in genotype frequencies through time. We also found that evolution of aphids within only 16 days, or approximately three generations, alters the rate of population growth and predicts density compared to nonevolving controls. The impact of evolution on population dynamics also depended on density. In one evolution treatment, evolution accelerated population growth by up to 10.3% at high initial density or reduced it by up to 6.4% at low initial density. The impact of evolution on population growth was as strong as or stronger than that caused by a threefold change in intraspecific density. We found that, taken together, ecological condition, here intraspecific density, alters evolutionary dynamics, which in turn alter concurrent population growth rate (ecological dynamics) in an eco-evolutionary feedback loop. Our results suggest that ignoring evolution in studies predicting population dynamics might lead us to over- or underestimate population density and that we cannot predict the evolutionary outcome within aphid populations without considering population size.

  9. 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

  10. 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.

  11. 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

  12. 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

  13. Feedback between Population and Evolutionary Dynamics Determines the Fate of Social Microbial Populations

    PubMed Central

    Sanchez, Alvaro; Gore, Jeff

    2013-01-01

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

  14. Dynamics and Predictability of Hurricane Dolly (2008)

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

    Through several cloud-resolving simulations with the Weather Research and Forecast (WRF-ARW) model, this study examines the dynamics and predictability of Hurricane Dolly (2008) with an emphasis on its initial development (around the time being declared as a tropical storm) and subsequent rapid intensification entering into the Gulf of Mexico. These WRF simulations include three that are directly initialized with the operational NCEP GFS analyses at 06, 12 and 18Z 20 July 2008, respectively (EXP06, EXP12, EXP18) and another the same as EXP06 except that the airborne Doppler velocity observations by a NOAA P3 aircraft during 12-15Z are assimilated with an ensemble-Kalman filter (ENKF06). Among the four experiments, only EXP06 fails to capture the rapid intensification and fails to develop the tropical storm into a mature hurricane. Preliminary comparison between the simulated fields of EXP06 and the GFS analysis at 12Z (e.g., IC of EXP12) indicates that large scale features favorable to the tropical cyclogenesis cannot be properly simulated in EXP06. The initial disturbance is rather weak positioned too far south-west that is far away from the primary convective. However, after the airborne radar data during 12-15Z are assimilated into the model, (from EXP06 into ENKF06), the ENKF06 simulation is greatly improved in that a well-organized warm-core vortex appears at the low level right after radar assimilation, which subsequently developed into a hurricane consistent with timing, track and intensity of observations. Interestingly, there are significant differences in the initial vortex position, structure and evolution among the three simulations (EXP12, EXP18, ENKF06) that all eventually develop a mature hurricane along the observed track (before landfall) with right timing after enters into the Gulf of Mexico. At 18Z 20 July, there is no apparent initial low-level cyclonic vortex in EXP12 and EXP18 (that is assimilated into ENKF06 due to radar observations

  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. Transient population dynamics: Relations to life history and initial population state

    USGS Publications Warehouse

    Koons, D.N.; Grand, J.B.; Zinner, B.; Rockwell, R.F.

    2005-01-01

    Most environments are variable and disturbances (e.g., hurricanes, fires) can lead to substantial changes in a population's state (i.e., age, stage, or size distribution). In these situations, the long-term (i.e., asymptotic) measure of population growth rate (??1) may inaccurately represent population growth in the short-term. Thus, we calculated the short-term (i.e., transient) population growth rate and its sensitivity to changes in the life-cycle parameters for three bird and three mammal species with widely varying life histories. Further, we performed these calculations for initial population states that spanned the entire range of possibilities. Variation in a population's initial net reproductive value largely explained the variation in transient growth rates and their sensitivities to changes in life-cycle parameters (all AICc ??? 6.67 units better than the null model, all R2 ??? 0.55). Additionally, the transient fertility and adult survival sensitivities tended to increase with the initial net reproductive value of the population, whereas the sub-adult survival sensitivity decreased. Transient population dynamics of long-lived, slow reproducing species were more variable and more different than asymptotic dynamics than they were for short-lived, fast reproducing species. Because ??1 can be a biased estimate of the actual growth rate in the short-term (e.g., 19% difference), conservation and wildlife biologists should consider transient dynamics when developing management plans that could affect a population's state, or whenever population state could be unstable.

  17. Dynamical population synthesis: constructing the stellar single and binary contents of galactic field populations

    NASA Astrophysics Data System (ADS)

    Marks, Michael; Kroupa, Pavel

    2011-11-01

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

  18. Spatial and temporal dynamics of fucoid populations (Ascophyllum nodosum and Fucus serratus): a comparison between central and range edge populations.

    PubMed

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

    2014-01-01

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

  19. 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

  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. Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics

    PubMed Central

    Noecker, Cecilia; Schaefer, Krista; Zaccheo, Kelly; Yang, Yiding; Day, Judy; Ganusov, Vitaly V.

    2015-01-01

    Upon infection of a new host, human immunodeficiency virus (HIV) replicates in the mucosal tissues and is generally undetectable in circulation for 1–2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the “standard” mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV). First, we found that the mode of virus production by infected cells (budding vs. bursting) has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral dose. These results

  2. 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

  3. Unstable dynamics and population limitation in mountain hares.

    PubMed

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

    2007-11-01

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

  4. 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.

  5. Population dynamics of white-winged scoters

    USGS Publications Warehouse

    Krementz, D.G.; Brown, P.W.; Kehoe, F.P.; Houston, C.S.

    1997-01-01

    A significant (P < 0.01) decline between 1961 and 1993 in ratio of harvested young per adult in the Atlantic Flyway (age ration) of white-winged scoters (Melanitta fusca) led us to examine annual survival rates and harvest of this species. Compared to waterfowl with similar life histories, black scoters (M. nigra) and surf scoters (M. perspicillata), the decline in age ratios of white-winged scoter age ratios was not significantly different (P = 0.11). Adult females banded at Redberry Lake, Saskatchewan that winter along both coasts, had high annual survival rates (0.773 plus or minus 0.0176 [SE]). High harvest in the Atlantic Flyway was not followed by an increase in production (age ratios) the following year or 2, i.e., there was no short-term rebound in recruitment by the population. Harvest of white-winged scoters in the Atlantic Flyway was explained by the age ratio in the fall flight and by hunter effort.

  6. 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.

  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. 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.

  9. Individual Identifiability Predicts Population Identifiability in Forensic Microsatellite Markers.

    PubMed

    Algee-Hewitt, Bridget F B; Edge, Michael D; Kim, Jaehee; Li, Jun Z; Rosenberg, Noah A

    2016-04-04

    Highly polymorphic genetic markers with significant potential for distinguishing individual identity are used as a standard tool in forensic testing [1, 2]. At the same time, population-genetic studies have suggested that genetically diverse markers with high individual identifiability also confer information about genetic ancestry [3-6]. The dual influence of polymorphism levels on ancestry inference and forensic desirability suggests that forensically useful marker sets with high levels of individual identifiability might also possess substantial ancestry information. We study a standard forensic marker set-the 13 CODIS loci used in the United States and elsewhere [2, 7-9]-together with 779 additional microsatellites [10], using direct population structure inference to test whether markers with substantial individual identifiability also produce considerable information about ancestry. Despite having been selected for individual identification and not for ancestry inference [11], the CODIS markers generate nontrivial model-based clustering patterns similar to those of other sets of 13 tetranucleotide microsatellites. Although the CODIS markers have relatively low values of the F(ST) divergence statistic, their high heterozygosities produce greater ancestry inference potential than is possessed by less heterozygous marker sets. More generally, we observe that marker sets with greater individual identifiability also tend toward greater population identifiability. We conclude that population identifiability regularly follows as a byproduct of the use of highly polymorphic forensic markers. Our findings have implications for the design of new forensic marker sets and for evaluations of the extent to which individual characteristics beyond identification might be predicted from current and future forensic data.

  10. Gardnerella vaginalis population dynamics in bacterial vaginosis.

    PubMed

    Hilbert, D W; Schuyler, J A; Adelson, M E; Mordechai, E; Sobel, J D; Gygax, S E

    2017-02-14

    Bacterial vaginosis (BV) is the leading cause of vaginal discharge and is associated with the facultative Gram-variable bacterium Gardnerella vaginalis, whose population structure consists of four clades. Our goal was to determine if these clades differ with regard to abundance during BV. We performed a short-term longitudinal study of BV. Patients were evaluated according to the Amsel criteria and Nugent scoring at initial diagnosis, immediately after treatment and at a 40- to 45-day follow-up visit. G. vaginalis clade abundance was determined by quantitative real-time polymerase chain reactions (qPCRs). Among all specimens, the abundance of clades 1 and 4 were higher than that of clades 2 and 3 (P < 0.001). In general, the abundance of each clade increased with the degree of vaginal dysbiosis, as determined by the Nugent score and was greater in women with Amsel 4 compared with those with Amsel 0. Only clade 1 abundance was greater when Amsel 0 or 1 specimens were compared with Amsel 2 or 3 specimens (P < 0.01). Following antimicrobial treatment, abundance of clades 1 (P < 0.001) and 4 (P < 0.05) decreased regardless of the clinical and microbiological outcome, whereas clade 2 only decreased in women who had a sustained treatment response for 40-45 days (P < 0.01). Recurrent BV was characterized by post-treatment increases of clade 1 and 2 (P < 0.01). Clades 1 and 4 predominate in vaginal specimens. Clade abundance differs with regard to the Nugent score, the Amsel criteria, and response to therapy and BV recurrence.

  11. 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

  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. Real-Time Bioluminescent Tracking of Cellular Population Dynamics

    PubMed Central

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

    2015-01-01

    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. PMID:24166372

  14. Spatially structured population dynamics in feral oilseed rape.

    PubMed Central

    Crawley, Michael J.; Brown, Susan L.

    2004-01-01

    We studied the population dynamics of feral oilseed rape (Brassica napus) for 10 years (1993-2002) in 3658 adjacent permanent 100 m quadrats in the verges of the M25 motorway around London, UK. The aim was to determine the relative importance of different factors affecting the observed temporal patterns of population dynamics and their spatial correlations. A wide range of population dynamics was observed (downward or upward trends, cycles, local extinctions and recolonizations), but overall the populations were not self-replacing (lambda < 1). Many quadrats remained unoccupied throughout the study period, but a few were occupied at high densities for all 10 years. Most quadrats showed transient oilseed rape populations, lasting 1-4 years. There were strong spatial patterns in mean population density, associated with soil conditions and the successional age of the plant community dominating the verge, and these large-scale spatial patterns were highly consistent from year to year. The importance of seed spilled from trucks in transit to the processing plant at Erith in Kent was confirmed: rape populations were significantly higher on the 'to Erith' verge than the 'from Erith' verge (overall mean 2.83-fold greater stem density). Quadrats in which lambda > 1 were much more frequent in the 'to Erith' verge, indicating that seed immigration can give the spurious impression of self-replacing population dynamics in time-series analysis. There was little evidence of a pervasive Moran effect, and climatic forcing did not produce widespread large-scale synchrony in population dynamics for the motorway as a whole; just 23% of quadrats had significant rank correlations with the mean time-series. There was, however, significant local spatial synchrony of population dynamics, apparently associated with soil disturbance and seed input. This study draws attention to the possibility that different processes may impose population synchrony at different scales. We hypothesize that

  15. 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,…

  16. A mathematical model of population dynamics for Batesian mimicry system.

    PubMed

    Seno, Hiromi; Kohno, Takahiro

    2012-01-01

    We analyse a mathematical model of the population dynamics among a mimic, a corresponding model, and their common predator populations. Predator changes its search-and-attack probability by forming and losing its search image. It cannot distinguish the mimic from the model. Once a predator eats a model individual, it comes to omit both the model and the mimic species from its diet menu. If a predator eats a mimic individual, it comes to increase the search-and-attack probability for both model and mimic. The predator may lose the repulsive/attractive search image with a probability per day. By analysing our model, we can derive the mathematical condition for the persistence of model and mimic populations, and then get the result that the condition for the persistence of model population does not depend on the mimic population size, while the condition for the persistence of mimic population does depend the predator's memory of search image.

  17. 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

  18. Stochastic Population Dynamics of a Montane Ground-Dwelling Squirrel

    PubMed Central

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

    2012-01-01

    Understanding the causes and consequences of population fluctuations is a central goal of ecology. We used demographic data from a long-term (1990–2008) study and matrix population models to investigate factors and processes influencing the dynamics and persistence of a golden-mantled ground squirrel (Callospermophilus lateralis) population, inhabiting a dynamic subalpine habitat in Colorado, USA. The overall deterministic population growth rate λ was 0.94±SE 0.05 but it varied widely over time, ranging from 0.45±0.09 in 2006 to 1.50±0.12 in 2003, and was below replacement (λ<1) for 9 out of 18 years. The stochastic population growth rate λs was 0.92, suggesting a declining population; however, the 95% CI on λs included 1.0 (0.52–1.60). Stochastic elasticity analysis showed that survival of adult females, followed by survival of juvenile females and litter size, were potentially the most influential vital rates; analysis of life table response experiments revealed that the same three life history variables made the largest contributions to year-to year changes in λ. Population viability analysis revealed that, when the influences of density dependence and immigration were not considered, the population had a high (close to 1.0 in 50 years) probability of extinction. However, probability of extinction declined to as low as zero when density dependence and immigration were considered. Destabilizing effects of stochastic forces were counteracted by regulating effects of density dependence and rescue effects of immigration, which allowed our study population to bounce back from low densities and prevented extinction. These results suggest that dynamics and persistence of our study population are determined synergistically by density-dependence, stochastic forces, and immigration. PMID:22479616

  19. Asynchronous population dynamics of Siberian lemmings across the Palaearctic tundra.

    PubMed

    Erlinge, Sam; Danell, Kjell; Frodin, Peter; Hasselquist, Dennis; Nilsson, Patric; Olofsson, Eva-Britt; Svensson, Mikael

    1999-06-01

    The synchrony of Siberian lemming (Lemmus sibiricus L.) population dynamics was investigated during a ship-borne expedition along the Palaearctic tundra coast in the summer of 1994. On 12 sites along the coast from the Kola Peninsula to Wrangel Island, relative densities of lemmings were recorded using a standardised snap-trapping programme. The phase position of the lemming cycle in each of the studied populations was determined based on current density estimates, signs of previous density and the age profile of each population (ageing based on eye lens mass). In addition, dendrochronological methods were used to determine when the last peak in the density of microtine populations occurred at each site. The examined lemming populations were in different phases of the lemming cycle. Some populations were in the peak phase, as indicated by high current densities, an age profile in which older individuals were well represented, and signs of high previous density (abundant old lemming faeces). Other populations were in the decline phase, as reflected in a moderate current density, a predominance of older individuals and signs of high previous density. Populations in the low phase had an extremely low current density and showed signs of high previous density, while populations in the increase phase had a moderate current density, a predominance of younger individuals and showed signs of low previous density. The results of phase determinations based on dendrochronological methods support the findings based on lemming demography. Recent Russian studies carried out on some of the sites also agreed with our phase determination results. Thus, on a regional scale (across the whole Palaearctic tundra), the population dynamics of Siberian lemmings can be considered asynchronous. However, sites situated adjacent to each other were often phase synchronous, suggesting a more fine-grained pattern of dynamics with synchrony over distances as long as 1000 km or so, e.g. the Yamal

  20. Stochastic population dynamics of a montane ground-dwelling squirrel.

    PubMed

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

    2012-01-01

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

  1. Dynamical Interactions Between Human Populations and Landscapes in Barrier Island Environments

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

  2. 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.

  3. Recolonizing wolves and mesopredator suppression of coyotes: impacts on pronghorn population dynamics.

    PubMed

    Berger, Kim Murray; Conner, Mary M

    2008-04-01

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

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

    USGS Publications Warehouse

    Emlen, John M.; Springman, Kathrine 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.

  5. 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.

  6. 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

  7. Predicting NCLEX-RN success in a diverse student population.

    PubMed

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

    2011-05-01

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

  8. A Theoretical Approach to Understanding Population Dynamics with Seasonal Developmental Durations

    NASA Astrophysics Data System (ADS)

    Lou, Yijun; Zhao, Xiao-Qiang

    2017-04-01

    There is a growing body of biological investigations to understand impacts of seasonally changing environmental conditions on population dynamics in various research fields such as single population growth and disease transmission. On the other side, understanding the population dynamics subject to seasonally changing weather conditions plays a fundamental role in predicting the trends of population patterns and disease transmission risks under the scenarios of climate change. With the host-macroparasite interaction as a motivating example, we propose a synthesized approach for investigating the population dynamics subject to seasonal environmental variations from theoretical point of view, where the model development, basic reproduction ratio formulation and computation, and rigorous mathematical analysis are involved. The resultant model with periodic delay presents a novel term related to the rate of change of the developmental duration, bringing new challenges to dynamics analysis. By investigating a periodic semiflow on a suitably chosen phase space, the global dynamics of a threshold type is established: all solutions either go to zero when basic reproduction ratio is less than one, or stabilize at a positive periodic state when the reproduction ratio is greater than one. The synthesized approach developed here is applicable to broader contexts of investigating biological systems with seasonal developmental durations.

  9. 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 ...

  10. 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

  11. 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

  12. 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."

