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1

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

PubMed Central

Background Culex pipiens/restuans mosquitoes are important vectors for a variety of arthropod borne viral infections. In this study, the associations between 20 years of mosquito capture data and the time lagged environmental quantities daytime length, temperature, precipitation, relative humidity and wind speed were used to generate a predictive model for the population dynamics of this vector species. Methods Mosquito population in the study area was represented by averaged time series of mosquitos counts captured at 6 sites in Cook County (Illinois, USA). Cross-correlation maps (CCMs) were compiled to investigate the association between mosquito abundances and environmental quantities. The results obtained from the CCMs were incorporated into a Poisson regression to generate a predictive model. To optimize the predictive model the time lags obtained from the CCMs were adjusted using a genetic algorithm. Results CCMs for weekly data showed a highly positive correlation of mosquito abundances with daytime length 4 to 5 weeks prior to capture (quantified by a Spearman rank order correlation of rS?=?0.898) and with temperature during 2 weeks prior to capture (rS?=?0.870). Maximal negative correlations were found for wind speed averaged over 3 week prior to capture (rS?=??0.621). Cx. pipiens/restuans population dynamics was predicted by integrating the CCM results in Poisson regression models. They were used to simulate the average seasonal cycle of the mosquito abundance. Verification with observations resulted in a correlation of rS?=?0.899 for daily and rS?=?0.917 for weekly data. Applying the optimized models to the entire 20-years time series also resulted in a suitable fit with rS?=?0.876 for daily and rS?=?0.899 for weekly data. Conclusions The study demonstrates the application of interval lagged weather data to predict mosquito abundances with a feasible accuracy, especially when related to weekly Cx. pipiens/restuans populations. PMID:23634763

2013-01-01

2

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

PubMed

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. PMID:15649520

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

2005-02-01

3

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

USGS Publications Warehouse

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.

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

2005-01-01

4

Predicting Relapsing-Remitting Dynamics in Multiple Sclerosis Using Discrete Distribution Models: A Population Approach  

PubMed Central

Background Relapsing-remitting dynamics are a hallmark of autoimmune diseases such as Multiple Sclerosis (MS). A clinical relapse in MS reflects an acute focal inflammatory event in the central nervous system that affects signal conduction by damaging myelinated axons. Those events are evident in T1-weighted post-contrast magnetic resonance imaging (MRI) as contrast enhancing lesions (CEL). CEL dynamics are considered unpredictable and are characterized by high intra- and inter-patient variability. Here, a population approach (nonlinear mixed-effects models) was applied to analyse of CEL progression, aiming to propose a model that adequately captures CEL dynamics. Methods and Findings We explored several discrete distribution models to CEL counts observed in nine MS patients undergoing a monthly MRI for 48 months. All patients were enrolled in the study free of immunosuppressive drugs, except for intravenous methylprednisolone or oral prednisone taper for a clinical relapse. Analyses were performed with the nonlinear mixed-effect modelling software NONMEM 7.2. Although several models were able to adequately characterize the observed CEL dynamics, the negative binomial distribution model had the best predictive ability. Significant improvements in fitting were observed when the CEL counts from previous months were incorporated to predict the current month’s CEL count. The predictive capacity of the model was validated using a second cohort of fourteen patients who underwent monthly MRIs during 6-months. This analysis also identified and quantified the effect of steroids for the relapse treatment. Conclusions The model was able to characterize the observed relapsing-remitting CEL dynamic and to quantify the inter-patient variability. Moreover, the nature of the effect of steroid treatment suggested that this therapy helps resolve older CELs yet does not affect newly appearing active lesions in that month. This model could be used for design of future longitudinal studies and clinical trials, as well as for the evaluation of new therapies. PMID:24039924

Velez de Mendizabal, Nieves; Hutmacher, Matthew M.; Troconiz, Iñaki F.; Goñi, Joaquín; Villoslada, Pablo; Bagnato, Francesca; Bies, Robert R.

2013-01-01

5

Predicting Population Curves.  

ERIC Educational Resources Information Center

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

Bunton, Matt

2003-01-01

6

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...

7

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

PubMed

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

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

2013-11-01

8

Population Characteristics, Development of a Predictive Population Viability Model, and Catch Dynamics for Pallid Sturgeon in the Lower Missouri River.  

E-print Network

??Population characteristics and long-term population trends of pallid sturgeon Scaphirhynchus albus in the lower Missouri River are relatively unknown. As recovery efforts continue, understanding and… (more)

Steffensen, Kirk D.

2012-01-01

9

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

PubMed

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

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

2012-04-01

10

Population Dynamics and Harvest Potential of Mountain  

Microsoft Academic Search

The understanding of population dynamics is a central issue for managing large mammals. Modeling has allowed population ecologists to increase their knowledge about complex systems and better predict population responses to diverse perturbations. Mountain goats (Oreamnos americanus) appear sensitive to harvest, but the relative influence of survival and reproductive rates on their population dynamics are not well understood. Using longitudinal

SANDRA HAMEL; STEEVE D. COTE; MARCO FESTA-BIANCHET

11

Research Article Population Dynamics and Harvest Potential of Mountain  

E-print Network

predict population responses to diverse perturbations. Mountain goats (Oreamnos americanus) appear, Oreamnos americanus, population dynamics, sensitivity analysis. A complex but central goal in population

Festa-Bianchet, Marco

12

Modelling the population dynamics of the Mt. Graham red squirrel: Can we predict its future in a  

E-print Network

S T R A C T The Mt. Graham red squirrel (Tamiasciurus hudsonicus grahamensis; MGRS) is among the most characteristics that ultimately drive population dynamics. Red squirrels (Tamiasciurus hudsonicus) are com- mon

Koprowski, John L.

13

Student Instructions Population Dynamics  

E-print Network

the population dynamics of wolves and bunnies that live in a meadow together. Figure 1. The Meadow. Population: "the wolves" 75 1" x 1" pink paper squares: "the bunnies" Instructions Overview: This simulation manager. The wolves (gray squares) will be randomly dropped onto the meadow (large sheet) covered

Spakowitz, Andrew J.

14

Uncertainty analysis of transient population dynamics  

Microsoft Academic Search

Two types of demographic analyses, perturbation analysis and uncertainty analysis, can be conducted to gain insights about matrix population models and guide population management. Perturbation analysis studies how the perturbation of demographic parameters (survival, growth, and reproduction parameters) may affect the population projection, while uncertainty analysis evaluates how much uncertainty there is in population dynamic predictions and where the uncertainty

Chonggang Xu; George Z. Gertner

2009-01-01

15

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

PubMed

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

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

2014-04-01

16

Population dynamic interference among childhood diseases  

E-print Network

is predicted and cannot be dismissed in the limited case-study data available for measles and whooping cough in England before the vaccination era. Keywords: measles; whooping cough; population dynamics; epidemiology

Rohani, Pejman

17

Teacher Instructions Population Dynamics  

E-print Network

how introducing a population of predators (in this case a population of wolves) into the meadow squares: "the wolves" 75 1" x 1" pink paper squares: "the bunnies" Overview: This simulation requires. The wolves (pink squares) will be randomly dropped onto the meadow (large sheet) covered in bunnies (gray

Spakowitz, Andrew J.

18

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...

19

Population dynamics simulations of functional model proteins  

NASA Astrophysics Data System (ADS)

In order to probe the fundamental principles that govern protein evolution, we use a minimalist model of proteins to provide a mapping from genotype to phenotype. The model is based on physically realistic forces of protein folding and includes an explicit definition of protein function. Thus, we can find the fitness of a sequence from its ability to fold to a stable structure and perform a function. We study the fitness landscapes of these functional model proteins, that is, the set of all sequences mapped on to their corresponding fitnesses and connected to their one mutant neighbors. Through population dynamics simulations we directly study the influence of the nature of the fitness landscape on evolution. Populations are observed to move to a steady state, the distribution of which can often be predicted prior to the population dynamics simulations from the nature of the fitness landscape and a quantity analogous to a partition function. In this paper, we develop a scheme for predicting the steady-state population on a fitness landscape, based on the nature of the fitness landscape, thereby obviating the need for explicit population dynamics simulations and providing some insight into the impact on molecular evolution of the nature of fitness landscapes. Poor predictions are indicative of fitness landscapes that consist of a series of weakly connected sublandscapes.

Blackburne, Benjamin P.; Hirst, Jonathan D.

2005-10-01

20

Evolutionary dynamics in finite populations  

NASA Astrophysics Data System (ADS)

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.

Hauert, Christoph

2013-03-01

21

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

PubMed Central

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

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

2014-01-01

22

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

PubMed

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

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

2013-09-01

23

Dose-structured population dynamics.  

PubMed

Applied population dynamics modeling is relied upon with increasing frequency to quantify how human activities affect human and non-human populations. Current techniques include variously the population's spatial transport, age, size, and physiology, but typically not the life-histories of exposure to other important things occurring in the ambient environment, such as chemicals, heat, or radiation. Consequently, the effects of such 'abiotic' aspects of an ecosystem on populations are only currently addressed through individual-based modeling approaches that despite broad utility are limited in their applicability to realistic ecosystems [V. Grimm, Ten years of individual-based modeling in ecology: what have we learned and what could we learn in the future? Ecol. Model. 115 (1999) 129-148][1]. We describe a new category of population dynamics modeling, wherein population dynamical states of the biotic phases are structured on dose, and apply this framework to demonstrate how chemical species or other ambient aspects can be included in population dynamics in three separate examples involving growth suppression in fish, inactivation of microorganisms with ultraviolet irradiation, and metabolic lag in population growth. Dose-structuring is based on a kinematic approach that is a simple generalization of age-structuring, views the ecosystem as a multi-component mixture with reacting biotic/abiotic components. The resulting model framework accommodates (a) different memories of exposure as in recovery from toxic ambient conditions, (b) differentiation between exogenous and endogenous sources of variation in population response, and (c) quantification of acute or sub-acute effects on populations arising from life-history exposures to abiotic species. Classical models do not easily address the very important fact that organisms differ and have different experiences over their life cycle. The dose structuring is one approach to incorporate some of these elements into the existing structures of the classical models, while retaining many of the features (and other limitations) of classical models. PMID:17296208

Ginn, Timothy R; Loge, Frank J

2007-07-01

24

Population dynamics in meerkats, Suricata suricatta  

E-print Network

mathematical and statistical models, in conjunction with long-term data from a wild meerkat population, to explore population dynamics, group dynamics, group demography, Allee effects, and territory dynamics in this species. I start out by examining broad...

Bateman, Andrew

2013-03-12

25

Population mixture model for nonlinear telomere dynamics  

NASA Astrophysics Data System (ADS)

Telomeres are DNA repeats protecting chromosomal ends which shorten with each cell division, eventually leading to cessation of cell growth. We present a population mixture model that predicts an exponential decrease in telomere length with time. We analytically solve the dynamics of the telomere length distribution. The model provides an excellent fit to available telomere data and accounts for the previously unexplained observation of telomere elongation following stress and bone marrow transplantation, thereby providing insight into the nature of the telomere clock.

Itzkovitz, Shalev; Shlush, Liran I.; Gluck, Dan; Skorecki, Karl

2008-12-01

26

Fuzzy modelling in population dynamics  

Microsoft Academic Search

The aim of this paper is to analyze the behavior of models which describe the population dynamics taking into account the subjectivity in the state variables or in the parameters. The models in this work have demographic and environmental fuzziness. The environmental fuzziness is presented using a life expectancy model where the fuzziness of parameters is considered. The demographic fuzziness

L. C. Barros; R. C. Bassanezi; P. A. Tonelli

2000-01-01

27

Flood trends and population dynamics  

NASA Astrophysics Data System (ADS)

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.

Di Baldassarre, G.

2012-04-01

28

Effects of seasonally varying dietary crude protein levels on collared peccary population dynamics: a simulation study.  

E-print Network

(Ofus asio) population dynamics. Yodzis and Kolenosky (1986) used a population model of black bears (Ursus amen canus) in eastcentral Ontario to predict intrinsic population growth rate and age specific reproduction based on mark-recapture data...

Wilber, James Paul

2012-06-07

29

Evolutionary Dynamics and Diversity in Microbial Populations  

NASA Astrophysics Data System (ADS)

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.

Thompson, Joel; Fisher, Daniel

2013-03-01

30

Optimal prediction in molecular dynamics  

E-print Network

Optimal prediction approximates the average solution of a large system of ordinary differential equations by a smaller system. We present how optimal prediction can be applied to a typical problem in the field of molecular dynamics, in order to reduce the number of particles to be tracked in the computations. We consider a model problem, which describes a surface coating process, and show how asymptotic methods can be employed to approximate the high dimensional conditional expectations, which arise in optimal prediction. The thus derived smaller system is compared to the original system in terms of statistical quantities, such as diffusion constants. The comparison is carried out by Monte-Carlo simulations, and it is shown under which conditions optimal prediction yields a valid approximation to the original system.

Benjamin Seibold

2008-08-22

31

Local extinction synchronizes population dynamics in spatial networks  

PubMed Central

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

Matter, Stephen F.; Roland, Jens

2010-01-01

32

A Quantitative Model of Honey Bee Colony Population Dynamics  

PubMed Central

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

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

2011-01-01

33

A quantitative model of honey bee colony population dynamics.  

PubMed

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

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

2011-01-01

34

Aphid population dynamics: does resistance to parasitism inuence population size?  

E-print Network

Aphid population dynamics: does resistance to parasitism in¯uence population size? R . A . H U F B and extrinsic factors can interact in their effects on population size. 2. Pea aphids Acyrthosiphon pisum Harris pea aphids specialised on clover. To assess the potential in¯uence of this genetically based

Hufbauer, Ruth A.

35

Co-infection alters population dynamics of infectious disease.  

PubMed

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

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

2015-01-01

36

Population dynamics of humpback whales o  

Microsoft Academic Search

This paper uses the population perturbation caused by the whaling industry during the 19th and 20th centuries to examine whether the population dynamics of the summer aggregation of humpback whales o West Greenland is best described by direct density regulation and an abundance that returns monotonically towards an equilibrium state, or by inertia dynamics that include also delayed density dependence

Lars Witting

37

Population dynamics of obligate cooperators  

PubMed Central

Obligate cooperative breeding species demonstrate a high rate of group extinction, which may be due to the existence of a critical number of helpers below which the group cannot subsist. Through a simple model, we study the population dynamics of obligate cooperative breeding species, taking into account the existence of a lower threshold below which the instantaneous growth rate becomes negative. The model successively incorporates (i) a distinction between species that need helpers for reproduction, survival or both, (ii) the existence of a migration rate accounting for dispersal, and (iii) stochastic mortality to simulate the effects of random catastrophic events. Our results suggest that the need for a minimum number of helpers increases the risk of extinction for obligate cooperative breeding species. The constraint imposed by this threshold is higher when helpers are needed for reproduction only or for both reproduction and survival. By driving them below this lower threshold, stochastic mortality of lower amplitude and/or lower frequency than for non-cooperative breeders may be sufficient to cause the extinction of obligate cooperative breeding groups. Migration may have a buffering effect only for groups where immigration is higher than emigration; otherwise (when immigrants from nearby groups are not available) it lowers the difference between actual group size and critical threshold, thereby constituting a higher constraint.

Courchamp, F.; Grenfell, B.; Clutton-Brock, T.

1999-01-01

38

Red, blue and green: Dyeing population dynamics  

Microsoft Academic Search

Numbers or densities of a natural population typically change over time. These fluctua- tions result from density-dependence mechanisms in the populations or external envi- ronmental variations. According to modern ecological research, time series describing population sizes and physical environments tend to be dominated by low-frequency fluctuations, whereas, contrary to this, simple population dynamic models are mostly dominated by short-term fluctuations.

Veijo Kaitala; Per Lundberg; Jörgen Rip; Janica Ylikarjula

39

Effects of virus on plant fecundity and population dynamics.  

PubMed

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

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

2014-06-01

40

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

PubMed Central

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

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

2006-01-01

41

Cyclic dynamics of eastern Canadian ermine populations  

Microsoft Academic Search

Based on partial autocorrelation analysis, 20 ermine (Mustela erminea) populations in Manitoba, Ontario, and Quebec demonstrated cyclic dynamics characterized by a latitudinal gradient of decreasing first-order feedback and increasing negativity of second-order feedback. Most of these populations exhibited three cyclic peaks and a 10-year interval of noncyclic dynamics during the sampling period (1915-1940). Changes in ermine density probably reflected those

Donald R. Johnson; Bradley J. Swanson; Judith L. Eger

2000-01-01

42

Population Dynamics of Harmful Cyanobacteria  

Microsoft Academic Search

huge number is sufficient to cover an area of 1.000.000 km 2 in which the upper meter of the water column is populated by an extremely dense population of 1.000.000 cyanobacterial cells per millilitre of water. Adding another 20 days would suffice to cover the entire planet Earth with a dense surface bloom. A frightful thought! Why, then, are most

Jef Huisman; Florence D. HULOT

43

Population dynamics on heterogeneous bacterial substrates  

NASA Astrophysics Data System (ADS)

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.

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

2012-02-01

44

Hidden Process Models For Animal Population Dynamics  

Microsoft Academic Search

Hidden process models are a conceptually useful and practical way to si- multaneously account for process variation in animal population dynamics and measurement errors in observations and estimates made on the population. Process variation, which can be both demographic and environmental, is modeled by linking a series of stochastic and deterministic subprocesses that characterize processes such as birth, survival, maturation,

K. B. Newman; S. T. Buckland; S. T. Lindley; L. Thomas; C. Fernández

2006-01-01

45

Fitting probability models to population dynamics data  

Microsoft Academic Search

Methods for modeling population dynamics in probability using the generalized point process approach are developed. The life history of these populations is such that seasonal reproduction occurs during a short time. Several models are developed and analyzed. Data about two species: colonial spiders (Stegodyphus dumicola) and a migratory bird (wood thrush, Hylocichla mustelina) are used to estimate model parameters with

Yosef Cohen

2009-01-01

46

Testing a Theoretical Model that Predicts Thresholds in Populations Forced by Imposing Random, Episodic Disturbances  

NASA Astrophysics Data System (ADS)

We do not fully understand reasons behind extinction of populations and species. Consequently, our ability to anticipate extinction (which can be considered a permanent type of an ecological threshold) has remained elusive. In particular, it is not clear how the attributes of episodic disturbance regimes can elicit extinction. Here, I test a stochastic model that predicts population extinction based on attributes of the disturbance regime and population growth rates using phytoplankton in a test tube. I examined the response of phytoplankton (Thalassiosira weissflogii) to stochastic disturbances implemented by having MATLAB control a hydraulic pump that episodically removed portions of the population through time in between episodes of population recovery. My experiment demonstrated evidence that a theoretical or mathematical threshold predicted to exist in theory may actually apply to a diatom population dynamics in a test tube; however, my results also open new questions about how the statistical attributes of the disturbance regimes under study may alter the predicted time to population extinction.

Olsen, C.; Lintz, H. E.; Peckham, S. D.

2013-12-01

47

Evolution and population dynamics in stochastic environments  

Microsoft Academic Search

Inter-generational temporal variability of the environment is important in the evolution and adaptation of phenotypic traits.\\u000a We discuss a population-dynamic approach which plays a central role in the analysis of evolutionary processes. The basic principle\\u000a is that the phenotypes with the greatest long-term average growth rate will dominate the entire population. The calculation\\u000a of longterm average growth rates for populations

Jin Yoshimura; Vincent A. A. Jansen

1996-01-01

48

Dynamic Properties of the Alkaline Vesicle Population at Hippocampal Synapses  

PubMed Central

In compensatory endocytosis, scission of vesicles from the plasma membrane to the cytoplasm is a prerequisite for intravesicular reacidification and accumulation of neurotransmitter molecules. Here, we provide time-resolved measurements of the dynamics of the alkaline vesicle population which appears upon endocytic retrieval. Using fast perfusion pH-cycling in live-cell microscopy, synapto-pHluorin expressing rat hippocampal neurons were electrically stimulated. We found that the relative size of the alkaline vesicle population depended significantly on the electrical stimulus size: With increasing number of action potentials the relative size of the alkaline vesicle population expanded. In contrast to that, increasing the stimulus frequency reduced the relative size of the population of alkaline vesicles. Measurement of the time constant for reacification and calculation of the time constant for endocytosis revealed that both time constants were variable with regard to the stimulus condition. Furthermore, we show that the dynamics of the alkaline vesicle population can be predicted by a simple mathematical model. In conclusion, here a novel methodical approach to analyze dynamic properties of alkaline vesicles is presented and validated as a convenient method for the detection of intracellular events. Using this method we show that the population of alkaline vesicles is highly dynamic and depends both on stimulus strength and frequency. Our results implicate that determination of the alkaline vesicle population size may provide new insights into the kinetics of endocytic retrieval. PMID:25079223

Röther, Mareike; Brauner, Jan M.; Ebert, Katrin; Welzel, Oliver; Jung, Jasmin; Bauereiss, Anna; Kornhuber, Johannes; Groemer, Teja W.

