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Sample records for predicting population dynamics

  1. Predicting population dynamics with analytical, simulation and supercomputer models

    SciTech Connect

    Onstad, D.W.

    1987-07-01

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

  2. Population Dynamics

    PubMed Central

    Juliano, Steven A.

    2007-01-01

    This chapter reviews aspects of population dynamics that may be conceptually important for biological control of mosquitoes. Density dependent population regulation among immature stages has important implications for biological control of mosquito populations, primarily because it can lead to compensatory or overcompensatory mortality due to additions of a biological control agent. This can result in control efforts leading to no change in the target population, or actual increases in the target population, respectively. Density dependent effects, and compensatory or overcompensatory mortality, appear to be most common in mosquitoes from container or highly ephemeral habitats. In permanent ground water habitats generalist predators appear to limit mosquito populations and so render mortality additive. Thus, biological control in permanent ground water habitats seems to have the highest likelihood of producing a satisfactory result. A central premise of classical biological control is that pest populations are reduced by enemies to stable equilibrium levels that are both below the pre-control equilibrium level, and well below the level producing detrimental effects. This premise results in predictions that successful biological control is likely to involve specialist enemies (usually parasitoids), with short generation times relative to the victim, high rates of successful search, rapid rates of increase, and needing only a few victims to complete their life cycle. These predictions largely fail for mosquito systems, in which successful biological control seems to be associated with generalist enemies that can kill a large portion of the target population, often causing local extinction, and can persist in the absence of the target organism. Biological control of mosquitoes appears to be inherently unstable, thus contrasting sharply with classical biological control. This review suggests a need for better data on density dependent regulation of mosquito populations. PMID:17853611

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

    USGS Publications Warehouse

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

    2010-01-01

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

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

    USGS Publications Warehouse

    Nichols, J.M.; Moniz, L.; Nichols, J.D.; Pecora, L.M.; Cooch, E.

    2005-01-01

    A number of important questions in ecology involve the possibility of interactions or ?coupling? among potential components of ecological systems. The basic question of whether two components are coupled (exhibit dynamical interdependence) is relevant to investigations of movement of animals over space, population regulation, food webs and trophic interactions, and is also useful in the design of monitoring programs. For example, in spatially extended systems, coupling among populations in different locations implies the existence of redundant information in the system and the possibility of exploiting this redundancy in the development of spatial sampling designs. One approach to the identification of coupling involves study of the purported mechanisms linking system components. Another approach is based on time series of two potential components of the same system and, in previous ecological work, has relied on linear cross-correlation analysis. Here we present two different attractor-based approaches, continuity and mutual prediction, for determining the degree to which two population time series (e.g., at different spatial locations) are coupled. Both approaches are demonstrated on a one-dimensional predator?prey model system exhibiting complex dynamics. Of particular interest is the spatial asymmetry introduced into the model as linearly declining resource for the prey over the domain of the spatial coordinate. Results from these approaches are then compared to the more standard cross-correlation analysis. In contrast to cross-correlation, both continuity and mutual prediction are clearly able to discern the asymmetry in the flow of information through this system.

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

    PubMed Central

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

    2015-01-01

    A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed, populated and analysed, initially using data for 19 common European weeds, to begin to consolidate trait data in a single repository. The initial choice of traits was driven by the requirements of empirical models of weed population dynamics to identify correlations between traits and model parameters. These relationships were used to build a generic model, operating at the level of functional traits, to simulate the impact of increasing herbicide and fertiliser use on virtual weeds along gradients of seed weight and maximum height. The model generated ‘fitness contours’ (defined as population growth rates) within this trait space in different scenarios, onto which two sets of weed species, defined as common or declining in the UK, were mapped. The effect of increasing inputs on the weed flora was successfully simulated; 77% of common species were predicted to have stable or increasing populations under high fertiliser and herbicide use, in contrast with only 29% of the species that have declined. Future development of the WTDB will aim to increase the number of species covered, incorporate a wider range of traits and analyse intraspecific variability under contrasting management and environments. PMID:26190870

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

    PubMed

    Peterman, W E; Semlitsch, R D

    2014-10-01

    Many patterns observed in ecology, such as species richness, life history variation, habitat use, and distribution, have physiological underpinnings. For many ectothermic organisms, temperature relationships shape these patterns, but for terrestrial amphibians, water balance may supersede temperature as the most critical physiologically limiting factor. Many amphibian species have little resistance to water loss, which restricts them to moist microhabitats, and may significantly affect foraging, dispersal, and courtship. Using plaster models as surrogates for terrestrial plethodontid salamanders (Plethodon albagula), we measured water loss under ecologically relevant field conditions to estimate the duration of surface activity time across the landscape. Surface activity time was significantly affected by topography, solar exposure, canopy cover, maximum air temperature, and time since rain. Spatially, surface activity times were highest in ravine habitats and lowest on ridges. Surface activity time was a significant predictor of salamander abundance, as well as a predictor of successful recruitment; the probability of a juvenile salamander occupying an area with high surface activity time was two times greater than an area with limited predicted surface activity. Our results suggest that survival, recruitment, or both are demographic processes that are affected by water loss and the ability of salamanders to be surface-active. Results from our study extend our understanding of plethodontid salamander ecology, emphasize the limitations imposed by their unique physiology, and highlight the importance of water loss to spatial population dynamics. These findings are timely for understanding the effects that fluctuating temperature and moisture conditions predicted for future climates will have on plethodontid salamanders. PMID:25154754

  7. 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)

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

    PubMed

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

    2016-05-01

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

  9. Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models.

    PubMed

    Keith, David A; Akçakaya, H Resit; Thuiller, Wilfried; Midgley, Guy F; Pearson, Richard G; Phillips, Steven J; Regan, Helen M; AraĂșjo, Miguel B; Rebelo, Tony G

    2008-10-23

    Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change. PMID:18664424

  10. 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...

  11. 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 (?T) for predicting masts for forest and grassland plants in New Zealand. We extend this climate-based method in the framework of a model for consumer-resource dynamics to predict invasive house mouse (Mus musculus) outbreaks in forest ecosystems. Compared with previous mast models based on absolute temperature, the ?T method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ?T on the likelihood of an outbreak occurring. The improved climate-based method for predicting resource pulses and consumer responses provides a straightforward rule of thumb for determining, with one year's advance warning, whether management intervention might be required in invaded ecosystems. The approach could be applied to consumer-resource systems worldwide where climatic variables are used to model the size and duration of resource pulses, and may have particular relevance for ecosystems where global change scenarios predict increased variability in climatic events. PMID:25785866

  12. 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

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

    PubMed

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

    2015-08-01

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

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

    PubMed

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

    2013-11-01

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

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

    PubMed

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

    2013-04-01

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

  16. Predicting School Populations.

    ERIC Educational Resources Information Center

    Smith, P. J.; Groom, K. N.

    This system for predicting enrollment in the London Borough of Bromley was first developed for the Hertfordshire County Council and was modified to fit the unique situation in Bromley, including high mobility of the population and high proportion of children in private schools. The system divides the borough into 207 zones and produces forecasts…

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

    PubMed Central

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

    2013-01-01

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

  18. 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 communities. Second, kill rate is the primary statistic for many traditional models of predation. However, our work suggests that kill rate and PR are similarly important for understanding why predation is such a complex process. PMID:21569029

  19. 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 identify the parameters most influencing the maximal abundance of mosquitoes. These key parameters were almost similar between species, but not with the same contributions. The emergence of adult mosquitoes was identified as a key process in the population dynamics of all of the three species considered here. Parameters associated with adult emergence therefore need to be precisely known to achieve accurate predictions. Our model is a flexible and efficient tool that predicts mosquito abundance based on local environmental factors. It is useful to and already used by a mosquito surveillance manager in France. PMID:25623972

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

    PubMed

    Price, Peter W; Hunter, Mark D

    2015-06-01

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

  1. A spatiotemporal model for predicting grain aphid population dynamics and optimizing insecticide sprays at the scale of continental France.

    PubMed

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

    2014-04-01

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

  2. A critical body residue approach for predicting persistent bioaccumulative toxicant effects on reproduction and population dynamics of meiobenthic copepods.

    PubMed

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

    2012-05-01

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

  3. 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.

  4. Coupling between evolutionary and population dynamics in experimental microbial populations

    NASA Astrophysics Data System (ADS)

    Sanchez, Alvaro; Gore, Jeff

    2012-02-01

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

  5. 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.

  6. Overcompensatory population dynamic responses to environmental stochasticity.

    PubMed

    Bull, James C; Bonsall, Michael B

    2008-11-01

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

  7. Microbial population dynamics on leaves.

    PubMed

    Kinkel, L L

    1997-01-01

    Microbial population dynamics on leaves in time and space are a function of immigration, emigration, growth, and death. Insight into the relative significance of each population process to the generation of specific dynamics for individual microorganisms is necessary to understanding the ecology and life history strategy of the microorganism and to developing effective control strategies. Additionally, information on the significance of within-leaf versus extra-leaf processes to the generation of phyllosphere dynamics is important to determining the range of spatial scales over which a population should be studied. Unfortunately, such information is difficult to obtain due to the lack of effective methodologies for distinguishing these processes within phyllosphere populations. Future research efforts should focus on the quantification of immigration, emigration, growth, and death relative to the population dynamics of phyllosphere microorganisms. PMID:15012527

  8. 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...

  9. 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.

  10. Predicting protein dynamics from structural ensembles

    NASA Astrophysics Data System (ADS)

    Copperman, J.; Guenza, M. G.

    2015-12-01

    The biological properties of proteins are uniquely determined by their structure and dynamics. A protein in solution populates a structural ensemble of metastable configurations around the global fold. From overall rotation to local fluctuations, the dynamics of proteins can cover several orders of magnitude in time scales. We propose a simulation-free coarse-grained approach which utilizes knowledge of the important metastable folded states of the protein to predict the protein dynamics. This approach is based upon the Langevin Equation for Protein Dynamics (LE4PD), a Langevin formalism in the coordinates of the protein backbone. The linear modes of this Langevin formalism organize the fluctuations of the protein, so that more extended dynamical cooperativity relates to increasing energy barriers to mode diffusion. The accuracy of the LE4PD is verified by analyzing the predicted dynamics across a set of seven different proteins for which both relaxation data and NMR solution structures are available. Using experimental NMR conformers as the input structural ensembles, LE4PD predicts quantitatively accurate results, with correlation coefficient ? = 0.93 to NMR backbone relaxation measurements for the seven proteins. The NMR solution structure derived ensemble and predicted dynamical relaxation is compared with molecular dynamics simulation-derived structural ensembles and LE4PD predictions and is consistent in the time scale of the simulations. The use of the experimental NMR conformers frees the approach from computationally demanding simulations.

  11. Predicting protein dynamics from structural ensembles.

    PubMed

    Copperman, J; Guenza, M G

    2015-12-28

    The biological properties of proteins are uniquely determined by their structure and dynamics. A protein in solution populates a structural ensemble of metastable configurations around the global fold. From overall rotation to local fluctuations, the dynamics of proteins can cover several orders of magnitude in time scales. We propose a simulation-free coarse-grained approach which utilizes knowledge of the important metastable folded states of the protein to predict the protein dynamics. This approach is based upon the Langevin Equation for Protein Dynamics (LE4PD), a Langevin formalism in the coordinates of the protein backbone. The linear modes of this Langevin formalism organize the fluctuations of the protein, so that more extended dynamical cooperativity relates to increasing energy barriers to mode diffusion. The accuracy of the LE4PD is verified by analyzing the predicted dynamics across a set of seven different proteins for which both relaxation data and NMR solution structures are available. Using experimental NMR conformers as the input structural ensembles, LE4PD predicts quantitatively accurate results, with correlation coefficient ? = 0.93 to NMR backbone relaxation measurements for the seven proteins. The NMR solution structure derived ensemble and predicted dynamical relaxation is compared with molecular dynamics simulation-derived structural ensembles and LE4PD predictions and is consistent in the time scale of the simulations. The use of the experimental NMR conformers frees the approach from computationally demanding simulations. PMID:26723616

  12. 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 (Όmax) 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 Όmax of TVC of marinated samples was significantly lower compared to control samples regardless temperature, while under dynamic temperature conditions the model satisfactorily predicted the growth of TVC in both control and marinated samples. The shelf-life of marinated samples was significantly extended compared to the control (5 days extension at 4 °C). The calculated activation energies (Ea), 82 and 52 kJ/mol for control and marinated samples, respectively, indicated higher temperature dependence of the shelf life of control samples compared to marinated ones. The present results indicated that pomegranate juice could be used as an alternative ingredient in marinades to prolong the shelf life of chicken. PMID:26742613

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

    PubMed

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

    2013-09-01

    Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 Ś 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate. PMID:24772388

  14. 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.

  15. 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.

  16. 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.

  17. PREDICTING WILDLIFE POPULATION EFFECTS FROM MULTIPLE 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...

  18. 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.

  19. Evolutionary Dynamics and Diversity in Microbial Populations

    NASA Astrophysics Data System (ADS)

    Thompson, Joel; Fisher, Daniel

    2013-03-01

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

  20. The genetic basis of population fecundity prediction across multiple field populations of Nilaparvata lugens.

    PubMed

    Sun, Zhong Xiang; Zhai, Yi Fan; Zhang, Jian Qing; Kang, Kui; Cai, Jing Heng; Fu, Yonggui; Qiu, Jie Qi; Shen, Jia Wei; Zhang, Wen Qing

    2015-02-01

    Identifying the molecular markers for complex quantitative traits in natural populations promises to provide novel insight into genetic mechanisms of adaptation and to aid in forecasting population dynamics. In this study, we investigated single nucleotide polymorphisms (SNPs) using candidate gene approach from high- and low-fecundity populations of the brown planthopper (BPH) Nilaparvata lugens Stćl (Hemiptera: Delphacidae) divergently selected for fecundity. We also tested whether the population fecundity can be predicted by a few SNPs. Seven genes (ACE, fizzy, HMGCR, LpR, Sxl, Vg and VgR) were inspected for SNPs in N. lugens, which is a serious insect pest of rice. By direct sequencing of the complementary DNA and promoter sequences of these candidate genes, 1033 SNPs were discovered within high- and low-fecundity BPH populations. A panel of 121 candidate SNPs were selected and genotyped in 215 individuals from 2 laboratory populations (HFP and LFP) and 3 field populations (GZP, SGP and ZSP). Prior to association tests, population structure and linkage disequilibrium (LD) among the 3 field populations were analysed. The association results showed that 7 SNPs were significantly associated with population fecundity in BPH. These significant SNPs were used for constructing general liner models with stepwise regression. The best predictive model was composed of 2 SNPs (ACE-862 and VgR-816 ) with very good fitting degree. We found that 29% of the phenotypic variation in fecundity could be accounted for by only two markers. Using two laboratory populations and a complete independent field population, the predictive accuracy was 84.35-92.39%. The predictive model provides an efficient molecular method to predict BPH fecundity of field populations and provides novel insights for insect population management. PMID:25581109

  1. Modeling population dynamics: A quantile approach.

    PubMed

    Chavas, Jean-Paul

    2015-04-01

    The paper investigates the modeling of population dynamics, both conceptually and empirically. It presents a reduced form representation that provides a flexible characterization of population dynamics. It leads to the specification of a threshold quantile autoregression (TQAR) model, which captures nonlinear dynamics by allowing lag effects to vary across quantiles of the distribution as well as with previous population levels. The usefulness of the model is illustrated in an application to the dynamics of lynx population. We find statistical evidence that the quantile autoregression parameters vary across quantiles (thus rejecting the AR model as well as the TAR model) as well as with past populations (thus rejecting the quantile autoregression QAR model). The results document the nature of dynamics and cycle in the lynx population over time. They show how both the period of the cycle and the speed of population adjustment vary with population level and environmental conditions. PMID:25661501

  2. Predictive Bayesian inference and dynamic treatment regimes.

    PubMed

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

    2015-11-01

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

  3. 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

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

    PubMed

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

    2011-01-01

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

  5. A Quantitative Model of Honey Bee Colony Population Dynamics

    PubMed Central

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

    2011-01-01

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

  6. Co-infection alters population dynamics of infectious disease

    PubMed Central

    Susi, Hanna; BarrĂšs, Benoit; Vale, Pedro F.; Laine, Anna-Liisa

    2015-01-01

    Co-infections by multiple pathogen strains are common in the wild. Theory predicts co-infections to have major consequences for both within- and between-host disease dynamics, but data are currently scarce. Here, using common garden populations of Plantago lanceolata infected by two strains of the pathogen Podosphaera plantaginis, either singly or under co-infection, we find the highest disease prevalence in co-infected treatments both at the host genotype and population levels. A spore-trapping experiment demonstrates that co-infected hosts shed more transmission propagules than singly infected hosts, thereby explaining the observed change in epidemiological dynamics. Our experimental findings are confirmed in natural pathogen populations—more devastating epidemics were measured in populations with higher levels of co-infection. Jointly, our results confirm the predictions made by theoretical and experimental studies for the potential of co-infection to alter disease dynamics across a large host–pathogen metapopulation. PMID:25569306

  7. 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.

  8. Immigration-extinction dynamics of stochastic populations

    NASA Astrophysics Data System (ADS)

    Meerson, Baruch; Ovaskainen, Otso

    2013-07-01

    How high should be the rate of immigration into a stochastic population in order to significantly reduce the probability of observing the population become extinct? Is there any relation between the population size distributions with and without immigration? Under what conditions can one justify the simple patch occupancy models, which ignore the population distribution and its dynamics in a patch, and treat a patch simply as either occupied or empty? We answer these questions by exactly solving a simple stochastic model obtained by adding a steady immigration to a variant of the Verhulst model: a prototypical model of an isolated stochastic population.

  9. Complex population dynamics and complex causation: devils, details and demography

    PubMed Central

    Benton, Tim G; Plaistow, Stewart J; Coulson, Tim N

    2006-01-01

    Population dynamics result from the interplay of density-independent and density-dependent processes. Understanding this interplay is important, especially for being able to predict near-term population trajectories for management. In recent years, the study of model systems—experimental, observational and theoretical—has shed considerable light on the way that the both density-dependent and -independent aspects of the environment affect population dynamics via impacting on the organism's life history and therefore demography. These model-based approaches suggest that (i) individuals in different states differ in their demographic performance, (ii) these differences generate structure that can fluctuate independently of current total population size and so can influence the dynamics in important ways, (iii) individuals are strongly affected by both current and past environments, even when the past environments may be in previous generations and (iv) dynamics are typically complex and transient due to environmental noise perturbing complex population structures. For understanding population dynamics of any given system, we suggest that ‘the devil is in the detail’. Experimental dissection of empirical systems is providing important insights into the details of the drivers of demographic responses and therefore dynamics and should also stimulate theory that incorporates relevant biological mechanism. PMID:16720388

  10. 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.

  11. 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.

  12. Pathwise thermodynamic structure in population dynamics

    NASA Astrophysics Data System (ADS)

    Sughiyama, Yuki; Kobayashi, Tetsuya J.; Tsumura, Koji; Aihara, Kazuyuki

    2015-03-01

    We reveal thermodynamic structure in population dynamics with phenotype switching. Mean fitness for a population of organisms is determined by a thermodynamic variational principle described by the large deviation of phenotype-switching dynamics. Owing to this variational principle, a response relation of the mean fitness with respect to changes of environments and phenotype-switching dynamics is represented as a thermodynamic differential form. Furthermore, we discuss the strength of the selection by using the difference between time-forward and time-backward (retrospective) processes.

  13. How Resource Phenology Affects Consumer Population Dynamics.

    PubMed

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

    2016-02-01

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

  14. Effects of virus on plant fecundity and population dynamics.

    PubMed

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

    2014-06-01

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

  15. 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. PMID:25026455

  16. 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.

  17. Random Leslie matrices in population dynamics.

    PubMed

    CĂĄceres, Manuel O; CĂĄceres-Saez, Iris

    2011-09-01

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

  18. Ecological processes can synchronize marine population dynamics over continental scales

    PubMed Central

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

    2010-01-01

    Determining the relative importance of local and regional processes for the distribution of population abundance is a fundamental but contentious issue in ecology. In marine systems, classical theory holds that the influence of demographic processes and dispersal is confined to local populations whereas the environment controls regional patterns of abundance. Here, we use spatial synchrony to compare the distribution of population abundance of the dominant mussel Mytilus californianus observed along the West Coast of the United States to that predicted by dynamical models undergoing different dispersal and environmental treatments to infer the relative influence of local and regional processes. We reveal synchronized fluctuations in the abundance of mussel populations across a whole continent despite limited larval dispersal and strong environmental forcing. We show that dispersal among neighboring populations interacts with local demographic processes to generate characteristic patterns of spatial synchrony that can govern the dynamic distribution of mussel abundance over 1,800 km of coastline. Our study emphasizes the importance of dispersal and local dynamics for the distribution of abundance at the continental scale. It further highlights potential limits to the use of “climate envelope” models for predicting the response of large-scale ecosystems to global climate change. PMID:20404141

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

    PubMed

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

    2016-01-01

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

  20. 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

  1. 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

  2. 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.

  3. 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).

  4. Predictive information in a sensory population.

    PubMed

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

    2015-06-01

    Guiding behavior requires the brain to make predictions about the future values of sensory inputs. Here, we show that efficient predictive computation starts at the earliest stages of the visual system. We compute how much information groups of retinal ganglion cells carry about the future state of their visual inputs and show that nearly every cell in the retina participates in a group of cells for which this predictive information is close to the physical limit set by the statistical structure of the inputs themselves. Groups of cells in the retina carry information about the future state of their own activity, and we show that this information can be compressed further and encoded by downstream predictor neurons that exhibit feature selectivity that would support predictive computations. Efficient representation of predictive information is a candidate principle that can be applied at each stage of neural computation. PMID:26038544

  5. Predictive information in a sensory population

    PubMed Central

    Marre, Olivier; Berry, Michael J.; Bialek, William

    2015-01-01

    Guiding behavior requires the brain to make predictions about the future values of sensory inputs. Here, we show that efficient predictive computation starts at the earliest stages of the visual system. We compute how much information groups of retinal ganglion cells carry about the future state of their visual inputs and show that nearly every cell in the retina participates in a group of cells for which this predictive information is close to the physical limit set by the statistical structure of the inputs themselves. Groups of cells in the retina carry information about the future state of their own activity, and we show that this information can be compressed further and encoded by downstream predictor neurons that exhibit feature selectivity that would support predictive computations. Efficient representation of predictive information is a candidate principle that can be applied at each stage of neural computation. PMID:26038544

  6. Population-based mechanistic prediction of oral drug absorption.

    PubMed

    Jamei, Masoud; Turner, David; Yang, Jiansong; Neuhoff, Sibylle; Polak, Sebastian; Rostami-Hodjegan, Amin; Tucker, Geoffrey

    2009-06-01

    The bioavailability of drugs from oral formulations is influenced by many physiological factors including gastrointestinal fluid composition, pH and dynamics, transit and motility, and metabolism and transport, each of which may vary with age, gender, race, food, and disease. Therefore, oral bioavailability, particularly of poorly soluble and/or poorly permeable compounds and those that are extensively metabolized, often exhibits a high degree of inter- and intra-individual variability. While several models and algorithms have been developed to predict bioavailability in an average person, efforts to accommodate intrinsic variability in the component processes are less common. An approach that incorporates such variability for human populations within a mechanistic framework is described together with examples of its application to drug and formulation development. PMID:19381840

  7. 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.