  13. Predicting the evolution of complex networks via similarity dynamics

    NASA Astrophysics Data System (ADS)

    Wu, Tao; Chen, Leiting; Zhong, Linfeng; Xian, Xingping

    2017-01-01

    Almost all real-world networks are subject to constant evolution, and plenty of them have been investigated empirically to uncover the underlying evolution mechanism. However, the evolution prediction of dynamic networks still remains a challenging problem. The crux of this matter is to estimate the future network links of dynamic networks. This paper studies the evolution prediction of dynamic networks with link prediction paradigm. To estimate the likelihood of the existence of links more accurate, an effective and robust similarity index is presented by exploiting network structure adaptively. Moreover, most of the existing link prediction methods do not make a clear distinction between future links and missing links. In order to predict the future links, the networks are regarded as dynamic systems in this paper, and a similarity updating method, spatial-temporal position drift model, is developed to simulate the evolutionary dynamics of node similarity. Then the updated similarities are used as input information for the future links' likelihood estimation. Extensive experiments on real-world networks suggest that the proposed similarity index performs better than baseline methods and the position drift model performs well for evolution prediction in real-world evolving networks.

  14. A discrete stage-structured model of California newt population dynamics during a period of drought.

    PubMed

    Jones, Marjorie T; Milligan, William R; Kats, Lee B; Vandergon, Thomas L; Honeycutt, Rodney L; Fisher, Robert N; Davis, Courtney L; Lucas, Timothy A

    2017-02-07

    We introduce a mathematical model for studying the population dynamics under drought of the California newt (Taricha torosa), a species of special concern in the state of California. Since 2012, California has experienced a record-setting drought, and multiple studies predict drought conditions currently underway will persist and even increase in severity. Recent declines and local extinctions of California newt populations in Santa Monica Mountain streams motivate our study of the impact of drought on newt population sizes. Although newts are terrestrial salamanders, they migrate to streams each spring to breed and lay eggs. Since egg and larval stages occur in water, a precipitation deficit due to drought conditions reduces the space for newt egg-laying and the necessary habitat for larval development. To mathematically forecast newt population dynamics, we develop a nonlinear system of discrete equations that includes demographic parameters such as survival rates for newt life stages and egg production, which depend on habitat availability and rainfall. We estimate these demographic parameters using 15 years of stream survey data collected from Cold Creek in Los Angeles County, California, and our model captures the observed decline of the parameterized Cold Creek newt population. Based upon data analysis, we predict how the number of available newt egg-laying sites varies with annual precipitation. Our model allows us to make predictions about how the length and severity of drought can affect the likelihood of persistence and the time to critical endangerment of a local newt population. We predict that sustained severe drought will critically endanger the newt population but that the newt population can rebound if a drought is sufficiently short.

  15. Improving structure-based function prediction using molecular dynamics

    PubMed Central

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

    2009-01-01

    Summary The number of molecules with solved three-dimensional structure but unknown function is increasing rapidly. Particularly problematic are novel folds with little detectable similarity to molecules of known function. Experimental assays can determine the functions of such molecules, but are time-consuming and expensive. Computational approaches can identify potential functional sites; however, these approaches generally rely on single static structures and do not use information about dynamics. In fact, structural dynamics can enhance function prediction: we coupled molecular dynamics simulations with structure-based function prediction algorithms that identify Ca2+ binding sites. When applied to 11 challenging proteins, both methods showed substantial improvement in performance, revealing 22 more sites in one case and 12 more in the other, with a modest increase in apparent false positives. Thus, we show that treating molecules as dynamic entities improves the performance of structure-based function prediction methods. PMID:19604472

  16. 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.

  17. Dynamical quorum sensing and clustering dynamics in a population of spatially distributed active rotators

    NASA Astrophysics Data System (ADS)

    Sakaguchi, Hidetsugu; Maeyama, Satomi

    2013-02-01

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

  18. Risk Prediction for Adverse Pregnancy Outcomes in a Medicaid Population

    PubMed Central

    Hall, Eric S.; Greenberg, James M.; Kelly, Elizabeth A.

    2015-01-01

    Abstract Background: Despite prior efforts to develop pregnancy risk prediction models, there remains a lack of evidence to guide implementation in clinical practice. The current aim was to develop and validate a risk tool grounded in social determinants theory for use among at-risk Medicaid patients. Methods: This was a retrospective cohort study of 409 women across 17 Cincinnati health centers between September 2013 and April 2014. The primary outcomes included preterm birth, low birth weight, intrauterine fetal demise, and neonatal death. After random allocation into derivation and validation samples, a multivariable model was developed, and a risk scoring system was assessed and validated using area under the receiver operating characteristic curve (AUROC) values. Results: The derived multivariable model (n=263) included: prior preterm birth, interpregnancy interval, late prenatal care, comorbid conditions, history of childhood abuse, substance use, tobacco use, body mass index, race, twin gestation, and short cervical length. Using a weighted risk score, each additional point was associated with an odds ratio of 1.57 for adverse outcomes, p<0.001, AUROC=0.79. In the validation sample (n=146), each additional point conferred an odds ratio of 1.20, p=0.03, AUROC=0.63. Using a cutoff of 20% probability for the outcome, sensitivity was 29%, with specificity 82%. Positive and negative predictive values were 22% and 85%, respectively. Conclusions: Risk scoring based on social determinants can discriminate pregnancy risk within a Medicaid population; however, performance is modest and consistent with prior prediction models. Future research is needed to evaluate whether implementation of risk scoring in Medicaid prenatal care programs improves clinical outcomes. PMID:26102375

  19. Radial propagation in population dynamics with density-dependent diffusion

    NASA Astrophysics Data System (ADS)

    Ngamsaad, Waipot

    2014-01-01

    Population dynamics that evolve in a radial symmetric geometry are investigated. The nonlinear reaction-diffusion model, which depends on population density, is employed as the governing equation for this system. The approximate analytical solution to this equation is found. It shows that the population density evolves from the initial state and propagates in a traveling-wave-like manner for a long-time scale. If the distance is insufficiently long, the curvature has an ineluctable influence on the density profile and front speed. In comparison, the analytical solution is in agreement with the numerical solution.

  20. Spatial structure, environmental heterogeneity, and population dynamics: analysis of the coupled logistic map.

    PubMed

    Kendall, B E; Fox, G A

    1998-08-01

    Spatial extent can have two important consequences for population dynamics: It can generate spatial structure, in which individuals interact more intensely with neighbors than with more distant conspecifics, and it allows for environmental heterogeneity, in which habitat quality varies spatially. Studies of these features are difficult to interpret because the models are complex and sometimes idiosyncratic. Here we analyze one of the simplest possible spatial population models, to understand the mathematical basis for the observed patterns: two patches coupled by dispersal, with dynamics in each patch governed by the logistic map. With suitable choices of parameters, this model can represent spatial structure, environmental heterogeneity, or both in combination. We synthesize previous work and new analyses on this model, with two goals: to provide a comprehensive baseline to aid our understanding of more complex spatial models, and to generate predictions about the effects of spatial structure and environmental heterogeneity on population dynamics. Spatial structure alone can generate positive, negative, or zero spatial correlations between patches when dispersal rates are high, medium, or low relative to the complexity of the local dynamics. It can also lead to quasiperiodicity and hyperchaos, which are not present in the nonspatial model. With density-independent dispersal, spatial structure cannot destabilize equilibria or periodic orbits that would be stable in the absence of space. When densities in the two patches are uncorrelated, the probability that the population in a patch reaches extreme low densities is reduced relative to the same patch in isolation; this "rescue effect" would reduce the probability of metapopulation extinction beyond the simple effect of spreading of risk. Pure environmental heterogeneity always produces positive spatial correlations. The dynamics of the entire population is approximated by a nonspatial model with mean patch

  1. 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.

  2. Within- and among-population variation in vital rates and population dynamics in a variable environment.

    PubMed

    Vincenzi, Simone; Mangel, Marc; Jesensˇek, Dusˇan; Garza, John C; Crivelli, Alain J

    2016-10-01

    Understanding the causes of within- and among-population differences in vital rates, life histories, and population dynamics is a central topic in ecology. To understand how within- and among-population variation emerges, we need long-term studies that include episodic events and contrasting environmental conditions, data to characterize individual and shared variation, and statistical models that can tease apart shared and individual contribution to the observed variation. We used long-term tag-recapture data to investigate and estimate within- and among-population differences in vital rates, life histories, and population dynamics of marble trout Salmo marmoratus, an endemic freshwater salmonid with a narrow range. Only ten populations of pure marble trout persist in headwaters of Alpine rivers in western Slovenia. Marble trout populations are also threatened by floods and landslides, which have already caused the extinction of two populations in recent years. We estimated and determined causes of variation in growth, survival, and recruitment both within and among populations, and evaluated trade-offs between them. Specifically, we estimated the responses of these traits to variation in water temperature, density, sex, early life conditions, and extreme events. We found that the effects of population density on traits were mostly limited to the early stages of life and that growth trajectories were established early in life. We found no clear effects of water temperature on vital rates. Population density varied over time, with flash floods and debris flows causing massive mortalities (>55% decrease in survival with respect to years with no floods) and threatening population persistence. Apart from flood events, variation in population density within streams was largely determined by variation in recruitment, with survival of older fish being relatively constant over time within populations, but substantially different among populations. Marble trout show a fast

  3. The ARIC predictive model reliably predicted risk of type II diabetes in Asian populations

    PubMed Central

    2012-01-01

    Background Identification of high-risk individuals is crucial for effective implementation of type 2 diabetes mellitus prevention programs. Several studies have shown that multivariable predictive functions perform as well as the 2-hour post-challenge glucose in identifying these high-risk individuals. The performance of these functions in Asian populations, where the rise in prevalence of type 2 diabetes mellitus is expected to be the greatest in the next several decades, is relatively unknown. Methods Using data from three Asian populations in Singapore, we compared the performance of three multivariate predictive models in terms of their discriminatory power and calibration quality: the San Antonio Health Study model, Atherosclerosis Risk in Communities model and the Framingham model. Results The San Antonio Health Study and Atherosclerosis Risk in Communities models had better discriminative powers than using only fasting plasma glucose or the 2-hour post-challenge glucose. However, the Framingham model did not perform significantly better than fasting glucose or the 2-hour post-challenge glucose. All published models suffered from poor calibration. After recalibration, the Atherosclerosis Risk in Communities model achieved good calibration, the San Antonio Health Study model showed a significant lack of fit in females and the Framingham model showed a significant lack of fit in both females and males. Conclusions We conclude that adoption of the ARIC model for Asian populations is feasible and highly recommended when local prospective data is unavailable. PMID:22497781

  4. 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.

  5. Suppression of Beneficial Mutations in Dynamic Microbial Populations

    NASA Astrophysics Data System (ADS)

    Bittihn, Philip; Hasty, Jeff; Tsimring, Lev S.

    2017-01-01

    Quantitative predictions for the spread of mutations in bacterial populations are essential to interpret evolution experiments and to improve the stability of synthetic gene circuits. We derive analytical expressions for the suppression factor for beneficial mutations in populations that undergo periodic dilutions, covering arbitrary population sizes, dilution factors, and growth advantages in a single stochastic model. We find that the suppression factor grows with the dilution factor and depends nontrivially on the growth advantage, resulting in the preferential elimination of mutations with certain growth advantages. We confirm our results by extensive numerical simulations.

  6. Predicting Subnational Ebola Virus Disease Epidemic Dynamics from Sociodemographic Indicators

    PubMed Central

    Valeri, Linda; Patterson-Lomba, Oscar; Gurmu, Yared; Ablorh, Akweley; Bobb, Jennifer; Townes, F. William; Harling, Guy

    2016-01-01

    Background The recent Ebola virus disease (EVD) outbreak in West Africa has spread wider than any previous human EVD epidemic. While individual-level risk factors that contribute to the spread of EVD have been studied, the population-level attributes of subnational regions associated with outbreak severity have not yet been considered. Methods To investigate the area-level predictors of EVD dynamics, we integrated time series data on cumulative reported cases of EVD from the World Health Organization and covariate data from the Demographic and Health Surveys. We first estimated the early growth rates of epidemics in each second-level administrative district (ADM2) in Guinea, Sierra Leone and Liberia using exponential, logistic and polynomial growth models. We then evaluated how these growth rates, as well as epidemic size within ADM2s, were ecologically associated with several demographic and socio-economic characteristics of the ADM2, using bivariate correlations and multivariable regression models. Results The polynomial growth model appeared to best fit the ADM2 epidemic curves, displaying the lowest residual standard error. Each outcome was associated with various regional characteristics in bivariate models, however in stepwise multivariable models only mean education levels were consistently associated with a worse local epidemic. Discussion By combining two common methods—estimation of epidemic parameters using mathematical models, and estimation of associations using ecological regression models—we identified some factors predicting rapid and severe EVD epidemics in West African subnational regions. While care should be taken interpreting such results as anything more than correlational, we suggest that our approach of using data sources that were publicly available in advance of the epidemic or in real-time provides an analytic framework that may assist countries in understanding the dynamics of future outbreaks as they occur. PMID:27732614

  7. 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.

  8. 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...

  9. Population Dynamics: A Curriculum Guide for Elementary and Secondary Teachers.

    ERIC Educational Resources Information Center

    Byrne, Robert; And Others

    Presented is one of five Wildlife and Environmental Education Teaching units that deal with resource management in a way that includes man as user and manager of natural resources. Included are activities (with their suggested grade levels) that deal with population dynamics. Fifteen supportive activities are described. A list of recommended films…

  10. Equilibrium solutions for microscopic stochastic systems in population dynamics.

    PubMed

    Lachowicz, Mirosław; Ryabukha, Tatiana

    2013-06-01

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

  11. 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.

  12. 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.

  13. 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

  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. 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

  16. Metamodels for transdisciplinary analysis of wildlife population dynamics.

    PubMed

    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.

  17. 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.

  18. 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

  19. Population dynamics and climate change: what are the links?

    PubMed

    Stephenson, Judith; Newman, Karen; Mayhew, Susannah

    2010-06-01

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

  20. Identifying interactions among salmon populations from observed dynamics.

    PubMed

    Fujiwara, Masami

    2008-01-01

    A simple direct correlation analysis of individual counts between different populations often fails to characterize the true nature of population interactions; however, the most common data type available for population studies is count data, and one of the most important objectives in population and community ecology is to identify interactions among populations. Here, I examine the dynamics of the spawning abundance of fall-run chinook salmon spawning within the California Central Valley and the Klamath Basin, California, and the Columbia River Basin, Oregon. I analyzed multiple time series from each watershed using a multivariate time-series technique called maximum autocorrelation factor analysis. This technique was used for finding common underlying trends in escapement abundance within each watershed. These trends were further investigated to identify potential resource-mediated interactions among the three groups of salmon. Each group is affected by multiple trends that are likely to be affected by environmental factors. In addition, some of the trends are coherent with each other, and the differences in population dynamics originate from variations in the relative importance of these trends among the three watershed groups.

  1. Rethinking the logistic approach for population dynamics of mutualistic interactions.

    PubMed

    García-Algarra, Javier; Galeano, Javier; Pastor, Juan Manuel; Iriondo, José María; Ramasco, José J

    2014-12-21

    Mutualistic communities have an internal structure that makes them resilient to external perturbations. Late research has focused on their stability and the topology of the relations between the different organisms to explain the reasons of the system robustness. Much less attention has been invested in analyzing the systems dynamics. The main population models in use are modifications of the r-K formulation of logistic equation with additional terms to account for the benefits produced by the interspecific interactions. These models have shortcomings as the so-called r-K formulation diverges under some conditions. In this work, we introduce a model for population dynamics under mutualism that preserves the original logistic formulation. It is mathematically simpler than the widely used type II models, although it shows similar complexity in terms of fixed points and stability of the dynamics. We perform an analytical stability analysis and numerical simulations to study the model behavior in general interaction scenarios including tests of the resilience of its dynamics under external perturbations. Despite its simplicity, our results indicate that the model dynamics shows an important richness that can be used to gain further insights in the dynamics of mutualistic communities.

  2. Diversity waves in collapse-driven population dynamics

    DOE PAGES

    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

  3. 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.

  4. 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.

  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. 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

  7. Detecting dynamical interdependence and generalized synchrony through mutual prediction in a neural ensemble

    NASA Astrophysics Data System (ADS)

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

    1996-12-01

    A method to characterize dynamical interdependence among nonlinear systems is derived based on mutual nonlinear prediction. Systems with nonlinear correlation will show mutual nonlinear prediction when standard analysis with linear cross correlation might fail. Mutual nonlinear prediction also provides information on the directionality of the coupling between systems. Furthermore, the existence of bidirectional mutual nonlinear prediction in unidirectionally coupled systems implies generalized synchrony. Numerical examples studied include three classes of unidirectionally coupled systems: systems with identical parameters, nonidentical parameters, and stochastic driving of a nonlinear system. This technique is then applied to the activity of motoneurons within a spinal cord motoneuron pool. The interrelationships examined include single neuron unit firing, the total number of neurons discharging at one time as measured by the integrated monosynaptic reflex, and intracellular measurements of integrated excitatory postsynaptic potentials (EPSP's). Dynamical interdependence, perhaps generalized synchrony, was identified in this neuronal network between simultaneous single unit firings, between units and the population, and between units and intracellular EPSP's.