2014-01-01

49

Predictive Dynamic Security Assessment through Advanced Computing  

SciTech Connect

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.

Huang, Zhenyu; Diao, Ruisheng; Jin, Shuangshuang; Chen, Yousu

2014-11-30

50

Differential Equations via Population Dynamics.  

ERIC Educational Resources Information Center

Some single species and two species interactions in population models are presented to show how credible examples can be used to teach an underlying, common mathematical structure within apparently different concepts. The models examined consist of differential equations, and focus on real-world issues. (MP)

Sofo, Anthony

1981-01-01

51

Animal Population Dynamics Jennifer Gervais  

E-print Network

, scientific study relatively recent Both mathematical exploration and empirical approaches; human demography in ag Development of a more scientific basis for the study of natural history Understanding population and vocation! Later, a professional demographer Author of "Elements of Physical Biology" application

Gervais, Jennifer

52

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

PubMed

ABSTRACT 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

Eyre, C A; Garbelotto, M

2015-01-01

53

Deterministic evolutionary game dynamics in finite populations.  

PubMed

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

Altrock, Philipp M; Traulsen, Arne

2009-07-01

54

Harvest and dynamics of duck populations  

USGS Publications Warehouse

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

Sedinger, James S.; Herzog, Mark P.

2012-01-01

55

Song Diversity Predicts the Viability of Fragmented Bird Populations  

PubMed Central

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

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

2008-01-01

56

Monitoring coyote population dynamics by genotyping faeces.  

PubMed

Reliable population estimates are necessary for effective conservation and management, and faecal genotyping has been used successfully to estimate the population size of several elusive mammalian species. Information such as changes in population size over time and survival rates, however, are often more useful for conservation biology than single population estimates. We evaluated the use of faecal genotyping as a tool for monitoring long-term population dynamics, using coyotes (Canis latrans) in the Alaska Range as a case study. We obtained 544 genotypes from 56 coyotes over 3 years (2000-2002). Tissue samples from all 15 radio-collared coyotes in our study area had > or = 1 matching faecal genotypes. We used flexible maximum-likelihood models to study coyote population dynamics, and we tested model performance against radio telemetry data. The staple prey of coyotes, snowshoe hares (Lepus americanus), dramatically declined during this study, and the coyote population declined nearly two-fold with a 1(1/2)-year time lag. Survival rates declined the year after hares crashed but recovered the following year. We conclude that long-term monitoring of elusive species using faecal genotyping is feasible and can provide data that are useful for wildlife conservation and management. We highlight some drawbacks of standard open-population models, such as low precision and the requirement of discrete sampling intervals, and we suggest that the development of open models designed for continuously collected data would enhance the utility of faecal genotyping as a monitoring tool. PMID:15813796

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

2005-04-01

57

Population dynamics with nonlinear delayed carrying capacity  

E-print Network

We consider a class of evolution equations describing population dynamics in the presence of a carrying capacity depending on the population with delay. In an earlier work, we presented an exhaustive classification of the logistic equation where the carrying capacity is linearly dependent on the population with a time delay, which we refer to as the "linear delayed carrying capacity" model. Here, we generalize it to the case of a nonlinear delayed carrying capacity. The nonlinear functional form of the carrying capacity characterizes the delayed feedback of the evolving population on the capacity of their surrounding by either creating additional means for survival or destroying the available resources. The previously studied linear approximation for the capacity assumed weak feedback, while the nonlinear form is applicable to arbitrarily strong feedback. The nonlinearity essentially changes the behavior of solutions to the evolution equation, as compared to the linear case. All admissible dynamical regimes a...

Yukalov, V I; Sornette, D

2014-01-01

58

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

USGS Publications Warehouse

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.

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

59

Multispecies population dynamics of prebiotic compositional assemblies.  

PubMed

Present life portrays a two-tier phenomenology: molecules compose supramolecular structures, such as cells or organisms, which in turn portray population behaviors, including selection, evolution and ecological dynamics. Prebiotic models have often focused on evolution in populations of self-replicating molecules, without explicitly invoking the intermediate molecular-to-supramolecular transition. Here, we explore a prebiotic model that allows one to relate parameters of chemical interaction networks within molecular assemblies to emergent population dynamics. We use the graded autocatalysis replication domain (GARD) model, which simulates the network dynamics within amphiphile-containing molecular assemblies, and exhibits quasi-stationary compositional states termed compotype species. These grow by catalyzed accretion, divide and propagate their compositional information to progeny in a replication-like manner. The model allows us to ask how molecular network parameters influence assembly evolution and population dynamics parameters. In 1000 computer simulations, each embodying different parameter set of the global chemical interaction network parameters, we observed a wide range of behaviors. These were analyzed by a multi species logistic model often used for analyzing population ecology (r-K or Lotka-Volterra competition model). We found that compotypes with a larger intrinsic molecular repertoire show a higher intrinsic growth (r) and lower carrying capacity (K), as well as lower replication fidelity. This supports a prebiotic scenario initiated by fast-replicating assemblies with a high molecular diversity, evolving into more faithful replicators with narrower molecular repertoires. PMID:24831416

Markovitch, Omer; Lancet, Doron

2014-09-21

60

Irruptive population dynamics in Yellowstone pronghorn.  

PubMed

Irruptive population dynamics appear to be widespread in large herbivore populations, but there are few empirical examples from long time series with small measurement error and minimal harvests. We analyzed an 89-year time series of counts and known removals for pronghorn (Antilocapra americana) in Yellowstone National Park of the western United States during 1918-2006 using a suite of density-dependent, density-independent, and irruptive models to determine if the population exhibited irruptive dynamics. Information-theoretic model comparison techniques strongly supported irruptive population dynamics (Leopold model) and density dependence during 1918-1946, with the growth rate slowing after counts exceeded 600 animals. Concerns about sagebrush (Artemisia spp.) degradation led to removals of >1100 pronghorn during 1947-1966, and counts decreased from approximately 700 to 150. The best models for this period (Gompertz, Ricker) suggested that culls replaced intrinsic density-dependent mechanisms. Contrary to expectations, the population did not exhibit enhanced demographic vigor soon after the termination of the harvest program, with counts remaining between 100 and 190 animals during 1967 1981. However, the population irrupted (Caughley model with a one-year lag) to a peak abundance of approximately 600 pronghorn during 1982-1991, with a slowing in growth rate as counts exceeded 500. Numbers crashed to 235 pronghorn during 1992-1995, perhaps because important food resources (e.g., sagebrush) on the winter range were severely diminished by high densities of browsing elk, mule deer, and pronghorn. Pronghorn numbers remained relatively constant during 1996-2006, at a level (196-235) lower than peak abundance, but higher than numbers following the release from culling. The dynamics of this population supported the paradigm that irruption is a fundamental pattern of growth in many populations of large herbivores with high fecundity and delayed density-dependent effects on recruitment when forage and weather conditions become favorable after range expansion or release from harvesting. Incorporating known removals into population models that can describe a wide range of dynamics can greatly improve our interpretation of observed dynamics in intensively managed populations. PMID:17913126

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

2007-09-01

61

Cyclic dynamics in simulated plant populations.  

PubMed Central

Despite the general interest in nonlinear dynamics in animal populations, plant populations are supposed to show a stable equilibrium that is attributed to fundamental differences compared with animals. Some studies find more complex dynamics, but empirical studies usually are too short and most modelling studies ignore important spatial aspects of local competition and establishment. Therefore, we used a spatially explicit individual-based model of a hypothetical, non-clonal perennial to explore which mechanisms might generate complex dynamics, i.e. cycles. The model is based on the field-of-neighbourhood approach that describes local competition and establishment in a phenomenological manner. We found cyclic population dynamics for a wide spectrum of model variants, provided that mortality is determined by local competition and recruitment is virtually completely suppressed within the zone of influence of established plants. This destabilizing effect of local processes within plant populations might have wide-ranging implications for the understanding of plant community dynamics and coexistence. PMID:12495487

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

2002-01-01

62

Predation, individual variability and vertebrate population dynamics  

Microsoft Academic Search

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

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

63

Density independent population dynamics by Trichoderma virens in soil and defined substrates  

Microsoft Academic Search

Classical models of population dynamics predict that with increasing initial population densities the per capita growth will diminish. Observations over a broad range of initial densities with a wild-type and a genetically engineered strain of the filamentous fungus, Trichoderma virens (Arx), in soil and autoclaved soil differed from these predictions. The per capita growth response of T. virens in vitro

Mark Weaver; Charles Kenerley

2005-01-01

64

(Meta)population dynamics of infectious diseases  

Microsoft Academic Search

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

Bryan Grenfell; John Harwood

1997-01-01

65

Population Dynamical Consequences of Climate Change for a Small Temperate Songbird  

Microsoft Academic Search

Predicting the effects of an expected climatic change requires estimates and modeling of stochastic factors as well as density-dependent effects in the population dynamics. In a population of a small songbird, the dipper (Cinclus cinclus), environmental stochasticity and density dependence both influenced the population growth rate. About half of the environmental variance was explained by variation in mean winter temperature.

B.-E. Sæther; J. Tufto; S. Engen; K. Jerstad; O. W. Røstad; J. E. Skåtan

2000-01-01

66

Connecting micro dynamics and population distributions in system dynamics models  

PubMed Central

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.

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

2014-01-01

67

Population dynamics of epiphytic orchids in a metapopulation context  

PubMed Central

Background and Aims Populations of many epiphytes show a patchy distribution where clusters of plants growing on individual trees are spatially separated and may thus function as metapopulations. Seed dispersal is necessary to (re)colonize unoccupied habitats, and to transfer seeds from high- to low-competition patches. Increasing dispersal distances, however, reduces local fecundity and the probability that seeds will find a safe site outside the original patch. Thus, there is a conflict between seed survival and colonization. Methods Populations of three epiphytic orchids were monitored over three years in a Mexican humid montane forest and analysed with spatially averaged and with spatially explicit matrix metapopulation models. In the latter, population dynamics at the scale of the subpopulations (epiphytes on individual host trees) are based on detailed stage-structured observations of transition probabilities and trees are connected by a dispersal function. Key Results Population growth rates differed among trees and years. While ignoring these differences, and averaging the population matrices over trees, yields negative population growth, metapopulation models predict stable or growing populations because the trees that support growing subpopulations determine the growth of the metapopulation. Stochastic models which account for the differences among years differed only marginally from deterministic models. Population growth rates were significantly lower, and extinctions of local patches more frequent in models where higher dispersal results in reduced local fecundity compared with hypothetical models where this is not the case. The difference between the two models increased with increasing mean dispersal distance. Though recolonization events increased with dispersal distance, this could not compensate the losses due to reduced local fecundity. Conclusions For epiphytes, metapopulation models are useful to capture processes beyond the level of the single host tree, but local processes are equally important to understand epiphyte population dynamics. PMID:19671576

Winkler, Manuela; Hülber, Karl; Hietz, Peter

2009-01-01

68

Delay differential systems for tick population dynamics.  

PubMed

Ticks play a critical role as vectors in the transmission and spread of Lyme disease, an emerging infectious disease which can cause severe illness in humans or animals. To understand the transmission dynamics of Lyme disease and other tick-borne diseases, it is necessary to investigate the population dynamics of ticks. Here, we formulate a system of delay differential equations which models the stage structure of the tick population. Temperature can alter the length of time delays in each developmental stage, and so the time delays can vary geographically (and seasonally which we do not consider). We define the basic reproduction number [Formula: see text] of stage structured tick populations. The tick population is uniformly persistent if [Formula: see text] and dies out if [Formula: see text]. We present sufficient conditions under which the unique positive equilibrium point is globally asymptotically stable. In general, the positive equilibrium can be unstable and the system show oscillatory behavior. These oscillations are primarily due to negative feedback within the tick system, but can be enhanced by the time delays of the different developmental stages. PMID:25348048

Fan, Guihong; Thieme, Horst R; Zhu, Huaiping

2014-10-28

69

The replicator dynamics with n players and population structure.  

PubMed

The well-known replicator dynamics is usually applied to 2-player games and random matching. Here we allow for games with n players, and for population structures other than random matching. This more general application leads to a version of the replicator dynamics of which the standard 2-player, well-mixed version is a special case, and which allows us to explore the dynamic implications of population structure. The replicator dynamics also allows for a reformulation of the central theorem in Van Veelen (2009), which claims that inclusive fitness gives the correct prediction for games with generalized equal gains from switching (or, in other words, when fitness effects are additive). If we furthermore also assume that relatedness is constant during selection - which is a reasonable assumption in a setting with kin recognition - then inclusive fitness even becomes a parameter that determines the speed as well as the direction of selection. For games with unequal gains from switching, inclusive fitness can give the wrong prediction. With equal gains however, not only the sign, but also even the value of inclusive fitness becomes meaningful. PMID:21295593

van Veelen, Matthijs

2011-05-01

70

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

PubMed Central

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

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

2012-01-01

71

Population dynamics in Er3+-doped fluoride glasses  

NASA Astrophysics Data System (ADS)

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

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

2001-05-01

72

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

PubMed

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

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

2014-07-01

73

Population dynamical consequences of climate change for a small temperate songbird.  

PubMed

Predicting the effects of an expected climatic change requires estimates and modeling of stochastic factors as well as density-dependent effects in the population dynamics. In a population of a small songbird, the dipper (Cinclus cinclus), environmental stochasticity and density dependence both influenced the population growth rate. About half of the environmental variance was explained by variation in mean winter temperature. Including these results in a stochastic model shows that an expected change in climate will strongly affect the dynamics of the population, leading to a nonlinear increase in the carrying capacity and in the expected mean population size. PMID:10657299

Saether, B; Tufto, J; Engen, S; Jerstad, K; Rostad, O W; Skâtan, J E

2000-02-01

74

API Requirements for Dynamic Graph Prediction  

SciTech Connect

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.

Gallagher, B; Eliassi-Rad, T

2006-10-13

75

Effects of culling on mesopredator population dynamics.  

PubMed

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

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

2013-01-01

76

Effects of Culling on Mesopredator Population Dynamics  

PubMed Central

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

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

2013-01-01

77

A common reference population from four European Holstein populations increases reliability of genomic predictions  

PubMed Central

Background Size of the reference population and reliability of phenotypes are crucial factors influencing the reliability of genomic predictions. It is therefore useful to combine closely related populations. Increased accuracies of genomic predictions depend on the number of individuals added to the reference population, the reliability of their phenotypes, and the relatedness of the populations that are combined. Methods This paper assesses the increase in reliability achieved when combining four Holstein reference populations of 4000 bulls each, from European breeding organizations, i.e. UNCEIA (France), VikingGenetics (Denmark, Sweden, Finland), DHV-VIT (Germany) and CRV (The Netherlands, Flanders). Each partner validated its own bulls using their national reference data and the combined data, respectively. Results Combining the data significantly increased the reliability of genomic predictions for bulls in all four populations. Reliabilities increased by 10%, compared to reliabilities obtained with national reference populations alone, when they were averaged over countries and the traits evaluated. For different traits and countries, the increase in reliability ranged from 2% to 19%. Conclusions Genomic selection programs benefit greatly from combining data from several closely related populations into a single large reference population. PMID:22152008

2011-01-01

78

Evolutionary dynamics in finite populations with zealots.  

PubMed

We investigate evolutionary dynamics of two-strategy matrix games with zealots in finite populations. Zealots are assumed to take either strategy regardless of the fitness. When the strategy selected by the zealots is the same, the fixation of the strategy selected by the zealots is a trivial outcome. We study fixation time in this scenario. We show that the fixation time is divided into three main regimes, in one of which the fixation time is short, and in the other two the fixation time is exponentially long in terms of the population size. Different from the case without zealots, there is a threshold selection intensity below which the fixation is fast for an arbitrary payoff matrix. We illustrate our results with examples of various social dilemma games. PMID:24610380

Nakajima, Yohei; Masuda, Naoki

2015-02-01

79

Assessing tiger population dynamics using photographic capture-recapture sampling  

USGS Publications Warehouse

Although wide-ranging, elusive, large carnivore species, such as the tiger, are of scientific and conservation interest, rigorous inferences about their population dynamics are scarce because of methodological problems of sampling populations at the required spatial and temporal scales. We report the application of a rigorous, noninvasive method for assessing tiger population dynamics to test model-based predictions about population viability. We obtained photographic capture histories for 74 individual tigers during a nine-year study involving 5725 trap-nights of effort. These data were modeled under a likelihood-based, ?robust design? capture?recapture analytic framework. We explicitly modeled and estimated ecological parameters such as time-specific abundance, density, survival, recruitment, temporary emigration, and transience, using models that incorporated effects of factors such as individual heterogeneity, trap-response, and time on probabilities of photo-capturing tigers. The model estimated a random temporary emigration parameter of =K' =Y' 0.10 ? 0.069 (values are estimated mean ? SE). When scaled to an annual basis, tiger survival rates were estimated at S = 0.77 ? 0.051, and the estimated probability that a newly caught animal was a transient was = 0.18 ? 0.11. During the period when the sampled area was of constant size, the estimated population size Nt varied from 17 ? 1.7 to 31 ? 2.1 tigers, with a geometric mean rate of annual population change estimated as = 1.03 ? 0.020, representing a 3% annual increase. The estimated recruitment of new animals, Bt, varied from 0 ? 3.0 to 14 ? 2.9 tigers. Population density estimates, D, ranged from 7.33 ? 0.8 tigers/100 km2 to 21.73 ? 1.7 tigers/100 km2 during the study. Thus, despite substantial annual losses and temporal variation in recruitment, the tiger density remained at relatively high levels in Nagarahole. Our results are consistent with the hypothesis that protected wild tiger populations can remain healthy despite heavy mortalities because of their inherently high reproductive potential. The ability to model the entire photographic capture history data set and incorporate reduced-parameter models led to estimates of mean annual population change that were sufficiently precise to be useful. This efficient, noninvasive sampling approach can be used to rigorously investigate the population dynamics of tigers and other elusive, rare, wide-ranging animal species in which individuals can be identified from photographs or other means.

Karanth, K.U.; Nichols, J.D.; Kumar, N.S.; Hines, J.E.

2006-01-01

80

Application of optimal prediction to molecular dynamics  

SciTech Connect

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

Barber IV, John Letherman

2004-12-01

81

Population Dynamics and Potential for Biological Control of an Exotic Invasive Shrub in Hawaiian Rainforests  

Microsoft Academic Search

Introduction of biological control agents to reduce the abundance of exotic invasive plant species is often considered necessary but risky. I used matrix projection models to investigate the current population dynamics of Clidemia  hirta (Melastomataceae), an invasive shrub, in two rainforest stands on the island of Hawaii and to predict the efficacy of hypothetical biological control agents in reducing population

Saara J. DeWalt

2006-01-01

82

Predicting spinor condensate dynamics from simple principles.  

PubMed

We study the spin dynamics of quasi-one-dimensional F=1 condensates both at zero and finite temperatures for arbitrary initial spin configurations. The rich dynamical evolution exhibited by these nonlinear systems is explained by surprisingly simple principles: minimization of energy at zero temperature and maximization of entropy at high temperature. Our analytical results for the homogeneous case are corroborated by numerical simulations for confined condensates in a wide variety of initial conditions. These predictions compare qualitatively well with recent experimental observations and can, therefore, serve as a guidance for ongoing experiments. PMID:17678203

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

2007-07-13

83

Predicting dynamic topography from mantle circulation models  

NASA Astrophysics Data System (ADS)

Dynamic topography is anomalous vertical motions of Earth's surface associated with viscous flow in the mantle. Deformable boundaries, such as the surface, CMB and phase transition boundaries, within a fluid (Earth's mantle) are deflected by viscous flow. Denser than average, sinking mantle creates inward deflections of Earth's surface. Equally, upwelling flow creates bulges in the surface; large plumes are commonly thought to produce superswells, such as the anomalously high elevation of Southern Africa. Dynamic topography appears to operate on a number of length scales. Mantle density anomalies estimated from seismic tomography indicate long wavelength dynamic topography at present day of around 2 km amplitude (e.g. Conrand & Husson, 2009) whilst continental scale studies suggest vertical motions of a few hundred metres. Furthermore, time scales must be an important factor to consider when assessing dynamic topography. Stable, dense lower mantle 'piles' may contribute to dynamic surface topography; as they appear stable over reasonably long time scales, long wavelength dynamic topography may be a fairly constant feature over the recent geological past. Shorter wavelength, smaller amplitude dynamic topography may be due to more transient features of mantle convection. Studies on a continental scale reveal shorter term changes in dynamic topography of the order of a few hundred metres (e.g. Roberts & White, 2010; Heine et al., 2010). Understanding dynamic topography is complicated by the fact it is difficult to observe as the signal is often masked by isostatic effects. We use forward mantle convection models with 300 million years of recent plate motion history as the surface boundary condition to generate a present day distribution of density anomalies associated with subducted lithosphere. From the modelled temperature and density fields we calculate the normal stress at or near the surface of the model. As the models generally have a free slip surface where no vertical motion is allowed, an excess or deficit of stress exists near the surface. A pointwise force balance between this stress excess and the weight of rock above is used to calculate the anomalous elevation associated with the stress. Here we present some of the results obtained from mantle circulation models. We look at different ways of predicting dynamic topography, including the depth at which the stress field is calculated and by removing lithospheric density anomalies from the calculation. We also assess the impact of crustal thickness and isostasy on the predictions of dynamic topography.