  8. Predictability of threshold exceedances in dynamical systems

    NASA Astrophysics Data System (ADS)

    BĂłdai, TamĂĄs

    2015-12-01

    In a low-order model of the general circulation of the atmosphere we examine the predictability of threshold exceedance events of certain observables. The likelihood of such binary events-the cornerstone also for the categoric (as opposed to probabilistic) prediction of threshold exceedances-is established from long time series of one or more observables of the same system. The prediction skill is measured by a summary index of the ROC curve that relates the hit- and false alarm rates. Our results for the examined systems suggest that exceedances of higher thresholds are more predictable; or in other words: rare large magnitude, i.e., extreme, events are more predictable than frequent typical events. We find this to hold provided that the bin size for binning time series data is optimized, but not necessarily otherwise. This can be viewed as a confirmation of a counterintuitive (and seemingly contrafactual) statement that was previously formulated for more simple autoregressive stochastic processes. However, we argue that for dynamical systems in general it may be typical only, but not universally true. We argue that when there is a sufficient amount of data depending on the precision of observation, the skill of a class of data-driven categoric predictions of threshold exceedances approximates the skill of the analogous model-driven prediction, assuming strictly no model errors. Therefore, stronger extremes in terms of higher threshold levels are more predictable both in case of data- and model-driven prediction. Furthermore, we show that a quantity commonly regarded as a measure of predictability, the finite-time maximal Lyapunov exponent, does not correspond directly to the ROC-based measure of prediction skill when they are viewed as functions of the prediction lead time and the threshold level. This points to the fact that even if the Lyapunov exponent as an intrinsic property of the system, measuring the instability of trajectories, determines predictability, it does that in a nontrivial manner.

  9. 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.

  10. 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

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

    PubMed

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

    2015-11-01

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

  12. 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

  13. 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.

  14. Population growth dynamics of carbon nanotubes.

    PubMed

    Bedewy, Mostafa; Meshot, Eric R; Reinker, Michael J; Hart, A John

    2011-11-22

    Understanding the population growth behavior of filamentary nanostructures, such as carbon nanotubes (CNTs), is hampered by the lack of characterization techniques capable of probing statistical variations with high spatial resolution. We present a comprehensive methodology for studying the population growth dynamics of vertically aligned CNT forests, utilizing high-resolution spatial mapping of synchrotron X-ray scattering and attenuation, along with real-time height kinetics. We map the CNT alignment and dimensions within CNT forests, revealing broadening and focusing of size distributions during different stages of the process. Then, we calculate the number density and mass density of the CNT population versus time, which are true measures of the reaction kinetics. We find that the mass-based kinetics of a CNT population is accurately represented by the S-shaped Gompertz model of population growth, although the forest height and CNT length kinetics are essentially linear. Competition between catalyst activation and deactivation govern the rapid initial acceleration and slow decay of the CNT number density. The maximum CNT density (i.e., the overall catalyst activity) is limited by gas-phase reactions and catalyst-surface interactions, which collectively exhibit autocatalytic behavior. Thus, we propose a comprehensive picture of CNT population growth which combines both chemical and mechanical cooperation. Our findings are relevant to both bulk and substrate-based CNT synthesis methods and provide general insights into the self-assembly and collective growth of filamentary nanostructures. PMID:22023221

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

    NASA Astrophysics Data System (ADS)

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

    2010-09-01

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

  16. The dynamics of density dependent population models.

    PubMed

    Guckenheimer, J; Oster, G; Ipaktchi, A

    1977-05-23

    The dynamics of density-dependent population models can be extraordinarily complex as numerous authors have displayed in numerical simulations. Here we commence a theoretical analysis of the mathematical mechanisms underlying this complexity from the viewpoint of modern dynamical systems theory. After discussing the chaotic behavior of one-dimensional difference equations we proceed to illustrate the general theory on a density-dependent Leslie model with two age classes. The pattern of bofurcations away from the equilibrium point is investigated and the existence of a "strange attractor" is demonstrated--i.e. an attracting limit set which is neither an equilibrium nor a limit cycle. Near the strange attractor the system exhibits essentially random behavior. An approach to the statical analysis of the dynamics in the chaotic regime is suggested. We then generalize our conclusions to higher dimensions and continuous models (e.g. the nonlinear von Foerster equation). PMID:886232

  17. 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 populations initiated by a larger number of individuals, where the random effects become negligible. PMID:24928885

  18. 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 populations initiated by a larger number of individuals, where the random effects become negligible. PMID:24928885

  19. Dynamical quorum sensing: Population density encoded in cellular dynamics

    PubMed Central

    De Monte, Silvia; d'Ovidio, Francesco; Danű, Sune; Sűrensen, Preben Graae

    2007-01-01

    Mutual synchronization by exchange of chemicals is a mechanism for the emergence of collective dynamics in cellular populations. General theories exist on the transition to coherence, but no quantitative, experimental demonstration has been given. Here, we present a modeling and experimental analysis of cell-density-dependent glycolytic oscillations in yeast. We study the disappearance of oscillations at low cell density and show that this phenomenon occurs synchronously in all cells and not by desynchronization, as previously expected. This study identifies a general scenario for the emergence of collective cellular oscillations and suggests a quorum-sensing mechanism by which the cell density information is encoded in the intracellular dynamical state. PMID:18003917

  20. Interval prediction in structural dynamic analysis

    NASA Technical Reports Server (NTRS)

    Hasselman, Timothy K.; Chrostowski, Jon D.; Ross, Timothy J.

    1992-01-01

    Methods for assessing the predictive accuracy of structural dynamic models are examined with attention given to the effects of modal mass, stiffness, and damping uncertainties. The methods are based on a nondeterministic analysis called 'interval prediction' in which interval variables are used to describe parameters and responses that are unknown. Statistical databases for generic modeling uncertainties are derived from experimental data and incorporated analytically to evaluate responses. Covariance matrices of modal mass, stiffness, and damping parameters are propagated numerically in models of large space structures by means of three methods. The test data tend to fall within the predicted intervals of uncertainty determined by the statistical databases. The present findings demonstrate the suitability of using data from previously analyzed and tested space structures for assessing the predictive accuracy of an analytical model.

  1. 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…

  2. Application of optimal prediction to molecular dynamics

    SciTech Connect

    Barber IV, John Letherman

    2004-12-01

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

  3. Predictive Dynamics of Human Pain Perception

    PubMed Central

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

    2012-01-01

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

  4. 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.

  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. PMID:23565966

  6. Population Code Dynamics in Categorical Perception.

    PubMed

    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

  7. 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

  8. Migratory diversity predicts population declines in birds.

    PubMed

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

    2016-03-01

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

  9. Population dynamics in Er3+-doped fluoride glasses

    NASA Astrophysics Data System (ADS)

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

    2001-05-01

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

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

    PubMed Central

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

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

    PubMed

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

  12. 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.

  13. 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.

  14. Monitoring microbial population dynamics at low densities

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

  15. A population dynamics approach to biological aging

    NASA Astrophysics Data System (ADS)

    de Almeida, R. M. C.

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

  16. 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 repopulation rates observed in our study, localized depopulation may be effective at reducing negative ecological impacts of mesopredators in fragmented landscapes at limited spatial and temporal scales. PMID:23527065

  17. Effects of culling on mesopredator population dynamics.

    PubMed

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

    2013-01-01

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

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

    PubMed Central

    Fromont, E; Pontier, D; Langlais, M

    1998-01-01

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

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

    PubMed

    Fromont, E; Pontier, D; Langlais, M

    1998-06-22

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

  20. Prediction and Control in a Dynamic Environment

    PubMed Central

    Osman, Magda; Speekenbrink, Maarten

    2011-01-01

    The present study compared the accuracy of cue-outcome knowledge gained during prediction-based and control-based learning in stable and unstable dynamic environments. Participants either learnt to make cue-interventions in order to control an outcome, or learnt to predict the outcome from observing changes to the cue values. Study 1 (N = 60) revealed that in tests of control, after a short period of familiarization, performance of Predictors was equivalent to Controllers. Study 2 (N = 28) showed that Controllers showed equivalent task knowledge when to compared to Predictors. Though both Controllers and Predictors showed good performance at test, overall Controllers showed an advantage. The cue-outcome knowledge acquired during learning was sufficiently flexible to enable successful transfer to tests of control and prediction. PMID:22419913

  1. Dynamic matching algorithm for viral structure prediction.

    PubMed

    Li, Hengwu; Zhu, Daming; Zhang, Caiming; Liu, Zhengdong; Han, Huijian; Xu, Zhenzhong

    2014-07-01

    Most viruses have RNA genomes, their biological functions are expressed more by folded architecture than by sequence. Among the various RNA structures, pseudoknots are the most typical. In general, RNA secondary structures prediction doesn't contain pseudoknots because of its difficulty in modeling. Here we present an algorithm of dynamic matching to predict RNA secondary structures with pseudoknots by combining the merits of comparative and thermodynamic approaches. We have tested and verified our algorithm on some viral RNA. Comparisons show that our algorithm and loop matching method has similar accuracy and time complexity, and are more sensitive than the maximum weighted matching method and Rivas algorithm. Among the four methods, our algorithm has the best prediction specificity. The results show that our algorithm is more reliable and efficient than the other methods. PMID:25016258

  2. Scaling up population dynamics: integrating theory and data.

    PubMed

    Melbourne, Brett A; Chesson, Peter

    2005-09-01

    How to scale up from local-scale interactions to regional-scale dynamics is a critical issue in field ecology. We show how to implement a systematic approach to the problem of scaling up, using scale transition theory. Scale transition theory shows that dynamics on larger spatial scales differ from predictions based on the local dynamics alone because of an interaction between local-scale nonlinear dynamics and spatial variation in density or the environment. Based on this theory, a systematic approach to scaling up has four steps: (1) derive a model to translate the effects of local dynamics to the regional scale, and to identify key interactions between nonlinearity and spatial variation, (2) measure local-scale model parameters to determine nonlinearities at local scales, (3) measure spatial variation, and (4) combine nonlinearity and variation measures to obtain the scale transition. We illustrate the approach, with an example from benthic stream ecology of caddisflies living in riffles. By sampling from a simulated system, we show how collecting the appropriate data at local (riffle) scales to measure nonlinearities, combined with measures of spatial variation, leads to the correct inference for dynamics at the larger scale of the stream. The approach provides a way to investigate the mechanisms and consequences of changes in population dynamics with spatial scale using a relatively small amount of field data. PMID:15891847

  3. 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

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

    PubMed

    Boland, B

    1995-12-01

    The impact is examined of socioeconomic factors on Caribbean population dynamics. This work begins by describing the socioeconomic context of the late 1980s and early 1990s, under the influence of the economic changes and crises of the 1980s. The small size, openness, dependency, and lack of diversification of the Caribbean economies have made them vulnerable to external pressures. The Bahamas and Belize had economic growth rates exceeding 5% annually during 1981-90, but most of the countries had low or negative growth. Unemployment, poverty, the structural adjustment measures adopted in the mid-1980s, and declines in social spending exacerbated general economic conditions. In broad terms, the population situation of the Caribbean is marked by diversity of sizes and growth rates. A few countries oriented toward services and tourism had demographic growth rates exceeding 3%, while at least 7 had almost no growth or negative growth. Population growth rates reflected different combinations of natural increase and migration. Crude death rates ranged from around 5/1000 to 11/1000, except in Haiti, and all countries of the region except Haiti had life expectancies of 70 years or higher. Despite fertility decline, the average crude birth rate was still relatively high at 26/1000, and the rate of natural increase was 1.8% annually for the region. Nearly half of the regional population was under 15 or over 65 years old. The body of this work provides greater detail on mortality patterns, variations by sex, infant mortality, causes of death, and implications for policy. The discussion of fertility includes general patterns and trends, age specific fertility rates, contraceptive prevalence, levels of adolescent fertility and age factors in adolescent sexual behavior, characteristics of adolescent unions, contraceptive usage, health and social consequences of adolescent childbearing, and the search for solutions. The final section describes the magnitude and causes of emigration from the Caribbean and the impact of emigration on population composition, with attention to intraregional and return migration. PMID:12320811

  5. Prediction of HAMR Debris Population Distribution Released from GEO Space

    NASA Astrophysics Data System (ADS)

    Rosengren, A.; Scheeres, D.

    2012-09-01

    The high area-to-mass ratio (HAMR) debris population is thought to have origins in the GEO region. Many of these objects are uncharacterized with apparent area-to-mass ratios of up to 30 meters squared per kilogram. The orbits of HAMR objects are highly perturbed due to the combined effect of solar radiation pressure (SRP), anomalies of the Earth gravitational field, and third-body gravitational interactions induced by the Sun and the Moon. A sound understanding of their nature, orbital evolution, and possible origin is critical for space situational awareness. The study of the orbital evolution of HAMR objects, taking into account both short-period and long-period terms, requires numerical integration of the precise set of differential equations, and the investigation of a broad range of possible parameter values. However, such computations become very costly when continuously applied over a period of several decades, as is necessary in the case of HAMR debris. It therefore seems reasonable to investigate the equations that govern the long-term behavior of orbits; such equations can be derived by the method of averaging. We have validated a semi-analytical averaged theory of HAMR object orbit evolution against high precision numerical integrations, and are able to capture the extreme dynamical behaviors reported for these objects. This new averaged model, explicitly given in terms of the eccentricity and angular momentum vectors, is several hundred times faster to numerically integrate than the non-averaged Newtonian counterpart, and provides a very accurate description of the long-term behavior. Using this model, it is possible to make predictions of how a population of HAMR objects, released into GEO orbit, will evolve over time. Our earlier analyses revealed that the population would have a range of orbits much different than circular GEO. Their orbits will suffer a sub-yearly oscillation in the eccentricity and inclination evolutions, and a longer-term drift in inclination. When the nodal rate of the system is commensurate with the nodal rate of the Moon, the perturbations build up more effectively over long periods to produce significant effects on the orbit. Such resonances, which occurs for a class of HAMR objects that are not cleared out of orbit, gives rise to strongly changing dynamics over longer time periods. In this paper, we present the averaged model, and discuss its fundamental predictions and comparisons with explicit long-term numerical integrations of HAMR objects in GEO space. Using this tool, we study a range of HAMR objects, released in geostationary orbit, with various area-to-mass ratios, and predict the spatiotemporal distribution of the population. We identified a unique systematic structure associated with their distribution in inclination and ascending node phase space. Given that HAMR objects are the most difficult to target from an observational point of view, this work will have many implications for the space surveillance community, and will allow observers to implement better search strategies for this class of debris.

  6. Dynamic analysis of a parasite population model

    NASA Astrophysics Data System (ADS)

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

    2002-03-01

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

  7. 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

  8. 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 healthy despite heavy mortalities because of their inherently high reproductive potential. The ability to model the entire photographic capture history data set and incorporate reduced-parameter models led to estimates of mean annual population change that were sufficiently precise to be useful. This efficient, noninvasive sampling approach can be used to rigorously investigate the population dynamics of tigers and other elusive, rare, wide-ranging animal species in which individuals can be identified from photographs or other means.

  9. 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.

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

    PubMed

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

    2011-11-01

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

  11. Extreme events: dynamics, statistics and prediction

    NASA Astrophysics Data System (ADS)

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

    2011-05-01

    We review work on extreme events, their causes and consequences, by a group of European and American researchers involved in a three-year project on these topics. The review covers theoretical aspects of time series analysis and of extreme value theory, as well as of the deterministic modeling of extreme events, via continuous and discrete dynamic models. The applications include climatic, seismic and socio-economic events, along with their prediction. Two important results refer to (i) the complementarity of spectral analysis of a time series in terms of the continuous and the discrete part of its power spectrum; and (ii) the need for coupled modeling of natural and socio-economic systems. Both these results have implications for the study and prediction of natural hazards and their human impacts.

  12. 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.

  13. Predictive Coding of Dynamical Variables in Balanced Spiking Networks

    PubMed Central

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

    2013-01-01

    Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated. PMID:24244113

  14. 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

  15. A PARTIAL DIFFERENTIAL EQUATION MODEL OF FISH POPULATION DYNAMICS AND ITS APPLICATION IN IMPINGEMENT IMPACT ANALYSIS

    EPA Science Inventory

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

  16. 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...

  17. Dynamics of genome rearrangement in bacterial populations.

    PubMed

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

    2008-01-01

    Genome structure variation has profound impacts on phenotype in organisms ranging from microbes to humans, yet little is known about how natural selection acts on genome arrangement. Pathogenic bacteria such as Yersinia pestis, which causes bubonic and pneumonic plague, often exhibit a high degree of genomic rearrangement. The recent availability of several Yersinia genomes offers an unprecedented opportunity to study the evolution of genome structure and arrangement. We introduce a set of statistical methods to study patterns of rearrangement in circular chromosomes and apply them to the Yersinia. We constructed a multiple alignment of eight Yersinia genomes using Mauve software to identify 78 conserved segments that are internally free from genome rearrangement. Based on the alignment, we applied Bayesian statistical methods to infer the phylogenetic inversion history of Yersinia. The sampling of genome arrangement reconstructions contains seven parsimonious tree topologies, each having different histories of 79 inversions. Topologies with a greater number of inversions also exist, but were sampled less frequently. The inversion phylogenies agree with results suggested by SNP patterns. We then analyzed reconstructed inversion histories to identify patterns of rearrangement. We confirm an over-representation of "symmetric inversions"-inversions with endpoints that are equally distant from the origin of chromosomal replication. Ancestral genome arrangements demonstrate moderate preference for replichore balance in Yersinia. We found that all inversions are shorter than expected under a neutral model, whereas inversions acting within a single replichore are much shorter than expected. We also found evidence for a canonical configuration of the origin and terminus of replication. Finally, breakpoint reuse analysis reveals that inversions with endpoints proximal to the origin of DNA replication are nearly three times more frequent. Our findings represent the first characterization of genome arrangement evolution in a bacterial population evolving outside laboratory conditions. Insight into the process of genomic rearrangement may further the understanding of pathogen population dynamics and selection on the architecture of circular bacterial chromosomes. PMID:18650965

  18. 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 evaluation. PMID:21799936

  19. Predicting population-level risk effects of predation from the responses of individuals.

    PubMed

    MacLeod, Colin D; MacLeod, Ross; Learmonth, Jennifer A; Cresswell, Will; Pierce, Graham J

    2014-07-01

    Fear of predation produces large effects on prey population dynamics through indirect risk effects that can cause even greater impacts than direct predation mortality. As yet, there is no general theoretical framework for predicting when and how these population risk effects will arise in specific prey populations, meaning that there is often little consideration given to the key role predator risk effects can play in understanding conservation and wildlife management challenges. Here, we propose that population predator risk effects can be predicted through an extension of individual risk trade-off theory and show for the first time that this is the case in a wild vertebrate system. Specifically, we demonstrate that the timing (in specific months of the year), occurrence (at low food availability), cause (reduction in individual energy reserves), and type (starvation mortality) of a population-level predator risk effect can be successfully predicted from individual responses using a widely applicable theoretical framework (individual-based risk trade-off theory). Our results suggest that individual-based risk trade-off frameworks could allow a wide range of population-level predator risk effects to be predicted from existing ecological theory, which would enable risk effects to be more routinely integrated into consideration of population processes and in applied situations such as conservation. PMID:25163131

  20. 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.

  1. Population dynamics of Yellowstone grizzly bears

    USGS Publications Warehouse

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

    1985-01-01

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

  2. The population dynamics and conservation of primate populations.

    PubMed

    Dobson, A P; Lees, A M

    1989-12-01

    Primates are among the most threatened taxa, with more than half of all species in jeopardy. In this paper we develop population models to use the kind of data on wild primates that primatologists actually collect. Our survey of recentprimate journals suggests that the average field study uses 1.5 years of data from 50 animals The models are based on the simple Leslie-Lefkovitch matrix. They suggest a simple method that allows assessment from a few years'data, of whether a population is collapsing and requires intervention To a good approximation, populations will collapse when adult survival, per inter-birth interval, is less than 70 percent. Modifications of the basic model incorporate more realistic assumptions about social organization and densitydependent resource limitation. These allow us to identify population densities at which potential Allee effects operate, and permit more precise estimates of the minimum population sizes and compositions required for successful reintroductions to the wild The most important result is that populations of primates that live in small family groups may be more prone to "demographic" extinction than are more promiscuous species that live in more extended groups. PMID:21129023

  3. Effects of an invasive plant on population dynamics in toads.

    PubMed

    Greenberg, Daniel A; Green, David M

    2013-10-01

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

  4. DEMOGRAPHIC PROCESSES: POPULATION DYNAMICS IN HETEROGENEOUS LANDSCAPES

    EPA Science Inventory

    Few topics have attracted the attention of ecologists more than fluctuations in the numbers of plants and animals through time and their variation in abundance through space. nderstanding population fluctuations, and thus population conservation, requires understanding the links ...

  5. Neutron Star Population Dynamics. I. Millisecond Pulsars

    NASA Astrophysics Data System (ADS)

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

    1997-06-01

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

  6. Microbial population dynamics by digital in-line holographic microscopy

    PubMed Central

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

    2010-01-01

    Measurements of population dynamics are ubiquitous in experiments with microorganisms. Studies with microbes elucidating adaptation, selection, and competition rely on measurements of changing populations in time. Despite this importance, quantitative methods for measuring population dynamics microscopically, with high time resolution, across many replicates remain limited. Here we present a new noninvasive method to precisely measure microbial spatiotemporal population dynamics based on digital in-line holographic (DIH) microscopy. Our inexpensive, replicate DIH microscopes imaged hundreds of swimming algae in three dimensions within a volume of several microliters on a time scale of minutes over periods of weeks. PMID:20815617

  7. Evolutionary dynamics with fluctuating population sizes and strong mutualism

    NASA Astrophysics Data System (ADS)

    Chotibut, Thiparat; Nelson, David R.

    2015-08-01

    Game theory ideas provide a useful framework for studying evolutionary dynamics in a well-mixed environment. This approach, however, typically enforces a strictly fixed overall population size, deemphasizing natural growth processes. We study a competitive Lotka-Volterra model, with number fluctuations, that accounts for natural population growth and encompasses interaction scenarios typical of evolutionary games. We show that, in an appropriate limit, the model describes standard evolutionary games with both genetic drift and overall population size fluctuations. However, there are also regimes where a varying population size can strongly influence the evolutionary dynamics. We focus on the strong mutualism scenario and demonstrate that standard evolutionary game theory fails to describe our simulation results. We then analytically and numerically determine fixation probabilities as well as mean fixation times using matched asymptotic expansions, taking into account the population size degree of freedom. These results elucidate the interplay between population dynamics and evolutionary dynamics in well-mixed systems.