  8. 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

  9. Population Dynamics of a Commercial Sponge in Biscayne Bay, Florida

    NASA Astrophysics Data System (ADS)

    Cropper, W. P.; Lirman, D.; Tosini, S. C.; DiResta, D.; Luo, J.; Wang, J.

    2001-07-01

    The dynamics of glove sponge ( Spongia graminea) population in Biscayne Bay, Florida were investigated using a series of matrix population models, a hydrodynamic model, and a GIS data base. Sponges at Billy's Point, on the eastern margin of Biscayne Bay, were sampled between 1993 and 1995 and resampled in 2000 for model calibration and testing. An iterative procedure was used to fit unmeasured fecundity and a growth parameter by minimizing the 1993 to 2000 simulated differences from the observed year 2000 size class distribution. A density dependent model was found to fit the total population size in 2000 better than the density independent matrix model. Systematic sampling of the bay was used to identify four local populations with sponge densities above 50 ha -1. The three western populations experienced salinity below 25, based on hydrodynamic model outputs for 1995, whereas the eastern Billy's Point population had a stable ocean salinity environment. The hydrodynamic model was used to simulate larval transport between local populations as lagrangian drifting particles. These simulations indicated that the Billy's Point population was likely to be demographically closed.

  10. 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.

  11. Wolbachia infections that reduce immature insect survival: Predicted impacts on population replacement

    PubMed Central

    2011-01-01

    Background The evolutionary success of Wolbachia bacteria, infections of which are widespread in invertebrates, is largely attributed to an ability to manipulate host reproduction without imposing substantial fitness costs. Here, we describe a stage-structured model with deterministic immature lifestages and a stochastic adult female lifestage. Simulations were conducted to better understand Wolbachia invasions into uninfected host populations. The model includes conventional Wolbachia parameters (the level of cytoplasmic incompatibility, maternal inheritance, the relative fecundity of infected females, and the initial Wolbachia infection frequency) and a new parameter termed relative larval viability (RLV), which is the survival of infected larvae relative to uninfected larvae. Results The results predict the RLV parameter to be the most important determinant for Wolbachia invasion and establishment. Specifically, the fitness of infected immature hosts must be close to equal to that of uninfected hosts before population replacement can occur. Furthermore, minute decreases in RLV inhibit the invasion of Wolbachia despite high levels of cytoplasmic incompatibility, maternal inheritance, and low adult fitness costs. Conclusions The model described here takes a novel approach to understanding the spread of Wolbachia through a population with explicit dynamics. By combining a stochastic female adult lifestage and deterministic immature/adult male lifestages, the model predicts that even those Wolbachia infections that cause minor decreases in immature survival are unlikely to invade and spread within the host population. The results are discussed in relation to recent theoretical and empirical studies of natural population replacement events and proposed applied research, which would use Wolbachia as a tool to manipulate insect populations. PMID:21975225

  12. Predicting reading ability for bilingual Latino children using dynamic assessment.

    PubMed

    Petersen, Douglas B; Gillam, Ronald B

    2015-01-01

    This study investigated the predictive validity of a dynamic assessment designed to evaluate later risk for reading difficulty in bilingual Latino children at risk for language impairment. During kindergarten, 63 bilingual Latino children completed a dynamic assessment nonsense-word recoding task that yielded pretest to posttest gain scores, residuum gain scores, and modifiability scores. At the end of first grade, the same participants completed criterion reading measures of word identification, decoding, and reading fluency. The dynamic assessment yielded high classification accuracy, with sensitivity and specificity at or above 80% for all three criterion reading measures, including 100% sensitivity for two out of the three first-grade measures. The dynamic assessment used in this study has promise as a means for predicting first-grade word-level reading ability in Latino, bilingual children.

  13. Limits and Uses of Dynamical Predictions of Meteorological Drought

    NASA Astrophysics Data System (ADS)

    Lyon, B.

    2012-12-01

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

  14. 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.

  15. [On the competition among discrete-structured populations: a matrix model for population dynamics of woodreed and birch growing together].

    PubMed

    Ulanova, N G; Belova, I N; Logofet, D O

    2008-01-01

    Presented is a synthesis of field, theoretical and modelling studies on joint dynamics of two species--common birch (Betula pendula Roth) and wood small reed (Calamagrostis epigeios (L.) Roth)--overgrowing a spruce forest clear-cut. A nonlinear matrix model for population dynamics of two species, which both possess non-trivial population structures and compete for a resource in common was developed as an expansion of the linear models for single-species, age-stage-structured population dynamics. Constant values of the age-stage-specific survival and reproduction rates have been modified with some decreasing functions of the (competitive group) abundances in the competitor species or/and the species itself. Special aggregation of the age-stage structure for each of the competitor species has reduced the dimension of the nonlinear matrix operator down to the level that admits accurate calibration of the model parameters on the observation data, as well as the search for an equilibrium and its stability analysis. When calibrated, the nonlinear model exhibits convergence to the steady equilibrium--a state of the phytocoenosis that is interpreted as young, closed-canopy, birch forest with suppressed woodreed population. The model illustrates the observed course of forest renewal: the appearance of birch germs and the growth of birch population overpass the woodreed competitive resistance and result in formation of young birch forest, where the birch exerts a strong suppressive impact on both the woodreed growth and the own young growth. Remarked is a potential of the model as an object of more general mathematical study and a tool to predict the course of forest renewal.

  16. Prediction-based Dynamic Energy Management in Wireless Sensor Networks

    PubMed Central

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

    2007-01-01

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

  17. Population Dynamics of the Stationary Phase Utilizing the ARGOS Method

    NASA Astrophysics Data System (ADS)

    Algarni, S.; Charest, A. J.; Iannacchione, G. S.

    2015-03-01

    The Area Recorded Generalized Optical Scattering (ARGOS) approach to light scattering employs large image capture array allowing for a well-defined geometry in which images may be manipulated to extract structure with intensity at a specific scattering wave vector (I(q)) and dynamics with intensity at a specific scattering wave vector over time (I (q,t)). The ARGOS method provides morphological dynamics noninvasively over a long time period and allows for a variety of aqueous conditions. This is important because traditional growth models do not provide for conditions similar to the natural environment. The present study found that the population dynamics of bacteria do not follow a traditional growth model and that the ARGOS method allowed for the observation of bacterial changes in terms of individual particles and population dynamics in real time. The observations of relative total intensity suggest that there is no stationary phase and that the bacterial population demonstrates sinusoidal type patterns consistently subsequent to the log phase growth. These observation were compared to shape changes by modeling fractal dimension and size changes by modeling effective radius.

  18. 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.

  19. 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.

  20. Evolutionary Dynamic Multiobjective Optimization Via Kalman Filter Prediction.

    PubMed

    Muruganantham, Arrchana; Tan, Kay Chen; Vadakkepat, Prahlad

    2016-12-01

    Evolutionary algorithms are effective in solving static multiobjective optimization problems resulting in the emergence of a number of state-of-the-art multiobjective evolutionary algorithms (MOEAs). Nevertheless, the interest in applying them to solve dynamic multiobjective optimization problems has only been tepid. Benchmark problems, appropriate performance metrics, as well as efficient algorithms are required to further the research in this field. One or more objectives may change with time in dynamic optimization problems. The optimization algorithm must be able to track the moving optima efficiently. A prediction model can learn the patterns from past experience and predict future changes. In this paper, a new dynamic MOEA using Kalman filter (KF) predictions in decision space is proposed to solve the aforementioned problems. The predictions help to guide the search toward the changed optima, thereby accelerating convergence. A scoring scheme is devised to hybridize the KF prediction with a random reinitialization method. Experimental results and performance comparisons with other state-of-the-art algorithms demonstrate that the proposed algorithm is capable of significantly improving the dynamic optimization performance.

  1. Coupling in goshawk and grouse population dynamics in Finland.

    PubMed

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

    2013-04-01

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

  2. 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.

  3. 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

  4. [Analysis on age structure and dynamics of Kindonia uniflora populations].

    PubMed

    Zhang, Wenhui; Li, Jingxia; Li, Hong; Liu, Xiangjun

    2004-04-01

    Kindonia uniflora is a perennial clone herbaceous plant, and also, a native endangered plant in China. This paper studied its age structure, life table and survivorship curve in different habitats in Taibai mountain area. The results indicated that the age structure and dynamics of K. uniflora populations in the Betula utilis forest at altitude 2500-2700 m, in the Abies fargesii forest at altitude 2700-2900 m, and in the Larix chinensis forest at altitude 2900-3100 m had the similar pattern and developing tendency. The number of younger ramets at 1-2 years old or older than 5 years was less, and the number of ramets at 3-5 years old was the highest in the age structures. The negative values of dx (dead number), qx (mortality rate) and Kx (Killing rate) in the life table showed the increasing rate of the population sizes during the age stage. The survivorship curve of K. uniflora populations in different habitats belonged to Deevey C after 3-5 years old. The mortality rate of populations during 5-10 years stage was higher, and was stable after 10 years old. As for the characters of asexual propagation and clone growth, the rhizomes of the populations were in humus of soil, and developed and expanded as guerilla line style. During growth season, only one leaf grew above ground at every inter-node, and the population growth and development were rarely influenced by external factors. The forest communities, such as Betula utilis, Abies fargesii and Larix chinensis forest, in which K. uniflora populations lived, were at middle or higher mountain, where there were rarely disturbance from human being. Therefore, the habitats for K. uniflora populations to live were relatively stable. As the altitude increased, the disturbances from human being became less, the density of K. uniflora populations increased, the life cycle expanded, the peak of population death delayed, and the population living strategy changed to adapt to the habitats. K. uniflora populations preferred to

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

    PubMed

    Hofreiter, Michael; Stewart, John

    2009-07-28

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

  6. 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.

  7. Effects of extreme environmental changes on population dynamics

    NASA Astrophysics Data System (ADS)

    De Falco, I.; Della Cioppa, A.; Tarantino, E.

    2006-09-01

    The effects of periodic environmental fluctuations on the adaptive behavior and on the survival chance of a population of individuals are investigated as a function of both the genotypes carried, i.e., haploid or diploid. Only extreme and exogenous changes have been taken into account in order not to complicate the model under investigation. Moreover, different rates of both environmental changes and mutation have been considered. The analysis has been performed by discussing the evolutionary dynamics exhibited by the population in terms of adaptation, density and, finally, survival probability.

  8. Changes in population dynamics in mutualistic versus pathogenic viruses.

    PubMed

    Roossinck, Marilyn J

    2011-01-01

    Although generally regarded as pathogens, viruses can also be mutualists. A number of examples of extreme mutualism (i.e., symbiogenesis) have been well studied. Other examples of mutualism are less common, but this is likely because viruses have rarely been thought of as having any beneficial effects on their hosts. The effect of mutualism on the population dynamics of viruses is a topic that has not been addressed experimentally. However, the potential for understanding mutualism and how a virus might become a mutualist may be elucidated by understanding these dynamics.

  9. Clinical time series prediction: towards a hierarchical dynamical system framework

    PubMed Central

    Liu, Zitao; Hauskrecht, Milos

    2014-01-01

    Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive

  10. Effects of dynamical evolution on the stellar mass function of multiple population globular clusters

    NASA Astrophysics Data System (ADS)

    Vesperini, Enrico

    2013-10-01

    Many observational studies have shown that globular clusters {GCs} host multiple stellar populations, challenging the standard view of GC formation, in which GCs are simple stellar populations composed of stars of uniform age and chemical composition.Theoretical models of multiple-population GC formation predict that second-generation {SG} stars form in a compact subsystem embedded in a more extended first-generation {FG} cluster. Observational studies have found that in several GCs SG stars are indeed more concentrated in the cluster inner regions and still retain memory of the initial segregation predicted by theoretical models. We propose to study the effects of dynamical evolution on the stellar mass function {MF} in multiple-population GCs. No study has previously addressed this problem in this context, taking into account the structural properties predicted by models of formation and evolution of multiple-population GCs and exploring the evolution of the SG and FG MFs. We will study the evolution of the total MF of the cluster as well as the individual MFs of the FG and SG populations. We will address a series of questions concerning the evolution of both the global MF and the local MF {measured at different distances from the cluster center}, and the relation between the present-day MF and the initial MF. We will determine how the evolution of the combined MF, and the differences between the FG and the SG MFs, can be used to explore the formation and dynamics of multiple-population GCs. As observational studies of these clusters continue to improve, our work will provide the tools needed to interpret existing data and guide future observational projects.

  11. 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.

  12. Accelerating ab initio molecular dynamics simulations by linear prediction methods

    NASA Astrophysics Data System (ADS)

    Herr, Jonathan D.; Steele, Ryan P.

    2016-09-01

    Acceleration of ab initio molecular dynamics (AIMD) simulations can be reliably achieved by extrapolation of electronic data from previous timesteps. Existing techniques utilize polynomial least-squares regression to fit previous steps' Fock or density matrix elements. In this work, the recursive Burg 'linear prediction' technique is shown to be a viable alternative to polynomial regression, and the extrapolation-predicted Fock matrix elements were three orders of magnitude closer to converged elements. Accelerations of 1.8-3.4× were observed in test systems, and in all cases, linear prediction outperformed polynomial extrapolation. Importantly, these accelerations were achieved without reducing the MD integration timestep.

  13. Can ocean acidification affect population dynamics of the barnacle Semibalanus balanoides at its southern range edge?

    PubMed

    Findlay, Helen S; Burrows, Michael T; Kendall, Michael A; Spicer, John I; Widdicombe, Stephen

    2010-10-01

    The global ocean and atmosphere are warming. There is increasing evidence suggesting that, in addition to other environmental factors, climate change is affecting species distributions and local population dynamics. Additionally, as a consequence of the growing levels of atmospheric carbon dioxide (CO2), the oceans are taking up increasing amounts of this CO2, causing ocean pH to decrease (ocean acidification). The relative impacts of ocean acidification on population dynamics have yet to be investigated, despite many studies indicating that there will be at least a sublethal impact on many marine organisms, particularly key calcifying organisms. Using empirical data, we forced a barnacle (Semibalanus balanoides) population model to investigate the relative influence of sea surface temperature (SST) and ocean acidification on a population nearing the southern limit of its geographic distribution. Hindcast models were compared to observational data from Cellar Beach (southwestern United Kingdom). Results indicate that a declining pH trend (-0.0017 unit/yr), indicative of ocean acidification over the past 50 years, does not cause an observable impact on the population abundance relative to changes caused by fluctuations in temperature. Below the critical temperature (here T(crit) = 13.1 degrees C), pH has a more significant affect on population dynamics at this southern range edge. However, above this value, SST has the overriding influence. At lower SST, a decrease in pH (according to the National Bureau of Standards, pHNBs) from 8.2 to 7.8 can significantly decrease the population abundance. The lethal impacts of ocean acidification observed in experiments on early life stages reduce cumulative survival by approximately 25%, which again will significantly alter the population level at this southern limit. Furthermore, forecast predictions from this model suggest that combined acidification and warming cause this local population to die out 10 years earlier than

  14. 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.

  15. Dynamics of molecular evolution in RNA virus populations depend on sudden versus gradual environmental change.

    PubMed

    Morley, Valerie J; Turner, Paul E

    2017-04-01

    Understanding the dynamics of molecular adaptation is a fundamental goal of evolutionary biology. While adaptation to constant environments has been well characterized, the effects of environmental complexity remain seldom studied. One simple but understudied factor is the rate of environmental change. Here we used experimental evolution with RNA viruses to investigate whether evolutionary dynamics varied based on the rate of environmental turnover. We used whole-genome next-generation sequencing to characterize evolutionary dynamics in virus populations adapting to a sudden versus gradual shift onto a novel host cell type. In support of theoretical models, we found that when populations evolved in response to a sudden environmental change, mutations of large beneficial effect tended to fix early, followed by mutations of smaller beneficial effect; as predicted, this pattern broke down in response to a gradual environmental change. Early mutational steps were highly parallel across replicate populations in both treatments. The fixation of single mutations was less common than sweeps of associated "cohorts" of mutations, and this pattern intensified when the environment changed gradually. Additionally, clonal interference appeared stronger in response to a gradual change. Our results suggest that the rate of environmental change is an important determinant of evolutionary dynamics in asexual populations.

  16. Predicted Ultrafast Dynamic Metallization of Dielectric Nanofilms by Strong Single-Cycle Optical Fields

    NASA Astrophysics Data System (ADS)

    Durach, Maxim; Rusina, Anastasia; Kling, Matthias F.; Stockman, Mark I.

    2011-08-01

    We predict a dynamic metallization effect where an ultrafast (single-cycle) optical pulse with a ≲1V/Å field causes plasmonic metal-like behavior of a dielectric film with a few-nm thickness. This manifests itself in plasmonic oscillations of polarization and a significant population of the conduction band evolving on a ˜1fs time scale. These phenomena are due to a combination of both adiabatic (reversible) and diabatic (for practical purposes irreversible) pathways.