Webb, Peter; Davies, J. Huw

2013-04-01

84

Consequences of population models for the dynamics of food chains.  

PubMed

A class of bioenergetic ecological models is studied for the dynamics of food chains with a nutrient at the base. A constant influx rate of the nutrient and a constant efflux rate for all trophic levels is assumed. Starting point is a simple model where prey is converted into predator with a fixed efficiency. This model is extended by the introduction of maintenance and energy reserves at all trophic levels, with two state variables for each trophic level, biomass and reserve energy. Then the dynamics of each population are described by two ordinary differential equations. For all models the bifurcation diagram for the bi-trophic food chain is simple. There are three important regions; a region where the predator goes to extinction, a region where there is a stable equilibrium and a region where a stable limit cycle exists. Bifurcation diagrams for tritrophic food chains are more complicated. Flip bifurcation curves mark regions where complex dynamic behaviour (higher periodic limit cycles as well as chaotic attractors) can occur. We show numerically that Shil'nikov homoclinic orbits to saddle-focus equilibria exists. The codimension 1 continuations of these orbits form a 'skeleton' for a cascade of flip and tangent bifurcations. The bifurcation analysis facilitates the study of the consequences of the population model for the dynamic behaviour of a food chain. Although the predicted transient dynamics of a food chain may depend sensitively on the underlying model for the populations, the global picture of the bifurcation diagram for the different models is about the same. PMID:9825635

Kooi, B W; Boer, M P; Kooijman, S A

1998-11-01

85

Modeling the population dynamics of phytoplankton in lacustrine ecosystems  

NASA Astrophysics Data System (ADS)

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

Leiterman, Terry Jo

2011-11-01

86

Mechanical reaction-diffusion model for bacterial population dynamics  

E-print Network

The effect of mechanical interaction between cells on the spreading of bacterial population was investigated in one-dimensional space. A nonlinear reaction-diffusion equation has been formulated as a model for this dynamics. In this model, the bacterial cells are treated as the rod-like particles that interact, when contacting each other, through the hard-core repulsion. The repulsion introduces the exclusion process that causes the fast diffusion in bacterial population at high density. The propagation of the bacterial density as the traveling wave front in long time behavior has been analyzed. The analytical result reveals that the front speed is enhanced by the exclusion process---and its value depends on the packing fraction of cell. The numerical solutions of the model have been solved to confirm this prediction.

Ngamsaad, Waipot

2015-01-01

87

How should environmental stress affect the population dynamics of disease?  

E-print Network

@lifesci.ucsb.edu Abstract We modelled how stress affects the population dynamics of infectious disease. We were specifically-specific diseases generally declined with stress while the impact of non-specific (or open) diseases increased and disease in natural populations. Keywords Disease, dynamics, host, infectious, model, pollution, population

Holt, Robert D.

88

Dynamic matching algorithm for viral structure prediction.  

PubMed

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

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

2014-07-01

89

Inverse dynamical population synthesis and star formation  

NASA Astrophysics Data System (ADS)

Recent observations of pre-main-sequence stars suggest that all stars may form in multiple systems. However, in the Galactic field only about 50 per cent of all systems are binary stars. We investigate the hypothesis that stars form in aggregates of binary systems and that the dynamical evolution of these aggregates leads to the observed properties of binary stars in the Galactic field. A thorough analysis of star count data implies that the initial stellar mass function rises monotonically with decreasing mass and that it can be approximated by three power-law segments. Together with our assumption that the birth mass-ratio distribution is not correlated, this leads to a contradiction with the distribution of secondary masses in Galactic field binaries with G dwarf primaries which have too few low-mass companions. For the inverse dynamical population synthesis we assume that the initial distribution of periods is flat in log_10P, where P is the orbital period in days, and 3<=log_10P<=7.5. This is consistent with pre-main-sequence data. We distribute N_bin=200 binaries in aggregates with half-mass radii 0.077<=R_0.5<=2.53 pc, corresponding to the range from tightly clustered to isolated star formation, and follow the subsequent evolution of the stellar systems by direct N-body integration. We find that hardening and softening of binary systems do not significantly increase the numbers of orbits with log_10P<3 and log_10P<~7.5, respectively. After the cluster with R_0.5~=0.8 pc disintegrates we obtain a population which consists of about 60 per cent binary systems with a period distribution for log_10P<~4, as is observed, and in which the G dwarf binaries have a mass-ratio distribution which agrees with the observed distribution. This result indicates that the majority of Galactic field stars may originate from a clustered star-formation mode, characterized by the dominant-mode cluster which has initially (N_bin, R_0.5)~=(200, 0.8 pc). We invert the orbit depletion function and obtain an approximation to the initial binary star period distribution for star formation in the dominant-mode cluster. Comparison with the measured distribution of orbits for pre-main-sequence stars formed in the distributed mode of star formation suggests that the initial distribution of binary star orbits may not depend on the star-formation environment. If a different stellar mass function to the one we adopted is assumed then inverse dynamical population synthesis cannot solve for an aggregate in which the initial binary star population evolves to the observed population in the Galactic field. This implies that the Galactic field stellar mass function may be related to the stellar density at birth in the most common, or dominant, mode of star formation.

Kroupa, Pavel

1995-12-01

90

Space and stochasticity in population dynamics  

PubMed Central

Organisms interact with each other mostly over local scales, so the local density experienced by an individual is of greater importance than the mean density in a population. This simple observation poses a tremendous challenge to theoretical ecology, and because nonlinear stochastic and spatial models cannot be solved exactly, much effort has been spent in seeking effective approximations. Several authors have observed that spatial population systems behave like deterministic nonspatial systems if dispersal averages the dynamics over a sufficiently large scale. We exploit this fact to develop an exact series expansion, which allows one to derive approximations of stochastic individual-based models without resorting to heuristic assumptions. Our approach makes it possible to calculate the corrections to mean-field models in the limit where the interaction range is large, and it provides insight into the performance of moment closure methods. With this approach, we demonstrate how the buildup of spatiotemporal correlations slows down the spread of an invasion, prolongs time lags associated with extinction debt, and leads to locally oscillating but globally stable coexistence of a host and a parasite. PMID:16912114

Ovaskainen, Otso; Cornell, Stephen J.

2006-01-01

91

Demographic dynamics and kinship in anthropological populations  

PubMed Central

Changes in fertility and mortality affect the size of surviving sibling sets and thus numbers of surviving kin. Because the genealogical generations specifying kinship relations are not temporal cohorts and most plausible demographic changes in anthropological populations are period shocks, the effect of such shocks on kin counts are complex. Shocks increasing fertility or decreasing mortality produce larger numbers of kin per ego and decrease the inequality of the distribution of kin and vice versa. Effects are more diffuse at more distant collateral ranges. Effects are stronger the more intense the shock and the longer its duration. Kinship distributions return to their initial state after the shock and as the original age structure of the population is ergodically reattained. Alternating shocks produce more complex patterns. Implications of these outcomes are that opportunities for political networking and consolidation by means of kinship are altered by demographic instabilities, as are the dynamics of kin selection. This analysis is limited for simplicity to unilineal agnatic reckoning of kin. PMID:15677714

Hammel, E. A.

2005-01-01

92

Biotic Population Dynamics: Creative Biotic Patterns  

NASA Astrophysics Data System (ADS)

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

Sabelli, Hector; Kovacevic, Lazar

93

Predictability of population displacement after the 2010 Haiti earthquake  

PubMed Central

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

Lu, Xin; Bengtsson, Linus; Holme, Petter

2012-01-01

94

THE POPULATION OF HELIUM-MERGER PROGENITORS: OBSERVATIONAL PREDICTIONS  

SciTech Connect

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

Fryer, Chris L. [CCS Division, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)] [CCS Division, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Belczynski, Krzysztof; Bulik, Tomasz [Astronomical Observatory, University of Warsaw, Al. Ujazdowskie 4, 00-478 Warsaw (Poland)] [Astronomical Observatory, University of Warsaw, Al. Ujazdowskie 4, 00-478 Warsaw (Poland); Berger, Edo [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States)] [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Thoene, Christina [IAA-CSIC, Glorieta de la Astronomia s/n, E-18008 Granada (Spain)] [IAA-CSIC, Glorieta de la Astronomia s/n, E-18008 Granada (Spain); Ellinger, Carola [Department of Physics, University of Texas at Arlington, 502 Yates Street, Box 19059, Arlington, TX 76019 (United States)] [Department of Physics, University of Texas at Arlington, 502 Yates Street, Box 19059, Arlington, TX 76019 (United States)

2013-02-20

95

Mapping Genes that Predict Treatment Outcome in Admixed Populations  

PubMed Central

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

Baye, Tesfaye M.; Wilke, Russell A.

2010-01-01

96

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

PubMed Central

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

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

2012-01-01

97

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

PubMed

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

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

2012-05-01

98

Population dynamics and biocontrol efficacy of the nematophagous fungus Hirsutella rhossiliensis as affected by stage of the soybean cyst nematode  

Microsoft Academic Search

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

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

2008-01-01

99

Spatial variation in population growth rate and community structure affects local and regional dynamics.  

PubMed

1. Theory predicting that populations with high maximum rates of increase (r(max)) will be less stable, and that metapopulations with high average r(max) will be less synchronous, was tested using a small protist, Bodo, that inhabits pitcher plant leaves (Sarracenia purpurea L.). The effects of predators and resources on these relationships were also determined. 2. Abundance data collected for a total of 60 populations of Bodo, over a period of 3 months, at six sites in three bogs in eastern Canada, were used to test these predictions. Mosquitoes were manipulated in half the leaves partway through the season to increase the range of predation rates. 3. Dynamics differed greatly among leaves and sites, but most populations exhibited one or more episodes of rapid increase followed by a population crash. Estimates of r(max) obtained using a linear mixed-effects model, ranged from 1 x 5 to 2 x 7 per day. Resource levels (captured insect) and midge abundances affected r(max). 4. Higher r(max) was associated with greater temporal variability and lower synchrony as predicted. However, in contrast to expectations, populations with higher r(max) also had lower mean abundance and were more suppressed by predators. 5. This study demonstrates that the link between r(max) and temporal variability is key to understanding the dynamics of populations that spend little time near equilibrium, and to predicting and interpreting the effects of community structure on the dynamics of such populations. PMID:18624742

Trzcinski, M Kurtis; Walde, Sandra J; Taylor, Philip D

2008-11-01

100

Dynamics of Genome Rearrangement in Bacterial Populations  

PubMed Central

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

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

2008-01-01

101

The population dynamics and conservation of primate populations.  

PubMed

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

Dobson, A P; Lees, A M

1989-12-01

102

Population Dynamics in Spatially Complex Environments: Theory and Data  

Microsoft Academic Search

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

Peter Kareiva

1990-01-01

103

Linking herbivore-induced defences to population dynamics  

Microsoft Academic Search

SUMMARY 1. Theoretical studies have shown that inducible defences have the potential to affect population stability and persistence in bi- and tritrophic food chains. Experimental studies on such effects of prey defence strategies on the dynamics of predator-prey systems are still rare. We performed replicated population dynamics experiments using the herbi- vorous rotifer Brachionus calyciflorus and four strains of closely

IRENE V; S TAP; ATTHIJS V OS; W OLF M. M OOIJ

2006-01-01

104

Dynamics of two phytoplankton populations under predation.  

PubMed

The aim of this paper is to investigate the manner in which predation and single-nutrient competition affect the dynamics of a non-toxic and a toxic phytoplankton species in a homogeneous environment (such as a chemostat). We allow for the possibility that both species serve as prey for an herbivorous zooplankton species. We assume that the toxic phytoplankton species produces toxins that affect only its own growth (autotoxicity). The autotoxicity assumption is ecologically explained by the fact that the toxin-producing phytoplankton is not mature enough to produce toxins that will affect the growth of its nontoxic competitor. We show that, in the absence of phytotoxic interactions and nutrient recycling, our model exhibits uniform persistence. The removal rates are distinct and we use general response functions. Finally, numerical simulations are carried out to show consistency with theoretical analysis. Our model has similarities with other food-chain models. As such, our results may be relevant to a wider spectrum of population models, not just those focused on plankton. Some open problems are discussed at the end of this paper. PMID:25365603

Kengwoung-Keumo, Jean-Jacques

2014-12-01

105

Microbial population dynamics by digital in-line holographic microscopy.  

PubMed

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

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

2010-08-01

106

Evolutionary games and population dynamics: maintenance of cooperation  

E-print Network

to populations of varying densities. Keywords: evolutionary game theory; cooperation; Prisoner's DilemmaEvolutionary games and population dynamics: maintenance of cooperation in public goods games members of the population at a cost to themselves. Thus, in the absence of supporting mechanisms

Hauert, Christoph

107

Dynamic models of infectious diseases as regulators of population sizes  

Microsoft Academic Search

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

Jaime Mena-Lorcat; Herbert W. Hethcote

1992-01-01

108

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

PubMed Central

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

Hart, Edmund M.; Avilés, Leticia

2014-01-01

109

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

USGS Publications Warehouse

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.

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

2004-01-01

110

Arthropod population and community dynamics in turfgrass  

E-print Network

Non-target arthropod and nematode populations in ographics. fungal and nematode treated bermudagrass were contrasted with populations in a chlorpyrifos and an untreated control treatment. Fifty-five arthropod families or suborder, herein referred...

Wang, Yong

2012-06-07

111

Accuracy of Four Tooth Size Prediction Methods on Malay Population  

PubMed Central

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

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

2012-01-01

112

Visibility of the environmental noise modulating population dynamics.  

PubMed Central

Characterizing population fluctuations and their causes is a major theme in population ecology. The debate is on the relative merits of density-dependent and density-independent effects. One paradigm (revived by the research on global warming and its relation to long-term population data) states that fluctuations in population densities can often be accounted for by external noise. Several empirical models have been suggested to support this view. We followed this by assuming a given population skeleton dynamics (Ricker dynamics and second-order autoregressive dynamics) topped off with noise composed of low- and high-frequency components. Our aim was to determine to what extent the modulated population dynamics correlate with the noise signal. High correlations (with time-lag -1) were observed with both model categories in the region of stable dynamics, but not in the region of periodic or complex dynamics. This finding is not very sensitive to low-frequency noise. High correlations throughout the entire range of dynamics are only achievable when the impact of the noise is very high. Fitted parameter values of skeleton dynamics modulated with noise are prone to err substantially. This casts doubt as to what degree the underlying dynamics are any more recognizable after being modulated by the external noise. PMID:11052535

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

2000-01-01

113

Population Dynamics of Diploid and Hexaploid Populations of a Perennial Herb  

PubMed Central

Background and Aims Despite the recent enormous increase in the number of studies on polyploid species, no studies to date have explored the population dynamics of these taxa. It is thus not known whether the commonly reported differences in single life-history traits between taxa of different ploidy levels result in differences in population dynamics. Methods This study explores differences in single life-history traits and in the complete life cycle between populations of different ploidy levels and compares these differences with differences observed between different habitat types and years. Diploid and hexaploid populations of a perennial herb, Aster amellus, are used as the study system. Transition matrix models were used to describe the dynamics of the populations, and population growth rates, elasticity values and life-table response experiments were used to compare the dynamics between populations and years. Key Results The results indicate that between-year variation in population dynamics is much larger than variation between different ploidy levels and different habitat conditions. Significant differences exist, however, in the structure of the transition matrices, indicating that the dynamics of the different ploidy levels are different. Strong differences in probability of extinction of local populations were also found, with hexaploid populations having higher probability than diploid populations, indicating strong potential differences in persistence of these populations. Conclusions This is the first study on complete population dynamics of plants of different ploidy levels. This knowledge will help to understand the ability of new ploidy levels to spread into new areas and persist there, and the interactions of different ploidy levels in secondary contact zones. This knowledge will also contribute to understanding of interactions of different ploidy levels with other plant species or other interacting organisms such as pollinators or herbivores. PMID:17881342

Münzbergová, Zuzana

2007-01-01

114

Dynamic situation assessment and prediction (DSAP)  

NASA Astrophysics Data System (ADS)

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

Sisti, Alex F.

2003-09-01

115

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 ...

116

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

PubMed

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

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

2015-01-01

117

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

PubMed Central

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

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

2015-01-01

118

Predicting High-Speed Machining Dynamics by Substructure Analysis  

Microsoft Academic Search

The practical implementation of high-speed machining (HSM) requires accurate knowledge of the machine dynamics. We apply receptance coupling substructure analysis to the prediction of the tool point dynamic response, combining frequency response measurements of individual components through appropriate connections to determine assembly dynamics using simple vector manipulations. This paper shows that the dynamic response before and after system changes may

T. L. Schmitz; R. R. Donalson

2000-01-01

119

Territory dynamics in a sage sparrow population: are shifts in site use adaptive?  

Microsoft Academic Search

In 1981–1985, we studied territory dynamics in a southeastern Idaho sage sparrow population to evaluate the hypothesis that territory shifts represent adaptive adjustments in site use. We predicted that shifts should (1) result in changes in territory characteristics, (2) be influenced by previous reproductive success and result in greater success, and (3) decline in magnitude for individual males over time.

Kenneth L. Petersen; Louis B. Best

1987-01-01

120

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

USGS Publications Warehouse

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.

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

2007-01-01

121

Size Dependent Population Dynamics of Microtus Ochrogaster  

E-print Network

. 1965a. The study of population growth in organisms grouped by stages. Biometrics 21:1-18. . 1965*. The effects of adult emigration on populations of Lasioderma serricorne. Oikos 15:200- 210. Leslie, P. H. 1945. The use of matrices in certain...

Sauer, John R.; Slade, Norman A.

1986-06-01

122

Spatial and Temporal Dynamics of Fucoid Populations (Ascophyllum nodosum and Fucus serratus): A Comparison between Central and Range Edge Populations  

PubMed Central

Persistence of populations at range edges relies on local population dynamics and fitness, in the case of geographically isolated populations of species with low dispersal potential. Focusing on spatial variations in demography helps to predict the long-term capability for persistence of populations across the geographical range of species’ distribution. The demography of two ecological and phylogenetically close macroalgal species with different life history characteristics was investigated by using stochastic, stage-based matrix models. Populations of Ascophyllum nodosum and Fucus serratus were sampled for up to 4 years at central locations in France and at their southern range limits in Portugal. The stochastic population growth rate (?s) of A. nodosum was lower and more variable in central than in southern sites whilst for F. serratus this trend was reversed with ?s much lower and more variable in southern than in central populations. Individuals were larger in central than in southern populations for both species, which was reflected in the lower transition probabilities of individuals to larger size classes and higher probability of shrinkage in the southern populations. In both central and southern populations elasticity analysis (proportional sensitivity) of population growth rate showed that fertility elements had a small contribution to ?s that was more sensitive to changes in matrix transitions corresponding to survival. The highest elasticities were found for loop transitions in A. nodosum and for growth to larger size classes in F. serratus. Sensitivity analysis showed high selective pressure on individual growth for both species at both locations. The results of this study highlight the deterministic role of species-specific life-history traits in population demography across the geographical range of species. Additionally, this study demonstrates that individuals’ life-transitions differ in vulnerability to environmental variability and shows the importance of vegetative compared to reproductive stages for the long-term persistence of populations. PMID:24651480

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

2014-01-01

123

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

NASA Astrophysics Data System (ADS)

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.