  8. Prediction Model for Gastric Cancer Incidence in Korean Population

    PubMed Central

    Kim, Sohee; Shin, Aesun; Yang, Hye-Ryung; Park, Junghyun; Choi, Il Ju; Kim, Young-Woo; Kim, Jeongseon; Nam, Byung-Ho

    2015-01-01

    Background Predicting high risk groups for gastric cancer and motivating these groups to receive regular checkups is required for the early detection of gastric cancer. The aim of this study is was to develop a prediction model for gastric cancer incidence based on a large population-based cohort in Korea. Method Based on the National Health Insurance Corporation data, we analyzed 10 major risk factors for gastric cancer. The Cox proportional hazards model was used to develop gender specific prediction models for gastric cancer development, and the performance of the developed model in terms of discrimination and calibration was also validated using an independent cohort. Discrimination ability was evaluated using Harrell’s C-statistics, and the calibration was evaluated using a calibration plot and slope. Results During a median of 11.4 years of follow-up, 19,465 (1.4%) and 5,579 (0.7%) newly developed gastric cancer cases were observed among 1,372,424 men and 804,077 women, respectively. The prediction models included age, BMI, family history, meal regularity, salt preference, alcohol consumption, smoking and physical activity for men, and age, BMI, family history, salt preference, alcohol consumption, and smoking for women. This prediction model showed good accuracy and predictability in both the developing and validation cohorts (C-statistics: 0.764 for men, 0.706 for women). Conclusions In this study, a prediction model for gastric cancer incidence was developed that displayed a good performance. PMID:26186332

  9. Leisure Today: Population Dynamics--The Changing Face of America.

    ERIC Educational Resources Information Center

    Dunn, Diana R., Ed.; And Others

    1981-01-01

    A collection of articles examines the changing character of the American population and the importance of planning new recreation and leisure services to meet changing population needs. Included are discussions on demography and population dynamics; the effects of immigration; changing work and life styles; and changes in family structure and…

  10. Population dynamics and the colour of environmental noise.

    PubMed

    Kaitala, V; Ylikarjula, J; Ranta, E; Lundberg, P

    1997-07-22

    The effect of red, white and blue environmental noise on discrete-time population dynamics is analyzed. The coloured noise is superimposed on Moran-Ricker and Maynard Smith dynamics, the resulting power spectra are less than examined. Time series dominated by short- and long-term fluctuations are said to be blue and red, respectively. In the stable range of the Moran-Ricker dynamics, environmental noise of any colour will make population dynamics red or blue depending the intrinsic growth rate. Thus, telling apart the colour of the noise from the colour of the population dynamics may not be possible. Population dynamics subjected to red and blue environmental noises show, respectively, more red or blue power spectra than those subjected to white noise. The sensitivity to differences in the noise colours decreases with increasing complexity and ultimately disappears in the chaotic range of the population dynamics. These findings are duplicated with the Maynard Smith model for high growth rates when the strength of density dependence changes. However, for low growth rates the power spectra of the population dynamics with noise are red in stable, periodic and aperiodic ranges irrespective of the noise colour. Since chaotic population fluctuations may show blue spectra in the deterministic case, this implies that blue deterministic chaos may become red under any colour of the noise. PMID:9304115

  11. 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.

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

    ERIC Educational Resources Information Center

    Pingle, Mark

    2003-01-01

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


  13. 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

  14. Mapping Genes that Predict Treatment Outcome in Admixed Populations

    PubMed Central

    Baye, Tesfaye M.; Wilke, Russell A.

    2010-01-01

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

  15. Circuit theory predicts gene flow in plant and animal populations.

    PubMed

    McRae, Brad H; Beier, Paul

    2007-12-11

    Maintaining connectivity for broad-scale ecological processes like dispersal and gene flow is essential for conserving endangered species in fragmented landscapes. However, determining which habitats should be set aside to promote connectivity has been difficult because existing models cannot incorporate effects of multiple pathways linking populations. Here, we test an ecological connectivity model that overcomes this obstacle by borrowing from electrical circuit theory. The model vastly improves gene flow predictions because it simultaneously integrates all possible pathways connecting populations. When applied to data from threatened mammal and tree species, the model consistently outperformed conventional gene flow models, revealing that barriers were less important in structuring populations than previously thought. Circuit theory now provides the best-justified method to bridge landscape and genetic data, and holds much promise in ecology, evolution, and conservation planning. PMID:18056641

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

    SciTech Connect

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

    2013-02-20

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

  17. The Population of Helium-merger Progenitors: Observational Predictions

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

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

  18. A simplified model of spatiotemporal population dynamics.

    PubMed

    Puu, T

    1985-09-01

    This paper is an extension of the model of population growth and migration originally developed by H. Hotelling in 1921. This model consists of two ingredients, a logistic growth function and a linear spatial diffusion term. The author notes that the saturation population can be affected by the development of new technology and that improvements in transportation have increased the possibilities for migration. "Basic nonlinearities are introduced by use of a production technology with increasing-decreasing returns to scale. It is demonstrated how industrial takeoffs, population transitions, and agglomerative spatial patterns can emerge by changing the model parameters." PMID:12267309

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

    PubMed

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

    2004-11-01

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

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

    USGS Publications Warehouse

    Ahumada, Jorge A.; LaPointe, D.; 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.

  1. From Neural Responses to Population Behavior: Neural Focus Group Predicts Population-Level Media Effects

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2012-05-01

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

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

    PubMed

    Nurmi, Tuomas; Parvinen, Kalle

    2013-03-21

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

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

    PubMed Central

    Hart, Edmund M.; Avilés, Leticia

    2014-01-01

    Reconstructing the dynamics of populations is complicated by the different types of stochasticity experienced by populations, in particular if some forms of stochasticity introduce bias in parameter estimation in addition to error. Identification of systematic biases is critical when determining whether the intrinsic dynamics of populations are stable or unstable and whether or not populations exhibit an Allee effect, i.e., a minimum size below which deterministic extinction should follow. Using a simulation model that allows for Allee effects and a range of intrinsic dynamics, we investigated how three types of stochasticity—demographic, environmental, and random catastrophes— affect our ability to reconstruct the intrinsic dynamics of populations. Demographic stochasticity aside, which is only problematic in small populations, we find that environmental stochasticity—positive and negative environmental fluctuations—caused increased error in parameter estimation, but bias was rarely problematic, except at the highest levels of noise. Random catastrophes, events causing large-scale mortality and likely to be more common than usually recognized, caused immediate bias in parameter estimates, in particular when Allee effects were large. In the latter case, population stability was predicted when endogenous dynamics were actually unstable and the minimum viable population size was overestimated in populations with small or non-existent Allee effects. Catastrophes also generally increased extinction risk, in particular when endogenous Allee effects were large. We propose a method for identifying data points likely resulting from catastrophic events when such events have not been recorded. Using social spider colonies (Anelosimus spp.) as models for populations, we show that after known or suspected catastrophes are accounted for, reconstructed growth parameters are consistent with intrinsic dynamical instability and substantial Allee effects. Our results are applicable to metapopulation or time series data and are relevant for predicting extinction in conservation applications or the management of invasive species. PMID:25360620

  5. Habitat type predicts genetic population differentiation in freshwater invertebrates.

    PubMed

    Marten, Andreas; Brändle, Martin; Brandl, Roland

    2006-08-01

    A basic challenge in evolutionary biology is to establish links between ecology and evolution of species. One important link is the habitat template. It has been hypothesized, that the spatial and temporal settings of a habitat strongly influence the evolution of species dispersal propensity. Here, we evaluate the importance of the habitat type on genetic population differentiation of species using freshwater habitats as a model system. Freshwater habitats are either lentic (standing) or lotic (running). On average, lotic habitats are more stable and predictable over space and time than lentic habitats. Therefore, lentic habitats should favour the evolution of higher dispersal propensity which ensures population survival of lentic species. To test for such a relationship, we used extensive data on species' genetic population differentiation of lentic and lotic freshwater invertebrates retrieved from published allozyme studies. Overall, we analysed more than 150 species from all over the world. Controlling for several experimental, biological and geographical confounding effects, we always found that lentic invertebrates exhibit, on average, lower genetic population differentiation than lotic species. This pattern was consistent across insects, crustaceans and molluscs. Our results imply fundamental differences in genetic population differentiation among species adapted to either lentic or lotic habitats. We propose that such differences should occur in a number of other habitat types that differ in spatio-temporal stability. Furthermore, our results highlight the important role of lotic habitats as reservoirs for evolutionary processes and the potential for rapid speciation. PMID:16842433

  6. Modelling Food and Population Dynamics in Honey Bee Colonies

    PubMed Central

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

    2013-01-01

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

  7. Galactic civilizations: Population dynamics and interstellar diffusion

    NASA Technical Reports Server (NTRS)

    Newman, W. I.; Sagan, C.

    1978-01-01

    The interstellar diffusion of galactic civilizations is reexamined by potential theory; both numerical and analytical solutions are derived for the nonlinear partial differential equations which specify a range of relevant models, drawn from blast wave physics, soil science, and, especially, population biology. An essential feature of these models is that, for all civilizations, population growth must be limited by the carrying capacity of the environment. Dispersal is fundamentally a diffusion process; a density-dependent diffusivity describes interstellar emigration. Two models are considered: the first describing zero population growth (ZPG), and the second which also includes local growth and saturation of a planetary population, and for which an asymptotic traveling wave solution is found.

  8. Stochastic dynamics and logistic population growth

    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.

  9. Applications of KAM theory to population dynamics.

    PubMed

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

    2011-01-01

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

  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. Dynamic population mapping using mobile phone data.

    PubMed

    Deville, Pierre; Linard, Catherine; Martin, Samuel; Gilbert, Marius; Stevens, Forrest R; Gaughan, Andrea E; Blondel, Vincent D; Tatem, Andrew J

    2014-11-11

    During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography. PMID:25349388

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

    USGS Publications Warehouse

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

    2005-01-01

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

  13. 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 4.8Ś and 2Ś greater in southern relative to northern populations. Moreover, southern populations produced 13Ś more aboveground biomass and 1.4Ś 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

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

    PubMed

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

    2015-08-01

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

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

    EPA Science Inventory

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

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

    PubMed Central

    Tallavaara, Miikka; Luoto, Miska; Korhonen, Natalia; JÀrvinen, Heikki; SeppÀ, 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

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

    PubMed

    Tallavaara, Miikka; Luoto, Miska; Korhonen, Natalia; JÀrvinen, Heikki; SeppÀ, Heikki

    2015-07-01

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

  18. The 5:1 Neptune Resonance: Dynamics and Population

    NASA Astrophysics Data System (ADS)

    Pike, Rosemary E.; Kavelaars, J. J.; Gladman, Brett; Petit, Jean-Marc; Alexandersen, Mike

    2014-11-01

    Based on 4 objects detected with semi-major axes near the 5:1 external resonance with Neptune, we estimate a substantial and previously unrecognized population of objects, perhaps more significant than the 3:2 (Plutino) resonance population. These external resonances are largely unexplored in both observations and dynamical simulations. However, understanding the characteristics and trapping history for objects in these populations is critical for constraining the dynamical history of the solar system. The 4 objects detected in the Canada-France Ecliptic Plane Survey (CFEPS) were classified using dynamical integrations. Three are resonant, and the last appears to be a resonant drop-off. The 3 objects are taken to be representative of the steady-state population, so by using these detections and the CFEPS characterization (pointings and detection limits) we calculate a population estimate for this resonance at ~3000(+5000 -2000) with Hg<8. This is at least as large as the Plutinos (3:2 resonance) at 90% confidence. The small number of detected objects results in such a large population estimate due to the numerous biases against detecting objects with semimajor axes at 88AU. Based on the dynamical behavior of the known objects, the trapping mechanism for the 5:1 resonance appears to be resonance sticking from the scattering objects. The long resonance lifetimes of some dynamical clones suggests that a steady state population could be maintained through periodic sticking.

  19. Prediction of X-33 Engine Dynamic Environments

    NASA Technical Reports Server (NTRS)

    Shi, John J.

    1999-01-01

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

  20. 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.

  1. [The dynamics of heath indicators of population of industrial town].

    PubMed

    Kalinkin, D E; Karpov, A B; Takhauov, R M; Samo?lova, Iu A

    2013-01-01

    The article presents the results of analysis of dynamics of health indicators of population of industrial town (medical demographic indicators, disability, morbidity of social hygienically important diseases) during 1970-2010. The classified administrative territorial municipality of Seversk constructed near the Siberian chemical industrial center, the internationally first-rate complex of nuclear industry enterprises was used as a research base. It is demonstrated that dynamics of health indicators of studied population had such negative tendencies as rapid population ageing, population loss due to decrease of natality and increase of mortality (population of able-bodied age included), prevalence of cardio-vascular diseases, malignant neoplasms and external causes, chronization of diseases. The established tendencies are to be considered in management decision making targeted to support and promote population health in industrial towns. PMID:24175380

  2. 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.

  3. 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...

  4. Population dynamics of HIV-1 inferred from gene sequences.

    PubMed Central

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

    1999-01-01

    A method for the estimation of population dynamic history from sequence data is described and used to investigate the past population dynamics of HIV-1 subtypes A and B. Using both gag and env gene alignments the effective population size of each subtype is estimated and found to be surprisingly small. This may be a result of the selective sweep of mutations through the population, or may indicate an important role of genetic drift in the fixation of mutations. The implications of these results for the spread of drug-resistant mutations and transmission dynamics, and also the roles of selection and recombination in shaping HIV-1 genetic diversity, are discussed. A larger estimated effective population size for subtype A may be the result of differences in time of origin, transmission dynamics, and/or population structure. To investigate the importance of population structure a model of population subdivision was fitted to each subtype, although the improvement in likelihood was found to be nonsignificant. PMID:9927440

  5. Dynamics and Predictability of Hurricane Dolly (2008)

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  6. STAMP: Sequence tag-based analysis of microbial population dynamics

    PubMed Central

    Abel, Sören; zur Wiesch, Pia Abel; Chang, Hsiao-Han; Davis, Brigid M.; Lipsitch, Marc; Waldor, Matthew K.

    2014-01-01

    We describe a new method (STAMP) for characterization of pathogen population dynamics during infection. STAMP analyzes the frequency changes of genetically “barcoded” organisms to quantify population bottlenecks and infer the founding population size. Analyses of intra-intestinal Vibrio cholerae revealed infection-stage and region-specific host barriers to infection, and unexpectedly showed V. cholerae migration counter to intestinal flow. STAMP provides a robust, widely applicable analytical framework for high confidence characterization of in vivo microbial dissemination. PMID:25599549

  7. A behaviorally explicit demographic model integrating habitat selection and population dynamics in california sea lions.

    PubMed

    González-Suárez, Manuela; Gerber, Leah R

    2008-12-01

    Although there has been a call for the integration of behavioral ecology and conservation biology, there are few tools currently available to achieve this integration. Explicitly including information about behavioral strategies in population viability analyses may enhance the ability of conservation biologists to understand and estimate patterns of extinction risk. Nevertheless, most behavioral-based PVA approaches require detailed individual-based data that are rarely available for imperiled species. We present a mechanistic approach that incorporates spatial and demographic consequences of behavioral strategies into population models used for conservation. We developed a stage-structured matrix model that includes the costs and benefits of movement associated with 2 habitat-selection strategies (philopatry and direct assessment). Using a life table for California sea lions (Zalophus californianus), we explored the sensitivity of model predictions to the inclusion of these behavioral parameters. Including behavioral information dramatically changed predicted population sizes, model dynamics, and the expected distribution of individuals among sites. Estimated population sizes projected in 100 years diverged up to 1 order of magnitude among scenarios that assumed different movement behavior. Scenarios also exhibited different model dynamics that ranged from stable equilibria to cycles or extinction. These results suggest that inclusion of behavioral data in viability models may improve estimates of extinction risk for imperiled species. Our approach provides a simple method for incorporating spatial and demographic consequences of behavioral strategies into population models and may be easily extended to other species and behaviors to understand the mechanisms of population dynamics for imperiled populations. PMID:18680502

  8. 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.

  9. Population dynamics and regulation in the cave salamander Speleomantes strinatii.

    PubMed

    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. PMID:17216185

  10. Simple mathematical models do not accurately predict early SIV dynamics.

    PubMed

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

    2015-03-01

    Upon infection of a new host, human immunodeficiency virus (HIV) replicates in the mucosal tissues and is generally undetectable in circulation for 1-2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the "standard" mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV). First, we found that the mode of virus production by infected cells (budding vs. bursting) has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral dose. These results suggest that, in order to appropriately model early HIV/SIV dynamics, additional factors must be considered in the model development. These may include variability in monkey susceptibility to infection, within-host competition between different viruses for target cells at the initial site of virus replication in the mucosa, innate immune response, and possibly the inclusion of several different tissue compartments. The sobering news is that while an increase in model complexity is needed to explain the available experimental data, testing and rejection of more complex models may require more quantitative data than is currently available. PMID:25781919

  11. 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 suggest that, in order to appropriately model early HIV/SIV dynamics, additional factors must be considered in the model development. These may include variability in monkey susceptibility to infection, within-host competition between different viruses for target cells at the initial site of virus replication in the mucosa, innate immune response, and possibly the inclusion of several different tissue compartments. The sobering news is that while an increase in model complexity is needed to explain the available experimental data, testing and rejection of more complex models may require more quantitative data than is currently available. PMID:25781919

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

    PubMed

    AraĂșjo, Rita M; SerrĂŁo, 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 shows the importance of vegetative compared to reproductive stages for the long-term persistence of populations. PMID:24651480

  13. Population dynamics and competitive outcome derive from resource allocation statistics: The governing influence of the distinguishability of individuals.

    PubMed

    Zhang, Yu J; Harte, John

    2015-11-01

    Model predictions for species competition outcomes highly depend on the assumed form of the population growth function. In this paper we apply an alternative inferential method based on statistical mechanics, maximizing Boltzmann entropy, to predict resource-constrained population dynamics and coexistence. Within this framework, population dynamics and competition outcome can be determined without assuming any particular form of the population growth function. The dynamics of each species is determined by two parameters: the mean resource requirement ? (related to the mean metabolic rate) and individual distinguishability Dr (related to intra- compared to interspecific functional variation). Our theory clarifies the condition for the energetic equivalence rule (EER) to hold, and provide a statistical explanation for the importance of species functional variation in determining population dynamics and coexistence patterns. PMID:26226230

  14. Bounds on the dynamics of sink populations with noisy immigration.

    PubMed

    Eager, Eric Alan; Guiver, Chris; Hodgson, Dave; Rebarber, Richard; Stott, Iain; Townley, Stuart

    2014-03-01

    Sink populations are doomed to decline to extinction in the absence of immigration. The dynamics of sink populations are not easily modelled using the standard framework of per capita rates of immigration, because numbers of immigrants are determined by extrinsic sources (for example, source populations, or population managers). Here we appeal to a systems and control framework to place upper and lower bounds on both the transient and future dynamics of sink populations that are subject to noisy immigration. Immigration has a number of interpretations and can fit a wide variety of models found in the literature. We apply the results to case studies derived from published models for Chinook salmon (Oncorhynchus tshawytscha) and blowout penstemon (Penstemon haydenii). PMID:24373938

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

    PubMed

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

    2015-09-01

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

  16. 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.

  17. Predictability in a highly stochastic system: final size of measles epidemics in small populations

    PubMed Central

    Caudron, Q.; Mahmud, A. S.; Metcalf, C. J. E.; GottfreĂ°sson, M.; Viboud, C.; Cliff, A. D.; Grenfell, B. T.

    2015-01-01

    A standard assumption in the modelling of epidemic dynamics is that the population of interest is well mixed, and that no clusters of metapopulations exist. The well-known and oft-used SIR model, arguably the most important compartmental model in theoretical epidemiology, assumes that the disease being modelled is strongly immunizing, directly transmitted and has a well-defined period of infection, in addition to these population mixing assumptions. Childhood infections, such as measles, are prime examples of diseases that fit the SIR-like mechanism. These infections have been well studied for many systems with large, well-mixed populations with endemic infection. Here, we consider a setting where populations are small and isolated. The dynamics of infection are driven by stochastic extinction–recolonization events, producing large, sudden and short-lived epidemics before rapidly dying out from a lack of susceptible hosts. Using a TSIR model, we fit prevaccination measles incidence and demographic data in Bornholm, the Faroe Islands and four districts of Iceland, between 1901 and 1965. The datasets for each of these countries suffer from different levels of data heterogeneity and sparsity. We explore the potential for prediction of this model: given historical incidence data and up-to-date demographic information, and knowing that a new epidemic has just begun, can we predict how large it will be? We show that, despite a lack of significant seasonality in the incidence of measles cases, and potentially severe heterogeneity at the population level, we are able to estimate the size of upcoming epidemics, conditioned on the first time step, to within reasonable confidence. Our results have potential implications for possible control measures for the early stages of new epidemics in small populations. PMID:25411411

  18. Predictability in a highly stochastic system: final size of measles epidemics in small populations.

    PubMed

    Caudron, Q; Mahmud, A S; Metcalf, C J E; GottfreĂ°sson, M; Viboud, C; Cliff, A D; Grenfell, B T

    2015-01-01

    A standard assumption in the modelling of epidemic dynamics is that the population of interest is well mixed, and that no clusters of metapopulations exist. The well-known and oft-used SIR model, arguably the most important compartmental model in theoretical epidemiology, assumes that the disease being modelled is strongly immunizing, directly transmitted and has a well-defined period of infection, in addition to these population mixing assumptions. Childhood infections, such as measles, are prime examples of diseases that fit the SIR-like mechanism. These infections have been well studied for many systems with large, well-mixed populations with endemic infection. Here, we consider a setting where populations are small and isolated. The dynamics of infection are driven by stochastic extinction-recolonization events, producing large, sudden and short-lived epidemics before rapidly dying out from a lack of susceptible hosts. Using a TSIR model, we fit prevaccination measles incidence and demographic data in Bornholm, the Faroe Islands and four districts of Iceland, between 1901 and 1965. The datasets for each of these countries suffer from different levels of data heterogeneity and sparsity. We explore the potential for prediction of this model: given historical incidence data and up-to-date demographic information, and knowing that a new epidemic has just begun, can we predict how large it will be? We show that, despite a lack of significant seasonality in the incidence of measles cases, and potentially severe heterogeneity at the population level, we are able to estimate the size of upcoming epidemics, conditioned on the first time step, to within reasonable confidence. Our results have potential implications for possible control measures for the early stages of new epidemics in small populations. PMID:25411411

  19. Strongly Deterministic Population Dynamics in Closed Microbial Communities

    NASA Astrophysics Data System (ADS)

    Frentz, Zak; Kuehn, Seppe; Leibler, Stanislas

    2015-10-01

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

  20. 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.

  1. 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.

  2. 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.

  3. 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,…

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

    USGS Publications Warehouse

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

    2007-01-01

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

  5. Cryptic Population Dynamics: Rapid Evolution Masks Trophic Interactions

    PubMed Central

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

    2007-01-01

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

  6. 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 ...

  7. Evaluation of predictive accuracy in structural dynamic models

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

    The evaluation of the predictive accuracy of dynamic models for future large space structures is addressed. Mass and stiffness uncertainties derived from a comparison of analytical and experimental modes are used to evaluate the uncertainty of response predictions based on the analytical model.

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

    ERIC Educational Resources Information Center

    Strauss, Jon C.