  17. Predicted ultrafast dynamic metallization of dielectric nanofilms by strong single-cycle optical fields.

    PubMed

    Durach, Maxim; Rusina, Anastasia; Kling, Matthias F; Stockman, Mark I

    2011-08-19

    We predict a dynamic metallization effect where an ultrafast (single-cycle) optical pulse with a ≲1 V/Å field causes plasmonic metal-like behavior of a dielectric film with a few-nm thickness. This manifests itself in plasmonic oscillations of polarization and a significant population of the conduction band evolving on a ~1 fs time scale. These phenomena are due to a combination of both adiabatic (reversible) and diabatic (for practical purposes irreversible) pathways.

  18. 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.

  19. 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

  20. 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…

  1. Populations dynamics of Australorbis glabratus in Puerto Rico

    PubMed Central

    Ritchie, Lawrence S.; Radke, Myron G.; Ferguson, Frederick F.

    1962-01-01

    This report on the population dynamics of Australorbis glabratus in Puerto Rico is based on observations made over about two years at 50 collecting-sites in a representative range of snail habitats. In some places a marked predominance of Tropicorbis was noted. No continuous or seasonal propagation of Australorbis was apparent. Dense populations seldom prevailed for more than a few months, and in most places very low population levels occurred at irregular intervals, and colony decimations were fairly common. A variety of pressures is exerted on Australorbis in Puerto Rico by a multiplicity of natural factors; detailed knowledge of this snail's natural history in the field is necessary for effective bilharziasis control and for a full understanding of the regional epidemiology of this disease. PMID:14492504

  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.

  4. IMF shape constraints from stellar populations and dynamics from CALIFA

    NASA Astrophysics Data System (ADS)

    Lyubenova, M.; Martín-Navarro, I.; van de Ven, G.; Falcón-Barroso, J.; Galbany, L.; Gallazzi, A.; García-Benito, R.; González Delgado, R.; Husemann, B.; La Barbera, F.; Marino, R. A.; Mast, D.; Mendez-Abreu, J.; Peletier, R. F. P.; Sánchez-Blázquez, P.; Sánchez, S. F.; Trager, S. C.; van den Bosch, R. C. E.; Vazdekis, A.; Walcher, C. J.; Zhu, L.; Zibetti, S.; Ziegler, B.; Bland-Hawthorn, J.; CALIFA Collaboration

    2016-12-01

    In this Paper, we describe how we use stellar dynamics information to constrain the shape of the stellar initial mass function (IMF) in a sample of 27 early-type galaxies from the CALIFA survey. We obtain dynamical and stellar mass-to-light ratios, Υdyn and Υ*, over a homogenous aperture of 0.5 Re. We use the constraint Υdyn≥Υ* to test two IMF shapes within the framework of the extended MILES stellar population models. We rule out a single power-law IMF shape for 75 per cent of the galaxies in our sample. Conversely, we find that a double power-law IMF shape with a varying high-mass end slope is compatible (within 1σ) with 95 per cent of the galaxies. We also show that dynamical and stellar IMF mismatch factors give consistent results for the systematic variation of the IMF in these galaxies.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Environmental influence on population dynamics of the bivalve Anomalocardia brasiliana

    NASA Astrophysics Data System (ADS)

    Corte, Guilherme Nascimento; Coleman, Ross A.; Amaral, A. Cecília Z.

    2017-03-01

    Understanding how species respond to the environment in terms of population attributes (e.g. abundance, growth, mortality, fecundity, and productivity) is essential to protect ecologically and economically important species. Nevertheless, responses of macrobenthic populations to environmental features are overlooked due to the need of consecutive samplings and time-consuming measurements. We examined the population dynamics of the filter-feeding bivalve Anomalocardia brasiliana on a tidal flat over the course of one year to investigate the hypothesis that, as accepted for macrobenthic communities, populations inhabiting environments with low hydrodynamic conditions such as tidal flat should have higher attributes than populations inhabiting more energetic habitats (i.e. areas more influenced by wave energy such as reflective and intermediate beaches). This would be expected because the harsh conditions of more energetic habitats force organisms to divert more energy towards maintenance, resulting in lower population attributes. We found that A. brasiliana showed moderate growth and secondary production at the study area. Moreover the recruitment period was restricted to a few months. A comparison with previous studies showed that, contrary to expected, A. brasiliana populations from areas with low hydrodynamic conditions have lower abundance, growth, recruitment and turnover rate. It is likely that morphodynamic characteristics recorded in these environments, such as larger periods of air exposure and lower water circulation, may affect food conditions for filter-feeding species and increase competition. In addition, these characteristics may negatively affect macrobenthic species by enhancing eutrophication processes and anoxia. Overall, our results suggest that models accepted and applied at the macrobenthic community level might not be directly extended to A. brasiliana populations.

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

    PubMed

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

    2007-10-01

    Synchrony in population fluctuations has been identified as an important component of population dynamics. In a previous study, we determined that local-scale (<15-km) spatial synchrony of bird populations in New England was correlated with synchronous fluctuations in lepidopteran larvae abundance and with the North Atlantic Oscillation. Here we address five questions that extend the scope of our earlier study using North American Breeding Bird Survey data. First, do bird populations in eastern North America exhibit spatial synchrony in abundances at scales beyond those we have documented previously? Second, does spatial synchrony depend on what population metric is analyzed (e.g., abundance, growth rate, or variability)? Third, is there geographic concordance in where species exhibit synchrony? Fourth, for those species that exhibit significant geographic concordance, are there landscape and habitat variables that contribute to the observed patterns? Fifth, is spatial synchrony affected by a species' life history traits? Significant spatial synchrony was common and its magnitude was dependent on the population metric analyzed. Twenty-four of 29 species examined exhibited significant synchrony in population abundance: mean local autocorrelation (rho)= 0.15; mean spatial extent (mean distance where rho=0) = 420.7 km. Five of the 29 species exhibited significant synchrony in annual population growth rate (mean local autocorrelation = 0.06, mean distance = 457.8 km). Ten of the 29 species exhibited significant synchrony in population abundance variability (mean local autocorrelation = 0.49, mean distance = 413.8 km). Analyses of landscape structure indicated that habitat variables were infrequent contributors to spatial synchrony. Likewise, we detected no effects of life history traits on synchrony in population abundance or growth rate. However, short-distance migrants exhibited more spatially extensive synchrony in population variability than either year

  11. [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.

  12. The effects of spatial correlations and demographic stochasticity on population dynamics

    NASA Astrophysics Data System (ADS)

    Snyder, Robin Elizabeth

    2001-12-01

    Because of limited mobility and localized interactions, most organisms do not interact equally with all parts of their environment but instead with a limited neighborhood. The resulting spatial correlations affect population dynamics. The discreteness of organisms can also affect population dynamics. Because population size cannot change by less than one, and size-changing events such as births and deaths occur at distinct times, population dynamics are noisy. For large populations, this so-called ``demographic stochasticity'' is often ignorable, but when population size is small, either throughout the system or in a region, noise can have important consequences. This dissertation explores the combined effects of spatial correlations and population discreteness. Chapter II discusses the limitations of many traditional physics techniques in analyzing ecological models. Chapters III and IV consider grid-based models. Every grid point can be vacant or occupied by an individual, and individuals interact according to simple, probabilistic rules. In chapter III, I develop approximate equations for the population mean and variance, including the effects of demographic stochasticity, by ignoring all but very short-range spatial correlations (a moment closure scheme). I apply this to a grid model and obtain expressions for population mean and variance. In chapter IV, I develop an empirical moment closure scheme based on observed spatial correlations. This leads to expressions for population mean and variance that are both simpler and more accurate, as well as to probability distributions for how long the population will take to reach a given, low level. Subsequently, I turn to the effects of population discreteness on the spread of newly introduced species. In chapter V, I analyze a common class of one- dimensional, single-species invasion models and find three effects of population discreteness and demographic stochasticity on invasion speed. The result is that for very

  13. 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.

  14. 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.

  15. The habits of highly effective phages: population dynamics as a framework for identifying therapeutic phages

    PubMed Central

    Bull, James J.; Gill, Jason J.

    2014-01-01

    The use of bacteriophages as antibacterial agents is being actively researched on a global scale. Typically, the phages used are isolated from the wild by plating on the bacteria of interest, and a far larger set of candidate phages is often available than can be used in any application. When an excess of phages is available, how should the best phages be identified? Here we consider phage-bacterial population dynamics as a basis for evaluating and predicting phage success. A central question is whether the innate dynamical properties of phages are the determinants of success, or instead, whether extrinsic, indirect effects can be responsible. We address the dynamical perspective, motivated in part by the absence of dynamics in previously suggested principles of phage therapy. Current mathematical models of bacterial-phage dynamics do not capture the realities of in vivo dynamics, nor is this likely to change, but they do give insight to qualitative properties that may be generalizable. In particular, phage adsorption rate may be critical to treatment success, so understanding the effects of the in vivo environment on host availability may allow prediction of useful phages prior to in vivo experimentation. Principles for predicting efficacy may be derived by developing a greater understanding of the in vivo system, or such principles could be determined empirically by comparing phages with known differences in their dynamic properties. The comparative approach promises to be a powerful method of discovering the key to phage success. We offer five recommendations for future study: (i) compare phages differing in treatment efficacy to identify the phage properties associated with success, (ii) assay dynamics in vivo, (iii) understand mechanisms of bacterial escape from phages, (iv) test phages in model infections that are relevant to the intended clinical applications, and (v) develop new classes of models for phage growth in spatially heterogeneous environments

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

    PubMed

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

    2016-02-18

    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.

  17. 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

  18. Dynamics of a feline virus with two transmission modes within exponentially growing host populations.

    PubMed Central

    Berthier, K; Langlais, M; Auger, P; Pontier, D

    2000-01-01

    Feline panleucopenia virus (FPLV) was introduced in 1977 on Marion Island (in the southern Indian Ocean) with the aim of eradicating the cat population and provoked a huge decrease in the host population within six years. The virus can be transmitted either directly through contacts between infected and healthy cats or indirectly between a healthy cat and the contaminated environment: a specific feature of the virus is its high rate of survival outside the host. In this paper, a model was designed in order to take these two modes of transmission into account. The results showed that a mass-action incidence assumption was more appropriate than a proportionate mixing one in describing the dynamics of direct transmission. Under certain conditions the virus was able to control the host population at a low density. The indirect transmission acted as a reservoir supplying the host population with a low but sufficient density of infected individuals which allowed the virus to persist. The dynamics of the infection were more affected by the demographic parameters of the healthy hosts than by the epidemiological ones. Thus, demographic parameters should be precisely measured in field studies in order to obtain accurate predictions. The predicted results of our model were in good agreement with observations. PMID:11416908

  19. 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.

  20. 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.

  1. 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...

  2. 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.

  3. 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

  4. Effectiveness of genomic prediction of maize hybrid performance in different breeding populations and environments.

    PubMed

    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

    2012-11-01

    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 F(2)-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 F(2)-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.

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

    PubMed

    Russell, Tanya L; Lwetoijera, Dickson W; Knols, Bart G J; Takken, Willem; Killeen, Gerry F; Ferguson, Heather M

    2011-10-22

    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% wAIC(c) 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.

  6. 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

  7. Seasonal drought predictability in Portugal using statistical-dynamical techniques

    NASA Astrophysics Data System (ADS)

    Ribeiro, A. F. S.; Pires, C. A. L.

    2016-08-01

    Atmospheric forecasting and predictability are important to promote adaption and mitigation measures in order to minimize drought impacts. This study estimates hybrid (statistical-dynamical) long-range forecasts of the regional drought index SPI (3-months) over homogeneous regions from mainland Portugal, based on forecasts from the UKMO operational forecasting system, with lead-times up to 6 months. ERA-Interim reanalysis data is used for the purpose of building a set of SPI predictors integrating recent past information prior to the forecast launching. Then, the advantage of combining predictors with both dynamical and statistical background in the prediction of drought conditions at different lags is evaluated. A two-step hybridization procedure is performed, in which both forecasted and observed 500 hPa geopotential height fields are subjected to a PCA in order to use forecasted PCs and persistent PCs as predictors. A second hybridization step consists on a statistical/hybrid downscaling to the regional SPI, based on regression techniques, after the pre-selection of the statistically significant predictors. The SPI forecasts and the added value of combining dynamical and statistical methods are evaluated in cross-validation mode, using the R2 and binary event scores. Results are obtained for the four seasons and it was found that winter is the most predictable season, and that most of the predictive power is on the large-scale fields from past observations. The hybridization improves the downscaling based on the forecasted PCs, since they provide complementary information (though modest) beyond that of persistent PCs. These findings provide clues about the predictability of the SPI, particularly in Portugal, and may contribute to the predictability of crops yields and to some guidance on users (such as farmers) decision making process.

  8. Scale-invariant model of marine population dynamics.

    PubMed

    Capitán, José A; Delius, Gustav W

    2010-06-01

    A striking feature of the marine ecosystem is the regularity in its size spectrum: the abundance of organisms as a function of their weight approximately follows a power law over almost ten orders of magnitude. We interpret this as evidence that the population dynamics in the ocean is approximately scale-invariant. We use this invariance in the construction and solution of a size-structured dynamical population model. Starting from a Markov model encoding the basic processes of predation, reproduction, maintenance respiration, and intrinsic mortality, we derive a partial integro-differential equation describing the dependence of abundance on weight and time. Our model represents an extension of the jump-growth model and hence also of earlier models based on the McKendrick-von Foerster equation. The model is scale-invariant provided the rate functions of the stochastic processes have certain scaling properties. We determine the steady-state power-law solution, whose exponent is determined by the relative scaling between the rates of the density-dependent processes (predation) and the rates of the density-independent processes (reproduction, maintenance, and mortality). We study the stability of the steady-state against small perturbations and find that inclusion of maintenance respiration and reproduction in the model has a strong stabilizing effect. Furthermore, the steady state is unstable against a change in the overall population density unless the reproduction rate exceeds a certain threshold.

  9. 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

  10. Network representation of dynamical systems: Connectivity patterns, information and predictability

    NASA Astrophysics Data System (ADS)

    García Cantú Ros, A.; Forti, G.; Nicolis, G.

    2013-08-01

    The present work elaborates on predictability and information aspects of dynamical systems, in connection with the connectivity features of their network representation. The basic idea underlying this work is to map the set of coarse-grained states of a dynamical system onto a set of network nodes and transitions between them onto a set of network links. Based on the vertex centrality of these nodes, we define (a) a local indicator of predictability, (b) a measure of the information that is available about the state of the system after one transition occurring within an arbitrary long time window and (c) an upper bound for the time horizon of predictability. We address the cases of the tent and the cusp maps, as representative examples of Markov and non-Markov processes. An analytical exact result for the horizon of predictability is obtained for the tent map, as well as for its higher iterates, and its connection with the corresponding network diameters is discussed. Similarly, analytical expressions are derived for the bounds of the predictability horizon in the case of the cusp map.

  11. 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.

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

    PubMed

    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.

  13. 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.

  14. 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.

  15. Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains.

    PubMed

    Zhao, Yuan; Park, Il Memming

    2017-05-01

    When governed by underlying low-dimensional dynamics, the interdependence of simultaneously recorded populations of neurons can be explained by a small number of shared factors, or a low-dimensional trajectory. Recovering these latent trajectories, particularly from single-trial population recordings, may help us understand the dynamics that drive neural computation. However, due to the biophysical constraints and noise in the spike trains, inferring trajectories from data is a challenging statistical problem in general. Here, we propose a practical and efficient inference method, the variational latent gaussian process (vLGP). The vLGP combines a generative model with a history-dependent point process observation, together with a smoothness prior on the latent trajectories. The vLGP improves on earlier methods for recovering latent trajectories, which assume either observation models inappropriate for point processes or linear dynamics. We compare and validate vLGP on both simulated data sets and population recordings from the primary visual cortex. In the V1 data set, we find that vLGP achieves substantially higher performance than previous methods for predicting omitted spike trains, as well as capturing both the toroidal topology of visual stimuli space and the noise correlation. These results show that vLGP is a robust method with the potential to reveal hidden neural dynamics from large-scale neural recordings.

  16. Cryptic genetic variation in natural populations: a predictive framework.

    PubMed

    Ledón-Rettig, Cris C; Pfennig, David W; Chunco, Amanda J; Dworkin, Ian

    2014-11-01

    Understanding how populations respond to rapid environmental change is critical both for preserving biodiversity and for human health. An increasing number of studies have shown that genetic variation that has no discernable effect under common ecological conditions can become amplified under stressful or novel conditions, suggesting that environmental change per se can provide the raw materials for adaptation. Indeed, the release of such hidden, or "cryptic," genetic variants has been increasingly viewed as playing a general and important role in allowing populations to respond to rapid environmental change. However, additional studies have suggested that there is a balance between cryptic genetic variants that are potentially adaptive in future environments and genetic variants that are deleterious. In this article, we begin by discussing how population and environmental parameters-such as effective population size and the historical frequency and strength of selection under inducing conditions-influence relative amounts of cryptic genetic variation among populations and the overall phenotypic effects of such variation. The amount and distribution of cryptic genetic variation will, in turn, determine the likelihood that cryptic variants, once expressed, will be adaptive or maladaptive during environmental transitions. We then present specific approaches for measuring these parameters in natural populations. Finally, we discuss one natural system that will be conducive to testing whether populations that vary in these parameters harbor different amounts, or types, of cryptic genetic variation. Generally, teasing apart how population and environmental parameters influence the accumulation of cryptic genetic variation will help us to understand how populations endure and adapt (or fail to adapt) to natural environmental change and anthropogenic disturbance.