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

2012-12-01

124

Periodically forced food-chain dynamics: model predictions and experimental validation.  

PubMed

Despite the recognition of the importance of seasonal forcing in nature, remarkably few studies have theoretically explored periodically forced community dynamics. Here we employ a novel approach called "successional state dynamics" (SSD) to model a seasonally forced predator-prey system. We first generated analytical predictions of the effects of altered seasonality on species persistence and the timing of community state transitions. We then parameterized the model using a zooplankton-phytoplankton system and tested quantitative predictions using controlled experiments. In the majority of cases, timing of zooplankton and algal population peaks matched model predictions. Decreases in growing-period length delayed algal blooms, consequently delaying peaks in zooplankton abundance. Predictions of increased probability of predator extinction at low growing-period lengths were also upheld experimentally. Our results highlight the utility of the SSD modeling approach as a framework for predicting the effects of altered seasonality on the structure and dynamics of multitrophic communities. PMID:19967865

Steiner, Christopher F; Schwaderer, Anne S; Huber, Veronika; Klausmeier, Christopher A; Litchman, Elena

2009-11-01

125

Dynamics of population rate codes in ensembles of neocortical neurons  

E-print Network

of Theoretical Physics, University of Bremen, Otto-Hahn-Alle 1, D-28334 Bremen, Germany running title: Dynamics of population rate codes corresponding author: Matthias Bethge, Institute of Theoretical Physics Otto-Hahn

Tsodyks, Misha

126

Galactic civilizations: Population dynamics and interstellar diffusion  

NASA Technical Reports Server (NTRS)

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.

Newman, W. I.; Sagan, C.

1978-01-01

127

Explaining "Noise" as Environmental Variations in Population Dynamics  

SciTech Connect

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.

Ginn, Timothy R.; Loge, Frank J.; Scheibe, Timothy D.

2007-03-01

128

Stage-Structured Population Dynamics of AEDES AEGYPTI  

NASA Astrophysics Data System (ADS)

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.

Yusoff, Nuraini; Budin, Harun; Ismail, Salemah

129

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

PubMed

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

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

2013-08-01

130

Atlantic bluefin tuna: population dynamics, ecology, fisheries and management  

Microsoft Academic Search

Both old and new information on the biology and ecology of Atlantic bluefin tuna have confronted scientists with research challenges: research needs to be connected to current stock-assessment and management issues. We review recent studies on habitat, migrations and population structure, stressing the importance of electronic tagging results in the modification of our perception of bluefin tuna population dynamics and

Jean-Marc Fromentin; Joseph E Powers

2005-01-01

131

Germination ecology and seed population dynamics of Digitalis purpurea  

Microsoft Academic Search

The germination ecology and the dynamics of the generative reproduction in populations of Digitalis purpurea L. were investigated in the field as well as in experiments. Germination of fresh seeds in the dark on moist filter paper appeared to differ between populations. These differences were eliminated when a moist natural soil functioned as germination substrate. An interaction between the spectral

J. van Baalen

1982-01-01

132

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...

133

Physiologically structured cell population dynamic models with applications to combined  

E-print Network

Physiologically structured cell population dynamic models with applications to combined drug cytotoxic drugs in the organism. An age-structured PDE cell population model has been designed with drug delivery in the general circulation targeted towards cancer cell pop- ulations, but inevitably reaching

Paris-Sud XI, Université de

134

Impact of Simian Immunodeficiency Virus Infection on Chimpanzee Population Dynamics  

Microsoft Academic Search

Like human immunodeficiency virus type 1 (HIV-1), simian immunodeficiency virus of chimpanzees (SIVcpz) can cause CD4+ T cell loss and premature death. Here, we used molecular surveillance tools and mathematical modeling to estimate the impact of SIVcpz infection on chimpanzee population dynamics. Habituated (Mitumba and Kasekela) and non-habituated (Kalande) chimpanzees were studied in Gombe National Park, Tanzania. Ape population sizes

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

2010-01-01

135

A delayed-recruitment model of population dynamics, with an application to baleen whale populations  

Microsoft Academic Search

This paper studies the delay equation xk+1=?xk+F(xk-ß), which has been employed as a model of baleen whale population dynamics. The two main questions discussed are (a) stability of equilibria, and (b) optimal exploitation policies.

Colin W. Clark

1976-01-01

136

Dynamic population mapping using mobile phone data  

PubMed Central

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

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

2014-01-01

137

Dynamic population mapping using mobile phone data.  

PubMed

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

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

2014-11-11

138

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

PubMed

A replicate long-term experiment was conducted using anaerobic digestion (AD) as a model process to determine the relative role of niche and neutral theory on microbial community assembly, and to link community dynamics to system performance. AD is performed by a complex network of microorganisms and process stability relies entirely on the synergistic interactions between populations belonging to different functional guilds. In this study, three independent replicate anaerobic digesters were seeded with the same diverse inoculum, supplied with a model substrate, ?-cellulose, and operated for 362 days at a 10-day hydraulic residence time under mesophilic conditions. Selective pressure imposed by the operational conditions and model substrate caused large reproducible changes in community composition including an overall decrease in richness in the first month of operation, followed by synchronised population dynamics that correlated with changes in reactor performance. This included the synchronised emergence and decline of distinct Ruminococcus phylotypes at day 148, and emergence of a Clostridium and Methanosaeta phylotype at day 178, when performance became stable in all reactors. These data suggest that many dynamic functional niches are predictably filled by phylogenetically coherent populations over long time scales. Neutral theory would predict that a complex community with a high degree of recognised functional redundancy would lead to stochastic changes in populations and community divergence over time. We conclude that deterministic processes may play a larger role in microbial community dynamics than currently appreciated, and under controlled conditions it may be possible to reliably predict community structural and functional changes over time. PMID:24739627

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

2014-10-01

139

Synchronization and stability in noisy population dynamics.  

PubMed

We study the stability and synchronization of predator-prey populations subjected to noise. The system is described by patches of local populations coupled by migration and predation over a neighborhood. When a single patch is considered, random perturbations tend to destabilize the populations, leading to extinction. If the number of patches is small, stabilization in the presence of noise is maintained at the expense of synchronization. As the number of patches increases, both the stability and the synchrony among patches increase. However, a residual asynchrony, large compared with the noise amplitude, seems to persist even in the limit of an infinite number of patches. Therefore, the mechanism of stabilization by asynchrony recently proposed by Abta [Phys. Rev. Lett. 98, 098104 (2007)], combining noise, diffusion, and nonlinearities, seems to be more general than first proposed. PMID:18352073

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

2008-02-01

140

Complex Population Dynamics in Mussels Arising from Density-Linked Stochasticity  

PubMed Central

Population fluctuations are generally attributed to the deterministic consequences of strong non-linear interactions among organisms, or the effects of random stochastic environmental variation superimposed upon the deterministic skeleton describing population change. Analysis of the population dynamics of the mussel Mytilus californianus taken in 16 plots over 18-years found no evidence that these processes explained observed strong fluctuations. Instead, population fluctuations arose because environmental stochasticity varied with abundance, which we term density-linked stochasticity. This phenomenon arises from biologically relevant mechanisms: recruitment variation and transmission of disturbance among neighboring individuals. Density-linked stochasticity is probably present frequently in populations, as it arises naturally from several general ecological processes, including stage structure variation with density, ontogenetic niche shifts, and local transmission of stochastic perturbations. More thoroughly characterizing and interpreting deviations from the mean behavior of a system will lead to better ecological prediction and improved insight into the important processes affecting populations and ecosystems. PMID:24086617

Wootton, J. Timothy; Forester, James D.

2013-01-01

141

Population Dynamics of Criconemoides simile on Soybean  

PubMed Central

Custer and Hood soybean cultivars were inoculated with nine levels of Criconemoides simile ranging from 300 to 20,600 nematodes per plant. Rate of reproduction decreased as inoculum level was increased beyond 900-2,000 nematodes. Final population density was influenced by both composition and level of inoculum. There was an indication that substance(s). inhibitory to larvae, accumnlated in soil in which Hood was grown for 11 months, Significant reduction of fresh weight of roots of Hood, but not Custer, occurred at population densities of 37,000 and 44,700 nematodes per plant. PMID:19295754

McGawley, E. C.; Chapman, R. A.

1982-01-01

142

POPULATION ECOLOGY Population Dynamics of Ips pini and Ips grandicollis in Red Pine  

E-print Network

POPULATION ECOLOGY Population Dynamics of Ips pini and Ips grandicollis in Red Pine Plantations pini (Say) and Ips grandicollis (Eichhoff). The predominant predators obtained were Thanasimus dubius-killingspeciesisthepine engraver, Ips pini (Say). Adult males select weakened trees as hosts and attract females; their brood

Erbilgin, Nadir

143

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

SciTech Connect

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.

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

2013-01-01

144

Laguerre-type population dynamics models  

E-print Network

, the exponential function ex is transformed into the Tricomi function C0(-x) := n=0 xn (n!)2 , the powers (x + y-exponentials en(t) are increasing convex functions for t 0, but increasing slower with respect to exp t. For this rea- son these functions are useful in order to approximate different behaviors of population growth

Bretti, Gabriella

145

INVESTIGATION Population Dynamics and Evolutionary History  

E-print Network

to patterns of phenotypic and genetic variation is important for understanding contemporary patterns of both of adaptation (significant leaf shape and flowering time clines), no population structure or neutral genetic shape Understanding the interplay between demographic and adaptive pro- cesses is important for making

Stinchcombe, John

146

Population dynamics and regulation in the cave salamander Speleomantes strinatii  

NASA Astrophysics Data System (ADS)

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.

Salvidio, Sebastiano

2007-05-01

147

Relationships between population size and loss of genetic diversity: comparisons of experimental results with theoretical predictions  

Microsoft Academic Search

Preservation of genetic diversity is of fundamental concern toconservation biology, as genetic diversity is required for evolutionarychange. Predictions of neutral theory are used to guide conservationactions, especially genetic management of captive populations ofendangered species. Loss of heterozygosity is predicted to be inverselyrelated to effective population size. However, there is controversy asto whether allozymes behave as predicted by this theory. Loss

Margaret E. Montgomery; Lynn M. Woodworth; Roderick K. Nurthen; Dean M. Gilligan; David A. Briscoe; Richard Frankham

2000-01-01

148

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

PubMed

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

Berger, Kim Murray; Conner, Mary M

2008-04-01

149

Parameterized multistate population dynamics and projections.  

PubMed

"This article reports progress on the development of a population projection process that emphasizes model selection over demographic accounting. Transparent multiregional/multistate population projections that rely on parameterized model schedules are illustrated [using data primarily from a number of developed countries, particularly Sweden], together with simple techniques that extrapolate the recent trends exhibited by the parameters of such schedules." The author notes that "the parameterized schedules condense the amount of demographic information, expressing it in a language and variables that are more readily understood by the users of the projections. In addition, they permit a concise specification of the expected temporal patterns of variation among these variables, and they allow a disaggregated focus on demographic change that otherwise would not be feasible." PMID:12155407

Rogers, A

1986-03-01

150

Dynamical Interactions Between Human Populations and Landscapes in Barrier Island Environments  

NASA Astrophysics Data System (ADS)

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.

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

2003-12-01

151

Extinction rate fragility in population dynamics  

E-print Network

Population extinction is a rare event which requires overcoming an effective barrier. We show that the extinction rate can be fragile: a small change in the system parameters leads to an exponentially strong change of the rate, with the barrier height depending on the parameters nonanalytically. General conditions of the fragility are established. The fragility is found in one of the best-known models of epidemiology, the SIS model. The analytical expressions are compared with simulations.

M. Khasin; M. I. Dykman

2009-04-10

152

Impact of transient climate change upon Grouse population dynamics in the Italian Alps  

NASA Astrophysics Data System (ADS)

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.

Pirovano, Andrea; Bocchiola, Daniele

2010-05-01

153

Reconsidering the Limits to World Population: Meta-analysis and Meta-prediction  

NSDL National Science Digital Library

This peer-reviewed article from BioScience journal is on the topic of population growth. We performed a meta-analysis on the basis of 69 past studies that have assessed a limit to the world population. The estimates of this limit range from 0.5 billion to 1 1021 billion people. A meta-analysis allows us to see what overall picture emerges when different methods, limiting factors, levels of aggregation, and data are taken into account. Limiting factors for the world population include water availability, energy, carbon, forest products, nonrenewable resources, heat removal, photosynthetic capacity, and the availability of land for food production. Methods employed in the population studies include spatial extrapolation, modeling of multiple regions, temporal extrapolation, actual supply of a resource, hypothetical modeling, and dynamic systems modeling. Many studies rely on important assumptions about the level of technology, the energy intake per person, and the available arable land. The meta-analysis employs both descriptive statistics and regression analysis. We used the findings of these analyses to propose a number of meta-estimates of limits to world population. When taking all studies into account, the best point estimate is 7.7 billion people; the lower and upper bounds, given current technology, are 0.65 billion and 98 billion people, respectively. We offer a range of other conditional estimates as well. An important conclusion of this study is that recent predictions of stabilized world population levels for 2050 exceed several of our meta-estimates of a world population limit.

JEROEN C. J. M. VAN DEN BERGH and PIET RIETVELD (;)

2004-03-01

154

SSE 2300/CE4990: System Dynamics Population Dynamics and Carrying Capacity  

E-print Network

SSE 2300/CE4990: System Dynamics Population Dynamics and Carrying Capacity April 12, 2010 at any time = P Net finite resources in the system = R0 Let per capita resource consumption = R Carrying capacity: The limiting population that the system can support given the resources: C = R0 R 1 #12

Mukherjee, Amlan

155

Unstable dynamics and population limitation in mountain hares.  

PubMed

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

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

2007-11-01

156

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

PubMed

Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (lambda(s)) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on lambda(s). The magnitude of variation in the proportion of gravid females and its effect on lambda(s) was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on lambda(s) was 4 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life-history traits in the two ecotypes, which, in turn, affect population dynamics. M-slow populations have evolved life-history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long-term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life-history evolution. PMID:21905432

Miller, David A; Clark, William R; Arnold, Stevan J; Bronikowski, Anne M

2011-08-01

157

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

USGS Publications Warehouse

Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (??s) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on ?? s. The magnitude of variation in the proportion of gravid females and its effect on ??s was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on ??s was 4- 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life-history traits in the two ecotypes, which, in turn, affect population dynamics. M-slow populations have evolved life-history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long-term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life-history evolution. ?? 2011 by the Ecological Society of America.

Miller, D.A.; Clark, W.R.; Arnold, S.J.; Bronikowski, A.M.

2011-01-01

158

Galaxy Dynamics and the PNe Population  

E-print Network

This review attempts to place the observations of extragalactic planetary nebulae in the context of galactic dynamics. From this point of view only the radial velocities of the PNe are important. We have built a specialised instrument to detect PNe in distant galaxies and measure their radial velocities in one step. This is explained in some detail, along with classical techniques for obtaining kinematic information. The review includes a vision of possible future developments in the field.

Nigel G. Douglas

2005-08-30

159

Cryptic Population Dynamics: Rapid Evolution Masks Trophic Interactions  

PubMed Central

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

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

2007-01-01

160

Stochastic population dynamics of a montane ground-dwelling squirrel.  

PubMed

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

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

2012-01-01

161

Real-Time Bioluminescent Tracking of Cellular Population Dynamics  

SciTech Connect

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.

Close, Dan [University of Tennessee, Knoxville (UTK)] [University of Tennessee, Knoxville (UTK); Sayler, Gary Steven [ORNL] [ORNL; Xu, Tingting [ORNL] [ORNL; Ripp, Steven Anthony [ORNL] [ORNL

2014-01-01

162

Temporal Dynamics and Linkage Disequilibrium in Natural Caenorhabditis elegans Populations  

PubMed Central

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

Barrière, Antoine; Félix, Marie-Anne

2007-01-01

163

The DynaMine webserver: predicting protein dynamics from sequence  

PubMed Central

Protein dynamics are important for understanding protein function. Unfortunately, accurate protein dynamics information is difficult to obtain: here we present the DynaMine webserver, which provides predictions for the fast backbone movements of proteins directly from their amino-acid sequence. DynaMine rapidly produces a profile describing the statistical potential for such movements at residue-level resolution. The predicted values have meaning on an absolute scale and go beyond the traditional binary classification of residues as ordered or disordered, thus allowing for direct dynamics comparisons between protein regions. Through this webserver, we provide molecular biologists with an efficient and easy to use tool for predicting the dynamical characteristics of any protein of interest, even in the absence of experimental observations. The prediction results are visualized and can be directly downloaded. The DynaMine webserver, including instructive examples describing the meaning of the profiles, is available at http://dynamine.ibsquare.be. PMID:24728994

Cilia, Elisa; Pancsa, Rita; Tompa, Peter; Lenaerts, Tom; Vranken, Wim F.

2014-01-01

164

Factors Affecting Dynamic Populations (title provided or enhanced by cataloger)  

NSDL National Science Digital Library

This lesson plan teaches students that populations are dynamic with identifiable characteristics and measurable growth patterns. Factors of population survival that are taught include immigration and emigration, environmental resistance, carrying capacity, and homeostasis. The lesson plan provides objectives, skills, time needed, a content outline, materials, and significant terms. The overarching goal is for students to develop an understanding of the interdependence of all organisms and the need for conserving natural resources.

165

In search of forage: predicting dynamic habitats of Mongolian gazelles using satellite-based estimates of vegetation productivity  

Microsoft Academic Search

Summary 1. Temporal variability in habitat suitability has important conservation and ecological implica- tions. In grasslands, changes in resource availability can occur at broad spatial scales and enlarge area requirements of ungulate populations, which increases their vulnerability to habitat loss and fragmentation. Understanding and predicting these dynamics, although critical, has received little attention so far. 2. We investigated habitat dynamics

Thomas Mueller; Kirk A. Olson; Todd K. Fuller; George B. Schaller; Martyn G. Murray; Peter Leimgruber

2008-01-01

166

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

PubMed Central

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

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

2012-01-01

167

Global Population Dynamics and Hot Spots of Response to Climate Change  

NSDL National Science Digital Library

Understanding how biotic and abiotic factors influence the abundance and distribution of organisms has become more important with the growing awareness of the ecological consequences of climate change. In this article, we outline an approach that complements bioclimatic envelope modeling in quantifying the effects of climate change at the species level. The global population dynamics approach, which relies on distribution-wide, data-driven analyses of dynamics, goes beyond quantifying biotic interactions in population dynamics to identify hot spots of response to climate change. Such hot spots highlight populations or locations within speciesâ distributions that are particularly sensitive to climate change, and identification of them should focus conservation and management efforts. An important result of the analyses highlighted here is pronounced variation at the species level in the strength and direction of population responses to warming. Although this variation complicates species-level predictions of responses to climate change, the global population dynamics approach may improve our understanding of the complex implications of climate change for species persistence or extinction.

Eric Post (Pennsylvania State University;)

2009-06-01

168

Dynamic knee loads during gait predict proximal tibial bone distribution  

Microsoft Academic Search

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

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

1998-01-01

169

Amplification Dynamics: Predicting the Effect of HIV on Tuberculosis Outbreaks  

E-print Network

Amplification Dynamics: Predicting the Effect of HIV on Tuberculosis Outbreaks *Travis C. Porco, U.S.A. Summary: HIV affects the pathogenesis and the transmission of Mycobacterium tuberculosis. We the probability and the expected severity of tuberculosis out- breaks. Our predictions reveal that an HIV epidemic

Blower, Sally

170

Dynamic modularity in protein interaction networks predicts breast cancer outcome  

E-print Network

cells drives phenotypic transformations that directly affect disease outcome. Here we examineDynamic modularity in protein interaction networks predicts breast cancer outcome Ian W Taylor1 the dynamic structure of the human protein interaction network (interactome) to determine whether changes

Morris, Quaid

171

Predicting Reading Ability for Bilingual Latino Children Using Dynamic Assessment  

ERIC Educational Resources Information Center

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,…

Petersen, Douglas B.; Gillam, Ronald B.