    1997-01-01

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

  9. Population-based prediction equations for neurobehavioral tests.

    PubMed

    Kilburn, K H; Thornton, J C; Hanscom, B

    1998-01-01

    Quantitative assessment of neurobehavioral function appraises brain injury from inhaled chemicals. Contemporary predicted values for tests useful in epidemiological studies have been developed with step-wise linear regression. In instances in which age and education do not match those of control groups, these equations assist in the interpretation of results of examinations of individual subjects and pilot studies. In this study, investigators considered brain function tests to be analogous in concept to pulmonary function tests. The authors used the tests to assess 293 adults in three unexposed groups from different areas of the United States. The subjects, who were contacted at random from voter registration rolls, were compensated for their time. The tests included balance, reaction time, strength, hearing, visual performance and cognitive recall, and perceptual motor and memory functions. Regression equations modeled the performance of each test and the influences of demographic factors. The investigators retained all influential factors in the equations. Age was a significant predictor for most tests. Education attainment was not a factor in any of the physiological measures, but it was a determinant in many psychological tests. Prediction equations assist investigators in the quantitative testing of chemically exposed individuals and other brain-injured individuals. The investigators verified the equations against other groups, including additional unexposed populations. PMID:9709989

  10. 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 abundance and particularly its peak timing and magnitude.

  11. 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 synchrony in this system is driven by at least three processes: small-scale, local forcing caused by soil disturbance, intermediate-scale forcing as a result of seed input, and large-scale climatic forcing (e.g. winter rainfall) that affects the motorway as a whole. PMID:15347513

  12. Characterizing mixed microbial population dynamics using time-series analysis.

    PubMed

    Trosvik, Pćl; Rudi, Knut; Naes, Tormod; Kohler, Achim; Chan, Kung-Sik; Jakobsen, Kjetill S; Stenseth, Nils C

    2008-07-01

    Due to a general shortage of temporal population data, dynamic structures in microbial communities remain largely unexplored. Knowledge of community dynamics is, however, essential for understanding the mechanisms by which microbes interact. Here, we have used a computational approach for quantification of bacteria in multispecies populations, generating data for time-series modeling. Moreover, we have used online FR-IR spectroscopy to monitor the main metabolic processes. The approach enabled us to provide a functional description of the parameters governing the population dynamics in a three-species model bacterial community, demonstrating density-dependent regulation, interspecies competition and even a case of cooperation between two species. Since the field of microbial ecology has yet to embrace many of the concepts and methods developed for the study of ecology of higher plants and animals, the realization that microbial systems can be analyzed within the same conceptual framework as other ecosystems is of fundamental importance. PMID:18385770

  13. 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.

  14. 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."

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

    PubMed

    Bonvanie, Irma J; van Gils, Anne; Janssens, Karin A M; Rosmalen, Judith G M

    2015-08-01

    The main aim of this study was to investigate the effect of childhood sexual abuse on medically not well explained or functional somatic symptoms (FSSs) in adolescents. We hypothesized that sexual abuse predicts higher levels of FSSs and that anxiety and depression contribute to this relationship. In addition, we hypothesized that more severe abuse is associated with higher levels of FSSs and that sexual abuse is related to gastrointestinal FSSs in particular. This study was part of the Tracking Adolescents' Individual Lives Survey (TRAILS): a general population cohort which started in 2001 (N=2,230; 50.8% girls, mean age 11.1 years). The current study uses data of 1,680 participants over four assessment waves (75% of baseline, mean duration of follow-up: 8 years). FSSs were measured by the Somatic Complaints subscale of the Youth Self-Report at all waves. Sexual abuse before the age of sixteen was assessed retrospectively with a questionnaire at T4. To test the hypotheses linear mixed models were used adjusted for age, sex, socioeconomic status, anxiety and depression. Sexual abuse predicted higher levels of FSSs after adjustment for age sex and socioeconomic status (B=.06) and after additional adjustment for anxiety and depression (B=.03). While sexual abuse involving physical contact significantly predicted the level of FSSs (assault; B=.08, rape; B=.05), non-contact sexual abuse was not significantly associated with FSSs (B=.04). Sexual abuse was not a stronger predictor of gastrointestinal FSSs (B=.06) than of all FSSs. Further research is needed to clarify possible mechanisms underlying relationship between sexual abuse and FSSs. PMID:26142915

  16. 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 [Senina, I., Sibert, J., Lehodey, P., 2008. Parameter estimation for basin-scale ecosystem-linked population models of large pelagic predators: application to skipjack tuna. Progress in Oceanography]. Once this evaluation and parameterization is complete, it may be possible to use the model for management of tuna stocks in the context of climate and ecosystem variability, and to investigate potential changes due to anthropogenic activities including global warming and fisheries pressures and management scenarios.

  17. 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. PMID:25914143

  18. 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

    1. Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment. 2. Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression. 3. Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring-summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect. 4. Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond. 5. Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions. PMID:25808951

  19. 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

  20. Pair approximations of takeover dynamics in regular population structures.

    PubMed

    Payne, Joshua L; Eppstein, Margaret J

    2009-01-01

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

  1. 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 moving beyond estimating changes in vital rates to analyses of population-level impacts. PMID:18488620

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

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

  3. Temporal dynamics and linkage disequilibrium in natural Caenorhabditis elegans populations.

    PubMed

    Barrière, Antoine; Félix, Marie-Anne

    2007-06-01

    Caenorhabditis elegans is a major laboratory model system yet a newcomer to the field of population genetics, and relatively little is known of its biology in the wild. Recent studies of natural populations at a single time point revealed strong spatial population structure and suggested that these populations may be very dynamic. We have therefore studied several natural C. elegans populations over time and genotyped them at polymorphic microsatellite loci. While some populations appear to be genetically stable over the course of observation, others seem to go extinct, with full replacement of multilocus genotypes upon regrowth. The frequency of heterozygotes indicates that outcrossing occurs at a mean frequency of 1.7% and is variable between populations. However, in genetically stable populations, linkage disequilibrium between different chromosomes can be maintained over several years at a level much higher than expected from the heterozygote frequency. C. elegans seems to follow metapopulation dynamics, and the maintenance of linkage disequilibrium despite a low yet significant level of outcrossing suggests that selection may act against the progeny of outcrossings. PMID:17409084

  4. 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.

  5. 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 (?(2)  = 2·039, P = 0·036). Buffalo in low body condition were associated with lower reproductive success (F = 2·683, P = 0·034), but there was no association between brucellosis and pregnancy or being observed with a calf. For the range of body condition scores observed in the population, the model-predicted growth rate was ? = 1·11 (95% CI = 1·02-1·21) in herds without brucellosis and ? = 1·00 (95% CI = 0·85-1·16) when brucellosis seroprevalence was 30%. Our results suggest that brucellosis infection can potentially result in reduced population growth rates, but because these effects varied with demographic and environmental conditions, they may remain unseen without intensive, longitudinal monitoring. PMID:25714466

  6. Density-dependent life history and the dynamics of small populations.

    PubMed

    Mugabo, Marianne; Perret, Samuel; Legendre, Stéphane; Le Galliard, Jean-François

    2013-11-01

    1. Small population dynamics depend importantly on the strength and shape of density dependence. Unfortunately, the lack of reliable life-history data often prevents to make accurate demographic predictions for populations regulated by density dependence. 2. We created a gradient from low to high densities in small experimental populations of common lizards (Zootoca vivipara) and investigated the shape and strength of the density dependence of life-history traits during a yearly cycle. We then analysed stochastic population dynamics using one-sex and two-sex age-structured matrix models. 3. Body growth and reproductive performances decreased with density, yearling and adult survival and body size at birth were density-independent, and juvenile survival increased with density. The density dependence of reproduction was partly explained by positive effects of body size on age at first reproduction and clutch size. 4. Parturition date decreased with density in sparse populations and then increased, providing one of the first empirical evidence of a component Allee effect in the phenology of reproduction. 5. Population growth rate (?) was most affected by variations in juvenile and yearling survival. However, density at equilibrium was most affected by juvenile access to reproduction and yearling clutch size. 6. Stochastic simulations revealed that negative density dependence buffers the effects of initial density on extinction probability, has positive effects on the persistence of sparse populations and interacts with sex ratio fluctuations to shape extinction dynamics. 7. This study demonstrates that negative density dependence modifies the dynamics of small populations and should be investigated together with Allee effects to predict extinction risks. PMID:23859253

  7. Density-dependent dispersal and spatial population dynamics

    PubMed Central

    Ims, Rolf A; Andreassen, Harry P

    2005-01-01

    The synchronization of the dynamics of spatially subdivided populations is of both fundamental and applied interest in population biology. Based on theoretical studies, dispersal movements have been inferred to be one of the most general causes of population synchrony, yet no empirical study has mapped distance-dependent estimates of movement rates on the actual pattern of synchrony in species that are known to exhibit population synchrony. Northern vole and lemming species are particularly well-known for their spatially synchronized population dynamics. Here, we use results from an experimental study to demonstrate that tundra vole dispersal movements did not act to synchronize population dynamics in fragmented habitats. In contrast to the constant dispersal rate assumed in earlier theoretical studies, the tundra vole, and many other species, exhibit negative density-dependent dispersal. Simulations of a simple mathematical model, parametrized on the basis of our experimental data, verify the empirical results, namely that the observed negative density-dependent dispersal did not have a significant synchronizing effect. PMID:16024345

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

    PubMed

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

    2015-12-01

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

  9. Parametric dynamic load prediction of a narrow gauge rocket sled

    NASA Astrophysics Data System (ADS)

    Furlow, John Scott

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

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

    PubMed Central

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

    2010-01-01

    Background We test whether the phenotypic variance of symbionts (Symbiodinium) in corals is closely related with the capacity of corals to acclimatize to increasing seawater temperatures. Moreover, we assess whether more specialist symbionts will increase within coral hosts under ocean warming. The present study is only applicable to those corals that naturally have the capacity to support more than one type of Symbiodinium within the lifetime of a colony; for example, Montastraea annularis and Montastraea faveolata. Methodology/Principal Findings The population dynamics of competing Symbiodinium symbiont populations were projected through time in coral hosts using a novel, discrete time optimal–resource model. Models were run for two Atlantic Ocean localities. Four symbiont populations, with different environmental optima and phenotypic variances, were modeled to grow, divide, and compete in the corals under seasonal fluctuations in solar insolation and seawater temperature. Elevated seawater temperatures were input into the model 1.5°C above the seasonal summer average, and the symbiont population response was observed for each location. The models showed dynamic fluctuations in Symbiodinium populations densities within corals. Population density predictions for Lee Stocking Island, the Bahamas, where temperatures were relatively homogenous throughout the year, showed a dominance of both type 2, with high phenotypic variance, and type 1, a high-temperature and high-insolation specialist. Whereas the densities of Symbiodinium types 3 and 4, a high-temperature, low-insolation specialist, and a high-temperature, low-insolation generalist, remained consistently low. Predictions for Key Largo, Florida, where environmental conditions were more seasonally variable, showed the coexistence of generalists (types 2 and 4) and low densities of specialists (types 1 and 3). When elevated temperatures were input into the model, population densities in corals at Lee Stocking Island showed an emergence of high-temperature specialists. However, even under high temperatures, corals in the Florida Keys were dominated by generalists. Conclusions/Significance Predictions at higher seawater temperatures showed endogenous shuffling and an emergence of the high-temperature Symbiodinium specialists, even though their phenotypic variance was low. The model shows that sustaining these “hidden” specialists becomes advantageous under thermal stress conditions, and shuffling symbionts may increase the corals' capacity to acclimatize but not adapt to climatechange–induced ocean warming. PMID:20169202

  11. 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.

  12. 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 characteristics. This approximation worsens as the difference between the patches increases and the dispersal rate decreases: Under extreme conditions, destabilization of equilibria and periodic orbits occurs at mean parameter values lower than those predicted by the mean parameters. Apparent within-patch dynamics are distorted: The local population appears to have the wrong growth parameter and a constant number of immigrants (or emigrants) per generation. Adding environmental heterogeneity to spatial structure increases the occurrence of spatially correlated population dynamics, but the resulting temporal dynamics are more complex than would be predicted by the mean parameter values. The three classes of spatial pattern (positive, negative, and zero correlation), while still mathematically distinct, become increasingly similar phenomenologically. PMID:9680486

  13. Predictions of a population of cataclysmic variables in globular clusters

    NASA Technical Reports Server (NTRS)

    Di Stefano, R.; Rappaport, S.

    1994-01-01

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

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

    PubMed

    Lindh, Markus V; Sjöstedt, Johanna; Andersson, Anders F; Baltar, Federico; Hugerth, Luisa W; Lundin, Daniel; Muthusamy, Saraladevi; Legrand, Catherine; Pinhassi, Jarone

    2015-07-01

    Multiyear comparisons of bacterioplankton succession reveal that environmental conditions drive community shifts with repeatable patterns between years. However, corresponding insight into bacterioplankton dynamics at a temporal resolution relevant for detailed examination of variation and characteristics of specific populations within years is essentially lacking. During 1 year, we collected 46 samples in the Baltic Sea for assessing bacterial community composition by 16S rRNA gene pyrosequencing (nearly twice weekly during productive season). Beta-diversity analysis showed distinct clustering of samples, attributable to seemingly synchronous temporal transitions among populations (populations defined by 97% 16S rRNA gene sequence identity). A wide spectrum of bacterioplankton dynamics was evident, where divergent temporal patterns resulted both from pronounced differences in relative abundance and presence/absence of populations. Rates of change in relative abundance calculated for individual populations ranged from 0.23 to 1.79 day(-1) . Populations that were persistently dominant, transiently abundant or generally rare were found in several major bacterial groups, implying evolution has favoured a similar variety of life strategies within these groups. These findings suggest that high temporal resolution sampling allows constraining the timescales and frequencies at which distinct populations transition between being abundant or rare, thus potentially providing clues about physical, chemical or biological forcing on bacterioplankton community structure. PMID:25403576

  15. Dynamic Predictions of Semi-Arid Land Cover Change

    NASA Astrophysics Data System (ADS)

    Foster-Wittig, T. A.

    2011-12-01

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

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

    EPA Science Inventory

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

  17. Interactions between predation and resources shape zooplankton population dynamics.

    PubMed

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

    2011-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. Binary Populations and Stellar Dynamics in Young Clusters

    NASA Astrophysics Data System (ADS)

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

    2008-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

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

  1. 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.

  2. Computer simulation of Boophilus cattle tick (Acari: Ixodidae) population dynamics.

    PubMed

    Mount, G A; Haile, D G; Davey, R B; Cooksey, L M

    1991-03-01

    A comprehensive computer model was developed for simulation of the population dynamics of the cattle ticks, Boophilus microplus (Canestrini) and B. annulatus (Say). The model is deterministic and based on a dynamic life table with weekly time steps. The model simulates the effects of major environmental variables, such as ambient temperature, saturation deficit, precipitation, type of pasture, type of cattle, and cattle density on Boophilus cattle tick population dynamics. General validity of the model is established by comparing simulated and observed yearly densities of standard female ticks/host/day. B. microplus population comparisons were made for a series of years using weekly weather data from two locations in Queensland, Australia. The model also produced acceptable values for initial population growth rate, generation time, and 3-yr population density when historical weather at 7 locations in Australia and 23 locations in the Americas were used. This model provides a framework for the study of Babesia transmission by Boophilus ticks, and can be used to study the effects of control technologies and to develop more efficient and environmentally acceptable eradication strategies for Boophilus ticks. PMID:2056504

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

    PubMed Central

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

    2013-01-01

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

  4. Nonequilibrium population dynamics of phenotype conversion of cancer cells.

    PubMed

    Zhou, Joseph Xu; Pisco, Angela Oliveira; Qian, Hong; Huang, Sui

    2014-01-01

    Tumorigenesis is a dynamic biological process that involves distinct cancer cell subpopulations proliferating at different rates and interconverting between them. In this paper we proposed a mathematical framework of population dynamics that considers both distinctive growth rates and intercellular transitions between cancer cell populations. Our mathematical framework showed that both growth and transition influence the ratio of cancer cell subpopulations but the latter is more significant. We derived the condition that different cancer cell types can maintain distinctive subpopulations and we also explain why there always exists a stable fixed ratio after cell sorting based on putative surface markers. The cell fraction ratio can be shifted by changing either the growth rates of the subpopulations (Darwinism selection) or by environment-instructed transitions (Lamarckism induction). This insight can help us to understand the dynamics of the heterogeneity of cancer cells and lead us to new strategies to overcome cancer drug resistance. PMID:25438251

  5. Nonequilibrium Population Dynamics of Phenotype Conversion of Cancer Cells

    PubMed Central

    Zhou, Joseph Xu; Pisco, Angela Oliveira; Qian, Hong; Huang, Sui

    2014-01-01

    Tumorigenesis is a dynamic biological process that involves distinct cancer cell subpopulations proliferating at different rates and interconverting between them. In this paper we proposed a mathematical framework of population dynamics that considers both distinctive growth rates and intercellular transitions between cancer cell populations. Our mathematical framework showed that both growth and transition influence the ratio of cancer cell subpopulations but the latter is more significant. We derived the condition that different cancer cell types can maintain distinctive subpopulations and we also explain why there always exists a stable fixed ratio after cell sorting based on putative surface markers. The cell fraction ratio can be shifted by changing either the growth rates of the subpopulations (Darwinism selection) or by environment-instructed transitions (Lamarckism induction). This insight can help us to understand the dynamics of the heterogeneity of cancer cells and lead us to new strategies to overcome cancer drug resistance. PMID:25438251

  6. 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

  7. Diversity Waves in Collapse-Driven Population Dynamics.

    PubMed

    Maslov, Sergei; Sneppen, Kim

    2015-09-01

    Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe reduction in size of the population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g. by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is characterized by cyclic ''diversity waves'' triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances have bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak--species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies. PMID:26367172

  8. 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.

  9. Diversity waves in collapse-driven population dynamics

    DOE PAGESBeta

    Maslov, Sergei; Sneppen, Kim

    2015-09-14

    Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe collapses of the entire population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g.more » by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is cyclic ‘‘diversity waves’’ triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances are characterized by a bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies.« less

  10. Metamodels for Transdisciplinary Analysis of Wildlife Population Dynamics

    PubMed Central

    Lacy, Robert C.; Miller, Philip S.; Nyhus, Philip J.; Pollak, J. P.; Raboy, Becky E.; Zeigler, Sara L.

    2013-01-01

    Wildlife population models have been criticized for their narrow disciplinary perspective when analyzing complexity in coupled biological – physical – human systems. We describe a “metamodel” approach to species risk assessment when diverse threats act at different spatiotemporal scales, interact in non-linear ways, and are addressed by distinct disciplines. A metamodel links discrete, individual models that depict components of a complex system, governing the flow of information among models and the sequence of simulated events. Each model simulates processes specific to its disciplinary realm while being informed of changes in other metamodel components by accessing common descriptors of the system, populations, and individuals. Interactions among models are revealed as emergent properties of the system. We introduce a new metamodel platform, both to further explain key elements of the metamodel approach and as an example that we hope will facilitate the development of other platforms for implementing metamodels in population biology, species risk assessments, and conservation planning. We present two examples – one exploring the interactions of dispersal in metapopulations and the spread of infectious disease, the other examining predator-prey dynamics – to illustrate how metamodels can reveal complex processes and unexpected patterns when population dynamics are linked to additional extrinsic factors. Metamodels provide a flexible, extensible method for expanding population viability analyses beyond models of isolated population demographics into more complete representations of the external and intrinsic threats that must be understood and managed for species conservation. PMID:24349567

  11. 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.

  12. Stochastic simulation of structured skin cell population dynamics.

    PubMed

    Nakaoka, Shinji; Aihara, Kazuyuki

    2013-03-01

    The epidermis is the outmost skin tissue. It operates as a first defense system to process inflammatory signals and responds by producing inflammatory mediators that promote the recruitment of immune cells. Various skin diseases such as atopic dermatitis occur as a result of the defect of proper skin barrier function and successive impaired inflammatory responses. The onset of such a skin disease links to the disturbed epidermal homeostasis regulated by appropriate self-renewal and differentiation of epidermal stem cells. The theory of physiologically structured population models provides a versatile framework to formulate mathematical models which describe the growth dynamics of a cell population such as the epidermis. In this paper, we develop an algorithm to implement stochastic simulation for a class of physiologically structured population models. We demonstrate that the developed algorithm is applicable to several cell population models and typical age-structured population models. On the basis of the developed algorithm, we investigate stochastic dynamics of skin cell populations and spread of inflammation. It is revealed that demographic stochasticity can bring considerable impact on the outcome of inflammation spread at the tissue level. PMID:23255068

  13. 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 treatment gaps during radiotherapy, apart from decreasing the probability of eradicating the primary cancer, substantially increase the risk of later second cancers.

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

    NASA Technical Reports Server (NTRS)

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

    1996-01-01

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

  16. 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.

  17. The population dynamics of an endemic collectible cactus

    NASA Astrophysics Data System (ADS)

    Mandujano, MarĂ­a 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.

  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. 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

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

    PubMed Central

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

    2009-01-01

    Parental effects arise when either the maternal or paternal phenotype influences the phenotypes of subsequent generations. Simple analytical models assume maternal effects are a mechanism creating delayed density dependence. Such models predict that maternal effects can very easily lead to population cycles. Despite this, unambiguous maternal-effect mediated cycles have not been demonstrated in any system. Additionally, much evidence has arisen to invalidate the underlying assumption that there is a simple positive correlation between maternal performance and offspring performance. A key issue in understanding how maternal effects may affect population dynamics is determining how the expression of parental effects changes in different environments. In this study, we tested the hypothesis that maternal effects influence population dynamics in a context-dependent way. Populations of the soil mite, Sancassania berlesei, were set up at high density (500 eggs) or low density (50 eggs), with eggs that were either laid by young mothers or old mothers (a previously documented maternal effect in this system). The influence of maternal age on both population and egg and body-size dynamics was only observed in the populations initiated under low density rather than high density. This difference was attributable to the context-dependence of maternal effects at the individual level. In low-density (high food) conditions, maternal effects have an impact on offspring reproductive performance, creating an impact on the population growth rate. In high density (low food), maternal effects impact more on juvenile survival (not adult size or reproduction), creating a smaller impact on the population growth rate. This context dependence of effects at the population level means that, in fluctuating populations, maternal effects cause intermittent delayed density dependence that does not lead to persistent cycles. PMID:19324610

  1. 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

  2. A new approach to quantify predictability: Nonlinear error growth dynamics

    NASA Astrophysics Data System (ADS)

    Li, J.; Ding, R.