  17. Population dynamics of wild rodents induce stochastic fadeouts of a zoonotic pathogen.

    PubMed

    Guzzetta, Giorgio; Tagliapietra, Valentina; Perkins, Sarah E; Hauffe, Heidi C; Poletti, Piero; Merler, Stefano; Rizzoli, Annapaola

    2017-02-19

    Stochastic processes play an important role in the infectious disease dynamics of wildlife, especially in species subject to large population oscillations. Here we study the case of a free ranging population of yellow-necked mice (Apodemus flavicollis) in northern Italy, where circulation of Dobrava-Belgrade hantavirus (DOBV) has been detected intermittently since 2001, until an outbreak emerged in 2010. We analyzed the transmission dynamics of the recent outbreak using a computational model that accounts for seasonal changes of the host population and territorial behavior. Model parameters were informed by capture-mark-recapture data collected over 14 years and longitudinal seroprevalence data from 2010 to 2013. The intermittent observation of DOBV before 2010 can be interpreted as repeated stochastic fadeouts after multiple introductions of infectious rodents migrating from neighboring areas. We estimated that only 20% of introductions in a naïve host population results in sustained transmission after two years, despite an effective reproduction number well above the epidemic threshold (mean 4.5, 95% credible intervals, CI: 0.65-15.8). Following the 2010 outbreak, DOBV has become endemic in the study area, but we predict a constant probability of about 4.7% per year that infection dies out, following large population drops in winter. In the absence of stochastic fadeout, viral prevalence is predicted to continue its growth to an oscillating equilibrium around a value of 24% (95% CI: 3-57%). We presented an example of invasion dynamics of a zoonotic virus where stochastic fadeout have played a major role and may induce future extinction of the endemic infection. This article is protected by copyright. All rights reserved.

  18. Measuring Predictability of Autonomous Network Transitions into Bursting Dynamics

    PubMed Central

    Mofakham, Sima; Zochowski, Michal

    2015-01-01

    Understanding spontaneous transitions between dynamical modes in a network is of significant importance. These transitions may separate pathological and normal functions of the brain. In this paper, we develop a set of measures that, based on spatio-temporal features of network activity, predict autonomous network transitions from asynchronous to synchronous dynamics under various conditions. These metrics quantify spike-timing distributions within a narrow time window as a function of the relative location of the active neurons. We applied these metrics to investigate the properties of these transitions in excitatory-only and excitatory-and-inhibitory networks and elucidate how network topology, noise level, and cellular heterogeneity affect both the reliability and the timeliness of the predictions. The developed measures can be calculated in real time and therefore potentially applied in clinical situations. PMID:25855975

  19. Measuring predictability of autonomous network transitions into bursting dynamics.

    PubMed

    Mofakham, Sima; Zochowski, Michal

    2015-01-01

    Understanding spontaneous transitions between dynamical modes in a network is of significant importance. These transitions may separate pathological and normal functions of the brain. In this paper, we develop a set of measures that, based on spatio-temporal features of network activity, predict autonomous network transitions from asynchronous to synchronous dynamics under various conditions. These metrics quantify spike-timing distributions within a narrow time window as a function of the relative location of the active neurons. We applied these metrics to investigate the properties of these transitions in excitatory-only and excitatory-and-inhibitory networks and elucidate how network topology, noise level, and cellular heterogeneity affect both the reliability and the timeliness of the predictions. The developed measures can be calculated in real time and therefore potentially applied in clinical situations.

  20. 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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Small reference populations limit the accuracy of genomic prediction in numerically small breeds, such as the Danish Jersey. The objective of this study was to investigate two approaches to improve genomic prediction by increasing the size of the reference population for Danish Jerseys. The first ap...

  2. Time-and-Spatially Adapting Simulations for Efficient Dynamic Stall Predictions

    DTIC Science & Technology

    2015-09-01

    SIMULATIONS FOR EFFICIENTDYNAMIC STALL PREDICTIONS The ability to accurately and efficiently predict the occurrence and severity of dynamic stall...The ability to accurately and efficiently predict the occurrence and severity of dynamic stall remains a major roadblock in the design and analysis...SPATIALLY ADAPTING SIMULATIONS FOR EFFICIENT DYNAMIC STALL PREDICTIONS Marilyn J. Smith Professor Georgia Tech Rohit Jain Aerospace Engineer US Army

  3. Whole-Brain Neural Dynamics of Probabilistic Reward Prediction.

    PubMed

    Bach, Dominik R; Symmonds, Mkael; Barnes, Gareth; Dolan, Raymond J

    2017-04-05

    Predicting future reward is paramount to performing an optimal action. Although a number of brain areas are known to encode such predictions, a detailed account of how the associated representations evolve over time is lacking. Here, we address this question using human magnetoencephalography (MEG) and multivariate analyses of instantaneous activity in reconstructed sources. We overtrained participants on a simple instrumental reward learning task where geometric cues predicted a distribution of possible rewards, from which a sample was revealed 2000 ms later. We show that predicted mean reward (i.e., expected value), and predicted reward variability (i.e., economic risk), are encoded distinctly. Early on, representations of mean reward are seen in parietal and visual areas, and later in frontal regions with orbitofrontal cortex emerging last. Strikingly, an encoding of reward variability emerges simultaneously in parietal/sensory and frontal sources and later than mean reward encoding. An orbitofrontal variability encoding emerged around the same time as that seen for mean reward. Crucially, cross-prediction showed that mean reward and variability representations are distinct and also revealed that instantaneous representations become more stable over time. Across sources, the best fitting metric for variability signals was coefficient of variation (rather than SD or variance), but distinct best metrics were seen for individual brain regions. Our data demonstrate how a dynamic encoding of probabilistic reward prediction unfolds in the brain both in time and space.SIGNIFICANCE STATEMENT Predicting future reward is paramount to optimal behavior. To gain insight into the underlying neural computations, we investigate how reward representations in the brain arise over time. Using magnetoencephalography, we show that a representation of predicted mean reward emerges early in parietal/sensory regions and later in frontal cortex. In contrast, predicted reward variability

  4. Host-Parasite Interactions and Population Dynamics of Rock Ptarmigan.

    PubMed

    Stenkewitz, Ute; Nielsen, Ólafur K; Skírnisson, Karl; Stefánsson, Gunnar

    2016-01-01

    evidence that E. muta through time-lag in prevalence with respect to host population size and by showing significant relations with host body condition, mortality, and fecundity could destabilize ptarmigan population dynamics in Iceland.

  5. 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.

  6. Host-Parasite Interactions and Population Dynamics of Rock Ptarmigan

    PubMed Central

    Stenkewitz, Ute; Nielsen, Ólafur K.; Skírnisson, Karl; Stefánsson, Gunnar

    2016-01-01

    evidence that E. muta through time-lag in prevalence with respect to host population size and by showing significant relations with host body condition, mortality, and fecundity could destabilize ptarmigan population dynamics in Iceland. PMID:27870855

  7. Programming microbial population dynamics by engineered cell-cell communication.

    PubMed

    Song, Hao; Payne, Stephen; Tan, Cheemeng; You, Lingchong

    2011-07-01

    A major aim of synthetic biology is to program novel cellular behavior using engineered gene circuits. Early endeavors focused on building simple circuits that fulfill simple functions, such as logic gates, bistable toggle switches, and oscillators. These gene circuits have primarily focused on single-cell behaviors since they operate intracellularly. Thus, they are often susceptible to cell-cell variations due to stochastic gene expression. Cell-cell communication offers an efficient strategy to coordinate cellular behavior at the population level. To this end, we review recent advances in engineering cell-cell communication to achieve reliable population dynamics, spanning from communication within single species to multispecies, from one-way sender-receiver communication to two-way communication in synthetic microbial ecosystems. These engineered systems serve as well-defined model systems to better understand design principles of their naturally occurring counterparts and to facilitate novel biotechnology applications.

  8. Coinfection Dynamics of Two Diseases in a Single Host Population.

    PubMed

    Gao, Daozhou; Porco, Travis C; Ruan, Shigui

    2016-10-01

    A susceptible-infectious-susceptible (SIS) epidemic model that describes the coinfection and cotransmission of two infectious diseases spreading through a single population is studied. The host population consists of two subclasses: susceptible and infectious, and the infectious individuals are further divided into three subgroups: those infected by the first agent/pathogen, the second agent/pathogen, and both. The basic reproduction numbers for all cases are derived which completely determine the global stability of the system if the presence of one agent/pathogen does not affect the transmission of the other. When the constraint on the transmissibility of the dually infected hosts is removed, we introduce the invasion reproduction number, compare it with two other types of reproduction number and show the uniform persistence of both diseases under certain conditions. Numerical simulations suggest that the system can display much richer dynamics such as backward bifurcation, bistability and Hopf bifurcation.

  9. 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.

  10. Fast stochastic algorithm for simulating evolutionary population dynamics

    NASA Astrophysics Data System (ADS)

    Tsimring, Lev; Hasty, Jeff; Mather, William

    2012-02-01

    Evolution and co-evolution of ecological communities are stochastic processes often characterized by vastly different rates of reproduction and mutation and a coexistence of very large and very small sub-populations of co-evolving species. This creates serious difficulties for accurate statistical modeling of evolutionary dynamics. In this talk, we introduce a new exact algorithm for fast fully stochastic simulations of birth/death/mutation processes. It produces a significant speedup compared to the direct stochastic simulation algorithm in a typical case when the total population size is large and the mutation rates are much smaller than birth/death rates. We illustrate the performance of the algorithm on several representative examples: evolution on a smooth fitness landscape, NK model, and stochastic predator-prey system.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. The population mean predicts the number of deviant individuals.

    PubMed Central

    Rose, G; Day, S

    1990-01-01

    OBJECTIVE--To examine the relation between the prevalence of deviation and the mean for the whole population in characteristics such as blood pressure and consumption of alcohol. DESIGN--Re-examination of standardised data from the Intersalt study, an international, multicentre study on the determinants of blood pressure. SETTING AND SUBJECTS--Samples of adults representing 52 populations in 32 countries. MAIN OUTCOME MEASURES--The relations, expressed as correlation coefficients, between the mean population values for blood pressure, body mass index, alcohol consumption, and sodium intake and the prevalence of, respectively, hypertension (greater than or equal to 140 mm Hg), obesity (body mass index greater than or equal to 30 kg/m2), high alcohol intake (greater than or equal to 300 ml/week), and high sodium intake (greater than or equal to 250 mmol/day). RESULTS--There were close and independent associations between the population mean and the prevalence of deviance for each of the variables examined: correlation coefficients were 0.85 for blood pressure, 0.94 for body mass index, 0.97 for alcohol intake, and 0.78 for sodium intake. CONCLUSIONS--These findings imply that distributions of health related characteristics move up and down as a whole: the frequency of "cases" can be understood only in the context of a population's characteristics. The population thus carries a collective responsibility for its own health and well being, including that of its deviants. PMID:2249053

  16. Dynamic vs. static social networks in models of parasite transmission: predicting Cryptosporidium spread in wild lemurs.

    PubMed

    Springer, Andrea; Kappeler, Peter M; Nunn, Charles L

    2016-12-14

    Social networks provide an established tool to implement heterogeneous contact structures in epidemiological models. Dynamic temporal changes in contact structure and ranging behaviour of wildlife may impact disease dynamics. A consensus has yet to emerge, however, concerning the conditions in which network dynamics impact model outcomes, as compared to static approximations that average contact rates over longer time periods. Furthermore, as many pathogens can be transmitted both environmentally and via close contact, it is important to investigate the relative influence of both transmission routes in real-world populations. Here, we use empirically derived networks from a population of wild primates, Verreaux's sifakas (Propithecus verreauxi), and simulated networks to investigate pathogen spread in dynamic vs. static social networks. First, we constructed a susceptible-exposed-infected-recovered model of Cryptosporidium spread in wild Verreaux's sifakas. We incorporated social and environmental transmission routes and parameterized the model for two different climatic seasons. Second, we used simulated networks and greater variation in epidemiological parameters to investigate the conditions in which dynamic networks produce larger outbreak sizes than static networks. We found that average outbreak size of Cryptosporidium infections in sifakas was larger when the disease was introduced in the dry season than in the wet season, driven by an increase in home range overlap towards the end of the dry season. Regardless of season, dynamic networks always produced larger average outbreak sizes than static networks. Larger outbreaks in dynamic models based on simulated networks occurred especially when the probability of transmission and recovery were low. Variation in tie strength in the dynamic networks also had a major impact on outbreak size, while network modularity had a weaker influence than epidemiological parameters that determine transmission and recovery

  17. Predictability and Coupled Dynamics of MJO During DYNAMO

    DTIC Science & Technology

    2015-02-03

    WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Woods Hole Oceanographic Institution 266 Woods Hole Road, MS#21 Woods Hole , MA...release: distribution is unlimited. Predictability and Coupled Dynamics of MJO During DYNAMO Hyodae Seo Woods Hole Oceanographic Institution Woods... Hole , MA 02543 phone: (508) 289-2792 fax: (508) 457-2181 email: hseo@whoi.edu Award Number: N00014-13-1-0133 LONG-TERM GOALS Our long-term goal

  18. Human mobility patterns predict divergent epidemic dynamics among cities.

    PubMed

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

    2013-09-07

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

  19. Spatial dynamics of a population with stage-dependent diffusion

    NASA Astrophysics Data System (ADS)

    Azevedo, F.; Coutinho, R. M.; Kraenkel, R. A.

    2015-05-01

    We explore the spatial dynamics of a population whose individuals go through life stages with very different dispersal capacities. We model it through a system of partial differential equations of the reaction-diffusion kind, with nonlinear diffusion terms that may depend on population density and on the stage. This model includes a few key biological ingredients: growth and saturation, life stage structure, small population effects, and diffusion dependent on the stage. In particular, we consider that adults exhibit two distinct classes: one highly mobile and the other less mobile but with higher fecundity rate, and the development of juveniles into one or the other depends on population density. We parametrize the model with estimated parameters of an insect species, the brown planthopper. We focus on a situation akin to an invasion of the species in a new habitat and find that the front of invasion is led by the most mobile adult class. We also show that the trade-off between dispersal and fecundity leads to invasion speed attaining its maximum at an intermediate value of the diffusion coefficient of the most mobile class.

  20. The population dynamics of black-white-mulatto racial systems.

    PubMed

    Montgomery, James D

    2011-07-01

    Building on Preston and Campbell's two-sex model of intergenerational transmission, this article provides a theoretical analysis of the dynamics of the racial distribution in black-white-mulatto systems. The author shows that "bounded" patterns of racial classification and switching imply long-run racial homogeneity in the absence of differential reproduction. Beyond the theoretical analysis, the author attempts to account for the dramatic growth of the white population share in Puerto Rico in the early 20th century. Because the effects of racial classification and differential reproduction were roughly offsetting, the observed growth of the white share can be attributed almost entirely to racial switching.

  1. Global climate drives southern right whale (Eubalaena australis) population dynamics.

    PubMed

    Leaper, Russell; Cooke, Justin; Trathan, Phil; Reid, Keith; Rowntree, Victoria; Payne, Roger

    2006-06-22

    Sea surface temperature (SST) time-series from the southwest Atlantic and the El Niño 4 region in the western Pacific were compared to an index of annual calving success of the southern right whale (Eubalaena australis) breeding in Argentina. There was a strong relationship between right whale calving output and SST anomalies at South Georgia in the autumn of the previous year and also with mean El Niño 4 SST anomalies delayed by 6 years. These results extend similar observations from other krill predators and show clear linkages between global climate signals and the biological processes affecting whale population dynamics.

  2. 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.

  3. Population Physiology: Leveraging Electronic Health Record Data to Understand Human Endocrine Dynamics

    PubMed Central

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

    2012-01-01

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

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

    PubMed

    Liao, David; Tlsty, Thea D

    2014-08-06

    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.

  5. 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.

  6. 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.

  7. 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.

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

    PubMed

    Steinbrück, Lars; McHardy, Alice Carolyn

    2011-01-01

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

  9. Decadal prediction of Sahel rainfall using dynamics-based indices

    NASA Astrophysics Data System (ADS)

    Otero, Noelia; Mohino, Elsa; Gaetani, Marco

    2016-12-01

    At decadal time scales, the capability of state-of-the-art atmosphere-ocean coupled climate models in predicting the precipitation in Sahel is assessed. A set of 14 models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) is selected and two experiments are analysed, namely initialized decadal hindcasts and forced historical simulations. Considering the strong linkage of the atmospheric circulation signatures over West Africa with the rainfall variability, this study aims to investigate the potential of using wind fields for decadal predictions. Namely, a West African monsoon index (WAMI) is defined, based on the coherence of low (925 hPa) and high (200 hPa) troposphere wind fields, which accounts for the intensity of the monsoonal circulation. A combined empirical orthogonal functions analysis is applied to explore the wind fields' covariance modes, and a set of indices is defined on the basis of the identified patterns. The WAMI predictive skill is assessed by comparing WAMI from coupled models with WAMI from reanalysis products and with a standardized precipitation index (SPI) from observations. Results suggest that the predictive skill is highly model dependent and it is strongly related to the WAMI definition. In addition, hindcasts are more skilful than historical simulations in both deterministic and probability forecasts, which suggests an added value of initialization for decadal predictability. Moreover, coupled models are more skilful in predicting the observed SPI than the WAMI obtained from reanalysis. WAMI performance is also compared with decadal predictions from CMIP5 models based on a Sahelian precipitation index, and an improvement in predictive skill is observed in some models when WAMI is used. Therefore, we conclude that dynamics-based indices are potentially more effective for decadal prediction of precipitation in Sahel than precipitation-based indices for those models in which Sahel rainfall variability is not well

  10. Aftershock Prediction for High-Frequency Financial Markets' Dynamics

    NASA Astrophysics Data System (ADS)

    Baldovin, Fulvio; Camana, Francesco; Caraglio, Michele; Stella, Attilio L.; Zamparo, Marco

    The occurrence of aftershocks following a major financial crash manifests the critical dynamical response of financial markets. Aftershocks put additional stress on markets, with conceivable dramatic consequences. Such a phenomenon has been shown to be common to most financial assets, both at high and low frequency. Its present-day description relies on an empirical characterization proposed by Omori at the end of 1800 for seismic earthquakes. We point out the limited predictive power in this phenomenological approach and present a stochastic model, based on the scaling symmetry of financial assets, which is potentially capable to predict aftershocks occurrence, given the main shock magnitude. Comparisons with S&P high-frequency data confirm this predictive potential.