2015-01-01

172

Guarded execution and branch prediction in dynamic ILP processors  

Microsoft Academic Search

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

Dionisios N. Pnevmatikatos; Gurindar S. Sohi

1994-01-01

173

Guarded Execution and Branch Prediction in Dynamic ILP Processors  

Microsoft Academic Search

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

Dionisios N. Pnevmatikatos; Gurindar S. Sohi

174

Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids  

PubMed Central

Inactivation of ?-lactam antibiotics by resistant bacteria is a ‘cooperative' behavior that may allow sensitive bacteria to survive antibiotic treatment. However, the factors that determine the fraction of resistant cells in the bacterial population remain unclear, indicating a fundamental gap in our understanding of how antibiotic resistance evolves. Here, we experimentally track the spread of a plasmid that encodes a ?-lactamase enzyme through the bacterial population. We find that independent of the initial fraction of resistant cells, the population settles to an equilibrium fraction proportional to the antibiotic concentration divided by the cell density. A simple model explains this behavior, successfully predicting a data collapse over two orders of magnitude in antibiotic concentration. This model also successfully predicts that adding a commonly used ?-lactamase inhibitor will lead to the spread of resistance, highlighting the need to incorporate social dynamics into the study of antibiotic resistance. PMID:23917989

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

2013-01-01

175

Heterogeneous Structure of Stem Cells Dynamics: Statistical Models and Quantitative Predictions  

NASA Astrophysics Data System (ADS)

Understanding stem cell (SC) population dynamics is essential for developing models that can be used in basic science and medicine, to aid in predicting cells fate. These models can be used as tools e.g. in studying patho-physiological events at the cellular and tissue level, predicting (mal)functions along the developmental course, and personalized regenerative medicine. Using time-lapsed imaging and statistical tools, we show that the dynamics of SC populations involve a heterogeneous structure consisting of multiple sub-population behaviors. Using non-Gaussian statistical approaches, we identify the co-existence of fast and slow dividing subpopulations, and quiescent cells, in stem cells from three species. The mathematical analysis also shows that, instead of developing independently, SCs exhibit a time-dependent fractal behavior as they interact with each other through molecular and tactile signals. These findings suggest that more sophisticated models of SC dynamics should view SC populations as a collective and avoid the simplifying homogeneity assumption by accounting for the presence of more than one dividing sub-population, and their multi-fractal characteristics.

Bogdan, Paul; Deasy, Bridget M.; Gharaibeh, Burhan; Roehrs, Timo; Marculescu, Radu

2014-04-01

176

Heterogeneous structure of stem cells dynamics: statistical models and quantitative predictions.  

PubMed

Understanding stem cell (SC) population dynamics is essential for developing models that can be used in basic science and medicine, to aid in predicting cells fate. These models can be used as tools e.g. in studying patho-physiological events at the cellular and tissue level, predicting (mal)functions along the developmental course, and personalized regenerative medicine. Using time-lapsed imaging and statistical tools, we show that the dynamics of SC populations involve a heterogeneous structure consisting of multiple sub-population behaviors. Using non-Gaussian statistical approaches, we identify the co-existence of fast and slow dividing subpopulations, and quiescent cells, in stem cells from three species. The mathematical analysis also shows that, instead of developing independently, SCs exhibit a time-dependent fractal behavior as they interact with each other through molecular and tactile signals. These findings suggest that more sophisticated models of SC dynamics should view SC populations as a collective and avoid the simplifying homogeneity assumption by accounting for the presence of more than one dividing sub-population, and their multi-fractal characteristics. PMID:24769917

Bogdan, Paul; Deasy, Bridget M; Gharaibeh, Burhan; Roehrs, Timo; Marculescu, Radu

2014-01-01

177

Optimisation of cancer drug treatments using cell population dynamics  

E-print Network

Optimisation of cancer drug treatments using cell population dynamics Fr´ed´erique Billy1 , Jean. The constraints at stake, met everyday in the clinic of cancers, are related mainly to resistance to treatment models used in cancer treatment in the last decades, together with the biological phenomena that can

Paris-Sud XI, Université de

178

Binary populations and stellar dynamics in young clusters  

E-print Network

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

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

2008-01-17

179

Binary populations and stellar dynamics in young clusters  

E-print Network

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

Vanbeveren, D; Van Bever, J; Mennekens, N

2008-01-01

180

Interactions between Predation and Resources Shape Zooplankton Population Dynamics  

PubMed Central

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

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

2011-01-01

181

Dynamical Quorum Sensing and Synchronization in Large Populations  

E-print Network

Dynamical Quorum Sensing and Synchronization in Large Populations of Chemical Oscillators Annette F oscillate in nearly complete synchrony (12). This type of transition is much like quorum-sensing transitions solution (15). Many examples of quorum- sensing transitions have been found, such as the appearance

Showalter, Kenneth

182

The HIV coreceptor switch: a population dynamical perspective  

E-print Network

for CCR5 to a preference for CXCR4 in w50% of infected individuals. The change in coreceptor usage resolved, the population dynamical mechanisms leading to the emergence of CXCR4-using HIV variants in some receptors CCR5 and CXCR4 [1]. Over the course of the infection, the coreceptor usage of HIV changes from

Bonhoeffer, Sebastian

183

Binary Populations and Stellar Dynamics in Young Clusters  

NASA Astrophysics Data System (ADS)

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

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

2008-06-01

184

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...

185

A Diffusion Model in Population Genetics with Mutation and Dynamic  

E-print Network

A Diffusion Model in Population Genetics with Mutation and Dynamic Fitness Mike O'Leary Department of Mathematics Towson University May 24, 2008 Mike O'Leary (Towson University) A Diffusion Model in Genetics May determine the long-time behavior of the total genetic variance? Portions of this work are joint with Judith

O'Leary, Michael

186

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

PubMed Central

In oncology trials, overall survival (OS) is considered the most reliable and preferred endpoint to evaluate the benefit of drug treatment. Other relevant variables are also collected from patients for a given drug and its indication, and it is important to characterize the dynamic effects and links between these variables in order to improve the speed and efficiency of clinical oncology drug development. However, the drug-induced effects and causal relationships are often difficult to interpret because of temporal differences. To address this, population pharmacokinetic–pharmacodynamic (PKPD) modelling and parametric time-to-event (TTE) models are becoming more frequently applied. Population PKPD and TTE models allow for exploration towards describing the data, understanding the disease and drug action over time, investigating relevance of biomarkers, quantifying patient variability and in designing successful trials. In addition, development of models characterizing both desired and adverse effects in a modelling framework support exploration of risk-benefit of different dosing schedules. In this review, we have summarized population PKPD modelling analyses describing tumour, tumour marker and biomarker responses, as well as adverse effects, from anticancer drug treatment data. Various model-based metrics used to drive PD response and predict OS for oncology drugs and their indications are also discussed. PMID:24134068

Bender, Brendan C; Schindler, Emilie; Friberg, Lena E

2015-01-01

187

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

NASA Technical Reports Server (NTRS)

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.

Holms, A. G.

1974-01-01

188

Assessment of algorithms for predicting drug–drug interactions via inhibition mechanisms: comparison of dynamic and static models  

PubMed Central

AIMS Static and dynamic models (incorporating the time course of the inhibitor) were assessed for their ability to predict drug–drug interactions (DDIs) using a population-based ADME simulator (Simcyp®V8). The impact of active metabolites, dosing time and the ability to predict inter-individual variability in DDI magnitude were investigated using the dynamic model. METHODS Thirty-five in vivo DDIs involving azole inhibitors and benzodiazepines were predicted using the static and dynamic model; both models were employed within Simcyp for consistency in parameters. Simulations comprised of 10 trials with matching population demographics and dosage regimen to the in vivo studies. Predictive utility of the static and dynamic model was assessed relative to the inhibitor or victim drug investigated. RESULTS Use of the dynamic and static models resulted in comparable prediction success, with 71 and 77% of DDIs predicted within two-fold, respectively. Over 40% of strong DDIs (>five-fold AUC increase) were under-predicted by both models. Incorporation of the itraconazole metabolite into the dynamic model resulted in increased prediction accuracy of strong DDIs (80% within two-fold). Bias and imprecision in prediction of triazolam DDIs were higher in comparison with midazolam and alprazolam; >50% of triazolam DDIs were under-predicted regardless of the model used. Predicted inter-individual variability in the AUC ratio (coefficient of variation of 45%) was consistent with the observed variability (50%). CONCLUSIONS High prediction accuracy was observed using both the Simcyp dynamic and static models. The differences observed with the dose staggering and the incorporation of active metabolite highlight the importance of these variables in DDI prediction. PMID:21143503

Guest, Eleanor J; Rowland-Yeo, Karen; Rostami-Hodjegan, Amin; Tucker, Geoffrey T; Houston, J Brian; Galetin, Aleksandra

2011-01-01

189

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

NASA Astrophysics Data System (ADS)

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

Sakaguchi, Hidetsugu; Maeyama, Satomi

2013-02-01

190

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

E-print Network

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.

Hidetsugu Sakaguchi; Satomi Maeyama

2013-02-05

191

Dynamic Cruising Range Prediction for Electric Vehicles  

Microsoft Academic Search

\\u000a Battery electric vehicles (BEVs) require new driver information systems. We anticipate a new integrated and networked information\\u000a system class, combining data input from central car systems, drivers’ behaviour and environmental parameters. By introducing\\u000a the system mapZero we propose an OEM-independent cruising range prediction system, which combines measurement and GIS-system\\u000a based calculations on the ride (see Fig. 1). For the first

Peter Conradi; Philipp Bouteiller; Sascha Hanßen

192

Metamodels for Transdisciplinary Analysis of Wildlife Population Dynamics  

PubMed Central

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

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

2013-01-01

193

Modeling structured population dynamics using data from unmarked individuals.  

PubMed

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. PMID:24649642

Zipkin, Elise F; Thorson, James T; See, Kevin; Lynch, Heather J; Grant, Evan H Campbell; Kanno, Yoichiro; Chandler, Richard B; Letcher, Benjamin H; Royle, J Andrew

2014-01-01

194

Identifying interactions among salmon populations from observed dynamics.  

PubMed

A simple direct correlation analysis of individual counts between different populations often fails to characterize the true nature of population interactions; however, the most common data type available for population studies is count data, and one of the most important objectives in population and community ecology is to identify interactions among populations. Here, I examine the dynamics of the spawning abundance of fall-run chinook salmon spawning within the California Central Valley and the Klamath Basin, California, and the Columbia River Basin, Oregon. I analyzed multiple time series from each watershed using a multivariate time-series technique called maximum autocorrelation factor analysis. This technique was used for finding common underlying trends in escapement abundance within each watershed. These trends were further investigated to identify potential resource-mediated interactions among the three groups of salmon. Each group is affected by multiple trends that are likely to be affected by environmental factors. In addition, some of the trends are coherent with each other, and the differences in population dynamics originate from variations in the relative importance of these trends among the three watershed groups. PMID:18376540

Fujiwara, Masami

2008-01-01

195

Population dynamics and climate change: what are the links?  

PubMed

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

Stephenson, Judith; Newman, Karen; Mayhew, Susannah

2010-06-01

196

Ecological constraints influence the emergence of cooperative breeding when population dynamics determine the fitness of helpers.  

PubMed

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

McLeod, David V; Wild, Geoff

2013-11-01

197

Nonequilibrium Population Dynamics of Phenotype Conversion of Cancer Cells  

PubMed Central

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

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

2014-01-01

198

Evolutionary dynamics of group interactions on structured populations: a review  

PubMed Central

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

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

2013-01-01

199

Nonequilibrium population dynamics of phenotype conversion of cancer cells.  

PubMed

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

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

2014-01-01

200

Borrowing Information across Populations in Estimating Positive and Negative Predictive Values  

PubMed Central

Summary A marker's capacity to predict risk of a disease depends on disease prevalence in the target population and its classification accuracy, i.e. its ability to discriminate diseased subjects from non-diseased subjects. The latter is often considered an intrinsic property of the marker; it is independent of disease prevalence and hence more likely to be similar across populations than risk prediction measures. In this paper, we are interested in evaluating the population-specific performance of a risk prediction marker in terms of positive predictive value (PPV) and negative predictive value (NPV) at given thresholds, when samples are available from the target population as well as from another population. A default strategy is to estimate PPV and NPV using samples from the target population only. However, when the marker's classification accuracy as characterized by a specific point on the receiver operating characteristics (ROC) curve is similar across populations, borrowing information across populations allows increased efficiency in estimating PPV and NPV. We develop estimators that optimally combine information across populations. We apply this methodology to a cross-sectional study where we evaluate PCA3 as a risk prediction marker for prostate cancer among subjects with or without previous negative biopsy. PMID:22021938

Huang, Ying; Fong, Youyi; Wei, John; Feng, Ziding

2011-01-01

201

Predicting Predatory Behavior in a Population of Incarcerated Young Offenders  

Microsoft Academic Search

Predatory relationships are characterized by violence or threats of violence and their prediction and prevention are matters of critical importance within the custodial setting. In an attempt to predict predatory behavior, 251 consecutive admissions to a secure custody Young Offenders Unit in a maximum security detention centre were administered the Young Offender-Level of Service Inventory (YO-LSI). Subjects ranged in age

IAN W. SHIELDS; DAVID J. SIMOURD

1991-01-01

202

How predictable : modeling rates of change in individuals and populations  

E-print Network

This thesis develops methodologies to measure rates of change in individual human behavior, and to capture statistical regularities in change at the population level, in three pieces: i) a model of individual rate of change ...

Krumme, Katherine

2013-01-01

203

Population dynamics of species-rich ecosystems: the mixture of matrix population models approach  

E-print Network

-rich ecosystems, population dynamics Introduction The conservation of animal and plant species and their biologi popula- tion demography in the context of species invasion (Hooten et al. 2007; Sebert-Cuvillier et al, tropical marine fish or coral reefs, high diversity implies that the sample size for most species

Rossi, Vivien

204

Second Cancers After Fractionated Radiotherapy: Stochastic Population Dynamics Effects  

NASA Technical Reports Server (NTRS)

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.

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

2007-01-01

205

Rethinking the logistic approach for population dynamics of mutualistic interactions.  

PubMed

Mutualistic communities have an internal structure that makes them resilient to external perturbations. Late research has focused on their stability and the topology of the relations between the different organisms to explain the reasons of the system robustness. Much less attention has been invested in analyzing the systems dynamics. The main population models in use are modifications of the r-K formulation of logistic equation with additional terms to account for the benefits produced by the interspecific interactions. These models have shortcomings as the so-called r-K formulation diverges under some conditions. In this work, we introduce a model for population dynamics under mutualism that preserves the original logistic formulation. It is mathematically simpler than the widely used type II models, although it shows similar complexity in terms of fixed points and stability of the dynamics. We perform an analytical stability analysis and numerical simulations to study the model behavior in general interaction scenarios including tests of the resilience of its dynamics under external perturbations. Despite its simplicity, our results indicate that the model dynamics shows an important richness that can be used to gain further insights in the dynamics of mutualistic communities. PMID:25173080

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

2014-12-21

206

Modeling Tools Predict Flow in Fluid Dynamics  

NASA Technical Reports Server (NTRS)

"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."

2010-01-01

207

Multi-step-ahead prediction using dynamic recurrent neural networks.  

PubMed

A method for the development of empirical predictive models for complex processes is presented. The models are capable of performing accurate multi-step-ahead (MS) predictions, while maintaining acceptable single-step-ahead (SS) prediction accuracy. Such predictors find applications in model predictive controllers and in fault diagnosis systems. The proposed method makes use of dynamic recurrent neural networks in the form of a nonlinear infinite impulse response (IIR) filter. A learning algorithm is presented, which is based on a dynamic gradient descent approach. The effectiveness of the method for accurate MS prediction is tested on an artificial problem and on a complex, open-loop unstable process. Comparative results are presented with polynomial Nonlinear AutoRegressive with eXogeneous (NARX) predictors, and with recurrent networks trained using teacher forcing. Validation studies indicate that excellent generalization is obtained for the range of operational dynamics studied. The research demonstrates that the proposed network architecture and the associated learning algorithm are quite effective in modeling the dynamics of complex processes and performing accurate MS predictions. PMID:11152208

Parlos, A G; Rais, O T; Atiya, A F

2000-09-01

208

Dynamics of a combined medea-underdominant population transformation system  

PubMed Central

Background Transgenic constructs intended to be stably established at high frequencies in wild populations have been demonstrated to “drive” from low frequencies in experimental insect populations. Linking such population transformation constructs to genes which render them unable to transmit pathogens could eventually be used to stop the spread of vector-borne diseases like malaria and dengue. Results Generally, population transformation constructs with only a single transgenic drive mechanism have been envisioned. Using a theoretical modelling approach we describe the predicted properties of a construct combining autosomal Medea and underdominant population transformation systems. We show that when combined they can exhibit synergistic properties which in broad circumstances surpass those of the single systems. Conclusion With combined systems, intentional population transformation and its reversal can be achieved readily. Combined constructs also enhance the capacity to geographically restrict transgenic constructs to targeted populations. It is anticipated that these properties are likely to be of particular value in attracting regulatory approval and public acceptance of this novel technology. PMID:24884575

2014-01-01

209

Coupling in goshawk and grouse population dynamics in Finland.  

PubMed

Different prey species can vary in their significance to a particular predator. In the simplest case, the total available density or biomass of a guild of several prey species might be most relevant to the predator, but behavioural and ecological traits of different prey species can alter the picture. We studied the population dynamics of a predator-prey setting in Finland by fitting first-order log-linear vector autoregressive models to long-term count data from active breeding sites of the northern goshawk (Accipiter gentilis; 1986-2009), and to three of its main prey species (1983-2010): hazel grouse (Bonasa bonasia), black grouse (Tetrao tetrix) and capercaillie (T. urogallus), which belong to the same forest grouse guild and show synchronous fluctuations. Our focus was on modelling the relative significance of prey species and estimating the tightness of predator-prey coupling in order to explain the observed population dynamics, simultaneously accounting for effects of density dependence, winter severity and spatial correlation. We established nine competing candidate models, where different combinations of grouse species affect goshawk dynamics with lags of 1-3 years. Effects of goshawk on grouse were investigated using one model for each grouse species. The most parsimonious model for goshawk indicated separate density effects of hazel grouse and black grouse, and different effects with lags of 1 and 3 years. Capercaillie showed no effects on goshawk populations, while the effect of goshawk on grouse was clearly negative only in capercaillie. Winter severity had significant adverse effects on goshawk and hazel grouse populations. In combination, large-scale goshawk-grouse population dynamics are coupled, but there are no clear mutual effects for any of the individual guild members. In a broader context, our study suggests that pooling data on closely related, synchronously fluctuating prey species can result in the loss of relevant information, rather than increased model parsimony. PMID:22961371

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

2013-04-01

210

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

PubMed

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

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

2010-01-01

211

From Single-Cell Genetic Architecture to Cell Population Dynamics: Quantitatively Decomposing the Effects of Different Population  

E-print Network

From Single-Cell Genetic Architecture to Cell Population Dynamics: Quantitatively Decomposing, Texas ABSTRACT Phenotypic cell-to-cell variability or cell population heterogeneity originates from two fundamentally different sources: unequal partitioning of cellular material at cell division and stochastic

Bernard, Samuel

212

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

PubMed Central

Understanding the endogenous factors that drive the population dynamics of malaria mosquitoes will facilitate more accurate predictions about vector control effectiveness and our ability to destabilize the growth of either low- or high-density insect populations. We assessed whether variation in phenotypic traits predict the dynamics of Anopheles gambiae sensu lato mosquitoes, the most important vectors of human malaria. Anopheles gambiae dynamics were monitored over a six-month period of seasonal growth and decline. The population exhibited density-dependent feedback, with the carrying capacity being modified by rainfall (97% wAICc support). The individual phenotypic expression of the maternal (p = 0.0001) and current (p = 0.040) body size positively influenced population growth. Our field-based evidence uniquely demonstrates that individual fitness can have population-level impacts and, furthermore, can mitigate the impact of exogenous drivers (e.g. rainfall) in species whose reproduction depends upon it. Once frontline interventions have suppressed mosquito densities, attempts to eliminate malaria with supplementary vector control tools may be attenuated by increased population growth and individual fitness. PMID:21389034

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

2011-01-01

213

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

PubMed

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

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

214

Structural Drift: The Population Dynamics of Sequential Learning  

E-print Network

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

Crutchfield, James P

2010-01-01

215

Structural Drift: The Population Dynamics of Sequential Learning  

PubMed Central

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

Crutchfield, James P.; Whalen, Sean

2012-01-01

216

Limits and Uses of Dynamical Predictions of Meteorological Drought  

NASA Astrophysics Data System (ADS)

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

Lyon, B.