    2009-04-01

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

  3. Can possible evolutionary outcomes be determined directly from the population dynamics?

    PubMed

    Hoyle, Andrew; Bowers, Roger G

    2008-12-01

    Traditionally, to determine the possible evolutionary behaviour of an ecological system using adaptive dynamics, it is necessary to calculate the fitness and its derivatives at a singular point. We investigate the claim that the possible evolutionary behaviour can be predicted directly from the population dynamics, without the need for calculation, by applying three criteria - one based on the form of the density dependent rates and two on the role played by the evolving parameters. Taking a general continuous time model, with broad ecological range, we show that the claim is true. Initially, we assume that individuals enter in class 1 and move through population classes sequentially; later we relax these assumptions and find that the criteria still apply. However, when we consider models where the evolving parameters appear non-linearly in the dynamics, we find some aspects of the criteria fail; useful but weaker results on possible evolutionary behaviour now apply. PMID:18840456

  4. Chaotic population dynamics can result from natural selection.

    PubMed

    Ferrière, R; Gatto, M

    1993-01-22

    The question of whether animal populations display chaotic dynamics has motivated a thriving body of research for two decades. Yet unambiguous evidence for chaos in the wild remains scarce. Accordingly, it has been proposed that evolutionary forces act to preserve populations from chaos as well as oscillations. We have tested for this hypothesis by considering the dynamics associated with evolutionarily stable life histories (including age of maturity, adult survivorship and recruitment to adulthood) in a simple, but general, demographic model. Contrary to expectation, individual selection operating on demographic traits should often lead to oscillatory or chaotic dynamics for species with late feasible ages of maturity and many age classes. Also, the optimality of chaos is more likely whenever trade-offs constrain recruitment to rapidly decrease with increasing adult survival or decreasing age of maturity. Our results bring evolutionary support to the possibility that chaotic population dynamics might be much more widespread than inferred until now from data analyses. Furthermore, these findings provide novel support for the view that chaos could be an optimal regime for several biological systems. PMID:8094563

  5. A comparison of six methods for stabilizing population dynamics.

    PubMed

    Tung, Sudipta; Mishra, Abhishek; Dey, Sutirth

    2014-09-01

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

  6. Nanoplankton population dynamics and dissolved oxygen change across the Bay of Izmir by neural networks.

    PubMed

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

    2009-06-01

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

  7. 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.

  8. How Predation and Landscape Fragmentation Affect Vole Population Dynamics

    PubMed Central

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

    2011-01-01

    Background Microtine species in Fennoscandia display a distinct north-south gradient from regular cycles to stable populations. The gradient has often been attributed to changes in the interactions between microtines and their predators. Although the spatial structure of the environment is known to influence predator-prey dynamics of a wide range of species, it has scarcely been considered in relation to the Fennoscandian gradient. Furthermore, the length of microtine breeding season also displays a north-south gradient. However, little consideration has been given to its role in shaping or generating population cycles. Because these factors covary along the gradient it is difficult to distinguish their effects experimentally in the field. The distinction is here attempted using realistic agent-based modelling. Methodology/Principal Findings By using a spatially explicit computer simulation model based on behavioural and ecological data from the field vole (Microtus agrestis), we generated a number of repeated time series of vole densities whose mean population size and amplitude were measured. Subsequently, these time series were subjected to statistical autoregressive modelling, to investigate the effects on vole population dynamics of making predators more specialised, of altering the breeding season, and increasing the level of habitat fragmentation. We found that fragmentation as well as the presence of specialist predators are necessary for the occurrence of population cycles. Habitat fragmentation and predator assembly jointly determined cycle length and amplitude. Length of vole breeding season had little impact on the oscillations. Significance There is good agreement between our results and the experimental work from Fennoscandia, but our results allow distinction of causation that is hard to unravel in field experiments. We hope our results will help understand the reasons for cycle gradients observed in other areas. Our results clearly demonstrate the importance of landscape fragmentation for population cycling and we recommend that the degree of fragmentation be more fully considered in future analyses of vole dynamics. PMID:21829528

  9. Integrating population dynamics into mapping human exposure to seismic hazard

    NASA Astrophysics Data System (ADS)

    Freire, S.; Aubrecht, C.

    2012-11-01

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

  10. 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. PMID:19640497

  11. Evolutionary dynamics of a multigroup fluctuating-population system

    NASA Astrophysics Data System (ADS)

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

    1993-03-01

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

  12. Changes in Population Dynamics in Mutualistic versus Pathogenic Viruses

    PubMed Central

    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. PMID:21994724

  13. 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…

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

    PubMed

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

    2010-11-01

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

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

    Cancer.gov

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

  16. 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 would occur if there was only global warming and no concomitant decrease in pH. PMID:21058553

  17. 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.

  18. Biology as population dynamics: heuristics for transmission risk.

    PubMed

    Keebler, Daniel; Walwyn, David; Welte, Alex

    2013-02-01

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

  19. Predicting the Dynamics of Network Connectivity in the Neocortex.

    PubMed

    Loewenstein, Yonatan; Yanover, Uri; Rumpel, Simon

    2015-09-01

    Dynamic remodeling of connectivity is a fundamental feature of neocortical circuits. Unraveling the principles underlying these dynamics is essential for the understanding of how neuronal circuits give rise to computations. Moreover, as complete descriptions of the wiring diagram in cortical tissues are becoming available, deciphering the dynamic elements in these diagrams is crucial for relating them to cortical function. Here, we used chronic in vivo two-photon imaging to longitudinally follow a few thousand dendritic spines in the mouse auditory cortex to study the determinants of these spines' lifetimes. We applied nonlinear regression to quantify the independent contribution of spine age and several morphological parameters to the prediction of the future survival of a spine. We show that spine age, size, and geometry are parameters that can provide independent contributions to the prediction of the longevity of a synaptic connection. In addition, we use this framework to emulate a serial sectioning electron microscopy experiment and demonstrate how incorporation of morphological information of dendritic spines from a single time-point allows estimation of future connectivity states. The distinction between predictable and nonpredictable connectivity changes may be used in the future to identify the specific adaptations of neuronal circuits to environmental changes. The full dataset is publicly available for further analysis. Significance statement: The neural architecture in the neocortex exhibits constant remodeling. The functional consequences of these modifications are poorly understood, in particular because the determinants of these changes are largely unknown. Here, we aimed to identify those modifications that are predictable from current network state. To that goal, we repeatedly imaged thousands of dendritic spines in the auditory cortex of mice to assess the morphology and lifetimes of synaptic connections. We developed models based on morphological features of dendritic spines that allow predicting future turnover of synaptic connections. The dynamic models presented in this paper provide a quantitative framework for adding putative temporal dynamics to the static description of a neuronal circuit from single time-point connectomics experiments. PMID:26354919

  20. Combined analytical and experimental approaches to dynamic component stress prediction

    NASA Astrophysics Data System (ADS)

    Chierichetti, Maria

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

  1. 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.

  2. A stochastic modeling of early HIV-1 population dynamics.

    PubMed

    Kamina, A; Makuch, R W; Zhao, H

    2001-04-01

    In a recent paper, Tuckwell and Le Corfec [J. Theor. Biol. 195 (1998) 450-463] applied the multi-dimensional diffusion process to model early human immunodeficiency virus type-1 (HIV-1) population dynamics. The purpose of this paper is to assess certain features and consequences of their model in the context of Tan and Wu's stochastic approach [Math. Biosci. 147 (1998) 173-205]. PMID:11292498

  3. 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

  4. Assessing predictability of a hydrological stochastic-dynamical system

    NASA Astrophysics Data System (ADS)

    Gelfan, Alexander

    2014-05-01

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

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

    PubMed

    McDowell, J J; Calvin, Nicholas T

    2015-05-01

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

  6. VCGDB: a dynamic genome database of the Chinese population

    PubMed Central

    2014-01-01

    Background The data released by the 1000 Genomes Project contain an increasing number of genome sequences from different nations and populations with a large number of genetic variations. As a result, the focus of human genome studies is changing from single and static to complex and dynamic. The currently available human reference genome (GRCh37) is based on sequencing data from 13 anonymous Caucasian volunteers, which might limit the scope of genomics, transcriptomics, epigenetics, and genome wide association studies. Description We used the massive amount of sequencing data published by the 1000 Genomes Project Consortium to construct the Virtual Chinese Genome Database (VCGDB), a dynamic genome database of the Chinese population based on the whole genome sequencing data of 194 individuals. VCGDB provides dynamic genomic information, which contains 35 million single nucleotide variations (SNVs), 0.5 million insertions/deletions (indels), and 29 million rare variations, together with genomic annotation information. VCGDB also provides a highly interactive user-friendly virtual Chinese genome browser (VCGBrowser) with functions like seamless zooming and real-time searching. In addition, we have established three population-specific consensus Chinese reference genomes that are compatible with mainstream alignment software. Conclusions VCGDB offers a feasible strategy for processing big data to keep pace with the biological data explosion by providing a robust resource for genomics studies; in particular, studies aimed at finding regions of the genome associated with diseases. PMID:24708222

  7. Genomic predictability of interconnected bi-parental maize populations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Intense structuring of plant breeding populations leads to new challenges for genomic selection (GS) not encountered in animal breeding. One important open question is how the training population (TP) should be constructed from multiple related or unrelated small bi-parental families. Knowing the pr...

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

    PubMed

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

    2016-01-01

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

  9. Physiologically structured populations with diffusion and dynamic boundary conditions.

    PubMed

    Farkas, József Z; Hinow, Peter

    2011-04-01

    We consider a linear size-structured population model with diffusion in the size-space. Individuals are recruited into the population at arbitrary sizes. We equip the model with generalized Wentzell-Robin (or dynamic) boundary conditions. This approach allows the modelling of populations in which individuals may have distinguished physiological states. We establish existence and positivity of solutions by showing that solutions are governed by a positive quasicontractive semigroup of linear operators on the biologically relevant state space. These results are obtained by establishing dissipativity of a suitably perturbed semigroup generator. We also show that solutions of the model exhibit balanced exponential growth, that is, our model admits a finite-dimensional global attractor. In case of strictly positive fertility we are able to establish that solutions in fact exhibit asynchronous exponential growth. PMID:21631142

  10. 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

  11. 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

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

    PubMed

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

    2006-02-28

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

  13. A new model with delay for mosquito population dynamics.

    PubMed

    Wan, Hui; Zhu, Huaiping

    2014-12-01

    In this paper, we formulate a new model with maturation delay for mosquito population incorporating the impact of blood meal resource for mosquito reproduction. Our results suggest that except for the usual crowded effect for adult mosquitoes, the impact of blood meal resource in a given region determines the mosquito abundance, it is also important for the population dynamics of mosquito which may induce Hopf bifurcation. The existence of a stable periodic solution is proved both analytically and numerically. The new model for mosquito also suggests that the resources for mosquito reproduction should not be ignored or mixed with the impact of blood meal resources for mosquito survival and both impacts should be considered in the model of mosquito population. The impact of maturation delay is also analyzed. PMID:25365606

  14. Connection between dynamically derived IMF normalisation and stellar populations

    NASA Astrophysics Data System (ADS)

    McDermid, Richard M.

    2015-04-01

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

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

    PubMed Central

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

    2016-01-01

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

  16. 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.

  17. 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(-?)(h) with ?(h)=0.22 ± 0.02; the same exponent holds for a quench to low but nonzero temperature. This "heritability exponent" may equal the persistence exponent for the two-dimensional Ising ferromagnet, but the two differ more generally. PMID:24229093

  18. 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-Ξh with Ξh=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.

  19. Predicting the timing of dynamic events through sound: Bouncing balls.

    PubMed

    Gygi, Brian; Giordano, Bruno L; Shafiro, Valeriy; Kharkhurin, Anatoliy; Zhang, Peter Xinya

    2015-07-01

    Dynamic information in acoustical signals produced by bouncing objects is often used by listeners to predict the objects' future behavior (e.g., hitting a ball). This study examined factors that affect the accuracy of motor responses to sounds of real-world dynamic events. In experiment 1, listeners heard 2-5 bounces from a tennis ball, ping-pong, basketball, or wiffle ball, and would tap to indicate the time of the next bounce in a series. Across ball types and number of bounces, listeners were extremely accurate in predicting the correct bounce time (CT) with a mean prediction error of only 2.58% of the CT. Prediction based on a physical model of bouncing events indicated that listeners relied primarily on temporal cues when estimating the timing of the next bounce, and to a lesser extent on the loudness and spectral cues. In experiment 2, the timing of each bounce pattern was altered to correspond to the bounce timing pattern of another ball, producing stimuli with contradictory acoustic cues. Nevertheless, listeners remained highly accurate in their estimates of bounce timing. This suggests that listeners can adopt their estimates of bouncing-object timing based on acoustic cues that provide most veridical information about dynamic aspects of object behavior. PMID:26233044

  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. 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. PMID:24944116

  2. 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.

  3. The Effect of Temperature on Anopheles Mosquito Population Dynamics and the Potential for Malaria Transmission

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2013-01-01

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

  5. Delayed induced silica defences in grasses and their potential for destabilising herbivore population dynamics.

    PubMed

    Reynolds, Jennifer J H; Lambin, Xavier; Massey, Fergus P; Reidinger, Stefan; Sherratt, Jonathan A; Smith, Matthew J; White, Andrew; Hartley, Sue E

    2012-10-01

    Some grass species mount a defensive response to grazing by increasing their rate of uptake of silica from the soil and depositing it as abrasive granules in their leaves. Increased plant silica levels reduce food quality for herbivores that feed on these grasses. Here we provide empirical evidence that a principal food species of an herbivorous rodent exhibits a delayed defensive response to grazing by increasing silica concentrations, and present theoretical modelling that predicts that such a response alone could lead to the population cycles observed in some herbivore populations. Experiments performed under greenhouse conditions revealed that the rate of deposition of silica defences in the grass Deschampsia caespitosa is a time-lagged, nonlinear function of grazing intensity and that, upon cessation of grazing, these defences take around one year to decay to within 5 % of control levels. Simple coupled grass-herbivore population models incorporating this functional response, and parameterised with empirical data, consistently predict population cycles for a wide range of realistic parameter values for a (Microtus) vole-grass system. Our results support the hypothesis that induced silica defences have the potential to strongly affect the population dynamics of their herbivores. Specifically, the feedback response we observed could be a driving mechanism behind the observed population cycles in graminivorous herbivores in cases where grazing levels in the field become sufficiently large and sustained to trigger an induced silica defence response. PMID:22526942

  6. Spatial structure and chaos in insect population dynamics

    NASA Astrophysics Data System (ADS)

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

    1991-09-01

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

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

    PubMed

    1994-03-01

    This article is an excerpt from a recently published article on interactions between population and development in the "Economic and Social Survey of Asia and the Pacific, 1993." Topics include the dynamics of change (growth, age structure, sex composition, migration); implications for specific development issues (population and education, population and health, population and employment, and population and the environment); and policy approaches (slowing growth, spatial distribution, and the role of women). The Asian focus is on population policy and fertility declines. Different conditions specific to each country and varying degrees of program success give rise to country-specific differences in rates of growth and declines in fertility. Population compositions and pressures on spatial distribution differ among countries. Development demands differ for education, health, employment, and environmental controls. A common feature is that population is integrated into social and economic development policies. The links between population and the environment are recognized and will be integrated into policy as knowledge emerges. The ESCAP region has about 58% of world population, and fertility has declined to 3.1 children per woman. Fertility declines do not result in demonstrable changes in the rate of population growth, because the proportion of reproductive age women has increased and will continue to do so until 2010. Reductions in fertility are balanced by mortality declines. The annual rate of increase has gradually slowed, however the absolute size is still huge. The goal of the Bali Declaration of 1992 is to reach replacement level fertility of 2.2 children per woman by 2010 in the ESCAP region. The UN median variant projects 2.4 children per woman by 2010. The countries unlikely to reach replacement level fertility are India, the Philippines, Vietnam, Bangladesh, and Pakistan. Age structure will determine the need for services. For example, South Asia will still have a large proportion aged 0-14 years in 2010 and will require infant care and primary education. Sex composition will be balanced at 20 years and favor females in older ages, except for Vietnam and Cambodia. About 50% of urban growth is accounted for by rural to urban migration, particularly among females. PMID:12288071

  8. The human ecological approach to the study of population dynamics.

    PubMed

    Namboodiri, K

    1994-01-01

    Human ecology is a specialization of ecology, tailored to suit the characteristic features of human populations. This essay focuses upon human ecology as set forth by Hawley and Duncan, although other conceptualizations are referred to. The bio-ecological framework is described together with an introduction of the distinction between population ecology and community ecology. Bio-ecology is an important subdiscipline of biology, but its subject has never been as complex as that of human ecology. Human ecologists developed their own theoretical framework distinct from that of bio-ecology. The author briefly outlines the history of human ecology, emphasizing the initial phase of the Chicago School, which focused upon spatial patterns of human phenomena, and the succeeding one, in which a reorientation focused upon the organizational aspects of population dynamics. The author then reviews some of the basic features of human ecology, discusses population ecology and its applications, with reference to the study of populations of households, and outlines the use of graph theory, input-output frameworks, and multilevel modeling to improve the formal and methodological aspects of human ecology. The spatial concern of human ecology is considered and situated in a broader context. PMID:12290834

  9. 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. PMID:25477869

  10. 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

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

    PubMed

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

    2016-01-01

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

  12. Prediction of Muscle Performance During Dynamic Repetitive Exercise

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

  13. 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

  14. Rational Prediction with Molecular Dynamics for Hit Identification

    PubMed Central

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

    2012-01-01

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

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

    PubMed

    Sinclair, A R E

    2003-10-29

    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

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

    PubMed Central

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

    2012-01-01

    Investigating the ecology of long lived birds is particularly challenging owing to the time scales involved. Here an analysis is presented of a long term study of the survival and population dynamics of the marabou stork (Leptoptilos crumeniferus), a wide ranging scavenging bird from Sub-Saharan Africa. Using resightings data of tagged nestlings and free flying birds we show that the stork population can be divided into three general life stages with unique survival probabilities and fecundities. Fecundity of the storks is inversely related to rainfall during their breeding season. Corroborative evidence for a metapopulation structure is discussed highlighting the impact of the Swaziland birds on the ecology of the species in the broader region. The importance of tag loss or illegibility over time is highlighted. Clearly, any attempt at conserving a species will require a detailed understanding of its population structure, of the sort examined here. PMID:23029517

  17. Uncoupling the effects of seed predation and seed dispersal by granivorous ants on plant population dynamics.

    PubMed

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

    2012-01-01

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

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

    PubMed Central

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

    2012-01-01

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

  19. 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.

  20. 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.

  1. Plasmodium vivax Population Structure and Transmission Dynamics in Sabah Malaysia

    PubMed Central

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

    2013-01-01

    Despite significant progress in the control of malaria in Malaysia, the complex transmission dynamics of P. vivax continue to challenge national efforts to achieve elimination. To assess the impact of ongoing interventions on P. vivax transmission dynamics in Sabah, we genotyped 9 short tandem repeat markers in a total of 97 isolates (8 recurrences) from across Sabah, with a focus on two districts, Kota Marudu (KM, n?=?24) and Kota Kinabalu (KK, n?=?21), over a 2 year period. STRUCTURE analysis on the Sabah-wide dataset demonstrated multiple sub-populations. Significant differentiation (FST ?=?0.243) was observed between KM and KK, located just 130 Km apart. Consistent with low endemic transmission, infection complexity was modest in both KM (mean MOI ?=?1.38) and KK (mean MOI ?=?1.19). However, population diversity remained moderate (HE ?=?0.583 in KM and HE ?=?0.667 in KK). Temporal trends revealed clonal expansions reflecting epidemic transmission dynamics. The haplotypes of these isolates declined in frequency over time, but persisted at low frequency throughout the study duration. A diverse array of low frequency isolates were detected in both KM and KK, some likely reflecting remnants of previous expansions. In accordance with clonal expansions, high levels of Linkage Disequilibrium (IAS >0.5 [P<0.0001] in KK and KM) declined sharply when identical haplotypes were represented once (IAS ?=?0.07 [P?=?0.0076] in KM, and IAS?=?-0.003 [P?=?0.606] in KK). All 8 recurrences, likely to be relapses, were homologous to the prior infection. These recurrences may promote the persistence of parasite lineages, sustaining local diversity. In summary, Sabah's shrinking P. vivax population appears to have rendered this low endemic setting vulnerable to epidemic expansions. Migration may play an important role in the introduction of new parasite strains leading to epidemic expansions, with important implications for malaria elimination. PMID:24358203

  2. 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.

  3. Improved semiconductor-laser dynamics from induced population pulsation.

    SciTech Connect

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

    2005-03-01

    This paper investigates theoretically the modification of dynamical properties in a semiconductor laser by a strong injected signal. It is found that enhanced relaxation oscillations are governed by the pulsations of the intracavity field and population at frequencies determined by the injected field and cavity resonances. Furthermore, the bandwidth enhancement is associated with the undamping of the injection-induced relaxation oscillation and strong population pulsation effects. There are two limitations to the modulation-bandwidth enhancement: Overdamping of relaxation oscillation and degradation of flat response at low frequencies. The injected-laser rate-equations used in the investigation reproduce the relevant aspects of modulation-bandwidth enhancement found in the experiment on injection-locked vertical-cavity surface-emitting lasers.

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

    PubMed Central

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

    2013-01-01

    A major aim of synthetic biology is to program novel cellular behaviors 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 behaviors 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. PMID:21681967

  5. Arbitrary nonlinearities in convective population dynamics with small diffusion

    NASA Astrophysics Data System (ADS)

    Peixoto, I. D.; Giuggioli, L.; Kenkre, V. M.

    2005-10-01

    Convective counterparts of variants of the nonlinear Fisher equation which describes reaction diffusion systems in population dynamics are studied with the help of an analytic prescription and shown to lead to interesting consequences for the evolution of population densities. The initial-value problem is solved explicitly for some cases, and for others it is shown how to find traveling-wave solutions analytically. The effect of adding diffusion to the convective equations is first studied through exact analysis through a piecewise linear representation of the nonlinearity. Using an appropriate small parameter suggested by that analysis, a perturbative treatment is developed to treat the case in which the convective evolution is augmented by a small amount of diffusion.

  6. pedagog: software for simulating eco-evolutionary population dynamics.

    PubMed

    Coombs, Jason A; Letcher, B H; Nislow, K H

    2010-05-01

    pedagog is a Windows program that can be used to determine power for, and validate inferences drawn from, eco-evolutionary studies. It models dynamics of multiple populations and their interactions through individual-based simulations while simultaneously recording genotype, pedigree and trait information at the individual level. pedagog also allows for specification of heritable traits, natural and sexual selection acting upon those traits, population sampling schemes and incorporation of genetic and demographic errors into the output. Overall, parameters can be specified for genetic diversity, demographics, mating design, genetic and demographic errors, individual growth models, trait heritability and selection, and output formatting. Demographic parameters can be either age or function based, and all parameters can be drawn from 12 statistical distributions where appropriate. Simulation results can be automatically formatted for 57 existing software programs to facilitate postsimulation analyses. pedagog is freely available for download at https://bcrc.bio.umass.edu/pedigreesoftware/. PMID:21565058

  7. 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.

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

    NASA Astrophysics Data System (ADS)

    Sippel, Anna C.; Hurley, Jarrod R.

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Otero, Noelia; Mohino, Elsa; Gaetani, Marco

    2015-07-01

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

  10. [Demographic population forecasts: theoretical framework, assumptions, and prediction uncertainty].

    PubMed

    Steinberg, J; Doblhammer-Reiter, G

    2010-05-01

    Population forecasts are not only highly demanded by scientists, politicians, and economists, but also by the general public. Thereby the wish of the users for only one forecast runs contrary to the uncertainty of the future developments of the population. In the past, but also today, population forecasts were and are predominantly accomplished by applying a deterministic approach: the Cohort Component Method. To counteract the uncertainty of future trends in the demographic processes in fertility, mortality, and migration, different scenarios are applied. Many studies have analyzed ex post the accuracy of past population projections. They show that, in addition to other factors, the time horizon and the level of regional aggregation influence the accuracy of the forecast outcomes. In particular, errors in the assumptions about future trends in fertility, mortality, and migration determine the accuracy of the forecasts. In many cases, these assumptions under- or overestimated the real trends. Progress in the question on uncertainty was made in recent years using a new approach: probabilistic forecasts which include probabilities of future trends in demographic processes. PMID:20437023

  11. 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


  12. 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…

  13. 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.