  11. 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.

  12. 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.

  13. 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.

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

    PubMed

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

    2008-11-04

    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 (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 (H(20), height of a 20-year-old open-grown tree) and late-successional performance (Z*, equilibrium canopy height in monoculture). These metrics predicted which species were early or late successional on each soil type. Decomposing Z* 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).

  15. Energy gains predict the distribution of plains bison across populations and ecosystems.

    PubMed

    Babin, Jean-Sébastien; Fortin, Daniel; Wilmshurst, John F; Fortin, Marie-Eve

    2011-01-01

    Developing tools that help predict animal distribution in the face of environmental change is central to understanding ecosystem function, but it remains a significant ecological challenge. We tested whether a single foraging currency could explain bison (Bison bison) distribution in dissimilar environments: a largely forested environment in Prince Albert National Park (Saskatchewan, Canada) and a prairie environment in Grasslands National Park (Saskatchewan, Canada). We blended extensive behavioral observations, relocations of radio-collared bison, vegetation surveys, and laboratory analyses to spatially link bison distribution in the two parks and expected gains for different nutritional currencies. In Prince Albert National Park, bison were more closely associated with the distribution of plants that maximized their instantaneous energy intake rate (IDE) than their daily intake of digestible energy. This result reflected both bison's intensity of use of individual meadows and their selection of foraging sites within meadows. On this basis, we tested whether IDE could explain the spatial dynamics of bison reintroduced to Grasslands National Park. As predicted, bison distribution in this park best matched spatial patterns of plants offering rapid IDE rather than rapid sodium intake, phosphorus intake, or daily intake of digestible energy. Because the two study areas have very different plant communities, a phenomenological model of resource selection developed in one area could not be used to predict animal distribution in the other. We were able, however, to successfully infer the distribution of bison from their foraging objective. This consistency in foraging currency across ecosystems and populations provides a strong basis for forecasting animal distributions in novel and dynamic environments.

  16. [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.

  17. 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.

  18. 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

  19. An Adaptive Multipopulation Differential Evolution With Dynamic Population Reduction.

    PubMed

    Ali, Mostafa Z; Awad, Noor H; Suganthan, Ponnuthurai Nagaratnam; Reynolds, Robert G

    2016-10-25

    Developing efficient evolutionary algorithms attracts many researchers due to the existence of optimization problems in numerous real-world applications. A new differential evolution algorithm, sTDE-dR, is proposed to improve the search quality, avoid premature convergence, and stagnation. The population is clustered in multiple tribes and utilizes an ensemble of different mutation and crossover strategies. In this algorithm, a competitive success-based scheme is introduced to determine the life cycle of each tribe and its participation ratio for the next generation. In each tribe, a different adaptive scheme is used to control the scaling factor and crossover rate. The mean success of each subgroup is used to calculate the ratio of its participation for the next generation. This guarantees that successful tribes with the best adaptive schemes are only the ones that guide the search toward the optimal solution. The population size is dynamically reduced using a dynamic reduction method. Comprehensive comparison of the proposed heuristic over a challenging set of benchmarks from the CEC2014 real parameter single objective competition against several state-of-the-art algorithms is performed. The results affirm robustness of the proposed approach compared to other state-of-the-art algorithms.

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

    PubMed Central

    Krkošek, Martin; Hilborn, Ray; Peterman, Randall M.; Quinn, Thomas P.

    2011-01-01

    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

  1. 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

    2015-05-28

    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.

  2. Dynamic Connectivity at Rest Predicts Attention Task Performance

    PubMed Central

    Askren, Mary K.; Boord, Peter; Grabowski, Thomas J.

    2015-01-01

    Abstract Consistent spatial patterns of coherent activity, representing large-scale networks, have been reliably identified in multiple populations. Most often, these studies have examined “stationary” connectivity. However, there is a growing recognition that there is a wealth of information in the time-varying dynamics of networks which has neural underpinnings, which changes with age and disease and that supports behavior. Using factor analysis of overlapping sliding windows across 25 participants with Parkinson disease (PD) and 21 controls (ages 41–86), we identify factors describing the covarying correlations of regions (dynamic connectivity) within attention networks and the default mode network, during two baseline resting-state and task runs. Cortical regions that support attention networks are affected early in PD, motivating the potential utility of dynamic connectivity as a sensitive way to characterize physiological disruption to these networks. We show that measures of dynamic connectivity are more reliable than comparable measures of stationary connectivity. Factors in the dorsal attention network (DAN) and fronto-parietal task control network, obtained at rest, are consistently related to the alerting and orienting reaction time effects in the subsequent Attention Network Task. In addition, the same relationship between the same DAN factor and the alerting effect was present during tasks. Although reliable, dynamic connectivity was not invariant, and changes between factor scores across sessions were related to changes in accuracy. In summary, patterns of time-varying correlations among nodes in an intrinsic network have a stability that has functional relevance. PMID:25014419

  3. 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.

  4. Neural Population Dynamics during Reaching Are Better Explained by a Dynamical System than Representational Tuning

    PubMed Central

    Dann, Benjamin

    2016-01-01

    Recent models of movement generation in motor cortex have sought to explain neural activity not as a function of movement parameters, known as representational models, but as a dynamical system acting at the level of the population. Despite evidence supporting this framework, the evaluation of representational models and their integration with dynamical systems is incomplete in the literature. Using a representational velocity-tuning based simulation of center-out reaching, we show that incorporating variable latency offsets between neural activity and kinematics is sufficient to generate rotational dynamics at the level of neural populations, a phenomenon observed in motor cortex. However, we developed a covariance-matched permutation test (CMPT) that reassigns neural data between task conditions independently for each neuron while maintaining overall neuron-to-neuron relationships, revealing that rotations based on the representational model did not uniquely depend on the underlying condition structure. In contrast, rotations based on either a dynamical model or motor cortex data depend on this relationship, providing evidence that the dynamical model more readily explains motor cortex activity. Importantly, implementing a recurrent neural network we demonstrate that both representational tuning properties and rotational dynamics emerge, providing evidence that a dynamical system can reproduce previous findings of representational tuning. Finally, using motor cortex data in combination with the CMPT, we show that results based on small numbers of neurons or conditions should be interpreted cautiously, potentially informing future experimental design. Together, our findings reinforce the view that representational models lack the explanatory power to describe complex aspects of single neuron and population level activity. PMID:27814352

  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. 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…

  7. 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

  8. Variation in the local population dynamics of the short-lived Opuntia macrorhiza (Cactaceae).

    PubMed

    Haridas, C V; Keeler, Kathleen H; Tenhumberg, Brigitte

    2015-03-01

    Spatiotemporal variation in demographic rates can have profound effects for population persistence, especially for dispersal-limited species living in fragmented landscapes. Long-term studies of plants in such habitats help with understanding the impacts of fragmentation on population persistence but such studies are rare. In this work, we reanalyzed demographic data from seven years of the short-lived cactus Opuntia macrorhiza var. macrorhiza at five plots in Boulder, Colorado. Previous work combining data from all years and all plots predicted a stable population (deterministic log lamda approximately 0). This approach assumed that all five plots were part of a single population. Since the plots were located in a suburban-agricultural interface separated by highways, grazing lands, and other barriers, and O. macrorhiza is likely dispersal limited, we analyzed the dynamics of each plot separately using stochastic matrix models assuming each plot represented a separate population. We found that the stochastic population growth rate log lamdaS varied widely between populations (log lamdaS = 0.1497, 0.0774, -0.0230, -0.2576, -0.4989). The three populations with the highest growth rates were located close together in space, while the two most isolated populations had the lowest growth rates suggesting that dispersal between populations is critical for the population viability of O. macrorhiza. With one exception, both our prospective (stochastic elasticity) and retrospective (stochastic life table response experiments) analysis suggested that means of stasis and growth, especially of smaller plants, were most important for population growth rate. This is surprising because recruitment is typically the most important vital rate in a short-lived species such as O. macrorhiza. We found that elasticity to the variance was mostly negligible, suggesting that O. macrorhiza populations are buffered against large temporal variation. Finally, single-year elasticities to means

  9. 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

  10. Predicting the High Redshift Galaxy Population for JWST

    NASA Astrophysics Data System (ADS)

    Flynn, Zoey; Benson, Andrew

    2017-01-01

    The James Webb Space Telescope will be launched in Oct 2018 with the goal of observing galaxies in the redshift range of z = 10 - 15. As redshift increases, the age of the Universe decreases, allowing us to study objects formed only a few hundred million years after the Big Bang. This will provide a valuable opportunity to test and improve current galaxy formation theory by comparing predictions for mass, luminosity, and number density to the observed data. We have made testable predictions with the semi-analytical galaxy formation model Galacticus. The code uses Markov Chain Monte Carlo methods to determine viable sets of model parameters that match current astronomical data. The resulting constrained model was then set to match the specifications of the JWST Ultra Deep Field Imaging Survey. Predictions utilizing up to 100 viable parameter sets were calculated, allowing us to assess the uncertainty in current theoretical expectations. We predict that the planned UDF will be able to observe a significant number of objects past redshift z > 9 but nothing at redshift z > 11. In order to detect these faint objects at redshifts z = 11-15 we need to increase exposure time by at least a factor of 1.66.

  11. Predicting population survival under future climate change: density dependence, drought and extraction in an insular bighorn sheep.

    PubMed

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

    2009-05-01

    1. Our understanding of the interplay between density dependence, climatic perturbations, and conservation practices on the dynamics of small populations is still limited. This can result in uninformed strategies that put endangered populations at risk. Moreover, the data available for a large number of populations in such circumstances are sparse and mined with missing data. Under the current climate change scenarios, it is essential to develop appropriate inferential methods that can make use of such data sets. 2. We studied a population of desert bighorn sheep introduced to Tiburon Island, Mexico in 1975 and subjected to irregular extractions for the last 10 years. The unique attributes of this population are absence of predation and disease, thereby permitting us to explore the combined effect of density dependence, environmental variability and extraction in a 'controlled setting.' Using a combination of nonlinear discrete models with long-term field data, we constructed three basic Bayesian state space models with increasing density dependence (DD), and the same three models with the addition of summer drought effects. 3. We subsequently used Monte Carlo simulations to evaluate the combined effect of drought, DD, and increasing extractions on the probability of population survival under two climate change scenarios (based on the Intergovernmental Panel on Climate Change predictions): (i) increase in drought variability; and (ii) increase in mean drought severity. 4. The population grew from 16 individuals introduced in 1975 to close to 700 by 1993. Our results show that the population's growth was dominated by DD, with drought having a secondary but still relevant effect on its dynamics. 5. Our predictions suggest that under climate change scenario (i), extraction dominates the fate of the population, while for scenario (ii), an increase in mean drought affects the population's probability of survival in an equivalent magnitude as extractions. Thus, for the

  12. World Trade, disease and Florida's animal populations. The changing dynamics.

    PubMed

    Coffman, L M

    2000-01-01

    One of Florida's three leading economic industries is agriculture. Agriculture feeds and enhances the lives of millions of people in Florida, the United States, and the entire world. Agriculture in Florida results in more than $6 billion in farm cash receipts, employment for more than 60,000 people a month, more than $18 billion in farm-related economic activity and stretches from the farm gate to the state's supermarkets with an impact of nearly $45 billion. The domestic and wild animal populations of Florida, our unique relationship to the Caribbean, Atlantic Ocean, Gulf of Mexico, Central and South America, as well as tourism, diverse human population growth and immigration, all add to the complexity of an environment capable of establishing many animals, animal pests and diseases not native to the United States. Never before have the dynamics of disease control involved as much challenge and diversity. Is the balance at risk, or is the risk over-balanced? Can science, economics and politics blend to maintain this balance? How will the balance affect world trade, disease control and the animal populations of Florida?

  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

    2015-11-07

    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.

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

    PubMed Central

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

    2015-01-01

    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

  15. 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.

  16. Integrating environmental and genetic effects to predict responses of tree populations to climate.

    PubMed

    Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N

    2010-01-01

    Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.

  17. Dynamic knee loads during gait predict proximal tibial bone distribution.

    PubMed

    Hurwitz, D E; Sumner, D R; Andriacchi, T P; Sugar, D A

    1998-05-01

    This study tested the validity of the prediction of dynamic knee loads based on gait measurements. The relationship between the predicted loads at the knee and the distribution of bone between the medial and lateral sides of the tibia was examined. The motion and external forces and moments at the knee were measured during gait and a statically determinate muscle model was used to predict the corresponding forces on the medial and lateral tibial plateaus. In particular, the relationship between the knee adduction moment during gait and the ratio or distribution of medial to lateral tibial bone mineral content was studied. Bone mineral content was measured with dual energy X-ray absorptiometry in four regions, two proximal regions 20 mm in height, one medial and one lateral and two distal regions 20 mm in height, one medial and one lateral. The best single predictor of the medial lateral ratio of proximal bone mineral content (bone distribution) was the adduction moment (R2=0.31, p=0.003). Adding weight (negative coefficient. p=0.0004) and the ratio of the average predicted peak force on the medial plateau to the predicted peak force on the lateral plateau (positive coefficient, p=0.0033) to the regression model significantly increased the ability to predict the proximal medial lateral bone distribution (R2=0.72, p=0.0001). Distally neither the subject characteristics nor the gait moments and predicted forces were significant predictors of the bone distribution. The lack of a correlation distally may be reflective of the forces being more evenly distributed further from the tibial plateau. While it has long been suggested that the adduction moment is the primary determinate of the distribution of load between the medial and lateral plateaus, this is the first evidence of its relationship to the underlying bone distribution.

  18. Dynamic hub load predicts cognitive decline after resective neurosurgery

    PubMed Central

    Carbo, Ellen W. S.; Hillebrand, Arjan; van Dellen, Edwin; Tewarie, Prejaas; de Witt Hamer, Philip C.; Baayen, Johannes C.; Klein, Martin; Geurts, Jeroen J. G.; Reijneveld, Jaap C.; Stam, Cornelis J.; Douw, Linda

    2017-01-01

    Resective neurosurgery carries the risk of postoperative cognitive deterioration. The concept of ‘hub (over)load’, caused by (over)use of the most important brain regions, has been theoretically postulated in relation to symptomatology and neurological disease course, but lacks experimental confirmation. We investigated functional hub load and postsurgical cognitive deterioration in patients undergoing lesion resection. Patients (n = 28) underwent resting-state magnetoencephalography and neuropsychological assessments preoperatively and 1-year after lesion resection. We calculated stationary hub load score (SHub) indicating to what extent brain regions linked different subsystems; high SHub indicates larger processing pressure on hub regions. Dynamic hub load score (DHub) assessed its variability over time; low values, particularly in combination with high SHub values, indicate increased load, because of consistently high usage of hub regions. Hypothetically, increased SHub and decreased DHub relate to hub overload and thus poorer/deteriorating cognition. Between time points, deteriorating verbal memory performance correlated with decreasing upper alpha DHub. Moreover, preoperatively low DHub values accurately predicted declining verbal memory performance. In summary, dynamic hub load relates to cognitive functioning in patients undergoing lesion resection: postoperative cognitive decline can be tracked and even predicted using dynamic hub load, suggesting it may be used as a prognostic marker for tailored treatment planning. PMID:28169349

  19. Dynamic hub load predicts cognitive decline after resective neurosurgery.

    PubMed

    Carbo, Ellen W S; Hillebrand, Arjan; van Dellen, Edwin; Tewarie, Prejaas; de Witt Hamer, Philip C; Baayen, Johannes C; Klein, Martin; Geurts, Jeroen J G; Reijneveld, Jaap C; Stam, Cornelis J; Douw, Linda

    2017-02-07

    Resective neurosurgery carries the risk of postoperative cognitive deterioration. The concept of 'hub (over)load', caused by (over)use of the most important brain regions, has been theoretically postulated in relation to symptomatology and neurological disease course, but lacks experimental confirmation. We investigated functional hub load and postsurgical cognitive deterioration in patients undergoing lesion resection. Patients (n = 28) underwent resting-state magnetoencephalography and neuropsychological assessments preoperatively and 1-year after lesion resection. We calculated stationary hub load score (SHub) indicating to what extent brain regions linked different subsystems; high SHub indicates larger processing pressure on hub regions. Dynamic hub load score (DHub) assessed its variability over time; low values, particularly in combination with high SHub values, indicate increased load, because of consistently high usage of hub regions. Hypothetically, increased SHub and decreased DHub relate to hub overload and thus poorer/deteriorating cognition. Between time points, deteriorating verbal memory performance correlated with decreasing upper alpha DHub. Moreover, preoperatively low DHub values accurately predicted declining verbal memory performance. In summary, dynamic hub load relates to cognitive functioning in patients undergoing lesion resection: postoperative cognitive decline can be tracked and even predicted using dynamic hub load, suggesting it may be used as a prognostic marker for tailored treatment planning.