2012-12-01

217

Dispersal differences predict population genetic structure in Mormon crickets  

Microsoft Academic Search

Research investigating the geographical context of speciation has primarily focused on abiotic factors such as the role of Pleistocene glacial cycles, or geotectonic events. Few study systems allow a direct comparison of how biological differences, such as dispersal beha- viour, affect population genetic structure of organisms that were subdivided during the Pleistocene. Mormon crickets exist in solitary and gregarious 'phases',

NATHAN W. B AILEY; DARRYL T. G WYNNE; MICHAEL G. R ITCHIE

2007-01-01

218

Lineage grammars: describing, simulating and analyzing population dynamics  

PubMed Central

Background Precise description of the dynamics of biological processes would enable the mathematical analysis and computational simulation of complex biological phenomena. Languages such as Chemical Reaction Networks and Process Algebras cater for the detailed description of interactions among individuals and for the simulation and analysis of ensuing behaviors of populations. However, often knowledge of such interactions is lacking or not available. Yet complete oblivion to the environment would make the description of any biological process vacuous. Here we present a language for describing population dynamics that abstracts away detailed interaction among individuals, yet captures in broad terms the effect of the changing environment, based on environment-dependent Stochastic Tree Grammars (eSTG). It is comprised of a set of stochastic tree grammar transition rules, which are context-free and as such abstract away specific interactions among individuals. Transition rule probabilities and rates, however, can depend on global parameters such as population size, generation count, and elapsed time. Results We show that eSTGs conveniently describe population dynamics at multiple levels including cellular dynamics, tissue development and niches of organisms. Notably, we show the utilization of eSTG for cases in which the dynamics is regulated by environmental factors, which affect the fate and rate of decisions of the different species. eSTGs are lineage grammars, in the sense that execution of an eSTG program generates the corresponding lineage trees, which can be used to analyze the evolutionary and developmental history of the biological system under investigation. These lineage trees contain a representation of the entire events history of the system, including the dynamics that led to the existing as well as to the extinct individuals. Conclusions We conclude that our suggested formalism can be used to easily specify, simulate and analyze complex biological systems, and supports modular description of local biological dynamics that can be later used as “black boxes” in a larger scope, thus enabling a gradual and hierarchical definition and simulation of complex biological systems. The simple, yet robust formalism enables to target a broad class of stochastic dynamic behaviors, especially those that can be modeled using global environmental feedback regulation rather than direct interaction between individuals. PMID:25047682

2014-01-01

219

Predicting reading ability for bilingual latino children using dynamic assessment.  

PubMed

This study investigated the predictive validity of a dynamic assessment designed to evaluate later risk for reading difficulty in bilingual Latino children at risk for language impairment. During kindergarten, 63 bilingual Latino children completed a dynamic assessment nonsense-word recoding task that yielded pretest to posttest gain scores, residuum gain scores, and modifiability scores. At the end of first grade, the same participants completed criterion reading measures of word identification, decoding, and reading fluency. The dynamic assessment yielded high classification accuracy, with sensitivity and specificity at or above 80% for all three criterion reading measures, including 100% sensitivity for two out of the three first-grade measures. The dynamic assessment used in this study has promise as a means for predicting first-grade word-level reading ability in Latino, bilingual children. PMID:23629729

Petersen, Douglas B; Gillam, Ronald B

2015-01-01

220

Predicting catastrophes in nonlinear dynamical systems by compressive sensing  

PubMed Central

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

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

2013-01-01

221

Nonlinear dynamics and predictability in the atmospheric sciences  

SciTech Connect

Systematic applications of nonlinear dynamics to studies of the atmosphere and climate are reviewed for the period 1987-1990. Problems discussed include paleoclimatic applications, low-frequency atmospheric variability, and interannual variability of the ocean-atmosphere system. Emphasis is placed on applications of the successive bifurcation approach and the ergodic theory of dynamical systems to understanding and prediction of intraseasonal, interannual, and Quaternary climate changes.

Ghil, M.; Kimoto, M.; Neelin, J.D. (USAF, Geophysics Laboratory, Hanscom AFB, MA (United States))

1991-01-01

222

Non-linearity and heterogeneity in modeling of population dynamics.  

PubMed

The study of population growth reveals that the behaviors that follow the power law appear in numerous biological, demographical, ecological, physical and other contexts. Parabolic models appear to be realistic approximations of real-life replicator systems, while hyperbolic models were successfully applied to problems of global demography and appear relevant in quasispecies and hypercycle modeling. Nevertheless, it is not always clear why non-exponential growth is observed empirically and what possible origins of the non-exponential models are. In this paper the power equation is considered within the frameworks of inhomogeneous population models; it is proven that any power equation describes the total population size of a frequency-dependent model with Gamma-distributed Malthusian parameter. Additionally, any super-exponential equation describes the dynamics of inhomogeneous Malthusian density-dependent population model. All statistical characteristics of the underlying inhomogeneous models are computed explicitly. The results of this analysis show that population heterogeneity can be a reasonable explanation for power law accurately describing total population growth. PMID:25262656

Karev, Georgy P

2014-12-01

223

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

NASA Technical Reports Server (NTRS)

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.

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

1996-01-01

224

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

PubMed

Radon plays an important role for human exposure to natural sources of ionizing radiation. The aim of this article is to compare two approaches to estimate mean radon exposure in the Swiss population: model-based predictions at individual level and measurement-based predictions based on measurements aggregated at municipality level. A nationwide model was used to predict radon levels in each household and for each individual based on the corresponding tectonic unit, building age, building type, soil texture, degree of urbanization, and floor. Measurement-based predictions were carried out within a health impact assessment on residential radon and lung cancer. Mean measured radon levels were corrected for the average floor distribution and weighted with population size of each municipality. Model-based predictions yielded a mean radon exposure of the Swiss population of 84.1 Bq/m(3) . Measurement-based predictions yielded an average exposure of 78 Bq/m(3) . This study demonstrates that the model- and the measurement-based predictions provided similar results. The advantage of the measurement-based approach is its simplicity, which is sufficient for assessing exposure distribution in a population. The model-based approach allows predicting radon levels at specific sites, which is needed in an epidemiological study, and the results do not depend on how the measurement sites have been selected. PMID:23464847

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

2013-10-01

225

Development of paradigms for the dynamics of structured populations  

SciTech Connect

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.

Not Available

1994-10-01

226

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

PubMed

New DNA-based predictive tests for physical characteristics and inference of ancestry are highly informative tools that are being increasingly used in forensic genetic analysis. Two eye colour prediction models: a Bayesian classifier - Snipper and a multinomial logistic regression (MLR) system for the Irisplex assay, have been described for the analysis of unadmixed European populations. Since multiple SNPs in combination contribute in varying degrees to eye colour predictability in Europeans, it is likely that these predictive tests will perform in different ways amongst admixed populations that have European co-ancestry, compared to unadmixed Europeans. In this study we examined 99 individuals from two admixed South American populations comparing eye colour versus ancestry in order to reveal a direct correlation of light eye colour phenotypes with European co-ancestry in admixed individuals. Additionally, eye colour prediction following six prediction models, using varying numbers of SNPs and based on Snipper and MLR, were applied to the study populations. Furthermore, patterns of eye colour prediction have been inferred for a set of publicly available admixed and globally distributed populations from the HGDP-CEPH panel and 1000 Genomes databases with a special emphasis on admixed American populations similar to those of the study samples. PMID:25051225

Freire-Aradas, A; Ruiz, Y; Phillips, C; Maroñas, O; Söchtig, J; Tato, A Gómez; Dios, J Álvarez; de Cal, M Casares; Silbiger, V N; Luchessi, A D; Luchessi, A D; Chiurillo, M A; Carracedo, Á; Lareu, M V

2014-11-01

227

A novel dynamic update framework for epileptic seizure prediction.  

PubMed

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

Han, Min; Ge, Sunan; Wang, Minghui; Hong, Xiaojun; Han, Jie

2014-01-01

228

A Novel Dynamic Update Framework for Epileptic Seizure Prediction  

PubMed Central

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

Wang, Minghui; Hong, Xiaojun; Han, Jie

2014-01-01

229

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...

230

Evolutionary dynamics of social dilemmas in structured heterogeneous populations  

NASA Astrophysics Data System (ADS)

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. complex networks | evolution of cooperation

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

2006-02-01

231

Populations dynamics of Australorbis glabratus in Puerto Rico  

PubMed Central

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

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

1962-01-01

232

Connection between dynamically derived IMF normalisation and stellar populations  

E-print Network

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 w...

McDermid, Richard M

2015-01-01

233

VCGDB: a dynamic genome database of the Chinese population  

PubMed Central

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

2014-01-01

234

Calculation of Disease Dynamics in a Population of Households  

PubMed Central

Early mathematical representations of infectious disease dynamics assumed a single, large, homogeneously mixing population. Over the past decade there has been growing interest in models consisting of multiple smaller subpopulations (households, workplaces, schools, communities), with the natural assumption of strong homogeneous mixing within each subpopulation, and weaker transmission between subpopulations. Here we consider a model of SIRS (susceptible-infectious-recovered-susceptible) infection dynamics in a very large (assumed infinite) population of households, with the simplifying assumption that each household is of the same size (although all methods may be extended to a population with a heterogeneous distribution of household sizes). For this households model we present efficient methods for studying several quantities of epidemiological interest: (i) the threshold for invasion; (ii) the early growth rate; (iii) the household offspring distribution; (iv) the endemic prevalence of infection; and (v) the transient dynamics of the process. We utilize these methods to explore a wide region of parameter space appropriate for human infectious diseases. We then extend these results to consider the effects of more realistic gamma-distributed infectious periods. We discuss how all these results differ from standard homogeneous-mixing models and assess the implications for the invasion, transmission and persistence of infection. The computational efficiency of the methodology presented here will hopefully aid in the parameterisation of structured models and in the evaluation of appropriate responses for future disease outbreaks. PMID:20305791

Ross, Joshua V.; House, Thomas; Keeling, Matt J.

2010-01-01

235

Interacting trophic forcing and the population dynamics of herring.  

PubMed

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

Lindegren, Martin; Ostman, Orjan; Gårdmark, Anna

2011-07-01

236

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

PubMed Central

Studying physiology and pathophysiology over a broad population for long periods of time is difficult primarily because collecting human physiologic data can be intrusive, dangerous, and expensive. One solution is to use data that have been collected for a different purpose. Electronic health record (EHR) data promise to support the development and testing of mechanistic physiologic models on diverse populations and allow correlation with clinical outcomes, but limitations in the data have thus far thwarted such use. For example, using uncontrolled population-scale EHR data to verify the outcome of time dependent behavior of mechanistic, constructive models can be difficult because: (i) aggregation of the population can obscure or generate a signal, (ii) there is often no control population with a well understood health state, and (iii) diversity in how the population is measured can make the data difficult to fit into conventional analysis techniques. This paper shows that it is possible to use EHR data to test a physiological model for a population and over long time scales. Specifically, a methodology is developed and demonstrated for testing a mechanistic, time-dependent, physiological model of serum glucose dynamics with uncontrolled, population-scale, physiological patient data extracted from an EHR repository. It is shown that there is no observable daily variation the normalized mean glucose for any EHR subpopulations. In contrast, a derived value, daily variation in nonlinear correlation quantified by the time-delayed mutual information (TDMI), did reveal the intuitively expected diurnal variation in glucose levels amongst a random population of humans. Moreover, in a population of continuously (tube) fed patients, there was no observable TDMI-based diurnal signal. These TDMI-based signals, via a glucose insulin model, were then connected with human feeding patterns. In particular, a constructive physiological model was shown to correctly predict the difference between the general uncontrolled population and a subpopulation whose feeding was controlled. PMID:23272040

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

2012-01-01

237

Population dynamics of Microtus pennsylvanicus in corridor-linked patches  

USGS Publications Warehouse

Corridors have become a key issue in the discussion of conservation planning: however, few empirical data exist on the use of corridors and their effects on population dynamics. The objective of this replicated, population level, capture-re-capture experiment on meadow voles was to estimate and compare population characteristics of voles between (1) corridor-linked fragments, (2) isolated or non-linked fragments, and (3) unfragmented areas. We conducted two field experiments involving 22600 captures of 5700 individuals. In the first, the maintained corridor study, corridors were maintained at the time of fragmentation, and in the second, the constructed corridor study, we constructed corridors between patches that had been fragmented for some period of time. We applied multistate capture-recapture models with the robust design to estimate adult movement and survival rates, population size, temporal variation in population size, recruitment, and juvenile survival rates. Movement rates increased to a greater extent on constructed corridor-linked grids than on the unfragmented or non-linked fragmented grids between the pre- and post-treatment periods. We found significant differences in local survival on the treated (corridor-linked) grids compared to survival on the fragmented and unfragmented grids between the pre- and post-treatment periods. We found no clear pattern of treatment effects on population size or recruitment in either study. However, in both studies, we found that unfragmented grids were more stable than the fragmented grids based on lower temporal variability in population size. To our knowledge, this is the first experimental study demonstrating that corridors constructed between existing fragmented populations can indeed cause increases in movement and associated changes in demography, supporting the use of constructed corridors for this purpose in conservation biology.

Coffman, C.J.; Nichols, J.D.; Pollock, K.H.

2001-01-01

238

Predicting dynamic performance limits for servosystems with saturating nonlinearities  

NASA Technical Reports Server (NTRS)

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.

Webb, J. A., Jr.; Blech, R. A.

1979-01-01

239

Dynamic bifurcations for predictability of climate tipping events  

NASA Astrophysics Data System (ADS)

Despite recent advances in understanding of the nonlinear processes responsible for changes in the climate system predicting the future abrupt climate changes remains an outstanding scientific challenge of special importance for the society. Better understanding of nonlinear mechanisms of tipping points is a major goal in treating this problem. Existed approaches to examine climatic tipping points allow identifying the climate-tipping events in the past but very limited to predict them in advance. Our recent theoretical findings suggest that for predicting tipping points it is crucial to distinguish which scenario of a bifurcation transition dominates: dynamic (predictable) or stochastic (unpredictable). In order to illustrate suggested approach we compare the features of dynamic and stochastic bifurcations in most common scenario of abrupt transition between two climate states. This scenario is associated with a saddle-node and a transcritical bifurcations. Such scenario has been used, in particularly, in the analysis of stability of the thermohaline circulation against freshwater flux, Indian summer monsoon against global change. We demonstrate the effect of the rate of change of the bifurcation parameter at dynamic bifurcation and noise effect at stochastic bifurcation transitions by theoretical estimates. We analyse pre-bifurcation noise-dependent and rate-dependent phenomena, and distinguish its roles as "precursors" of impending bifurcations for dynamic and stochastic transitions. We show that appropriate choice of "precursors" might lead to improving predictability of climate tipping points. Additionally, the evaluation of the role of dynamic and stochastic factors might be also useful for the assessment of the vulnerability of tipping elements to noise-induced changes. Finally, our preliminary investigations suggest that a hitherto neglected dynamic effect induced by such small parameter as rate of change of the bifurcation parameter may have had important influence on abrupt climate changes on the scale of the geological history of the Earth.

Surovyatkina, Elena; Kurths, Juergen

2014-05-01

240

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...

241

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...

242

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

PubMed Central

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

Bull, James J.; Gill, Jason J.

2014-01-01

243

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) ...

244

Numerical algorithms for estimation and calculation of parameters in modeling pest population dynamics and evolution of resistance  

Microsoft Academic Search

Computational simulation models can provide a way of understanding and predicting insect population dynamics and evolution of resistance, but the usefulness of such models depends on generating or estimating the values of key parameters. In this paper, we describe four numerical algorithms generating or estimating key parameters for simulating four different processes within such models. First, we describe a novel

Mingren Shi; Michael Renton

2011-01-01

245

Advances in the dynamic prediction of ash deposition  

SciTech Connect

A new ash deposition code, FOULER, has been created as part of the Coal Quality Expert (CQE) program. This code incorporates the latest advances in predicting ash deposition in both pulverized-coal and cyclone-fired steam generators. The FOULER code predicts numerous deposition characteristics for the convective pass of a boiler, including the hanging pendants. As part of the final stages of the CQE project, this code is being integrated with the dynamic heat and mass transfer predictions of the existing CQE boiler model. The resultant predictions encompass strength development rates, mass growth rates, removal properties, and sootblower effectiveness cycles. Though testing and validation are continuing, predictions comparing two coals have been made and are presented in this paper.

Erickson, T.A.; Allan, S.E.; McCollor, D.P. [Univ. of North Dakota, Grand Forks, ND (United States). Energy and Environmental Research Center; Ferguson, D.W. [Black and Veatch, Kansas City, MO (United States)

1995-12-31

246

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

PubMed Central

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

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

2012-01-01

247

Prediction of Cardiovascular Risk Using Framingham, ASSIGN and QRISK2: How Well Do They Predict Individual Rather than Population Risk?  

PubMed Central

Background The objective of this study was to evaluate the performance of risk scores (Framingham, Assign and QRISK2) in predicting high cardiovascular disease (CVD) risk in individuals rather than populations. Methods and findings This study included 1.8 million persons without CVD and prior statin prescribing using the Clinical Practice Research Datalink. This contains electronic medical records of the general population registered with a UK general practice. Individual CVD risks were estimated using competing risk regression models. Individual differences in the 10-year CVD risks as predicted by risk scores and competing risk models were estimated; the population was divided into 20 subgroups based on predicted risk. CVD outcomes occurred in 69,870 persons. In the subgroup with lowest risks, risk predictions by QRISK2 were similar to individual risks predicted using our competing risk model (99.9% of people had differences of less than 2%); in the subgroup with highest risks, risk predictions varied greatly (only 13.3% of people had differences of less than 2%). Larger deviations between QRISK2 and our individual predicted risks occurred with calendar year, different ethnicities, diabetes mellitus and number of records for medical events in the electronic health records in the year before the index date. A QRISK2 estimate of low 10-year CVD risk (<15%) was confirmed by Framingham, ASSIGN and our individual predicted risks in 89.8% while an estimate of high 10-year CVD risk (?20%) was confirmed in only 48.6% of people. The majority of cases occurred in people who had predicted 10-year CVD risk of less than 20%. Conclusions Application of existing CVD risk scores may result in considerable misclassification of high risk status. Current practice to use a constant threshold level for intervention for all patients, together with the use of different scoring methods, may inadvertently create an arbitrary classification of high CVD risk. PMID:25271417

van Staa, Tjeerd-Pieter; Gulliford, Martin; Ng, Edmond S.-W.; Goldacre, Ben; Smeeth, Liam

2014-01-01

248

Modelling Sparse Dynamical Systems with Compressed Predictive State Representations  

E-print Network

structure is used to compress information during learning, al- lowing for an increase in both the efficiencyModelling Sparse Dynamical Systems with Compressed Predictive State Representations William L Abstract Efficiently learning accurate models of dy- namical systems is of central importance

Pineau, Joelle

249

Comparison of Ionospheric Observations and Dynamical Predictions of Meteor  

E-print Network

Comparison of Ionospheric Observations and Dynamical Predictions of Meteor Showers at Mars Paul intervals when there are many of these profiles and call them meteor showers We study cometary orbits to identify the parent bodies responsible for the meteor showers #12;Meteoric Layers (MEX) Profile with EUV

Withers, Paul

250

Ocean Dynamics and Prediction Research Naval Research Laboratory  

E-print Network

Ocean Dynamics and Prediction Research Naval Research Laboratory The Naval Research Laboratory has openings for PhD researchers to push forward the frontiers of ocean forecasting. Problems that must circulation, estuarine and riverine modeling, Arctic ice modeling, internal waves and ocean

251

Ocean Dynamics and Prediction Research Naval Research Laboratory  

E-print Network

Ocean Dynamics and Prediction Research Naval Research Laboratory The Naval Research Laboratory has openings for PhD researchers (both permanent and postdoctoral) to push forward the frontiers of ocean of oceanic processes, construction and analysis of ocean models and forecast systems, and basic and applied

252

Ocean Dynamics and Prediction Research Naval Research Laboratory  

E-print Network

Ocean Dynamics and Prediction Research Naval Research Laboratory The Naval Research Laboratory has openings for Ph.D. researchers to advance capabilities in ocean data assimilation and probabilistic, representation of ocean processes affecting temperature, salinity, and mixed- layer depth, uncertainty analysis

253

Effects of Peanut-Tobacco Rotations on Population Dynamics of Meloidogyne arenaria in Mixed Race Populations  

PubMed Central

A 3-year microplot study was initiated to characterize the population dynamics, reproduction potential, and survivorship of single or mixed populations of Meloidogyne arenaria race 1 (Ma1) and race 2 (Ma2), as affected by crop rotations of peanut 'Florigiant' and M. incognita races 1 and 3-resistant 'McNair 373' and susceptible 'Coker 371-Gold' tobacco. Infection, reproduction, and root damage by Ma2 on peanut and by Ma1 on resistant tobacco were limited in the first year. Infection, reproduction, and root-damage potentials on susceptible tobacco were similar for Ma1 and Ma2. In the mixed (1:1) population, Ma1 was dominant on peanut and Ma2 was dominant on both tobacco cultivars. Crop rotation affected the population dynamics of different nematode races. For years 2 and 3, the low numbers of Ma1 and Ma2 from a previous-year poor host increased rapidly on suitable hosts. Ma1 had greater reproduction factors ([RF] = population density at harvest/population density at preplandng) than did Ma2 and Ma1 + Ma2 in second-year peanut plots following first-year resistant tobacco, and in third-year peanut plots following second-year tobacco. In mixed infestations, Ma1 predominated over Ma2 in previous-year peanut plots, whereas Ma2 predominated over Ma1 in previous-year tobacco plots. Moderate damage on resistant tobacco was induced by Ma1 in the second year. In the third year, moderate damage on peanut was associated with 'Ma2' from previous-year peanut plots. The resistant tobacco supported sufficient reproduction of Ma1 over 2 years to effect moderate damage and yield suppression to peanut in year 3. PMID:19277278

Hirunsalee, Anan; Barker, K. R.; Beute, M. K.