  14. 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.

  15. 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

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

    PubMed

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

    2016-01-01

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

  17. Predictability experiments using a low order empirically corrected dynamical model

    NASA Technical Reports Server (NTRS)

    Schubert, S.

    1984-01-01

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

  18. 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.

  19. 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.

  20. Time-delayed coupled logistic capacity model in population dynamics

    NASA Astrophysics Data System (ADS)

    CĂĄceres, Manuel O.

    2014-08-01

    This study proposes a delay-coupled system based on the logistic equation that models the interaction of a population with its varying environment. The integro-diferential equations of the model are presented in terms of a distributed time-delayed coupled logistic-capacity equation. The model eliminates the need for a prior knowledge of the maximum saturation environmental carrying capacity value. Therefore the dynamics toward the final attractor in a distributed time-delayed coupled logistic-capacity model is studied. Exact results are presented, and analytical conclusions have been done in terms of the two parameters of the model.

  1. A Stochastic Super-Exponential Growth Model for Population Dynamics

    NASA Astrophysics Data System (ADS)

    Avila, P.; Rekker, A.

    2010-11-01

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

  2. Periodically varying externally imposed environmental effects on population dynamics

    NASA Astrophysics Data System (ADS)

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

    2004-09-01

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

  3. Applications of Perron-Frobenius theory to population dynamics.

    PubMed

    Li, Chi-Kwong; Schneider, Hans

    2002-05-01

    By the use of Perron-Frobenius theory, simple proofs are given of the Fundamental Theorem of Demography and of a theorem of Cushing and Yicang on the net reproductive rate occurring in matrix models of population dynamics. The latter result, which is closely related to the Stein-Rosenberg theorem in numerical linear algebra, is further refined with some additional nonnegative matrix theory. When the fertility matrix is scaled by the net reproductive rate, the growth rate of the model is $1$. More generally, we show how to achieve a given growth rate for the model by scaling the fertility matrix. Demographic interpretations of the results are given. PMID:12021984

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

    PubMed

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

    2013-01-01

    Understanding why certain species can successfully colonize new areas while others do not is a central question in ecology. The nine-banded armadillo (Dasypus novemcinctus) is a conspicuous example of a successful invader, having colonized much of the southern United States in the last 200 years. We used 15 years (1992-2006) of capture-mark-recapture data from a population of armadillos in northern Florida in order to estimate, and examine relationships among, various demographic parameters that may have contributed to this ongoing range expansion. Modeling across a range of values for ?, the probability of juveniles surviving in the population until first capture, we found that population growth rates varied from 0.80 for ? = 0.1, to 1.03 for ? = 1.0. Growth rates approached 1.0 only when ? ? 0.80, a situation that might not occur commonly because of the high rate of disappearance of juveniles. Net reproductive rate increased linearly with ?, but life expectancy (estimated at 3 years) was independent of ?. We also found that growth rates were lower during a 3-year period of hardwood removal that removed preferred habitat than in the years preceding or following. Life-table response experiment (LTRE) analysis indicated the decrease in growth rate during logging was primarily due to changes in survival rates of adults. Likewise, elasticity analyses of both deterministic and stochastic population growth rates revealed that survival parameters were more influential on population growth than were those related to reproduction. Collectively, our results are consistent with recent theories regarding biological invasions which posit that populations no longer at the leading edge of range expansion do not exhibit strong positive growth rates, and that high reproductive output is less critical in predicting the likelihood of successful invasion than are life-history strategies that emphasize allocation of resources to future, as opposed to current, reproduction. PMID:23844183

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

    PubMed Central

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

    2013-01-01

    Understanding why certain species can successfully colonize new areas while others do not is a central question in ecology. The nine-banded armadillo (Dasypus novemcinctus) is a conspicuous example of a successful invader, having colonized much of the southern United States in the last 200 years. We used 15 years (1992–2006) of capture-mark-recapture data from a population of armadillos in northern Florida in order to estimate, and examine relationships among, various demographic parameters that may have contributed to this ongoing range expansion. Modeling across a range of values for ?, the probability of juveniles surviving in the population until first capture, we found that population growth rates varied from 0.80 for ??=?0.1, to 1.03 for ??=?1.0. Growth rates approached 1.0 only when ? ?0.80, a situation that might not occur commonly because of the high rate of disappearance of juveniles. Net reproductive rate increased linearly with ?, but life expectancy (estimated at 3 years) was independent of ?. We also found that growth rates were lower during a 3-year period of hardwood removal that removed preferred habitat than in the years preceding or following. Life-table response experiment (LTRE) analysis indicated the decrease in growth rate during logging was primarily due to changes in survival rates of adults. Likewise, elasticity analyses of both deterministic and stochastic population growth rates revealed that survival parameters were more influential on population growth than were those related to reproduction. Collectively, our results are consistent with recent theories regarding biological invasions which posit that populations no longer at the leading edge of range expansion do not exhibit strong positive growth rates, and that high reproductive output is less critical in predicting the likelihood of successful invasion than are life-history strategies that emphasize allocation of resources to future, as opposed to current, reproduction. PMID:23844183

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

    PubMed Central

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

    2008-01-01

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

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

    PubMed

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

    2008-11-01

    The perfect-plasticity approximation (PPA) is an analytically tractable model of forest dynamics, defined in terms of parameters for individual trees, including allometry, growth, and mortality. We estimated these parameters for the eight most common species on each of four soil types in the US Lake states (Michigan, Wisconsin, and Minnesota) by using short-term (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). PMID:18971335

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

    PubMed Central

    Liao, David; Tlsty, Thea D.

    2014-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Host-plant quality influences insect population dynamics and the timing and extent of insect dispersal. An understanding of how these factors influence Homalodisca vitripennis, the glassy-winged sharpshooters’ development and movement is needed to better predict the spread of Pierce’s Disease (PD) ...

  10. Predictive markers in calpastatin for tenderness in commercial pig populations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The identification of predictive DNA markers for pork quality would allow U.S. pork producers and breeders to more quickly and efficiently select genetically superior animals for production of consistent, high quality meat. Genome scans have identified QTL for tenderness on pig chromosome 2 which ha...

  11. 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.

  12. Dynamic connectivity at rest predicts attention task performance.

    PubMed

    Madhyastha, Tara M; Askren, Mary K; Boord, Peter; Grabowski, Thomas J

    2015-02-01

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

  13. 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.

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

    PubMed

    Nedorezov, L V

    2015-01-01

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

  15. 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

  16. Rhythmic manipulation of objects with complex dynamics: predictability over chaos.

    PubMed

    Nasseroleslami, Bahman; Hasson, Christopher J; Sternad, Dagmar

    2014-10-01

    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

  17. Predicting individual brain maturity using dynamic functional connectivity

    PubMed Central

    Qin, Jian; Chen, Shan-Guang; Hu, Dewen; Zeng, Ling-Li; Fan, Yi-Ming; Chen, Xiao-Ping; Shen, Hui

    2015-01-01

    Neuroimaging-based functional connectivity (FC) analyses have revealed significant developmental trends in specific intrinsic connectivity networks linked to cognitive and behavioral maturation. However, knowledge of how brain functional maturation is associated with FC dynamics at rest is limited. Here, we examined age-related differences in the temporal variability of FC dynamics with data publicly released by the Nathan Kline Institute (NKI; n = 183, ages 7–30) and showed that dynamic inter-region interactions can be used to accurately predict individual brain maturity across development. Furthermore, we identified a significant age-dependent trend underlying dynamic inter-network FC, including increasing variability of the connections between the visual network, default mode network (DMN) and cerebellum as well as within the cerebellum and DMN and decreasing variability within the cerebellum and between the cerebellum and DMN as well as the cingulo-opercular network. Overall, the results suggested significant developmental changes in dynamic inter-network interaction, which may shed new light on the functional organization of typical developmental brains. PMID:26236224

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

    PubMed

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

    2010-01-01

    Like human immunodeficiency virus type 1 (HIV-1), simian immunodeficiency virus of chimpanzees (SIVcpz) can cause CD4+ T cell loss and premature death. Here, we used molecular surveillance tools and mathematical modeling to estimate the impact of SIVcpz infection on chimpanzee population dynamics. Habituated (Mitumba and Kasekela) and non-habituated (Kalande) chimpanzees were studied in Gombe National Park, Tanzania. Ape population sizes were determined from demographic records (Mitumba and Kasekela) or individual sightings and genotyping (Kalande), while SIVcpz prevalence rates were monitored using non-invasive methods. Between 2002-2009, the Mitumba and Kasekela communities experienced mean annual growth rates of 1.9% and 2.4%, respectively, while Kalande chimpanzees suffered a significant decline, with a mean growth rate of -6.5% to -7.4%, depending on population estimates. A rapid decline in Kalande was first noted in the 1990s and originally attributed to poaching and reduced food sources. However, between 2002-2009, we found a mean SIVcpz prevalence in Kalande of 46.1%, which was almost four times higher than the prevalence in Mitumba (12.7%) and Kasekela (12.1%). To explore whether SIVcpz contributed to the Kalande decline, we used empirically determined SIVcpz transmission probabilities as well as chimpanzee mortality, mating and migration data to model the effect of viral pathogenicity on chimpanzee population growth. Deterministic calculations indicated that a prevalence of greater than 3.4% would result in negative growth and eventual population extinction, even using conservative mortality estimates. However, stochastic models revealed that in representative populations, SIVcpz, and not its host species, frequently went extinct. High SIVcpz transmission probability and excess mortality reduced population persistence, while intercommunity migration often rescued infected communities, even when immigrating females had a chance of being SIVcpz infected. Together, these results suggest that the decline of the Kalande community was caused, at least in part, by high levels of SIVcpz infection. However, population extinction is not an inevitable consequence of SIVcpz infection, but depends on additional variables, such as migration, that promote survival. These findings are consistent with the uneven distribution of SIVcpz throughout central Africa and explain how chimpanzees in Gombe and elsewhere can be at equipoise with this pathogen. PMID:20886099

  19. Impact of Simian Immunodeficiency Virus Infection on Chimpanzee Population Dynamics

    PubMed Central

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

    2010-01-01

    Like human immunodeficiency virus type 1 (HIV-1), simian immunodeficiency virus of chimpanzees (SIVcpz) can cause CD4+ T cell loss and premature death. Here, we used molecular surveillance tools and mathematical modeling to estimate the impact of SIVcpz infection on chimpanzee population dynamics. Habituated (Mitumba and Kasekela) and non-habituated (Kalande) chimpanzees were studied in Gombe National Park, Tanzania. Ape population sizes were determined from demographic records (Mitumba and Kasekela) or individual sightings and genotyping (Kalande), while SIVcpz prevalence rates were monitored using non-invasive methods. Between 2002–2009, the Mitumba and Kasekela communities experienced mean annual growth rates of 1.9% and 2.4%, respectively, while Kalande chimpanzees suffered a significant decline, with a mean growth rate of ?6.5% to ?7.4%, depending on population estimates. A rapid decline in Kalande was first noted in the 1990s and originally attributed to poaching and reduced food sources. However, between 2002–2009, we found a mean SIVcpz prevalence in Kalande of 46.1%, which was almost four times higher than the prevalence in Mitumba (12.7%) and Kasekela (12.1%). To explore whether SIVcpz contributed to the Kalande decline, we used empirically determined SIVcpz transmission probabilities as well as chimpanzee mortality, mating and migration data to model the effect of viral pathogenicity on chimpanzee population growth. Deterministic calculations indicated that a prevalence of greater than 3.4% would result in negative growth and eventual population extinction, even using conservative mortality estimates. However, stochastic models revealed that in representative populations, SIVcpz, and not its host species, frequently went extinct. High SIVcpz transmission probability and excess mortality reduced population persistence, while intercommunity migration often rescued infected communities, even when immigrating females had a chance of being SIVcpz infected. Together, these results suggest that the decline of the Kalande community was caused, at least in part, by high levels of SIVcpz infection. However, population extinction is not an inevitable consequence of SIVcpz infection, but depends on additional variables, such as migration, that promote survival. These findings are consistent with the uneven distribution of SIVcpz throughout central Africa and explain how chimpanzees in Gombe and elsewhere can be at equipoise with this pathogen. PMID:20886099

  20. 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. PMID:20349837

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

    PubMed

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

    2015-11-01

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

  2. Effects of the infectious period distribution on predicted transitions in childhood disease dynamics

    PubMed Central

    Krylova, Olga; Earn, David J. D.

    2013-01-01

    The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced ‘susceptible–exposed–infectious–removed’ (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible–infectious–removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions. PMID:23676892

  3. Effects of the infectious period distribution on predicted transitions in childhood disease dynamics.

    PubMed

    Krylova, Olga; Earn, David J D

    2013-07-01

    The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced 'susceptible-exposed-infectious-removed' (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible-infectious-removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions. PMID:23676892

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

    PubMed

    Burski?, O V; Demidova, E Iu; Morkovin, A A

    2014-01-01

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

  5. Predicting dynamic signaling network response under unseen perturbations

    PubMed Central

    Zhu, Fan; Guan, Yuanfang

    2014-01-01

    Motivation: Predicting trajectories of signaling networks under complex perturbations is one of the most valuable, but challenging, tasks in systems biology. Signaling networks are involved in most of the biological pathways, and modeling their dynamics has wide applications including drug design and treatment outcome prediction. Results: In this paper, we report a novel model for predicting the cell type-specific time course response of signaling proteins under unseen perturbations. This algorithm achieved the top performance in the 2013 8th Dialogue for Reverse Engineering Assessments and Methods (DREAM 8) subchallenge: time course prediction in breast cancer cell lines. We formulate the trajectory prediction problem into a standard regularization problem; the solution becomes solving this discrete ill-posed problem. This algorithm includes three steps: denoising, estimating regression coefficients and modeling trajectories under unseen perturbations. We further validated the accuracy of this method against simulation and experimental data. Furthermore, this method reduces computational time by magnitudes compared to state-of-the-art methods, allowing genome-wide modeling of signaling pathways and time course trajectories to be carried out in a practical time. Availability and implementation: Source code is available at http://guanlab.ccmb.med.umich.edu/DREAM/code.html and as supplementary file online. Contact: gyuanfan@umich.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24919880

  6. 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

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

    PubMed Central

    KrkoĆĄek, 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

  8. Artificial nighttime light changes aphid-parasitoid population dynamics

    PubMed Central

    Sanders, Dirk; Kehoe, Rachel; Tiley, Katie; Bennie, Jonathan; Cruse, Dave; Davies, Thomas W.; Frank van Veen, F. J.; Gaston, Kevin J.

    2015-01-01

    Artificial light at night (ALAN) is recognized as a widespread and increasingly important anthropogenic environmental pressure on wild species and their interactions. Understanding of how these impacts translate into changes in population dynamics of communities with multiple trophic levels is, however, severely lacking. In an outdoor mesocosm experiment we tested the effect of ALAN on the population dynamics of a plant-aphid-parasitoid community with one plant species, three aphid species and their specialist parasitoids. The light treatment reduced the abundance of two aphid species by 20% over five generations, most likely as a consequence of bottom-up effects, with reductions in bean plant biomass being observed. For the aphid Megoura viciae this effect was reversed under autumn conditions with the light treatment promoting continuous reproduction through asexuals. All three parasitoid species were negatively affected by the light treatment, through reduced host numbers and we discuss induced possible behavioural changes. These results suggest that, in addition to direct impacts on species behaviour, the impacts of ALAN can cascade through food webs with potentially far reaching effects on the wider ecosystem. PMID:26472251

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

    PubMed

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

    2011-07-01

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

  10. Artificial nighttime light changes aphid-parasitoid population dynamics.

    PubMed

    Sanders, Dirk; Kehoe, Rachel; Tiley, Katie; Bennie, Jonathan; Cruse, Dave; Davies, Thomas W; Frank van Veen, F J; Gaston, Kevin J

    2015-01-01

    Artificial light at night (ALAN) is recognized as a widespread and increasingly important anthropogenic environmental pressure on wild species and their interactions. Understanding of how these impacts translate into changes in population dynamics of communities with multiple trophic levels is, however, severely lacking. In an outdoor mesocosm experiment we tested the effect of ALAN on the population dynamics of a plant-aphid-parasitoid community with one plant species, three aphid species and their specialist parasitoids. The light treatment reduced the abundance of two aphid species by 20% over five generations, most likely as a consequence of bottom-up effects, with reductions in bean plant biomass being observed. For the aphid Megoura viciae this effect was reversed under autumn conditions with the light treatment promoting continuous reproduction through asexuals. All three parasitoid species were negatively affected by the light treatment, through reduced host numbers and we discuss induced possible behavioural changes. These results suggest that, in addition to direct impacts on species behaviour, the impacts of ALAN can cascade through food webs with potentially far reaching effects on the wider ecosystem. PMID:26472251

  11. The Dynamics of Genetic Draft in Rapidly Adapting Populations

    PubMed Central

    Kosheleva, Katya; Desai, Michael M.

    2013-01-01

    The accumulation of beneficial mutations on competing genetic backgrounds in rapidly adapting populations has a striking impact on evolutionary dynamics. This effect, known as clonal interference, causes erratic fluctuations in the frequencies of observed mutations, randomizes the fixation times of successful mutations, and leaves distinct signatures on patterns of genetic variation. Here, we show how this form of “genetic draft” affects the forward-time dynamics of site frequencies in rapidly adapting asexual populations. We calculate the probability that mutations at individual sites shift in frequency over a characteristic timescale, extending Gillespie’s original model of draft to the case where many strongly selected beneficial mutations segregate simultaneously. We then derive the sojourn time of mutant alleles, the expected fixation time of successful mutants, and the site frequency spectrum of beneficial and neutral mutations. Finally, we show how this form of draft affects inferences in the McDonald–Kreitman test and how it relates to recent observations that some aspects of genetic diversity are described by the Bolthausen–Sznitman coalescent in the limit of very rapid adaptation. PMID:24002646

  12. Fast stochastic algorithm for simulating evolutionary population dynamics

    PubMed Central

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

    2012-01-01

    Motivation: Many important aspects of evolutionary dynamics can only be addressed through simulations. However, accurate simulations of realistically large populations over long periods of time needed for evolution to proceed are computationally expensive. Mutants can be present in very small numbers and yet (if they are more fit than others) be the key part of the evolutionary process. This leads to significant stochasticity that needs to be accounted for. Different evolutionary events occur at very different time scales: mutations are typically much rarer than reproduction and deaths. Results: We introduce a new exact algorithm for fast fully stochastic simulations of evolutionary dynamics that include birth, death and mutation events. It produces a significant speedup compared to direct stochastic simulations in a typical case when the population size is large and the mutation rates are much smaller than birth and death rates. The algorithm performance is illustrated by several examples that include evolution on a smooth and rugged fitness landscape. We also show how this algorithm can be adapted for approximate simulations of more complex evolutionary problems and illustrate it by simulations of a stochastic competitive growth model. Contact: ltsimring@ucsd.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22437850

  13. 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.

  14. 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 population size. Results suggest that understanding the population dynamics of a species over its range may be facilitated by taking the spatial structure of population size into account as well as by considering changes in population processes as a function of position within the range of the species. PMID:24738826

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

    PubMed

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

    2015-06-01

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

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

    PubMed Central

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

    2015-01-01

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

  17. Stochastic population dynamics in astrochemistry and aerosol science

    NASA Astrophysics Data System (ADS)

    Losert-Valiente Kroon, C. M.

    Classical, non-equilibrium systems of diffusing species or entities undergoing depletion, evaporation and reaction processes are at the heart of many problems in Physics, Chemistry, Biology and Financial Mathematics. It is well known that fluctuations and correlations in statistical systems can have a profound influence on the macroscopic properties of the system. However, the traditional rate equations that describe the evolution of mean populations in time and space do not incorporate statistical fluctuations. This becomes an issue of great importance when population densities are low. In order to develop a stochastic description of birth-and-death processes beyond the mean field approximation I employ techniques in classical many-body Physics in a manner analogous to the treatment of quantum systems. I obtain promising results to understand and quantify the exact circumstances of the failure of the mean-field approximation in specific problems in Astrophysics, namely heterogeneous chemical reactions in interstellar clouds, and in Aerosol Science, namely heterogeneous nucleation processes, and deliver the means to manipulate the alternative stochastic framework according to the Doi-Peliti formalism. In this framework the mean population of a species is given by the average of a solution to a set of constraint equations over all realisations of the stochastic noise. The constraint equations are inhomogeneous stochastic partial differential equations with multiplicative real or complex Gaussian noise. In general, these equations cannot be solved analytically. Therefore I resort to the numerical implementation of the Doi-Peliti formalism. The main code is written in the GNU C language, some algebraic calculations are performed by means of the MapleV package. In the case of large population densities the stochastic framework renders the same results as the mean field approximation whereas for low population densities its predictions differ substantially from the calculations using the traditional model.

  18. 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 of transitions to the smallest stage (mostly due to reproduction) and growth differed considerably from their long-term elasticities. It is important to be aware of this difference when using models to predict the effect of manipulating plant vital rates within the time frame of typical plant demographic studies. PMID:26236875

  19. 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

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

    PubMed

    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 Q (2) 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

  1. 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. PMID:9727339

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

    PubMed Central

    2011-01-01

    Background The oddball paradigm is widely applied to the investigation of cognitive function in neuroscience and in neuropsychiatry. Whether cortical oscillation in the resting state can predict the elicited oddball event-related potential (ERP) is still not clear. This study explored the relationship between resting electroencephalography (EEG) and oddball ERPs. The regional powers of 18 electrodes across delta, theta, alpha and beta frequencies were correlated with the amplitude and latency of N1, P2, N2 and P3 components of oddball ERPs. A multivariate analysis based on partial least squares (PLS) was applied to further examine the spatial pattern revealed by multiple correlations. Results Higher synchronization in the resting state, especially at the alpha spectrum, is associated with higher neural responsiveness and faster neural propagation, as indicated by the higher amplitude change of N1/N2 and shorter latency of P2. None of the resting quantitative EEG indices predict P3 latency and amplitude. The PLS analysis confirms that the resting cortical dynamics which explains N1/N2 amplitude and P2 latency does not show regional specificity, indicating a global property of the brain. Conclusions This study differs from previous approaches by relating dynamics in the resting state to neural responsiveness in the activation state. Our analyses suggest that the neural characteristics carried by resting brain dynamics modulate the earlier/automatic stage of target detection. PMID:22114868

  3. A simple model for simulating immunity rate dynamics in a tropical free-range poultry population after avian influenza vaccination.

    PubMed

    Lesnoff, M; Peyre, M; Duarte, P C; Renard, J-F; Mariner, J C

    2009-10-01

    In developing countries, vaccination against highly pathogenic avian influenza subtype H5N1 (HPAI) in free-range poultry flocks is usually implemented as periodic campaigns and newborn chicks are generally not vaccinated by farmers between vaccination passes. The demographic population turnover leads to a continuous decrease in the population immunity rate (PIR) over time. We present a simple Leslie matrix model for estimating population turnover and PIR dynamics in a hypothetical small-size vaccinated free-range poultry population. Four different vaccination scenarios were identified assuming necessary procedures to achieve immunity. The results indicate that high levels of population immunity are difficult to sustain. Assuming an animal immunity response of 80% after vaccination and a constant population size, PIR 4 months after vaccination was 30% in all the scenarios. Predictions averaged over time showed mean PIR between 36% and 48%, which is below the population immunity thresholds for eradication approximated from R0 estimates. PMID:19327199

  4. 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.