  20. Mechanisms Underlying Population Response Dynamics in Inhibitory Interneurons of the Drosophila Antennal Lobe

    PubMed Central

    Nagel, Katherine I.

    2016-01-01

    Local inhibitory neurons control the timing of neural activity in many circuits. To understand how inhibition controls timing, it is important to understand the dynamics of activity in populations of local inhibitory interneurons, as well as the mechanisms that underlie these dynamics. Here we describe the in vivo response dynamics of a large population of inhibitory local neurons (LNs) in the Drosophila melanogaster antennal lobe, the analog of the vertebrate olfactory bulb, and we dissect the network and intrinsic mechanisms that give rise to these dynamics. Some LNs respond to odor onsets (“ON” cells) and others to offsets (“OFF” cells), whereas still others respond at both times. Moreover, different LNs signal odor concentration fluctuations on different timescales. Some respond rapidly, and can track rapid concentration fluctuations. Others respond slowly, and are best at tracking slow fluctuations. We found a continuous spectrum of preferred stimulation timescales among LNs, as well as a continuum of ON–OFF behavior. Using in vivo whole-cell recordings, we show that the timing of an LN′s response (ON vs OFF) can be predicted from the interplay of excitatory and inhibitory synaptic currents that it receives. Meanwhile, the preferred timescale of an LN is related to its intrinsic properties. These results illustrate how a population of inhibitory interneurons can collectively encode bidirectional changes in stimulus intensity on multiple timescales, and how this can arise via an interaction between synaptic and intrinsic mechanisms. SIGNIFICANCE STATEMENT Most neural circuits contain diverse populations of inhibitory interneurons. The way inhibition shapes network activity will depend on the spiking dynamics of the interneuron population. Here we describe the dynamics of activity in a large population of inhibitory interneurons in the first brain relay of the fruit fly olfactory system. Because odor plumes fluctuate on multiple timescales, the drive

  1. A Predictive Model for Wind Farms Using Dynamic Mode Decomposition

    NASA Astrophysics Data System (ADS)

    Thomas, Vaughan; Meneveau, Charles; Gayme, Dennice

    2016-11-01

    In this work we extend traditional dynamic mode decomposition (DMD) to develop a linear predictive model for the time evolution of the velocity field for a multiple-turbine wind farm. Traditional DMD identifies a set of DMD modes which can be used to produce a linear system that approximates the dynamics of the original system. Typically, these DMD modes consist of those that both grow and decay, but in order to develop a predictive model we need a system that evolves along a manifold that neither grows nor decays. Here we modify the DMD calculation to build such a model. We then apply this method to three dimensional large eddy simulations (LES) of a multi-turbine wind farm. Our predictive wind farm model is initialized with a small time series of data independent of the original data used to create the system. When initialized in this manner our DMD based model can reproduce the subsequent time evolution of the velocity field over ten inter-turbine convective timescales with a gradual falloff in performance. This work is supported by the National Science Foundation (Grants ECCS-1230788 and OISE-1243482, the WINDINSPIRE project).

  2. Connectionist Architectures for Time Series Prediction of Dynamical Systems

    NASA Astrophysics Data System (ADS)

    Weigend, Andreas Sebastian

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

  3. 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.

  4. 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.

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

    PubMed

    Lorenzen, Kai

    2005-01-29

    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.

  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. Interactions between local climate and grazing determine the population dynamics of the small herb Viola biflora.

    PubMed

    Evju, Marianne; Halvorsen, Rune; Rydgren, Knut; Austrheim, Gunnar; Mysterud, Atle

    2010-08-01

    Plants of low stature may benefit from the presence of large herbivores through removal of tall competitive neighbours and increased light availability. Accordingly, removal of grazers has been predicted to disfavour small species. In addition to this indirect beneficial effect, the population dynamics of plants is strongly influenced by variation in external conditions such as temperature and precipitation. However, few studies have examined the interaction between large herbivores and inter-annual variation in climate for the population dynamics of small plant species not preferred by herbivores. We studied three populations of the perennial herb Viola biflora exposed to different sheep densities (high, low and zero) for 6 years in a field experiment. Plants were also impacted by invertebrate and small vertebrate herbivores (rodents). Rates of growth were marginally higher at high sheep densities, and during warm summers both survival and growth were higher when sheep were present. Thus, while the height of tall herbs was positively related to July temperature, it was less so in the treatments with sheep, suggesting that sheep reduce the negative effects of interspecific competition for this small herb. Life table response experiment analyses revealed that the population growth rate (lambda) was slightly lower in the absence of sheep, but between-year variation in lambda was larger than variation among sheep density treatments. lambda was negatively related to July temperature, with an additional negative effect of vertebrate grazing frequency (sheep or rodent grazing). The evidence from this 6-year study suggests that the population dynamics of Viola biflora is determined by a complex interplay between climate and grazing by both large and small herbivores.

  8. Prediction of residential radon exposure of the whole Swiss population: comparison of model-based predictions with measurement-based predictions.

    PubMed

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

    2013-10-01

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

  9. 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.

  10. 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.

  11. A skinning prediction scheme for dynamic 3D mesh compression

    NASA Astrophysics Data System (ADS)

    Mamou, Khaled; Zaharia, Titus; Prêteux, Françoise

    2006-08-01

    This paper presents a new prediction-based compression technique for dynamic 3D meshes with constant connectivity and time-varying geometry. The core of the proposed algorithm is a skinning model used for motion compensation. The mesh is first partitioned within vertex clusters that can be described by a single affine motion model. The proposed segmentation technique automatically determines the number of clusters and relays on a decimation strategy privileging the simplification of vertices exhibiting the same affine motion over the whole animation sequence. The residual prediction errors are finally compressed using a temporal-DCT representation. The performances of our encoder are objectively evaluated on a data set of eight animation sequences with various sizes, geometries and topologies, and exhibiting both rigid and elastic motions. The experimental evaluation shows that the proposed compression scheme outperforms state of the art techniques such as MPEG-4/AFX, Dynapack, RT, GV, MCGV, TDCT, PCA and RT compression schemes.

  12. Predictability and Coupled Dynamics of MJO During DYNAMO

    DTIC Science & Technology

    2013-09-30

    00-2013 to 00-00-2013 4 . TITLE AND SUBTITLE Predictability and Coupled Dynamics of MJO During DYNAMO 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c...during DYNAMO, large number of vertical layers are allocated in the upper ocean to allow 4 - 5 layers in the upper 1-meter and 33 layers in the upper...whereas CF24 lacks the diurnal variation. While the mean SST appears to be slightly warmer in CF24 than 4 CF1, due to the large range of diurnal

  13. Predictability and Coupled Dynamics of MJO During DYNAMO

    DTIC Science & Technology

    2013-09-30

    2013 2. REPORT TYPE 3. DATES COVERED 00-00-2013 to 00-00-2013 4 . TITLE AND SUBTITLE Predictability and Coupled Dynamics of MJO During DYNAMO 5a...allocated in the upper ocean to allow 4 - 5 layers in the upper 1-meter and 33 layers in the upper 55 meters. WRF and ROMS share the identical grids and...SST appears to be slightly warmer in CF24 than 4 CF1, due to the large range of diurnal variation in temperature, higher SST is achieved on

  14. Predicting protein dynamic binding capacity from batch adsorption tests.

    PubMed

    Carta, Giorgio

    2012-10-01

    The dynamic binding capacity (DBC) and its dependence on residence time influence the design and productivity of adsorption columns used in protein capture applications. This paper offers a very simple approach to predict the DBC of an adsorption column based on a measurement of the equilibrium binding capacity (EBC) and of the time needed to achieve one-half of the EBC in a batch adsorption test. The approach is based on a mass transfer kinetics model that assumes pore diffusion with a rectangular isotherm; however, the same approach is also shown to work for other systems where solute transport inside the particle occurs through other transport mechanisms.

  15. 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.

  16. Dynamic modeling of cellular populations within iBioSim.

    PubMed

    Stevens, Jason T; Myers, Chris J

    2013-05-17

    As the complexity of synthetic genetic circuits increases, modeling is becoming a necessary first step to inform subsequent experimental efforts. In recent years, the design automation community has developed a wealth of computational tools for assisting experimentalists in designing and analyzing new genetic circuits at several scales. However, existing software primarily caters to either the DNA- or single-cell level, with little support for the multicellular level. To address this need, the iBioSim software package has been enhanced to provide support for modeling, simulating, and visualizing dynamic cellular populations in a two-dimensional space. This capacity is fully integrated into the software, capitalizing on iBioSim's strengths in modeling, simulating, and analyzing single-celled systems.

  17. 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.

  18. "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.

  19. 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.

  20. Study of a mixed dispersal population dynamics model

    DOE PAGES

    Chugunova, Marina; Jadamba, Baasansuren; Kao, Chiu -Yen; ...

    2016-08-27

    In this study, we consider a mixed dispersal model with periodic and Dirichlet boundary conditions and its corresponding linear eigenvalue problem. This model describes the time evolution of a population which disperses both locally and non-locally. We investigate how long time dynamics depend on the parameter values. Furthermore, we study the minimization of the principal eigenvalue under the constraints that the resource function is bounded from above and below, and with a fixed total integral. Biologically, this minimization problem is motivated by the question of determining the optimal spatial arrangement of favorable and unfavorable regions for the species to diemore » out more slowly or survive more easily. Our numerical simulations indicate that the optimal favorable region tends to be a simply-connected domain. Numerous results are shown to demonstrate various scenarios of optimal favorable regions for periodic and Dirichlet boundary conditions.« less

  1. Study of a mixed dispersal population dynamics model

    SciTech Connect

    Chugunova, Marina; Jadamba, Baasansuren; Kao, Chiu -Yen; Klymko, Christine F.; Thomas, Evelyn; Zhao, Bingyu

    2016-08-27

    In this study, we consider a mixed dispersal model with periodic and Dirichlet boundary conditions and its corresponding linear eigenvalue problem. This model describes the time evolution of a population which disperses both locally and non-locally. We investigate how long time dynamics depend on the parameter values. Furthermore, we study the minimization of the principal eigenvalue under the constraints that the resource function is bounded from above and below, and with a fixed total integral. Biologically, this minimization problem is motivated by the question of determining the optimal spatial arrangement of favorable and unfavorable regions for the species to die out more slowly or survive more easily. Our numerical simulations indicate that the optimal favorable region tends to be a simply-connected domain. Numerous results are shown to demonstrate various scenarios of optimal favorable regions for periodic and Dirichlet boundary conditions.

  2. Homeochaos: dynamics stability of a symbiotic network with population dynamics and evolving mutation rates

    NASA Astrophysics Data System (ADS)

    Kaneko, Kunihiko; Ikegami, Takashi

    1992-06-01

    Evolution of mutation rates is studied, in a population model with mutation of species coded by bit sequences and mutation rates. Even without interaction among species, the mutation rate is initially enhanced to search for fitted species and then is lowered towards zero. This enhancement opens a possibility of automatic simulated annealing. With the interaction among species (hosts versus parasites), high mutation rates are sustained. The rates go up with the interaction strength abruptly if the fitness landscape is rugged. A large cluster of species, connected by mutation, is formed by a sustained high mutation rate. With the formation of this symbiotic network resolved is the paradox of mutation rates; paradox on the stability of a rule to change itself. Population dynamics of each species shows high-dimensional chaos with small positive Lyapunov exponents. Stability of our symbiotic network is dynamically sustained through this weak high-dimensional chaos, termed “homeochaos”.

  3. 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.

  4. 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

  5. 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.

  6. Building dynamic population graph for accurate correspondence detection.

    PubMed

    Du, Shaoyi; Guo, Yanrong; Sanroma, Gerard; Ni, Dong; Wu, Guorong; Shen, Dinggang

    2015-12-01

    In medical imaging studies, there is an increasing trend for discovering the intrinsic anatomical difference across individual subjects in a dataset, such as hand images for skeletal bone age estimation. Pair-wise matching is often used to detect correspondences between each individual subject and a pre-selected model image with manually-placed landmarks. However, the large anatomical variability across individual subjects can easily compromise such pair-wise matching step. In this paper, we present a new framework to simultaneously detect correspondences among a population of individual subjects, by propagating all manually-placed landmarks from a small set of model images through a dynamically constructed image graph. Specifically, we first establish graph links between models and individual subjects according to pair-wise shape similarity (called as forward step). Next, we detect correspondences for the individual subjects with direct links to any of model images, which is achieved by a new multi-model correspondence detection approach based on our recently-published sparse point matching method. To correct those inaccurate correspondences, we further apply an error detection mechanism to automatically detect wrong correspondences and then update the image graph accordingly (called as backward step). After that, all subject images with detected correspondences are included into the set of model images, and the above two steps of graph expansion and error correction are repeated until accurate correspondences for all subject images are established. Evaluations on real hand X-ray images demonstrate that our proposed method using a dynamic graph construction approach can achieve much higher accuracy and robustness, when compared with the state-of-the-art pair-wise correspondence detection methods as well as a similar method but using static population graph.

  7. Zooplankton population dynamics in experimentally toxified pond ecosystems

    SciTech Connect

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

    1989-01-01

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

  8. 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

  9. Eukaryotic transcriptional dynamics: from single molecules to cell populations

    PubMed Central

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

    2013-01-01

    Transcriptional regulation is achieved through combinatorial interactions between regulatory elements in the human genome and a vast range of factors that modulate the recruitment and activity of RNA polymerase. Experimental approaches for studying transcription in vivo now extend from single-molecule techniques to genome-wide measurements. Parallel to these developments is the need for testable quantitative and predictive models for understanding gene regulation. These conceptual models must also provide insight into the dynamics of transcription and the variability that is observed at the single-cell level. In this Review, we discuss recent results on transcriptional regulation and also the models those results engender. We show how a non-equilibrium description informs our view of transcription by explicitly considering time-and energy-dependence at the molecular level. PMID:23835438

  10. Separating direct and indirect effects of global change: a population dynamic modeling approach using readily available field data.

    PubMed

    Farrer, Emily C; Ashton, Isabel W; Knape, Jonas; Suding, Katharine N

    2014-04-01

    Two sources of complexity make predicting plant community response to global change particularly challenging. First, realistic global change scenarios involve multiple drivers of environmental change that can interact with one another to produce non-additive effects. Second, in addition to these direct effects, global change drivers can indirectly affect plants by modifying species interactions. In order to tackle both of these challenges, we propose a novel population modeling approach, requiring only measurements of abundance and climate over time. To demonstrate the applicability of this approach, we model population dynamics of eight abundant plant species in a multifactorial global change experiment in alpine tundra where we manipulated nitrogen, precipitation, and temperature over 7 years. We test whether indirect and interactive effects are important to population dynamics and whether explicitly incorporating species interactions can change predictions when models are forecast under future climate change scenarios. For three of the eight species, population dynamics were best explained by direct effect models, for one species neither direct nor indirect effects were important, and for the other four species indirect effects mattered. Overall, global change had negative effects on species population growth, although species responded to different global change drivers, and single-factor effects were slightly more common than interactive direct effects. When the fitted population dynamic models were extrapolated under changing climatic conditions to the end of the century, forecasts of community dynamics and diversity loss were largely similar using direct effect models that do not explicitly incorporate species interactions or best-fit models; however, inclusion of species interactions was important in refining the predictions for two of the species. The modeling approach proposed here is a powerful way of analyzing readily available datasets which should be

  11. Irruptive dynamics of introduced caribou on Adak Island, Alaska: an evaluation of Riney-Caughley model predictions

    USGS Publications Warehouse

    Ricca, Mark A.; Van Vuren, Dirk H.; Weckerly, Floyd W.; Williams, Jeffrey C.; Miles, A. Keith

    2014-01-01

    Large mammalian herbivores introduced to islands without predators are predicted to undergo irruptive population and spatial dynamics, but only a few well-documented case studies support this paradigm. We used the Riney-Caughley model as a framework to test predictions of irruptive population growth and spatial expansion of caribou (Rangifer tarandus granti) introduced to Adak Island in the Aleutian archipelago of Alaska in 1958 and 1959. We utilized a time series of spatially explicit counts conducted on this population intermittently over a 54-year period. Population size increased from 23 released animals to approximately 2900 animals in 2012. Population dynamics were characterized by two distinct periods of irruptive growth separated by a long time period of relative stability, and the catalyst for the initial irruption was more likely related to annual variation in hunting pressure than weather conditions. An unexpected pattern resembling logistic population growth occurred between the peak of the second irruption in 2005 and the next survey conducted seven years later in 2012. Model simulations indicated that an increase in reported harvest alone could not explain the deceleration in population growth, yet high levels of unreported harvest combined with increasing density-dependent feedbacks on fecundity and survival were the most plausible explanation for the observed population trend. No studies of introduced island Rangifer have measured a time series of spatial use to the extent described in this study. Spatial use patterns during the post-calving season strongly supported Riney-Caughley model predictions, whereby high-density core areas expanded outwardly as population size increased. During the calving season, caribou displayed marked site fidelity across the full range of population densities despite availability of other suitable habitats for calving. Finally, dispersal and reproduction on neighboring Kagalaska Island represented a new dispersal front

  12. 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

  13. Dynamic equilibrium of reconstituting hematopoietic stem cell populations.

    PubMed

    O'Quigley, John

    2010-12-01

    Clonal dominance in hematopoietic stem cell populations is an important question of interest but not one we can directly answer. Any estimates are based on indirect measurement. For marked populations, we can equate empirical and theoretical moments for binomial sampling, in particular we can use the well-known formula for the sampling variation of a binomial proportion. The empirical variance itself cannot always be reliably estimated and some caution is needed. We describe the difficulties here and identify ready solutions which only require appropriate use of variance-stabilizing transformations. From these we obtain estimators for the steady state, or dynamic equilibrium, of the number of hematopoietic stem cells involved in repopulating the marrow. The calculations themselves are not too involved. We give the distribution theory for the estimator as well as simple approximations for practical application. As an illustration, we rework on data recently gathered to address the question as to whether or not reconstitution of marrow grafts in the clinical setting might be considered to be oligoclonal.