1995-01-01

254

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

USGS Publications Warehouse

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.

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

2012-01-01

255

European eel (Anguilla anguilla): prediction of spawner escapement from continental population  

E-print Network

European eel (Anguilla anguilla): prediction of spawner escapement from continental population the assessment of silver European eel (Anguilla anguilla) escapement based on a "sed- entary" population fraction using eel traps and related to environmental factors. Intensive electrofishing and fyke-net fishing were

Paris-Sud XI, Université de

256

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...

257

Evidence of large-scale source-sink dynamics and long-distance dispersal among Wood Thrush populations.  

PubMed

Source-sink dynamics are commonly thought to occur among Wood Thrush (Hylocichla mustelina) and other songbird populations, allowing for the persistence of populations with negative growth rates ("sinks") through immigration from populations with positive growth rates ("sources"). Knowledge of source-sink dynamics is important for management and conservation because the removal of source habitat should result in the extinction of dependent sinks. However, since research has focused on identifying individual sources/sink populations, not source-sink pairs, we cannot predict these effects or the scale over which they occur. We posit that, when dispersal occurs from a source to a sink year after year, there will be a one-year time-lagged correlation in abundance between the two populations. This should occur for populations separated by distances over which juveniles disperse. Using the North American Breeding Bird Survey data, we tested for such time-lagged correlations between paired Wood Thrush populations from 10 to 200 km apart. Populations were linked with a one-year time lag over distances from 60 to 80 km, indicating that dispersal and source-sink dynamics may occur over these long distances. There was also a declining trend in forest cover from sources to sinks. Conservation and management strategies should therefore be designed at large scales, with consideration for source-sink dynamics and forest cover. PMID:17249228

Tittler, Rebecca; Fahrig, Lenore; Villard, Marc-André

2006-12-01

258

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

PubMed

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

Fukaya, Keiichi; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi

2014-04-16

259

Assessing predictability of a hydrological stochastic-dynamical system  

NASA Astrophysics Data System (ADS)

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.

Gelfan, Alexander

2014-05-01

260

Montane refugia predict population genetic structure in the Large-blotched Ensatina salamander  

E-print Network

Montane refugia predict population genetic structure in the Large-blotched Ensatina salamander in the Large-blotched Ensatina (Ensatina eschscholtzii klauberi), a plethodon- tid salamander endemic to middle and northern Baja California. A compos- ite SDM representing the range through time predicts two disjunct

McGuire, Jimmy A.

261

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

PubMed

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

Liao, David; Tlsty, Thea D

2014-08-01

262

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

PubMed Central

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

Liao, David; Tlsty, Thea D.

2014-01-01

263

Mammal population regulation, keystone processes and ecosystem dynamics.  

PubMed Central

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

Sinclair, A R E

2003-01-01

264

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

PubMed

Understanding the drivers and consequences of disease epidemics is an important frontier in ecology. However, long-term data on hosts, their parasites, and the corresponding environmental conditions necessary to explore these interactions are often unavailable. We examined the dynamics of Daphnia pulicaria, a keystone zooplankter in lake ecosystems, to explore the long-term causes and consequences of infection by a chytridiomycete parasitoid (Polycaryum laeve). After quantifying host-pathogen dynamics from vouchered samples collected over 15 years, we used autoregressive models to evaluate (1) hypothesized drivers of infection, including host density, water temperature, dissolved oxygen, host-food availability, and lake mixing; and (2) the effects of epidemics on host populations. Infection was present in most years but varied widely in prevalence, from < 1% to 34%, with seasonal peaks in early spring and late fall. Within years, lake stratification strongly inhibited P. laeve transmission, such that epidemics occurred primarily during periods of water mixing. Development of the thermocline likely reduced transmission by spatially separating susceptible hosts from infectious zoospores. Among years, ice duration and cumulative snowfall correlated negatively with infection prevalence, likely because of reductions in spring phytoplankton and D. pulicaria density in years with extended winters. Epidemics also influenced dynamics of the host population. Infected D. pulicaria rarely (< 1%) contained eggs, and P. laeve prevalence was positively correlated with sexual reproduction in D. pulicaria. Analyses of D. pulicaria density-dependent population dynamics predicted that, in the absence of P. laeve infection, host abundance would be 11-50% higher than what was observed. By underscoring the importance of complex physical processes in controlling host-parasite interactions and of epidemic disease in influencing host populations, our results highlight the value of long-term data for understanding wildlife disease dynamics. PMID:19294920

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

2009-01-01

265

Population dynamics in Digitalis purpurea: the interaction of disturbance and seed bank dynamics  

Microsoft Academic Search

Summary 1. Plant ecologists have long since realized that the persistence of many facultative biennial plants depends upon disturbance. However, we still have a limited knowledge of the population-level effects of disturbance, and the connection between adult and seed bank dynamics. 2. Using data from a 3-year demographic study combined with experimental gap-opening in a large population of Digitalis purpurea

NINA SLETVOLD; KNUT RYDGREN

2007-01-01

266

Dynamics of Nanoparticle-Protein Corona Complex Formation: Analytical Results from Population Balance Equations  

PubMed Central

Background Nanoparticle-protein corona complex formation involves absorption of protein molecules onto nanoparticle surfaces in a physiological environment. Understanding the corona formation process is crucial in predicting nanoparticle behavior in biological systems, including applications of nanotoxicology and development of nano drug delivery platforms. Method This paper extends the modeling work in to derive a mathematical model describing the dynamics of nanoparticle corona complex formation from population balance equations. We apply nonlinear dynamics techniques to derive analytical results for the composition of nanoparticle-protein corona complex, and validate our results through numerical simulations. Results The model presented in this paper exhibits two phases of corona complex dynamics. In the first phase, proteins rapidly bind to the free surface of nanoparticles, leading to a metastable composition. During the second phase, continuous association and dissociation of protein molecules with nanoparticles slowly changes the composition of the corona complex. Given sufficient time, composition of the corona complex reaches an equilibrium state of stable composition. We find analytical approximate formulae for metastable and stable compositions of corona complex. Our formulae are very well-structured to clearly identify important parameters determining corona composition. Conclusion The dynamics of biocorona formation constitute vital aspect of interactions between nanoparticles and living organisms. Our results further understanding of these dynamics through quantitation of experimental conditions, modeling results for in vitro systems to better predict behavior for in vivo systems. One potential application would involve a single cell culture medium related to a complex protein medium, such as blood or tissue fluid. PMID:23741371

Darabi Sahneh, Faryad; Scoglio, Caterina; Riviere, Jim

2013-01-01

267

Population dynamics and range expansion in nine-banded armadillos.  

PubMed

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

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

2013-01-01

268

Orbit determination and prediction study for Dynamic Explorer 2  

NASA Technical Reports Server (NTRS)

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.

Smith, R. L.; Nakai, Y.; Doll, C. E.

1983-01-01

269

Synconset Waves and Chains: Spiking Onsets in Synchronous Populations Predict and Are Predicted by  

E-print Network

waves, and define `synconset wave' as a cascade of first spikes within a synchronisation event framework to several aspects of network physiology including cell assemblies, population codes an oscillation, networks of inhibitory neurons selectively suppress different groups of principal cells

Narayanan, Rishikesh

270

Nature versus nurture: Predictability in low-temperature Ising dynamics  

NASA Astrophysics Data System (ADS)

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.

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

2013-10-01

271

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

PubMed

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

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

2013-10-01

272

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

USGS Publications Warehouse

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

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

2009-01-01

273

Dynamic viscosity estimation of hydrogen sulfide using a predictive scheme based on molecular dynamics.  

E-print Network

1 Dynamic viscosity estimation of hydrogen sulfide using a predictive scheme based on molecular on molecular dynamics results on Lennard-Jones spheres is proposed to model the viscosity of hydrogen sulfide is that the adjustment does not involve any viscosity data because only density values have been used in order

Boyer, Edmond

274

New methods for inferring population dynamics from microbial sequences  

PubMed Central

The reduced cost of high throughput sequencing, increasing automation, and the amenability of sequence data for evolutionary analysis are making DNA data (or the corresponding amino acid sequences) the molecular marker of choice for studying microbial population genetics and phylogenetics. Concomitantly, due to the ever-increasing computational power, new, more accurate (and sometimes faster), sequence-based analytical approaches are being developed and applied to these new data. Here we review some commonly used, recently improved, and newly developed methodologies for inferring population dynamics and evolutionary relationships using nucleotide and amino acid sequence data, including: alignment, model selection, bifurcating and network phylogenetic approaches, and methods for estimating demographic history, population structure, and population parameters (recombination, genetic diversity, growth, and natural selection). Because of the extensive literature published on these topics this review cannot be comprehensive in its scope. Instead, for all the methods discussed we introduce the approaches we think are particularly useful for analyses of microbial sequences and where possible, include references to recent and more inclusive reviews. PMID:16627010

Pérez-Losada, Marcos; Porter, Megan L.; Tazi, Loubna; Crandall, Keith A.

2007-01-01

275

State-dependent neutral delay equations from population dynamics.  

PubMed

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

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

2014-10-01

276

Transoceanic migration, spatial dynamics, and population linkages of white sharks.  

PubMed

The large-scale spatial dynamics and population structure of marine top predators are poorly known. We present electronic tag and photographic identification data showing a complex suite of behavioral patterns in white sharks. These include coastal return migrations and the fastest known transoceanic return migration among swimming fauna, which provide direct evidence of a link between widely separated populations in South Africa and Australia. Transoceanic return migration involved a return to the original capture location, dives to depths of 980 meters, and the tolerance of water temperatures as low as 3.4 degrees C. These findings contradict previous ideas that female white sharks do not make transoceanic migrations, and they suggest natal homing behavior. PMID:16210537

Bonfil, Ramón; Meÿer, Michael; Scholl, Michael C; Johnson, Ryan; O'Brien, Shannon; Oosthuizen, Herman; Swanson, Stephan; Kotze, Deon; Paterson, Michael

2005-10-01

277

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)

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.

Schweikhard, W. G.; Chen, Y. S.

1986-01-01

278

Time-delayed coupled logistic capacity model in population dynamics.  

PubMed

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. PMID:25215718

Cáceres, Manuel O

2014-08-01

279

Periodically varying externally imposed environmental effects on population dynamics  

NASA Astrophysics Data System (ADS)

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.

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

2004-09-01

280

Front acceleration by dynamic selection in Fisher population waves  

NASA Astrophysics Data System (ADS)

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.

Bénichou, O.; Calvez, V.; Meunier, N.; Voituriez, R.

2012-10-01

281

Auctions with Dynamic Populations: Efficiency and Revenue Maximization  

NASA Astrophysics Data System (ADS)

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.

Said, Maher

282

Knowledge epidemics and population dynamics models for describing idea diffusion  

E-print Network

The diffusion of ideas is often closely connected to the creation and diffusion of knowledge and to the technological evolution of society. Because of this, knowledge creation, exchange and its subsequent transformation into innovations for improved welfare and economic growth is briefly described from a historical point of view. Next, three approaches are discussed for modeling the diffusion of ideas in the areas of science and technology, through (i) deterministic, (ii) stochastic, and (iii) statistical approaches. These are illustrated through their corresponding population dynamics and epidemic models relative to the spreading of ideas, knowledge and innovations. The deterministic dynamical models are considered to be appropriate for analyzing the evolution of large and small societal, scientific and technological systems when the influence of fluctuations is insignificant. Stochastic models are appropriate when the system of interest is small but when the fluctuations become significant for its evolution...

Vitanov, Nikolay K

2012-01-01

283

The spatial population dynamics of insects exploiting a patchy food resource  

Microsoft Academic Search

The population dynamics of insects in a spatially fragmented environment were studied by examining three main aspects of their ecology, namely, rates of local population extinction, density dependence in population change, and movements between populations. Ten phytophagous insects and seven parasitoids inhabiting the flowerheads of two herbaceous plants, Centaurea nigra and Arctium minus, were studied by monitoring their populations on

J. P. Dempster; D. A. Atkinson; O. D. Cheesman

1995-01-01

284

Molecular dynamics prediction of density for metastable liquid noble metals  

NASA Astrophysics Data System (ADS)

The thermophysical properties of metastable liquid noble metals are not readily available due to the great experimental difficulties. Here the densities of liquid Pd, Pt, Ag, and Au are predicted by molecular dynamics method. The pair distribution functions are computed to monitor the atomic structure of these noble metals, which indicate that the systems remain in liquid state in the process of simulation. The calculated densities exhibit nonlinear temperature dependences and prove to have a high accuracy. The density data are obtained in a much broader temperature range, especially in the undercooled regime. Moreover, the molar volumes and the thermal expansion coefficients are also derived from the density predictions.

Wang, H. P.; Yang, S. J.; Wei, B.

2012-06-01

285

Prediction of Muscle Performance During Dynamic Repetitive Exercise  

NASA Technical Reports Server (NTRS)

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.

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

2002-01-01

286

Sea lice and salmon population dynamics: effects of exposure time for migratory fish  

PubMed Central

The ecological impact of parasite transmission from fish farms is probably mediated by the migration of wild fishes, which determines the period of exposure to parasites. For Pacific salmon and the parasitic sea louse, Lepeophtheirus salmonis, analysis of the exposure period may resolve conflicting observations of epizootic mortality in field studies and parasite rejection in experiments. This is because exposure periods can differ by 2–3 orders of magnitude, ranging from months in the field to hours in experiments. We developed a mathematical model of salmon–louse population dynamics, parametrized by a study that monitored naturally infected juvenile salmon held in ocean enclosures. Analysis of replicated trials indicates that lice suffer high mortality, particularly during pre-adult stages. The model suggests louse populations rapidly decline following brief exposure of juvenile salmon, similar to laboratory study designs and data. However, when the exposure period lasts for several weeks, as occurs when juvenile salmon migrate past salmon farms, the model predicts that lice accumulate to abundances that can elevate salmon mortality and depress salmon populations. The duration of parasite exposure is probably critical to salmon–louse population dynamics, and should therefore be accommodated in coastal planning and management where fish farms are situated on wild fish migration routes. PMID:19419983

Krkošek, Martin; Morton, Alexandra; Volpe, John P.; Lewis, Mark A.

2009-01-01

287

Impact of Simian Immunodeficiency Virus Infection on Chimpanzee Population Dynamics  

PubMed Central

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

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

2010-01-01

288

Human mobility patterns predict divergent epidemic dynamics among cities.  

PubMed

The epidemic dynamics of infectious diseases vary among cities, but it is unclear how this is caused by patterns of infectious contact among individuals. Here, we ask whether systematic differences in human mobility patterns are sufficient to cause inter-city variation in epidemic dynamics for infectious diseases spread by casual contact between hosts. We analyse census data on the mobility patterns of every full-time worker in 48 Canadian cities, finding a power-law relationship between population size and the level of organization in mobility patterns, where in larger cities, a greater fraction of workers travel to work in a few focal locations. Similarly sized cities also vary in the level of organization in their mobility patterns, equivalent on average to the variation expected from a 2.64-fold change in population size. Systematic variation in mobility patterns is sufficient to cause significant differences among cities in infectious disease dynamics-even among cities of the same size-according to an individual-based model of airborne pathogen transmission parametrized with the mobility data. This suggests that differences among cities in host contact patterns are sufficient to drive differences in infectious disease dynamics and provides a framework for testing the effects of host mobility patterns in city-level disease data. PMID:23864593

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

2013-09-01

289

Predicting the consequences of carry-over effects for migratory populations  

PubMed Central

Migratory animals present a unique challenge for predicting population size because they are influenced by events in multiple stages of the annual cycle that are separated by large geographic distances. Here, we develop a model that incorporates non-fatal carry-over effects to predict changes in population size and show how this can be integrated with predictive models of habitat loss and deterioration. Examples from Barn swallows, Greater snow geese and American redstarts show how carry-over effects can be estimated and integrated into the model. Incorporation of carry-over effects should increase the predictive power of models. However, the challenge for developing accurate predictions rests both on the ability to estimate parameters from multiple stages of the annual cycle and to understand how events between these periods interact to influence individual success. PMID:17148350

Norris, D. Ryan; Taylor, Caz M

2005-01-01

290

Using GRASS and Spatial Explicit Population dynamics Modelling as a conservation tool to manage grey squirrel (Sciurus carolinensis) in northern Italy  

Microsoft Academic Search

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

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

2004-01-01

291

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

SciTech Connect

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.

Schmieder, R.W.

1995-07-01

292

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  

Microsoft Academic Search

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

W. G. Schweikhard; Y. S. Chen

1986-01-01

293

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

PubMed

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

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

2014-04-01

294

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

PubMed Central

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

Krylova, Olga; Earn, David J. D.

2013-01-01

295

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

PubMed Central

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

Lorenzen, Kai

2005-01-01

296

The model of fungal population dynamics affected by nystatin  

NASA Astrophysics Data System (ADS)

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

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

297

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

PubMed

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

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

2011-07-01

298

Cycles, stochasticity and density dependence in pink salmon population dynamics  

PubMed Central

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

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

2011-01-01

299

Parsimonious snow model explains reindeer population dynamics and ranging behavior  

NASA Astrophysics Data System (ADS)

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

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

2008-12-01

300

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

PubMed

Interest in cell heterogeneity and differentiation has recently led to increased use of time-lapse microscopy. Previous studies have shown that cell fate may be determined well in advance of the event. We used a mixture of automation and manual review of time-lapse live cell imaging to track the positions, contours, divisions, deaths and lineage of 44 B-lymphocyte founders and their 631 progeny in vitro over a period of 108 hours. Using this data to train a Support Vector Machine classifier, we were retrospectively able to predict the fates of individual lymphocytes with more than 90% accuracy, using only time-lapse imaging captured prior to mitosis or death of 90% of all cells. The motivation for this paper is to explore the impact of labour-efficient assistive software tools that allow larger and more ambitious live-cell time-lapse microscopy studies. After training on this data, we show that machine learning methods can be used for realtime prediction of individual cell fates. These techniques could lead to realtime cell culture segregation for purposes such as phenotype screening. We were able to produce a large volume of data with less effort than previously reported, due to the image processing, computer vision, tracking and human-computer interaction tools used. We describe the workflow of the software-assisted experiments and the graphical interfaces that were needed. To validate our results we used our methods to reproduce a variety of published data about lymphocyte populations and behaviour. We also make all our data publicly available, including a large quantity of lymphocyte spatio-temporal dynamics and related lineage information. PMID:24404133

Chakravorty, Rajib; Rawlinson, David; Zhang, Alan; Markham, John; Dowling, Mark R; Wellard, Cameron; Zhou, Jie H S; Hodgkin, Philip D

2014-01-01

301

Labour-Efficient In Vitro Lymphocyte Population Tracking and Fate Prediction Using Automation and Manual Review  

PubMed Central

Interest in cell heterogeneity and differentiation has recently led to increased use of time-lapse microscopy. Previous studies have shown that cell fate may be determined well in advance of the event. We used a mixture of automation and manual review of time-lapse live cell imaging to track the positions, contours, divisions, deaths and lineage of 44 B-lymphocyte founders and their 631 progeny in vitro over a period of 108 hours. Using this data to train a Support Vector Machine classifier, we were retrospectively able to predict the fates of individual lymphocytes with more than 90% accuracy, using only time-lapse imaging captured prior to mitosis or death of 90% of all cells. The motivation for this paper is to explore the impact of labour-efficient assistive software tools that allow larger and more ambitious live-cell time-lapse microscopy studies. After training on this data, we show that machine learning methods can be used for realtime prediction of individual cell fates. These techniques could lead to realtime cell culture segregation for purposes such as phenotype screening. We were able to produce a large volume of data with less effort than previously reported, due to the image processing, computer vision, tracking and human-computer interaction tools used. We describe the workflow of the software-assisted experiments and the graphical interfaces that were needed. To validate our results we used our methods to reproduce a variety of published data about lymphocyte populations and behaviour. We also make all our data publicly available, including a large quantity of lymphocyte spatio-temporal dynamics and related lineage information. PMID:24404133

Chakravorty, Rajib; Rawlinson, David; Zhang, Alan; Markham, John; Dowling, Mark R.; Wellard, Cameron; Zhou, Jie H. S.; Hodgkin, Philip D.