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

    PubMed

    Soukhovolsky, V G; Ponomarev, V I; Sokolov, G I; Tarasova, O V; Krasnoperova, P A

    2015-01-01

    The analysis is conducted on population dynamics of gypsy moth from different habitats of the South Urals. The pattern of cyclic changes in population density is examined, the assessment of temporal conjugation in time series of gypsy moth population dynamics from separate habitats of the South Urals is carried out, the relationships between population density and weather conditions are studied. Based on the results obtained, a statistical model of gypsy moth population dynamics in the South Urals is designed, and estimations are given of regulatory and modifying factors effects on the population dynamics. PMID:26201216

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  7. 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? PMID:11193619

  8. Predicting oscillatory dynamics in the movement of territorial animals

    PubMed Central

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

    2012-01-01

    Understanding ecological processes relies upon the knowledge of the dynamics of each individual component. In the context of animal population ecology, the way animals move and interact is of fundamental importance in explaining a variety of observed patterns. Here, we present a theoretical investigation on the movement dynamics of interacting scent-marking animals. We study how the movement statistics of territorial animals is responsible for the appearance of damped oscillations in the mean square displacement (MSD) of the animals. This non-monotonicity is shown to depend on one dimensionless parameter, given by the ratio of the correlation distance between successive steps to the size of the territory. As that parameter increases, the time dependence of the animal's MSD displays a transition from monotonic, characteristic of Brownian walks, to non-monotonic, characteristic of highly correlated walks. The results presented here represent a novel way of determining the degree of persistence in animal movement processes within confined regions. PMID:22262814

  9. Population dynamics of islet-infiltrating cells in autoimmune diabetes

    PubMed Central

    Magnuson, Angela M.; Thurber, Greg M.; Kohler, Rainer H.; Weissleder, Ralph; Mathis, Diane; Benoist, Christophe

    2015-01-01

    Type-1 diabetes in the nonobese diabetic (NOD) mouse starts with an insulitis stage, wherein a mixed population of leukocytes invades the pancreas, followed by overt diabetes once enough insulin-producing ?-cells are destroyed by invading immunocytes. Little is known of the dynamics of lymphocyte movement into the pancreas during disease progression. We used the Kaede transgenic mouse, whose photoconvertible fluorescent reporter permits noninvasive labeling and subsequent tracking of immunocytes, to investigate pancreatic infiltrate dynamics and the requirement for antigen specificity during progression of autoimmune diabetes in the unmanipulated NOD mouse. Our results indicate that the insulitic lesion is very open with constant cell influx and active turnover, predominantly of B and T lymphocytes, but also CD11b+c+ myeloid cells. Both naïve- and memory-phenotype lymphocytes trafficked to the insulitis, but Foxp3+ regulatory T cells circulated less than their conventional CD4+ counterparts. Receptor specificity for pancreatic antigens seemed irrelevant for this homing, because similar kinetics were observed in polyclonal and antigen-specific transgenic contexts. This “open” configuration was also observed after reversal of overt diabetes by anti-CD3 treatment. These results portray insulitis as a dynamic lesion at all stages of disease, continuously fed by a mixed influx of immunocytes, and thus susceptible to evolve over time in response to immunologic or environmental influences. PMID:25605891

  10. Phonon-induced population dynamics and intersystem crossing in nitrogen-vacancy centers.

    PubMed

    Goldman, M L; Sipahigil, A; Doherty, M W; Yao, N Y; Bennett, S D; Markham, M; Twitchen, D J; Manson, N B; Kubanek, A; Lukin, M D

    2015-04-10

    We report direct measurement of population dynamics in the excited state manifold of a nitrogen-vacancy (NV) center in diamond. We quantify the phonon-induced mixing rate and demonstrate that it can be completely suppressed at low temperatures. Further, we measure the intersystem crossing (ISC) rate for different excited states and develop a theoretical model that unifies the phonon-induced mixing and ISC mechanisms. We find that our model is in excellent agreement with experiment and that it can be used to predict unknown elements of the NV center's electronic structure. We discuss the model's implications for enhancing the NV center's performance as a room-temperature sensor. PMID:25910136

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

    NASA Astrophysics Data System (ADS)

    Goldman, M. L.; Sipahigil, A.; Doherty, M. W.; Yao, N. Y.; Bennett, S. D.; Markham, M.; Twitchen, D. J.; Manson, N. B.; Kubanek, A.; Lukin, M. D.

    2015-04-01

    We report direct measurement of population dynamics in the excited state manifold of a nitrogen-vacancy (NV) center in diamond. We quantify the phonon-induced mixing rate and demonstrate that it can be completely suppressed at low temperatures. Further, we measure the intersystem crossing (ISC) rate for different excited states and develop a theoretical model that unifies the phonon-induced mixing and ISC mechanisms. We find that our model is in excellent agreement with experiment and that it can be used to predict unknown elements of the NV center's electronic structure. We discuss the model's implications for enhancing the NV center's performance as a room-temperature sensor.

  12. A population-level model from the microscopic dynamics in Escherichia coli chemotaxis via Langevin approximation

    NASA Astrophysics Data System (ADS)

    He, Zhuo-Ran; Wu, Tai-Lin; Ouyang, Qi; Tu, Yu-Hai

    2012-09-01

    Recent extensive studies of Escherichia coli (E. coli) chemotaxis have achieved a deep understanding of its microscopic control dynamics. As a result, various quantitatively predictive models have been developed to describe the chemotactic behavior of E. coli motion. However, a population-level partial differential equation (PDE) that rationally incorporates such microscopic dynamics is still insufficient. Apart from the traditional Keller-Segel (K-S) equation, many existing population-level models developed from the microscopic dynamics are integro-PDEs. The difficulty comes mainly from cell tumbles which yield a velocity jumping process. Here, we propose a Langevin approximation method that avoids such a difficulty without appreciable loss of precision. The resulting model not only quantitatively reproduces the results of pathway-based single-cell simulators, but also provides new inside information on the mechanism of E. coli chemotaxis. Our study demonstrates a possible alternative in establishing a simple population-level model that allows for the complex microscopic mechanisms in bacterial chemotaxis.

  13. 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 (?) was most sensitive to changes in adult female survival. Further, the relatively high sensitivity of ? to duckling survival suggests that low duckling survival may be a bottleneck to productivity in some years. These data represent the first attempt to synthesize a population model for this species. Although our analyses were hampered by the small sample sizes inherent in studying a dispersed nesting species, our model provides a basis for management actions and can be enhanced as additional data become available.

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

    PubMed

    Chackiel, J

    1992-01-01

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

  15. Population dynamics of a diverse rodent assemblage in mixed grass-shrub habitat, southeastern Colorado, 1995-2000.

    PubMed

    Calisher, Charles H; Mills, James N; Sweeney, William P; Root, J Jeffrey; Reeder, Serena A; Jentes, Emily S; Wagoner, Kent; Beaty, Barry J

    2005-01-01

    We followed seasonal and year-to-year population dynamics for a diverse rodent assemblage in a short-grass prairie ecosystem in southeastern Colorado (USA) for 6 yr. We captured 2,798 individual rodents (range, one to 812 individuals per species) belonging to 19 species. The two most common species, deer mice (Peromyscus maniculatus) and western harvest mice (Reithrodontomys megalotis), generally had population peaks in winter and nadirs in summer; several other murid species demonstrated autumn peaks and spring nadirs; heteromyids were infrequently captured in winter, and populations generally peaked in summer or autumn. Inter-annual trends indicated an interactive effect between temperature and precipitation. Conditions associated with low rodent populations or population declines were high precipitation during cold periods (autumn and winter) and low precipitation during warm periods (spring and summer). Severity of adverse effects varied by species. Heteromyids, for example, were apparently not negatively affected by the hot, dry spring and summer of 2000. Cross-correlations for the temporal series of relative population abundances between species pairs (which are affected by both seasonal and interannual population dynamics) revealed positive associations among most murids and among most heteromyids, but there were negative associations between murids and heteromyids. These results have important implications for those attempting to model population dynamics of rodent populations for purposes of predicting disease risk. PMID:15827207

  16. 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.

  17. Cooperative Bacterial Growth Dynamics Predict the Evolution of Antibiotic Resistance

    NASA Astrophysics Data System (ADS)

    Artemova, Tatiana; Gerardin, Ylaine; Hsin-Jung Li, Sophia; Gore, Jeff

    2011-03-01

    Since the discovery of penicillin, antibiotics have been our primary weapon against bacterial infections. Unfortunately, bacteria can gain resistance to penicillin by acquiring the gene that encodes beta-lactamase, which inactivates the antibiotic. However, mutations in this gene are necessary to degrade the modern antibiotic cefotaxime. Understanding the conditions that favor the spread of these mutations is a challenge. Here we show that bacterial growth in beta-lactam antibiotics is cooperative and that the nature of this growth determines the conditions in which resistance evolves. Quantitative analysis of the growth dynamics predicts a peak in selection at very low antibiotic concentrations; competition between strains confirms this prediction. We also find significant selection at higher antibiotic concentrations, close to the minimum inhibitory concentrations of the strains. Our results argue that an understanding of the evolutionary forces that lead to antibiotic resistance requires a quantitative understanding of the evolution of cooperation in bacteria.

  18. IQ predicts word decoding skills in populations with intellectual disabilities.

    PubMed

    Levy, Yonata

    2011-01-01

    This is a study of word decoding in adolescents with Down syndrome and in adolescents with Intellectual Deficits of unknown etiology. It was designed as a replication of studies of word decoding in English speaking and in Hebrew speaking adolescents with Williams syndrome (Levy & Antebi, 2004; Levy, Smith, & Tager-Flusberg, 2003). Participants' IQ was matched to IQ in the groups with Williams syndrome and was within the range of mental retardation or borderline intelligence. Our aim was to investigate the impact of IQ on word decoding in these populations, rather than estimate their overall reading level. Similar to the results seen in people with Williams syndrome, word decoding was correlated with auditory short term memory and with phonological awareness tasks yet these correlations were mediated by IQ. It is argued that learning to decode is an explicit task that relies primarily on general cognitive resources of the kind that are most vulnerable in people with sub-normal IQ. PMID:21862282

  19. Hydroprene effects on the dynamics of laboratory populations of the German cockroach (Dictyoptera: Blattellidae).

    PubMed

    Reid, B L; Bennett, G W

    1994-12-01

    The influence of sterilization by hydroprene on population dynamics in the German cockroach, Blattella germanica (L.), was studied in the laboratory where more detailed and accurate assessments could be achieved than would be possible under typical field situations. The gradual accumulation of sterile adultoids (i.e., adults with twisted wings, indicating exposure to hydroprene) during treatment, or their decreasing abundance after treatment, produced distinctive patterns in the dynamics of treated populations. The percentage of gravid females (a reproductive index) was first to respond to treatments, because increases (or decreases) in the percentage of gravid females preceded reductions (or recoveries) in sample density and nymph-to-adult ratios by 4-6 wk. Trends in the percentage of adultoids were negatively correlated with the percentage of gravid females and indirectly measure the activity of hydroprene. Initial reductions in the percentage of gravid females, sample density, and nymph-to-adult ratios began at or about the time when approximately 80% of adults had twisted wings (i.e., were adultoids). As the percentage of adultoids attained (or declined below) the 80% level, we can accurately predict the subsequent decline (or recovery) in nymph-to-adult ratios and, thus, sample density. These data support a proposal to adopt the 80% level of adultoids as an action threshold for regulating juvenoid treatments to maximize population suppression. The role of this action threshold in the long-term management of chronic B. germanica infestations or insecticide resistant populations is discussed. PMID:7836613

  20. Optimal Dynamic Regimes: Presenting a Case for Predictive Inference

    PubMed Central

    Arjas, Elja; Saarela, Olli

    2010-01-01

    Dynamic treatment regime is a decision rule in which the choice of the treatment of an individual at any given time can depend on the known past history of that individual, including baseline covariates, earlier treatments, and their measured responses. In this paper we argue that finding an optimal regime can, at least in moderately simple cases, be accomplished by a straightforward application of nonparametric Bayesian modeling and predictive inference. As an illustration we consider an inference problem in a subset of the Multicenter AIDS Cohort Study (MACS) data set, studying the effect of AZT initiation on future CD4-cell counts during a 12-month follow-up. PMID:20648215

  1. Local predictability and information flow in complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Liang, X. San

    2013-04-01

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

  2. Transmembrane topology and signal peptide prediction using dynamic bayesian networks.

    PubMed

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

    2008-11-01

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

  3. BINOCS: The Dynamical Evolution of Binary Populations in Star Clusters

    NASA Astrophysics Data System (ADS)

    Frinchaboy, Peter M.; Thompson, Benjamin A.

    2016-01-01

    Studies of the internal dynamics of stellar clusters is conducted primarily through N-Body simulations. A key input into these simulations is the fraction and mass distribution of binary stars. The internal dynamics of stellar clusters is conducted primarily through N-Body simulations. A key input into these simulations is the fraction and mass distribution of binary stars. Currently the N-body input relations are taken from "field" binary stars studies, but to truly understand how clustered environments evolve, binary data from within star clusters is needed, including detailed mass information. The detailed information on binaries masses, primary and secondary, in star clusters has been limited to bright high mass stars that are reachable using decade-long radial velocity surveys. We introduce a new binary detection method, Binary INformation from Open Clusters Using SEDs (BINOCS) that covers the wide mass range needed to improve cluster N-body simulation inputs and comparisons. Using newly-observed multi-wavelength photometric catalogs (0.3 - 8 microns) of the key open clusters with a range of ages, we can show that the BINOCS method determines accurate binary component masses for unresolved cluster binaries through comparison to available RV-based studies. Using this method, we present results on the dynamical evolution of binaries from 0.4 - 2.5 solar masses within nine prototypical clusters, spaning 30 Myr to 7 Gyr, and show how the binary populations evolve, and discover significant variations in the "dynamical age" of a clusters as a function of the stellar mass range studied.

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

    PubMed

    Pokallus, John W; Pauli, Jonathan N

    2015-09-01

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

  6. Summer temperature can predict the distribution of wild yeast populations.

    PubMed

    Robinson, Heather A; Pinharanda, Ana; Bensasson, Douda

    2016-02-01

    The wine yeast, Saccharomyces cerevisiae, is the best understood microbial eukaryote at the molecular and cellular level, yet its natural geographic distribution is unknown. Here we report the results of a field survey for S. cerevisiae,S. paradoxus and other budding yeast on oak trees in Europe. We show that yeast species differ in their geographic distributions, and investigated which ecological variables can predict the isolation rate of S. paradoxus, the most abundant species. We find a positive association between trunk girth and S. paradoxus abundance suggesting that older trees harbor more yeast. S. paradoxus isolation frequency is also associated with summer temperature, showing highest isolation rates at intermediate temperatures. Using our statistical model, we estimated a range of summer temperatures at which we expect high S. paradoxus isolation rates, and show that the geographic distribution predicted by this optimum temperature range is consistent with the worldwide distribution of sites where S. paradoxus has been isolated. Using laboratory estimates of optimal growth temperatures for S. cerevisiae relative to S. paradoxus, we also estimated an optimum range of summer temperatures for S. cerevisiae. The geographic distribution of these optimum temperatures is consistent with the locations where wild S. cerevisiae have been reported, and can explain why only human-associated S. cerevisiae strains are isolated at northernmost latitudes. Our results provide a starting point for targeted isolation of S. cerevisiae from natural habitats, which could lead to a better understanding of climate associations and natural history in this important model microbe. PMID:26941949

  7. 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...

  8. 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...

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

    PubMed Central

    Lorenzen, Kai

    2005-01-01

    The population dynamics of fisheries stock enhancement, and its potential for generating benefits over and above those obtainable from optimal exploitation of wild stocks alone are poorly understood and highly controversial. I review pertinent knowledge of fish population biology, and extend the dynamic pool theory of fishing to stock enhancement by unpacking recruitment, incorporating regulation in the recruited stock, and accounting for biological differences between wild and hatchery fish. I then analyse the dynamics of stock enhancement and its potential role in fisheries management, using the candidate stock of North Sea sole as an example and considering economic as well as biological criteria. Enhancement through release of recruits or advanced juveniles is predicted to increase total yield and stock abundance, but reduce abundance of the naturally recruited stock component through compensatory responses or overfishing. Economic feasibility of enhancement is subject to strong constraints, including trade-offs between the costs of fishing and hatchery releases. Costs of hatchery fish strongly influence optimal policy, which may range from no enhancement at high cost to high levels of stocking and fishing effort at low cost. Release of genetically maladapted fish reduces the effectiveness of enhancement, and is most detrimental overall if fitness of hatchery fish is only moderately compromised. As a temporary measure for the rebuilding of depleted stocks, enhancement cannot substitute for effort limitation, and is advantageous as an auxiliary measure only if the population has been reduced to a very low proportion of its unexploited biomass. Quantitative analysis of population dynamics is central to the responsible use of stock enhancement in fisheries management, and the necessary tools are available. PMID:15713596

  10. 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 for irruptive dynamics and a new challenge for resource managers. The future demography of caribou on both islands is far from certain, yet sustained and significant hunting pressure should be a vital management tool.

  11. Urban aerosols harbor diverse and dynamic bacterial populations

    PubMed Central

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

    2007-01-01

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

  12. On signals of phase transitions in salmon population dynamics

    PubMed Central

    Krkošek, Martin; Drake, John M.

    2014-01-01

    Critical slowing down (CSD) reflects the decline in resilience of equilibria near a bifurcation and may reveal early warning signals (EWS) of ecological phase transitions. We studied CSD in the recruitment dynamics of 120 stocks of three Pacific salmon (Oncorhynchus spp.) species in relation to critical transitions in fishery models. Pink salmon (Oncorhynchus gorbuscha) exhibited increased variability and autocorrelation in populations that had a growth parameter, r, close to zero, consistent with EWS of extinction. However, models and data for sockeye salmon (Oncorhynchus nerka) indicate that portfolio effects from heterogeneity in age-at-maturity may obscure EWS. Chum salmon (Oncorhynchus keta) show intermediate results. The data do not reveal EWS of Ricker-type bifurcations that cause oscillations and chaos at high r. These results not only provide empirical support for CSD in some ecological systems, but also indicate that portfolio effects of age structure may conceal EWS of some critical transitions. PMID:24759855

  13. 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. PMID:26519794

  14. 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

  15. Modelling lipid competition dynamics in heterogeneous protocell populations.

    PubMed

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

    2014-01-01

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

  16. 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.

  17. Modelling Lipid Competition Dynamics in Heterogeneous Protocell Populations

    NASA Astrophysics Data System (ADS)

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

    2014-07-01

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

  18. A dynamic Bayesian network approach to protein secondary structure prediction

    PubMed Central

    Yao, Xin-Qiu; Zhu, Huaiqiu; She, Zhen-Su

    2008-01-01

    Background Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful information relevant to sequence-structure relationship. However, at present, the prediction accuracy of pure HMM-type methods is much lower than that of machine learning-based methods such as neural networks (NN) or support vector machines (SVM). Results In this paper, we report a new method of probabilistic nature for protein secondary structure prediction, based on dynamic Bayesian networks (DBN). The new method models the PSI-BLAST profile of a protein sequence using a multivariate Gaussian distribution, and simultaneously takes into account the dependency between the profile and secondary structure and the dependency between profiles of neighboring residues. In addition, a segment length distribution is introduced for each secondary structure state. Tests show that the DBN method has made a significant improvement in the accuracy compared to other pure HMM-type methods. Further improvement is achieved by combining the DBN with an NN, a method called DBNN, which shows better Q3 accuracy than many popular methods and is competitive to the current state-of-the-arts. The most interesting feature of DBN/DBNN is that a significant improvement in the prediction accuracy is achieved when combined with other methods by a simple consensus. Conclusion The DBN method using a Gaussian distribution for the PSI-BLAST profile and a high-ordered dependency between profiles of neighboring residues produces significantly better prediction accuracy than other HMM-type probabilistic methods. Owing to their different nature, the DBN and NN combine to form a more accurate method DBNN. Future improvement may be achieved by combining DBNN with a method of SVM type. PMID:18218144

  19. 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...

  20. 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 added to our toolbox to tease apart complex drivers of global change. PMID:24115317

  1. 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

  2. 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.

  3. Bayesian coalescent inference of past population dynamics from molecular sequences.

    PubMed

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

    2005-05-01

    We introduce the Bayesian skyline plot, a new method for estimating past population dynamics through time from a sample of molecular sequences without dependence on a prespecified parametric model of demographic history. We describe a Markov chain Monte Carlo sampling procedure that efficiently samples a variant of the generalized skyline plot, given sequence data, and combines these plots to generate a posterior distribution of effective population size through time. We apply the Bayesian skyline plot to simulated data sets and show that it correctly reconstructs demographic history under canonical scenarios. Finally, we compare the Bayesian skyline plot model to previous coalescent approaches by analyzing two real data sets (hepatitis C virus in Egypt and mitochondrial DNA of Beringian bison) that have been previously investigated using alternative coalescent methods. In the bison analysis, we detect a severe but previously unrecognized bottleneck, estimated to have occurred 10,000 radiocarbon years ago, which coincides with both the earliest undisputed record of large numbers of humans in Alaska and the megafaunal extinctions in North America at the beginning of the Holocene. PMID:15703244

  4. 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

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

    USGS Publications Warehouse

    Wildhaber, Mark L.; Wikle, Christopher K.; Anderson, Christopher J.; Franz, Kristie J.; Moran, Edward H.; Dey, Rima

    2012-01-01

    Climate change operates over a broad range of spatial and temporal scales. Understanding its effects on ecosystems requires multi-scale models. For understanding effects on fish populations of riverine ecosystems, climate predicted by coarse-resolution Global Climate Models must be downscaled to Regional Climate Models to watersheds to river hydrology to population response. An additional challenge is quantifying sources of uncertainty given the highly nonlinear nature of interactions between climate variables and community level processes. We present a modeling approach for understanding and accomodating uncertainty by applying multi-scale climate models and a hierarchical Bayesian modeling framework to Midwest fish population dynamics and by linking models for system components together by formal rules of probability. The proposed hierarchical modeling approach will account for sources of uncertainty in forecasts of community or population response. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. This understanding will aid evaluation of management options for coping with global climate change. In our initial analyses, we found that predicted pallid sturgeon population responses were dependent on the climate scenario considered.

  6. 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 essential to model and resolve the details of physical behaviour of populations in ultrafast spectroscopy such as pump-probe, pump-dump-probe and pump-repump-probe experiments. PMID:21445294

  7. 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

    2015-01-01

    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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  10. 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 waves that vertically propagate upward through the stratosphere will be addressed further in the presentation.