  14. 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.

  15. Sensory dynamics of visual hallucinations in the normal population

    PubMed Central

    Pearson, Joel; Chiou, Rocco; Rogers, Sebastian; Wicken, Marcus; Heitmann, Stewart; Ermentrout, Bard

    2016-01-01

    Hallucinations occur in both normal and clinical populations. Due to their unpredictability and complexity, the mechanisms underlying hallucinations remain largely untested. Here we show that visual hallucinations can be induced in the normal population by visual flicker, limited to an annulus that constricts content complexity to simple moving grey blobs, allowing objective mechanistic investigation. Hallucination strength peaked at ~11 Hz flicker and was dependent on cortical processing. Hallucinated motion speed increased with flicker rate, when mapped onto visual cortex it was independent of eccentricity, underwent local sensory adaptation and showed the same bistable and mnemonic dynamics as sensory perception. A neural field model with motion selectivity provides a mechanism for both hallucinations and perception. Our results demonstrate that hallucinations can be studied objectively, and they share multiple mechanisms with sensory perception. We anticipate that this assay will be critical to test theories of human consciousness and clinical models of hallucination. DOI: http://dx.doi.org/10.7554/eLife.17072.001 PMID:27726845

  16. 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

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

    PubMed

    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.

  18. 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.

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

    PubMed Central

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

    2016-01-01

    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

  20. 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...

  1. 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...

  2. [The Prediction Model of Cardiovascular Events Among the Russian Population: Methodological Aspects].

    PubMed

    Kontsevaya, A V; Shalnova, S A; Suvorova, E I; Balanova, Y A; Evstifeeva, S E; Imaeva, A E; Kapustina, A V; Deev, A D; Karpov, Y A; Ostroumova, O D; Ageev, F T; Blinkov, O S; Zinchuk, I Yu; Repekto, K A; Boytsov S, A

    2016-12-01

    Modeling is the common approach for predicting not only the population health, but also the social and economic burden of disease, which is an important argument while making decisions in health care and prevention.

  3. The role of resting cysts in Alexandrium minutum population dynamics

    NASA Astrophysics Data System (ADS)

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

    2010-02-01

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

  4. 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

  5. Predicted equations for ventilatory function among Kuching (Sarawak, Malaysia) population.

    PubMed

    Djojodibroto, R D; Pratibha, G; Kamaluddin, B; Manjit, S S; Sumitabha, G; Kumar, A Deva; Hashami, B

    2009-12-01

    Spirometry data of 869 individuals (males and females) between the ages of 10 to 60 years were analyzed. The analysis yielded the following conclusions: 1. The pattern of Forced Vital Capacity (FVC) and Forced Expiratory Volume in One Second (FEV1) for the selected subgroups seems to be gender dependant: in males, the highest values were seen in the Chinese, followed by the Malay, and then the Dayak; in females, the highest values were seen in the Chinese, followed by the Dayak, and then the Malay. 2. Smoking that did not produce respiratory symptom was not associated with a decline in lung function, in fact we noted higher values in smokers as compared to nonsmokers. 3. Prediction formulae (54 in total) are worked out for FVC & FEV1 for the respective gender and each of the selected subgroups.

  6. Impact of climate change on fish population dynamics in the Baltic sea: a dynamical downscaling investigation.

    PubMed

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

    2012-09-01

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

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

    PubMed

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

    2016-05-07

    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.

  8. Statistical mechanics of epidemics and population dynamics on networks

    NASA Astrophysics Data System (ADS)

    Joo, Jaewook

    After a short introduction to the modeling of epidemics and population dynamics, we investigate in chapter 2, the time-evolution and steady states of an epidemic model (susceptible-infected-recovered-susceptible) on a network having the topology of the hypercubic lattice. We compare the behavior of this system, obtained from computer simulations, with those obtained from the mean-field approximation and pair-approximation. We find that the latter is significantly better than the former. In chapter 3, we study the behavior of a simple epidemic process (susceptible-infected-susceptible) on realistic networks in which vertices represent individuals and edges the interactions between them. Of particular interest are scale free networks with power-law distribution of degree, the number of edges emanating from a vertex. Considering cases where the transmission of infection between vertices depends on their degree, we introduce a saturation function which reduces the infection transmission rate across an edge leading to a node with high connectivity. This leads to a finite epidemic threshold on scale free networks with infinite second moment degree distribution above which the endemic infected state will be sustained and below which the disease dies out. In chapter 4, we study the time evolution and stationary states of a stochastic population model (contact process) with spatial heterogeneity and imposed drift (wind) on one- and two-dimensional lattices. We consider in particular a situation in which space is divided into two regions: an oasis and a desert (low and high death rates). Depending on the values of the drift and other parameters the population in the stationary state will be zero, localized, or delocalized. Finally, in appendix A we discuss a very different delocalized to localized type phase transition: the Mott metal insulator transition occurring in a half-filled single-band Hubbard model on a Bethe lattice. In the limit of infinite lattice coordination

  9. 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

  10. Modeling effects of environmental change on wolf population dynamics, trait evolution, and life history.

    PubMed

    Coulson, Tim; MacNulty, Daniel R; Stahler, Daniel R; vonHoldt, Bridgett; Wayne, Robert K; Smith, Douglas W

    2011-12-02

    Environmental change has been observed to generate simultaneous responses in population dynamics, life history, gene frequencies, and morphology in a number of species. But how common are such eco-evolutionary responses to environmental change likely to be? Are they inevitable, or do they require a specific type of change? Can we accurately predict eco-evolutionary responses? We address these questions using theory and data from the study of Yellowstone wolves. We show that environmental change is expected to generate eco-evolutionary change, that changes in the average environment will affect wolves to a greater extent than changes in how variable it is, and that accurate prediction of the consequences of environmental change will probably prove elusive.

  11. Postfire seedling dynamics and performance in Pinus halepensis Mill. populations

    NASA Astrophysics Data System (ADS)

    Daskalakou, Evangelia N.; Thanos, Costas A.

    2010-09-01

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

  12. Dynamic biochemical reaction process analysis and pathway modification predictions.

    PubMed

    Conejeros, R; Vassiliadis, V S

    2000-05-05

    Recently, the area of model predictive modification of biochemical pathways has received attention with the aim to increase the productivity of microbial systems. In this study, we present a generalization of previous work, where, using a sensitivity study over the fermentation as a dynamic system, the optimal selection of reaction steps for modification (amplification or attenuation) is determined. The influence of metabolites in the activity of enzymes has also been considered (through activation or inhibition). We further introduce a new concept in the dynamic modeling of biochemical reaction systems including a generalized continuous superstructure in which two artificial multiplicative terms are included to account for: (a) enzyme overexpression or underexpression (attenuation or amplification) for the whole enzyme pool; and (b) modification of the apparent order of a kinetic expression with respect to the concentration of a metabolite or any subset of metabolites participating in the pathway. This new formulation allows the prediction of the sensitivity of the pathway performance index (objective function) with respect to the concentration of the enzyme, as well as the interaction of the enzyme with other metabolites. Using this framework, a case study for the production of penicillin V is analyzed, obtaining the most sensitive reaction steps (or bottlenecks) and the most significant regulations of the system, due to the effect of concentration of intracellular metabolites on the activity of each enzyme.

  13. 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

  14. 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

  15. 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.

  16. Dynamic Measures of RSA Predict Distress and Regulation in Toddlers

    PubMed Central

    Brooker, Rebecca J.; Buss, Kristin A.

    2010-01-01

    In this study, we examined a new method for quantifying individual variability using dynamic measures of Respiratory Sinus Arrhythmia (RSA). This method incorporated temporal variation into the measurement of RSA and provided information beyond that offered by more traditional quantifications such as difference scores. Dynamic and static measures of change in RSA were tested in relation to displays of emotion and affective behaviors during a fear eliciting episode in a sample of 88 typically-developing and high-fear toddlers during a laboratory visit at age 24 months. Dynamic measures of RSA contributed information that was unique from traditionally-employed, static change scores in predicting high-fear toddlers’ displays of shyness during a fear-eliciting episode. In contrast, RSA change scores offered information related to boldness in non-high-fear children. In addition, several associations included estimates of nonlinear change in RSA. Implications for the study of individual differences in RSA and relations with emotion and emotion regulation are discussed. PMID:20373328

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

    PubMed

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

    2015-09-21

    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.

  18. 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

  19. 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

  20. 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

  1. 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; Mader, Helmut; Kraml, Julia

    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.

  2. 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...

  3. 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.

  4. Population cycles and species diversity in dynamic Kill-the-Winner model of microbial ecosystems

    NASA Astrophysics Data System (ADS)

    Maslov, Sergei; Sneppen, Kim

    2017-01-01

    Determinants of species diversity in microbial ecosystems remain poorly understood. Bacteriophages are believed to increase the diversity by the virtue of Kill-the-Winner infection bias preventing the fastest growing organism from taking over the community. Phage-bacterial ecosystems are traditionally described in terms of the static equilibrium state of Lotka-Volterra equations in which bacterial growth is exactly balanced by losses due to phage predation. Here we consider a more dynamic scenario in which phage infections give rise to abrupt and severe collapses of bacterial populations whenever they become sufficiently large. As a consequence, each bacterial population in our model follows cyclic dynamics of exponential growth interrupted by sudden declines. The total population of all species fluctuates around the carrying capacity of the environment, making these cycles cryptic. While a subset of the slowest growing species in our model is always driven towards extinction, in general the overall ecosystem diversity remains high. The number of surviving species is inversely proportional to the variation in their growth rates but increases with the frequency and severity of phage-induced collapses. Thus counter-intuitively we predict that microbial communities exposed to more violent perturbations should have higher diversity.

  5. Population cycles and species diversity in dynamic Kill-the-Winner model of microbial ecosystems.

    PubMed

    Maslov, Sergei; Sneppen, Kim

    2017-01-04

    Determinants of species diversity in microbial ecosystems remain poorly understood. Bacteriophages are believed to increase the diversity by the virtue of Kill-the-Winner infection bias preventing the fastest growing organism from taking over the community. Phage-bacterial ecosystems are traditionally described in terms of the static equilibrium state of Lotka-Volterra equations in which bacterial growth is exactly balanced by losses due to phage predation. Here we consider a more dynamic scenario in which phage infections give rise to abrupt and severe collapses of bacterial populations whenever they become sufficiently large. As a consequence, each bacterial population in our model follows cyclic dynamics of exponential growth interrupted by sudden declines. The total population of all species fluctuates around the carrying capacity of the environment, making these cycles cryptic. While a subset of the slowest growing species in our model is always driven towards extinction, in general the overall ecosystem diversity remains high. The number of surviving species is inversely proportional to the variation in their growth rates but increases with the frequency and severity of phage-induced collapses. Thus counter-intuitively we predict that microbial communities exposed to more violent perturbations should have higher diversity.

  6. Population cycles and species diversity in dynamic Kill-the-Winner model of microbial ecosystems

    PubMed Central

    Maslov, Sergei; Sneppen, Kim

    2017-01-01

    Determinants of species diversity in microbial ecosystems remain poorly understood. Bacteriophages are believed to increase the diversity by the virtue of Kill-the-Winner infection bias preventing the fastest growing organism from taking over the community. Phage-bacterial ecosystems are traditionally described in terms of the static equilibrium state of Lotka-Volterra equations in which bacterial growth is exactly balanced by losses due to phage predation. Here we consider a more dynamic scenario in which phage infections give rise to abrupt and severe collapses of bacterial populations whenever they become sufficiently large. As a consequence, each bacterial population in our model follows cyclic dynamics of exponential growth interrupted by sudden declines. The total population of all species fluctuates around the carrying capacity of the environment, making these cycles cryptic. While a subset of the slowest growing species in our model is always driven towards extinction, in general the overall ecosystem diversity remains high. The number of surviving species is inversely proportional to the variation in their growth rates but increases with the frequency and severity of phage-induced collapses. Thus counter-intuitively we predict that microbial communities exposed to more violent perturbations should have higher diversity. PMID:28051127

  7. 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.

  8. Population dynamics of hispid cotton rats (Sigmodon hispidus) across a nitrogen-amended landscape

    USGS Publications Warehouse

    Clark, J.E.; Hellgren, E.C.; Jorgensen, E.E.; Tunnell, S.J.; Engle, David M.; Leslie, David M.

    2003-01-01

    We conducted a mark-recapture experiment to examine the population dynamics of hispid cotton rats (Sigmodon hispidus) in response to low-level nitrogen amendments (16.4 kg nitrogen/ha per year) and exclosure fencing in an old-field grassland. The experimental design consisted of sixteen 0.16-ha plots with 4 replicates of each treatment combination. We predicted that densities, reproductive success, movement probabilities, and survival rates of cotton rats would be greater on nitrogen-amended plots because of greater aboveground biomass and canopy cover. Population densities of cotton rats tended to be highest on fenced nitrogen plots, but densities on unfenced nitrogen plots were similar to those on control and fenced plots. We observed no distinct patterns in survival rates, reproductive success, or movement probabilities with regard to nitrogen treatments. However, survival rates and reproductive success tended to be higher for cotton rats on fenced plots than for those on unfenced plots and this was likely attributable to decreased predation on fenced plots. As low-level nitrogen amendments continue to be applied, we predict that survival, reproduction, and population-growth rates of cotton rats on control plots, especially fenced plots with no nitrogen amendment, will eventually exceed those on nitrogen-amended plots as a result of higher plant-species diversity, greater food availability, and better quality cover.

  9. Mean occupancy time: linking mechanistic movement models, population dynamics and landscape ecology to population persistence.

    PubMed

    Cobbold, Christina A; Lutscher, Frithjof

    2014-02-01

    Reaction-diffusion models for the dynamics of a biological population in a fragmented landscape can incorporate detailed descriptions of movement and behavior, but are difficult to analyze and hard to parameterize. Patch models, on the other hand, are fairly easy to analyze and can be parameterized reasonably well, but miss many details of the movement process within and between patches. We develop a framework to scale up from a reaction-diffusion process to a patch model and, in particular, to determine movement rates between patches based on behavioral rules for individuals. Our approach is based on the mean occupancy time, the mean time that an individuals spends in a certain area of the landscape before it exits that area or dies. We illustrate our approach using several different landscape configurations. We demonstrate that the resulting patch model most closely captures persistence conditions and steady state densities as compared with the reaction-diffusion model.

  10. 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

  11. 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

  12. 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.

  13. 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...

  14. Predicting the size of the progeny mapping population required to positionally clone a gene.

    PubMed

    Dinka, Stephen J; Campbell, Matthew A; Demers, Tyler; Raizada, Manish N

    2007-08-01

    A key frustration during positional gene cloning (map-based cloning) is that the size of the progeny mapping population is difficult to predict, because the meiotic recombination frequency varies along chromosomes. We describe a detailed methodology to improve this prediction using rice (Oryza sativa L.) as a model system. We derived and/or validated, then fine-tuned, equations that estimate the mapping population size by comparing these theoretical estimates to 41 successful positional cloning attempts. We then used each validated equation to test whether neighborhood meiotic recombination frequencies extracted from a reference RFLP map can help researchers predict the mapping population size. We developed a meiotic recombination frequency map (MRFM) for approximately 1400 marker intervals in rice and anchored each published allele onto an interval on this map. We show that neighborhood recombination frequencies (R-map, >280-kb segments) extracted from the MRFM, in conjunction with the validated formulas, better predicted the mapping population size than the genome-wide average recombination frequency (R-avg), with improved results whether the recombination frequency was calculated as genes/cM or kb/cM. Our results offer a detailed road map for better predicting mapping population size in diverse eukaryotes, but useful predictions will require robust recombination frequency maps based on sampling more progeny.

  15. 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