  11. Simulation analysis of the population dynamics of the mite, Psoroptes ovis, infesting sheep.

    PubMed

    Wall, R; Smith, K E; Berriatua, E; French, N P

    1999-06-30

    The pattern of population growth of the ectoparasitic mite, Psoroptes ovis (Acari: Psoroptidae), on its ovine host is considered through the development of a Leslie matrix-based, simulation model. The model is parameterised using experimental data in conjunction with reanalysis of published data. The model shows that on sheep P. ovis populations grow at a rate of approximately 11% per day and the population doubles every 6.3 days. Additional rates of adult mortality, in excess of 50% per day, need to be imposed to prevent population growth. The predictions of the model are tested by comparison of the expected numbers of mites with the numbers recorded in lesions either on naturally infested sheep where the date of infestation can be estimated or on one artificially infested animal, where the initial number of mites and date of infestation are known precisely. In both cases the observed number of mites in lesions relate closely to the numbers expected from the simulations. The model simulations do not support the concept of a 'lag' phase as distinct from the 'growth' phase in the changing pattern of mite abundance on an infested sheep and suggests that the observed pattern of growth is a natural function of an exponential increase in numbers. The development of such models and their use in explaining the demographic processes which drive mite population dynamics are discussed. PMID:10423007

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

    PubMed Central

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

    2012-01-01

    A series of experiments were performed to examine the population dynamics of the sugarbeet cyst nematode, Heterodera schachtii, and the nematophagus fungus Dactylella oviparasitica. After two nematode generations, the population densities of H. schachtii were measured in relation to various initial infestation densities of both D. oviparasitica and H. schachtii. In general, higher initial population densities of D. oviparasitica were associated with lower final population densities of H. schachtii. Regression models showed that the initial densities of D. oviparasitica were only significant when predicting the final densities of H. schachtii J2 and eggs as well as fungal egg parasitism, while the initial densities of J2 were significant for all final H. schachtii population density measurements. We also showed that the densities of H. schachtii-associated D. oviparasitica fluctuate greatly, with rRNA gene numbers going from zero in most field-soil-collected cysts to an average of 4.24 x 108 in mature females isolated directly from root surfaces. Finally, phylogenetic analysis of rRNA genes suggested that D. oviparasitica belongs to a clade of nematophagous fungi that includes Arkansas Fungus strain L (ARF-L) and that these fungi are widely distributed. We anticipate that these findings will provide foundational data facilitating the development of more effective decision models for sugar beet planting. PMID:23481664

  13. Adaptive Sex Determination and Population Dynamics in a Brackish-water Amphipod

    NASA Astrophysics Data System (ADS)

    Watt, Penelope J.; Adams, Jonathan

    1993-09-01

    Gammarus duebeni is a sexually dimorphic amphipod with an unusual and environmentally mediated sex determining system. In seasonal populations, environmental sex determination (ESD) is selectively advantageous and males and females are produced at different times of the year, but it has been predicted that where generations overlap or the breeding season is long, ESD should no longer have a selective advantage over genetic mechanisms of sex determination and males and females should be produced simultaneously. The dynamics of a supposedly bivoltine population at Totton Marsh on the south coast of England were investigated. The field study showed that the breeding season at Totton was not in fact bivoltine but long, extending through most of the year with a short break in early summer. Population sex ratio fluctuated seasonally: this pattern appears to be the product of differences in production of males and females rather than growth or mortality. Thus, contrary to expectations, ESD does occur in this population. Photoperiod is the cue for sex determination in the laboratory, but in the field this alone could not account for the observed pattern of male and female production at Totton Marsh. Another major variable must be involved and it is proposed that it also has an influence on other G. duebeni populations.

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

    PubMed

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

    2012-09-01

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

  15. Forest Ecosystem Dynamics Assessment and Predictive Modelling in Eastern Himalaya

    NASA Astrophysics Data System (ADS)

    Kushwaha, S. P. S.; Nandy, S.; Ahmad, M.; Agarwal, R.

    2011-09-01

    This study focused on the forest ecosystem dynamics assessment and predictive modelling deforestation and forest cover prediction in a part of north-eastern India i.e. forest areas along West Bengal, Bhutan, Arunachal Pradesh and Assam border in Eastern Himalaya using temporal satellite imagery of 1975, 1990 and 2009 and predicted forest cover for the period 2028 using Cellular Automata Markov Modedel (CAMM). The exercise highlighted large-scale deforestation in the study area during 1975-1990 as well as 1990-2009 forest cover vectors. A net loss of 2,334.28 km2 forest cover was noticed between 1975 and 2009, and with current rate of deforestation, a forest area of 4,563.34 km2 will be lost by 2028. The annual rate of deforestation worked out to be 0.35 and 0.78% during 1975-1990 and 1990-2009 respectively. Bamboo forest increased by 24.98% between 1975 and 2009 due to opening up of the forests. Forests in Kokrajhar, Barpeta, Darrang, Sonitpur, and Dhemaji districts in Assam were noticed to be worst-affected while Lower Subansiri, West and East Siang, Dibang Valley, Lohit and Changlang in Arunachal Pradesh were severely affected. Among different forest types, the maximum loss was seen in case of sal forest (37.97%) between 1975 and 2009 and is expected to deplete further to 60.39% by 2028. The tropical moist deciduous forest was the next category, which decreased from 5,208.11 km2 to 3,447.28 (33.81%) during same period with further chances of depletion to 2,288.81 km2 (56.05%) by 2028. It noted progressive loss of forests in the study area between 1975 and 2009 through 1990 and predicted that, unless checked, the area is in for further depletion of the invaluable climax forests in the region, especially sal and moist deciduous forests. The exercise demonstrated high potential of remote sensing and geographic information system for forest ecosystem dynamics assessment and the efficacy of CAMM to predict the forest cover change.

  16. Dynamical evolution and spatial mixing of multiple population globular clusters

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  17. 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 expected worldwide, demographic collapse of many other coral populations may soon be widespread. PMID:26119322

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

    PubMed

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

    2014-02-01

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

  19. 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.

  20. 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

    2011-12-01

    Environmental change has been observed to generate simultaneous responses in population dynamics, life history, gene frequencies, and morphology in a number of species. But how common are such eco-evolutionary responses to environmental change likely to be? Are they inevitable, or do they require a specific type of change? Can we accurately predict eco-evolutionary responses? We address these questions using theory and data from the study of Yellowstone wolves. We show that environmental change is expected to generate eco-evolutionary change, that changes in the average environment will affect wolves to a greater extent than changes in how variable it is, and that accurate prediction of the consequences of environmental change will probably prove elusive. PMID:22144626

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

    PubMed Central

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

    2013-01-01

    It is well known that ecological processes such as population regulation and natural enemy interactions potentially occur over a range of spatial scales, and there is a substantial body of literature developing theoretical understanding of the interplay between these processes. However, there are comparatively few studies quantifying the long-term effects of spatial scaling in natural ecosystems. A key challenge is that trophic complexity in real-world biological communities quickly obscures the signal from a focal process. Seagrass meadows provide an excellent opportunity in this respect: in many instances, seagrasses effectively form extensive natural monocultures, in which hypotheses about endogenous dynamics can be formulated and tested. We present amongst the longest unbroken, spatially explict time series of seagrass abundance published to date. Data include annual measures of shoot density, total above-ground abundance, and associated epiphyte cover from five Zostera marina meadows distributed around the Isles of Scilly, UK, from 1996 to 2011. We explore empirical patterns at the local and metapopulation scale using standard time series analysis and develop a simple population dynamic model, testing the hypothesis that both local and metapopulation scale feedback processes are important. We find little evidence of an interaction between scales in seagrass dynamics but that both scales contribute approximately equally to observed local epiphyte abundance. By quantifying the long-term dynamics of seagrass-epiphyte interactions we show how measures of density and extent are both important in establishing baseline information relevant to predicting responses to environmental change and developing management plans. We hope that this study complements existing mechanistic studies of physiology, genetics and productivity in seagrass, whilst highlighting the potential of seagrass as a model ecosystem. More generally, this study provides a rare opportunity to test some of the predictions of ecological theory in a natural ecosystem of global conservation and economic value. PMID:23437313

  2. An Equation to Predict the Accuracy of Genomic Values by Combining Data from Multiple Traits, Populations, or Environments.

    PubMed

    Wientjes, Yvonne C J; Bijma, Piter; Veerkamp, Roel F; Calus, Mario P L

    2016-02-01

    Predicting the accuracy of estimated genomic values using genome-wide marker information is an important step in designing training populations. Currently, different deterministic equations are available to predict accuracy within populations, but not for multipopulation scenarios where data from multiple breeds, lines or environments are combined. Therefore, our objective was to develop and validate a deterministic equation to predict the accuracy of genomic values when different populations are combined in one training population. The input parameters of the derived prediction equation are the number of individuals and the heritability from each of the populations in the training population; the genetic correlations between the populations, i.e., the correlation between allele substitution effects of quantitative trait loci; the effective number of chromosome segments across predicted and training populations; and the proportion of the genetic variance in the predicted population captured by the markers in each of the training populations. Validation was performed based on real genotype information of 1033 Holstein-Friesian cows that were divided into three different populations by combining half-sib families in the same population. Phenotypes were simulated for multiple scenarios, differing in heritability within populations and in genetic correlations between the populations. Results showed that the derived equation can accurately predict the accuracy of estimating genomic values for different scenarios of multipopulation genomic prediction. Therefore, the derived equation can be used to investigate the potential accuracy of different multipopulation genomic prediction scenarios and to decide on the most optimal design of training populations. PMID:26637542

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

    NASA Astrophysics Data System (ADS)

    Knezevic, Zoran; Milani, Andrea

    2005-05-01

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

  4. Predicting the Size of the Progeny Mapping Population Required to Positionally Clone a Gene

    PubMed Central

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

    2007-01-01

    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 ?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. PMID:17565938

  5. 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. PMID:17565938

  6. 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.

  7. Evaluating physiological dynamics via synchrosqueezing: prediction of ventilator weaning.

    PubMed

    Wu, Hau-Tieng; Hseu, Shu-Shua; Bien, Mauo-Ying; Kou, Yu Ru; Daubechies, Ingrid

    2014-03-01

    Oscillatory phenomena abound in many types of signals. Identifying the individual oscillatory components that constitute an observed biological signal leads to profound understanding about the biological system. The instantaneous frequency (IF), the amplitude modulation (AM), and their temporal variability are widely used to describe these oscillatory phenomena. In addition, the shape of the oscillatory pattern, repeated in time for an oscillatory component, is also an important characteristic that can be parametrized appropriately. These parameters can be viewed as phenomenological surrogates for the hidden dynamics of the biological system. To estimate jointly the IF, AM, and shape, this paper applies a novel and robust time-frequency analysis tool, referred to as the synchrosqueezing transform (SST). The usefulness of the model and SST are shown directly in predicting the clinical outcome of ventilator weaning. Compared with traditional respiration parameters, the breath-to-breath variability has been reported to be a better predictor of the outcome of the weaning procedure. So far, however, all these indices normally require at least 20 min of data acquisition to ensure predictive power. Moreover, the robustness of these indices to the inevitable noise is rarely discussed. We find that based on the proposed model, SST and only 3 min of respiration data, the ROC area under curve of the prediction accuracy is 0.76. The high predictive power that is achieved in the weaning problem, despite a shorter evaluation period, and the stability to noise suggest that other similar kinds of signal may likewise benefit from the proposed model and SST. PMID:24235294

  8. Statistical predictability in the atmosphere and other dynamical systems

    NASA Astrophysics Data System (ADS)

    Kleeman, Richard

    2007-06-01

    Ensemble predictions are an integral part of routine weather and climate prediction because of the sensitivity of such projections to the specification of the initial state. In many discussions it is tacitly assumed that ensembles are equivalent to probability distribution functions (p.d.f.s) of the random variables of interest. In general for vector valued random variables this is not the case (not even approximately) since practical ensembles do not adequately sample the high dimensional state spaces of dynamical systems of practical relevance. In this contribution we place these ideas on a rigorous footing using concepts derived from Bayesian analysis and information theory. In particular we show that ensembles must imply a coarse graining of state space and that this coarse graining implies loss of information relative to the converged p.d.f. To cope with the needed coarse graining in the context of practical applications, we introduce a hierarchy of entropic functionals. These measure the information content of multivariate marginal distributions of increasing order. For fully converged distributions (i.e. p.d.f.s) these functionals form a strictly ordered hierarchy. As one proceeds up the hierarchy with ensembles instead however, increasingly coarser partitions are required by the functionals which implies that the strict ordering of the p.d.f. based functionals breaks down. This breakdown is symptomatic of the necessarily limited sampling by practical ensembles of high dimensional state spaces and is unavoidable for most practical applications. In the second part of the paper the theoretical machinery developed above is applied to the practical problem of mid-latitude weather prediction. We show that the functionals derived in the first part all decline essentially linearly with time and there appears in fact to be a fairly well defined cut off time (roughly 45 days for the model analyzed) beyond which initial condition information is unimportant to statistical prediction.

  9. 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.

  10. 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, D.M.; Leslie, David M., Jr.

    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.

  11. An approach to predict risks to wildlife populations from mercury and other stressors.

    PubMed

    Nacci, Diane; Pelletier, Marguerite; Lake, Jim; Bennett, Rick; Nichols, John; Haebler, Romona; Grear, Jason; Kuhn, Anne; Copeland, Jane; Nicholson, Matthew; Walters, Steven; Munns, Wayne R

    2005-03-01

    Ecological risk assessments for mercury (Hg) require measured and modeled information on exposure and effects. While most of this special issue focuses on the former, i.e., distribution and fate of Hg within aquatic food webs, this paper describes an approach to predict the effects of dietary methylmercury (CH3Hg) on populations of piscivorous birds. To demonstrate this approach, the U.S. Environmental Protection Agency's National Health and Environmental Effects Research Laboratory (U.S. EPA NHEERL) is working cooperatively with environmental and conservation organizations to develop models to predict CH3Hg effects on populations of the common loon, Gavia immer. Specifically, a biologically-based toxicokinetic model is being used to extrapolate CH3Hg effects on the reproduction of a tested bird species, the American kestrel (Falco sparverius), to the loon. Population models are being used to incorporate stressor effects on survival and reproduction into projections of loon population effects. Finally, habitat and spatially-explicit population models are being used to project results spatially, assess the relative importance of CH3Hg and non-chemical stressors, and produce testable predictions of the effects of biologically-available Hg on loon populations. This stepwise process provides an integrated approach to estimate the impact on wildlife populations of regulations that limit atmospherically-distributed Hg, and to develop risk-based population-level regulatory criteria. PMID:15931973

  12. Predicting large area surface reconstructions using molecular dynamics methods

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  14. Parsimonious description for predicting high-dimensional dynamics

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Nicolle, J.; Cupillard, S.

    2015-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Miller, Christopher J.

    2011-01-01

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

  17. Parsimonious description for predicting high-dimensional dynamics

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

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

    PubMed

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

    2012-06-01

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

  19. 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...

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

    PubMed

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

    2016-01-01

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

  1. 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

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

    PubMed

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

    2014-05-01

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

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

    PubMed

    Aussem, A; Murtagh, F; Sarazin, M

    1995-06-01

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

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

    PubMed

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

    2013-12-15

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

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

    PubMed

    Eduati, Federica; Mangravite, Lara M; Wang, Tao; Tang, Hao; Bare, J Christopher; Huang, Ruili; Norman, Thea; Kellen, Mike; Menden, Michael P; Yang, Jichen; Zhan, Xiaowei; Zhong, Rui; Xiao, Guanghua; Xia, Menghang; Abdo, Nour; Kosyk, Oksana; Friend, Stephen; Dearry, Allen; Simeonov, Anton; Tice, Raymond R; Rusyn, Ivan; Wright, Fred A; Stolovitzky, Gustavo; Xie, Yang; Saez-Rodriguez, Julio

    2015-09-01

    The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson's r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal. PMID:26258538

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

    PubMed Central

    Eduati, Federica; Mangravite, Lara M.; Wang, Tao; Tang, Hao; Bare, J. Christopher; Huang, Ruili; Norman, Thea; Kellen, Mike; Menden, Michael P.; Yang, Jichen; Zhan, Xiaowei; Zhong, Rui; Xiao, Guanghua; Xia, Menghang; Abdo, Nour; Kosyk, Oksana; Friend, Stephen; Dearry, Allen; Simeonov, Anton; Tice, Raymond; Rusyn, Ivan; Wright, Fred A.; Stolovitzky, Gustavo; Xie, Yang; Saez-Rodriguez, Julio

    2015-01-01

    The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000-Genomes Project. The challenge participants developed algorithms to predict inter-individual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against a blinded experimental dataset. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson’s r<0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r<0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal. PMID:26258538

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

    PubMed Central

    ?erná, Lucie; Münzbergová, Zuzana

    2013-01-01

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

  8. Predicting intentions and behaviours in populations with or at-risk of diabetes: A systematic review

    PubMed Central

    Akbar, Heena; Anderson, Debra; Gallegos, Danielle

    2015-01-01

    Purpose To systematically review the Theory of Planned Behaviour studies predicting self-care intentions and behaviours in populations with and at-risk of diabetes. Methods A systematic review using six electronic databases was conducted in 2013. A standardised protocol was used for appraisal. Studies eligibility included a measure of behaviour for healthy eating, physical activity, glucose monitoring, medication use (ii) the TPB variables (iii) the TPB tested in populations with diabetes or at-risk. Results Sixteen studies were appraised for testing the utility of the TPB. Studies included cross-sectional (n = 7); prospective (n = 5) and randomised control trials (n = 4). Intention (18%–76%) was the most predictive construct for all behaviours. Explained variance for intentions was similar across cross-sectional (28–76%); prospective (28–73%); and RCT studies (18–63%). RCTs (18–43%) provided slightly stronger evidence for predicting behaviour. Conclusions Few studies tested predictability of the TPB in populations with or at-risk of diabetes. This review highlighted differences in the predictive utility of the TPB suggesting that the model is behaviour and population specific. Findings on key determinants of specific behaviours contribute to a better understanding of mechanisms of behaviour change and are useful in designing targeted behavioural interventions for different diabetes populations. PMID:26844083

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-07-01

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

  11. Can foot anthropometric measurements predict dynamic plantar surface contact area?

    PubMed Central

    2009-01-01

    Background Previous studies have suggested that increased plantar surface area, associated with pes planus, is a risk factor for the development of lower extremity overuse injuries. The intent of this study was to determine if a single or combination of foot anthropometric measures could be used to predict plantar surface area. Methods Six foot measurements were collected on 155 subjects (97 females, 58 males, mean age 24.5 ± 3.5 years). The measurements as well as one ratio were entered into a stepwise regression analysis to determine the optimal set of measurements associated with total plantar contact area either including or excluding the toe region. The predicted values were used to calculate plantar surface area and were compared to the actual values obtained dynamically using a pressure sensor platform. Results A three variable model was found to describe the relationship between the foot measures/ratio and total plantar contact area (R2 = 0.77, p < 0.0001)). A three variable model was also found to describe the relationship between the foot measures/ratio and plantar contact area minus the toe region (R2 = 0.76, p < 0.0001). Conclusion The results of this study indicate that the clinician can use a combination of simple, reliable, and time efficient foot anthropometric measurements to explain over 75% of the plantar surface contact area, either including or excluding the toe region. PMID:19863799

  12. Long-range prediction of epileptic seizures with nonlinear dynamics.

    PubMed

    Guastello, Stephen J; Boeh, Henry; Lynn, Mark

    2011-07-01

    Patients with uncontrolled epilepsy have some significant problems with planning life routines, and thus one goal of the present study was to explore the viability of predicting seizures in time intervals of one week. The second goal was to utilize the principle of dynamic diseases and to assess the viability of a cusp catastrophe model for seizure onset that was proposed by Cerf (2006). A seizure history of 124 weeks from one adult male patient fit both the cusp and fold catastrophe models (R2 = .92 and .88 respectively) reasonably well using the pdf method and more accurately than counterpart linear models. Prediction of future states was possible, but somewhat compromised because of the nonstationary nature of the data and uncertainties regarding the control variables in the catastrophe models. Analyses of lag functions, however, revealed some surprising elements, suggesting that the precursory conditions for a seizure could be building up over a period of several weeks and that a self-correcting effect within the nervous system could have been occurring. PMID:21645436

  13. The dynamics of nestedness predicts the evolution of industrial ecosystems.

    PubMed

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

    2012-01-01

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

  14. Modelling the impact of marine reserves on a population with depensatory dynamics.

    PubMed

    Chan, Matthew H; Kim, Peter S

    2014-09-01

    In this study, we use a spatially implicit, stage-structured model to evaluate marine reserve effectiveness for a fish population exhibiting depensatory (strong Allee) effects in its dynamics. We examine the stability and sensitivity of the equilibria of the modelled system with regards to key system parameters and find that for a reasonable set of parameters, populations can be protected from a collapse if a small percentage of the total area is set aside in reserves. Furthermore, the overall abundance of the population is predicted to achieve a maximum at a certain ratio A of reserve area to fished area, which depends heavily on the other system parameters such as the net export rate of fish from the marine reserves to the fished areas. This finding runs contrary to the contested "equivalence at best" result when comparing fishery management through traditional catch or effort control and management through marine reserves. Lastly, we analyse the problem from a bioeconomics perspective by computing the optimal harvesting policy using Pontryagin's Maximum Principle, which suggests that the value for A which maximizes the optimal equilibrium fishery yield also maximizes population abundance when the cost per unit harvest is constant, but can increase substantially when the cost per unit harvest increases with the area being harvested. PMID:25124763

  15. Intertidal population genetic dynamics at a microgeographic seascape scale.

    PubMed

    Hu, Zi-Min

    2013-06-01

    The intertidal community is among the most physically harsh niches on earth, with highly heterogeneous environmental and biological factors that impose strong habitat selection on population abundance, genetic connectivity and ecological adaptation of organisms in nature. However, most genetic studies to date have concentrated on the influence of basin-wide or regional marine environments (e.g. habitat discontinuities, oceanic currents and fronts, and geographic barriers) on spatiotemporal distribution and composition of intertidal invertebrates having planktonic stages or long-distance dispersal capability. Little is known about sessile marine organisms (e.g. seaweeds) in the context of topographic tidal gradients and reproductive traits at the microgeographic scale. In this issue of Molecular Ecology, Krueger-Hadfield et al. () implemented an elaborate sampling strategy with red seaweed (Chondrus crispus) from a 90-m transect stand near Roscoff and comprehensively detected genome-scale genetic differentiation and biases in ploidy level. This study not only revealed that tidal height resulted in genetic differentiation between high- and low-shore stands and restricted the genetic exchange within the high-shore habitat, but also demonstrated that intergametophytic nonrandom fertilization in C. crispus can cause significant deviation from Hardy-Weinberg equilibrium. Such new genetic insights highlight the importance of microgeographic genetic dynamics and life history characteristics for better understanding the evolutionary processes of speciation and diversification of intertidal marine organisms. PMID:24433569

  16. Fluctuation Relations of Fitness and Information in Population Dynamics

    NASA Astrophysics Data System (ADS)

    Kobayashi, Tetsuya J.; Sughiyama, Yuki

    2015-12-01

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

  17. Catalysis of Protein Folding by Chaperones Accelerates Evolutionary Dynamics in Adapting Cell Populations

    PubMed Central

    Çetinba?, Murat; Shakhnovich, Eugene I.

    2013-01-01

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