2014-01-01

302

Macromolecular symmetric assembly prediction using swarm intelligence dynamic modeling.  

PubMed

Proteins often assemble in multimeric complexes to perform a specific biologic function. However, trapping these high-order conformations is difficult experimentally. Therefore, predicting how proteins assemble using in silico techniques can be of great help. The size of the associated conformational space and the fact that proteins are intrinsically flexible structures make this optimization problem extremely challenging. Nonetheless, known experimental spatial restraints can guide the search process, contributing to model biologically relevant states. We present here a swarm intelligence optimization protocol able to predict the arrangement of protein symmetric assemblies by exploiting a limited amount of experimental restraints and steric interactions. Importantly, within this scheme the native flexibility of each protein subunit is taken into account as extracted from molecular dynamics (MD) simulations. We show that this is a key ingredient for the prediction of biologically functional assemblies when, upon oligomerization, subunits explore activated states undergoing significant conformational changes. PMID:23810695

Degiacomi, Matteo T; Dal Peraro, Matteo

2013-07-01

303

Uncertainty estimation and prediction for interdisciplinary ocean dynamics  

SciTech Connect

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

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

2006-09-01

304

Two-Speed Gearbox Dynamic Simulation Predictions and Test Validation  

NASA Technical Reports Server (NTRS)

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.

Lewicki, David G.; DeSmidt, Hans; Smith, Edward C.; Bauman, Steven W.

2010-01-01

305

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

PubMed Central

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

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

2012-01-01

306

Predicting and understanding forest dynamics using a simple tractable model  

PubMed Central

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

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

2008-01-01

307

The role of ethnicity in predicting diabetes risk at the population level  

PubMed Central

Background. The current form of the Diabetes Population Risk Tool (DPoRT) includes a non-specific category of ethnicity in concordance with publicly data available. Given the importance of ethnicity in influencing diabetes risk and its significance in a multi-ethnic population, it is prudent to determine its influence on a population-based risk prediction tool. Objective. To apply and compare the DPoRT with a modified version that includes detailed ethnic information in Canada's largest and most ethnically diverse province. Methods. Two additional diabetes prediction models were created: a model that contained predictors specific to the following ethnic groups – White, Black, Asian, south Asian, and First Nation; and a reference model which did not include a term for ethnicity. In addition to discrimination and calibration, 10-year diabetes incidence was compared. The algorithms were developed in Ontario using the 1996–1997 National Population Health Survey (N = 19,861) and validated in the 2000/2001 Canadian Community Health Survey (N = 26,465). Results. All non-white ethnicities were associated with higher risk for developing diabetes with south Asians having the highest risk. Discrimination was similar (0.75–0.77) and sufficient calibration was maintained for all models except the detailed ethnicity models for males. DPoRT produced the lowest overall ratio between observed and predicted diabetes risk. DPoRT identified more high risk cases than the other algorithms in males, whereas in females both DPoRT and the full ethnicity model identified more high risk cases. Overall DPoRT and full ethnicity algorithms were very similar in terms of predictive accuracy and population risk. Conclusion. Although from the individual risk perspective, incorporating information on ethnicity is important, when predicting new cases of diabetes at the population level and accounting for other risk factors, detailed ethnic information did not improve the discrimination and accuracy of the model or identify significantly more diabetes cases in the population. PMID:22292745

Rosella, Laura C.; Mustard, Cameron A.; Stukel, Therese A.; Corey, Paul; Hux, Jan; Roos, Les; Manuel, Douglas G.

2012-01-01

308

Telomere length and dynamics predict mortality in a wild longitudinal study.  

PubMed

Explaining variation in life expectancy between individuals of the same age is fundamental to our understanding of population ecology and life history evolution. Variation in the length and rate of loss of the protective telomere chromosome caps has been linked to cellular lifespan. Yet, the extent to which telomere length and dynamics predict organismal lifespan in nature is still contentious. Using longitudinal samples taken from a closed population of Acrocephalus sechellensis (Seychelles warblers) studied for over 20 years, we describe the first study into life-long adult telomere dynamics (1-17 years) and their relationship to mortality under natural conditions (n = 204 individuals). We show that telomeres shorten with increasing age and body mass, and that shorter telomeres and greater rates of telomere shortening predicted future mortality. Our results provide the first clear and unambiguous evidence of a relationship between telomere length and mortality in the wild, and substantiate the prediction that telomere length and shortening rate can act as an indicator of biological age further to chronological age when exploring life history questions in natural conditions. PMID:23167566

Barrett, Emma L B; Burke, Terry A; Hammers, Martijn; Komdeur, Jan; Richardson, David S

2013-01-01

309

CONCEPTS, REVIEWS AND SYNTHESES Population dynamics of red-backed voles (Myodes)  

E-print Network

CONCEPTS, REVIEWS AND SYNTHESES Population dynamics of red-backed voles (Myodes) in North America-Verlag 2011 Abstract We review the population dynamics of red- backed voles (Myodes species) in North America of population changes in Myodes in North America. Using autoregressive and spectral analysis, we found that only

Krebs, Charles J.

310

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

Microsoft Academic Search

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

M. G. Roberts; R. R. Kao

1998-01-01

311

Population dynamics of islet-infiltrating cells in autoimmune diabetes.  

PubMed

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

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

2015-02-01

312

Ecological and life history characteristics predict population genetic divergence of two salmonids in the same landscape.  

PubMed

Ecological and life history characteristics such as population size, dispersal pattern, and mating system mediate the influence of genetic drift and gene flow on population subdivision. Bull trout (Salvelinus confluentus) and mountain whitefish (Prosopium williamsoni) differ markedly in spawning location, population size and mating system. Based on these differences, we predicted that bull trout would have reduced genetic variation within and greater differentiation among populations compared with mountain whitefish. To test this hypothesis, we used microsatellite markers to determine patterns of genetic divergence for each species in the Clark Fork River, Montana, USA. As predicted, bull trout had a much greater proportion of genetic variation partitioned among populations than mountain whitefish. Among all sites, FST was seven times greater for bull trout (FST = 0.304 for bull trout, 0.042 for mountain whitefish. After removing genetically differentiated high mountain lake sites for each species FST, was 10 times greater for bull trout (FST = 0.176 for bull trout; FST = 0.018 for mountain whitefish). The same characteristics that affect dispersal patterns in these species also lead to predictions about the amount and scale of adaptive divergence among populations. We provide a theoretical framework that incorporates variation in ecological and life history factors, neutral divergence, and adaptive divergence to interpret how neutral and adaptive divergence might be correlates of ecological and life history factors. PMID:15548282

Whiteley, Andrew R; Spruell, Paul; Allendorf, Fred W

2004-12-01

313

Rhythmic Manipulation of Objects with Complex Dynamics: Predictability over Chaos  

PubMed Central

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

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

2014-01-01

314

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

PubMed Central

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

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

2013-01-01

315

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

SciTech Connect

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.

Ashley, A.E.; Sherman, S.L. [Emory Univ. School of Medicine, Atlanta, GA (United States)

1995-12-01

316

A Biologically Informed, Mechanistic Model of Desert Shrub Population Dynamics Bearing on Arid Landscape Evolution  

NASA Astrophysics Data System (ADS)

In arid landscapes, desert shrubs individually and collectively modify how sediment is transported (e.g by wind, overland-flow, and rain-splash). Addressing how desert shrubs modify landscapes on geomorphic timescales therefore necessitates spanning multiple shrub lifetimes and accounting for how processes affecting shrub dynamics on these longer timescales (e.g. fire, grazing, drought, and climate change) may in turn impact sediment transport. To fulfill this need, we present a mechanistic model of the spatiotemporal dynamics of a desert-shrub population that uses a simple accounting framework and tracks individual shrubs as they enter, age, and exit the population (via recruitment, growth, and mortality). Our model is novel insomuch as it (1) features a strong biophysical foundation, (2) mimics well-documented aspects of how shrub populations respond to changes in precipitation, and (3) possesses the process granularity appropriate for use in geomorphic simulations. In a complimentary abstract (Fathel et al. 2014), we demonstrate the potential of this biological model by coupling it to a physical model of rain-splash sediment transport: We mechanistically reproduce the empirical observation that the erosion rate of a hillslope decreases as its vegetation coverage increases and we predict erosion rates under different climate-change scenarios.

Worman, Stacey; Furbish, David; Fathel, Siobhan

2014-05-01

317

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

NASA Astrophysics Data System (ADS)

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.

Farooq, M.; Muslim, M.

2014-11-01

318

Predicting local adaptation in fragmented plant populations: implications for restoration genetics  

PubMed Central

Understanding patterns and correlates of local adaptation in heterogeneous landscapes can provide important information in the selection of appropriate seed sources for restoration. We assessed the extent of local adaptation of fitness components in 12 population pairs of the perennial herb Rutidosis leptorrhynchoides (Asteraceae) and examined whether spatial scale (0.7–600 km), environmental distance, quantitative (QST) and neutral (FST) genetic differentiation, and size of the local and foreign populations could predict patterns of adaptive differentiation. Local adaptation varied among populations and fitness components. Including all population pairs, local adaptation was observed for seedling survival, but not for biomass, while foreign genotype advantage was observed for reproduction (number of inflorescences). Among population pairs, local adaptation increased with QST and local population size for biomass. QST was associated with environmental distance, suggesting ecological selection for phenotypic divergence. However, low FST and variation in population structure in small populations demonstrates the interaction of gene flow and drift in constraining local adaptation in R. leptorrhynchoides. Our study indicates that for species in heterogeneous landscapes, collecting seed from large populations from similar environments to candidate sites is likely to provide the most appropriate seed sources for restoration. PMID:23346235

Pickup, Melinda; Field, David L; Rowell, David M; Young, Andrew G

2012-01-01

319

Modelling Lipid Competition Dynamics in Heterogeneous Protocell Populations  

PubMed Central

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

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

2014-01-01

320

On signals of phase transitions in salmon population dynamics.  

PubMed

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

Krkošek, Martin; Drake, John M

2014-06-01

321

Neural Population Dynamics Modeled by Mean-Field Graphs  

NASA Astrophysics Data System (ADS)

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

Kozma, Robert; Puljic, Marko

2011-09-01

322

Wave trains in a model of gypsy moth population dynamics  

NASA Astrophysics Data System (ADS)

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

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

1995-12-01

323

Emergence of Drug-Resistant Influenza Virus: Population Dynamical Considerations  

NSDL National Science Digital Library

Access to the article is free, however registration and sign-in are required: Given the considerable challenges to the rapid development of an effective vaccine against influenza, antiviral agents will play an important role as a first-line defense if a new pandemic occurs. The large-scale use of drugs for chemoprophylaxis and treatment will impose strong selection for the evolution of drug-resistant strains. The ensuing transmission of those strains could substantially limit the effectiveness of the drugs as a first-line defense. Summarizing recent data on the rate at which the treatment of influenza infection generates resistance de novo and on the transmission fitness of resistant virus, we discuss possible implications for the epidemiological spread of drug resistance in the context of an established population dynamic model.

Roland R. Regoes (Institute of Integrative Biology, ETH Zürich;); Sebastian Bonhoeffer (Institute of Integrative Biology, ETH Zürich;)

2006-04-21

324

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

Microsoft Academic Search

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

Wakgari Deressa; Ahmed Ali; Yemane Berhane

325

The spatial population dynamics of insects exploiting a patchy food resource  

Microsoft Academic Search

The population dynamics of ten species of phytophagous insects and seven parasitoids inhabiting the flowerheads of two herbaceous plants, Centaurea nigra and Arctium minus, were studied, and three main aspects of their ecology were examined, namely, rates of population extinction, density dependence in population changes from one generation to the next, and movements between populations. The study was based on

J. P. Dempster; D. A. Atkinson; M. C. French

1995-01-01

326

213 WILDLIFE BIOLOGY 9:3 (2003) The population dynamics of mountain goats Oreamnos  

E-print Network

213© WILDLIFE BIOLOGY · 9:3 (2003) The population dynamics of mountain goats Oreamnos americanus and unhunted mountain goat Oreamnos americanus populations Alejandro Gonzalez Voyer, Kirby G. Smith & Marco and unhunted mountain goat Oreamnos americanus populations. - Wildl. Biol. 9: 213-218. Native populations

Festa-Bianchet, Marco

327

Multi-population genomic prediction using a multi-task Bayesian learning model  

PubMed Central

Background Genomic prediction in multiple populations can be viewed as a multi-task learning problem where tasks are to derive prediction equations for each population and multi-task learning property can be improved by sharing information across populations. The goal of this study was to develop a multi-task Bayesian learning model for multi-population genomic prediction with a strategy to effectively share information across populations. Simulation studies and real data from Holstein and Ayrshire dairy breeds with phenotypes on five milk production traits were used to evaluate the proposed multi-task Bayesian learning model and compare with a single-task model and a simple data pooling method. Results A multi-task Bayesian learning model was proposed for multi-population genomic prediction. Information was shared across populations through a common set of latent indicator variables while SNP effects were allowed to vary in different populations. Both simulation studies and real data analysis showed the effectiveness of the multi-task model in improving genomic prediction accuracy for the smaller Ayshire breed. Simulation studies suggested that the multi-task model was most effective when the number of QTL was small (n?=?20), with an increase of accuracy by up to 0.09 when QTL effects were lowly correlated between two populations (??=?0.2), and up to 0.16 when QTL effects were highly correlated (??=?0.8). When QTL genotypes were included for training and validation, the improvements were 0.16 and 0.22, respectively, for scenarios of the low and high correlation of QTL effects between two populations. When the number of QTL was large (n?=?200), improvement was small with a maximum of 0.02 when QTL genotypes were not included for genomic prediction. Reduction in accuracy was observed for the simple pooling method when the number of QTL was small and correlation of QTL effects between the two populations was low. For the real data, the multi-task model achieved an increase of accuracy between 0 and 0.07 in the Ayrshire validation set when 28,206 SNPs were used, while the simple data pooling method resulted in a reduction of accuracy for all traits except for protein percentage. When 246,668 SNPs were used, the accuracy achieved from the multi-task model increased by 0 to 0.03, while using the pooling method resulted in a reduction of accuracy by 0.01 to 0.09. In the Holstein population, the three methods had similar performance. Conclusions Results in this study suggest that the proposed multi-task Bayesian learning model for multi-population genomic prediction is effective and has the potential to improve the accuracy of genomic prediction. PMID:24884927

2014-01-01

328

Temporal dynamics of genetic variability in a mountain goat (Oreamnos americanus) population  

E-print Network

Temporal dynamics of genetic variability in a mountain goat (Oreamnos americanus) population JOAQUI diversity over 14 cohorts in a small and relatively isolated population of mountain goats (Oreamnos americanus) during a period of demographic increase. Offspring heterozygosity decreased while parental

Festa-Bianchet, Marco

329

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

PubMed

The investigation of individual heterogeneity in vital rates has recently received growing attention among population ecologists. Individual heterogeneity in wild animal populations has been accounted for and quantified by including individually varying effects in models for mark-recapture data, but the real need for underlying individual effects to account for observed levels of individual variation has recently been questioned by the work of Tuljapurkar et al. (Ecology Letters, 12, 93, 2009) on dynamic heterogeneity. Model-selection approaches based on information criteria or Bayes factors have been used to address this question. Here, we suggest that, in addition to model-selection, model-checking methods can provide additional important insights to tackle this issue, as they allow one to evaluate a model's misfit in terms of ecologically meaningful measures. Specifically, we propose the use of posterior predictive checks to explicitly assess discrepancies between a model and the data, and we explain how to incorporate model checking into the inferential process used to assess the practical implications of ignoring individual heterogeneity. Posterior predictive checking is a straightforward and flexible approach for performing model checks in a Bayesian framework that is based on comparisons of observed data to model-generated replications of the data, where parameter uncertainty is incorporated through use of the posterior distribution. If discrepancy measures are chosen carefully and are relevant to the scientific context, posterior predictive checks can provide important information allowing for more efficient model refinement. We illustrate this approach using analyses of vital rates with long-term mark-recapture data for Weddell seals and emphasize its utility for identifying shortfalls or successes of a model at representing a biological process or pattern of interest. We show how posterior predictive checks can be used to strengthen inferences in ecological studies. We demonstrate the application of this method on analyses dealing with the question of individual reproductive heterogeneity in a population of Antarctic pinnipeds. PMID:24834335

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

2014-04-01

330

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

PubMed Central

The investigation of individual heterogeneity in vital rates has recently received growing attention among population ecologists. Individual heterogeneity in wild animal populations has been accounted for and quantified by including individually varying effects in models for mark–recapture data, but the real need for underlying individual effects to account for observed levels of individual variation has recently been questioned by the work of Tuljapurkar et al. (Ecology Letters, 12, 93, 2009) on dynamic heterogeneity. Model-selection approaches based on information criteria or Bayes factors have been used to address this question. Here, we suggest that, in addition to model-selection, model-checking methods can provide additional important insights to tackle this issue, as they allow one to evaluate a model's misfit in terms of ecologically meaningful measures. Specifically, we propose the use of posterior predictive checks to explicitly assess discrepancies between a model and the data, and we explain how to incorporate model checking into the inferential process used to assess the practical implications of ignoring individual heterogeneity. Posterior predictive checking is a straightforward and flexible approach for performing model checks in a Bayesian framework that is based on comparisons of observed data to model-generated replications of the data, where parameter uncertainty is incorporated through use of the posterior distribution. If discrepancy measures are chosen carefully and are relevant to the scientific context, posterior predictive checks can provide important information allowing for more efficient model refinement. We illustrate this approach using analyses of vital rates with long-term mark–recapture data for Weddell seals and emphasize its utility for identifying shortfalls or successes of a model at representing a biological process or pattern of interest. We show how posterior predictive checks can be used to strengthen inferences in ecological studies. We demonstrate the application of this method on analyses dealing with the question of individual reproductive heterogeneity in a population of Antarctic pinnipeds. PMID:24834335

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

2014-01-01

331

DYNAMIC PREDICTION OF CH4 EMISSION IN LONGWALLS Christian TAUZffiDE and Zbigniew POKRYSZKA  

E-print Network

DYNAMIC PREDICTION OF CH4 EMISSION IN LONGWALLS Christian TAUZffiDE and Zbigniew POKRYSZKA INERIS Vemeuil en Halatte France SUMMARY Methods for predicting mean CH4 emission in longwalls have been, development of dynamic prediction methods - e.g. allowing prediction of emission on a daily or weekly basis

Paris-Sud XI, Université de

332

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

SciTech Connect

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

Beamesderfer, R.C.P.; Rien, T.A.; Nigro, A.A. [Oregon Department of Fish and Wildlife, Clackamas, OR (United States)

1995-11-01

333

Modelling Lipid Competition Dynamics in Heterogeneous Protocell Populations  

E-print Network

In addressing the origins of Darwinian evolution, recent experimental work has been focussed on the discovery of simple physical effects which would provide a relevant selective advantage to protocells competing with each other for a limited supply of lipid. In particular, data coming from Szostak's lab suggest that the transition from simple prebiotically plausible lipid membranes to more complex and heterogeneous ones, closer to real biomembranes, may have been driven by changes in the fluidity of the membrane and its affinity for the available amphiphilic compound, which in turn would involve changes in vesicle growth dynamics. Earlier work from the same group reported osmotically-driven competition effects, whereby swelled vesicles grow at the expense of isotonic ones. In this paper, we try to expand on these experimental studies by providing a simple mathematical model of a population of competing vesicles, studied at the level of lipid kinetics. In silico simulations of the model are able to reproduce qualitatively and often quantitatively the experimentally reported competition effects in both scenarios. We also develop a method for numerically solving the equilibrium of a population of competing model vesicles, which is quite general and applicable to different vesicle kinetics schemes.

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

2014-01-30

334

Modelling multi-pulse population dynamics from ultrafast spectroscopy.  

PubMed

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

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

2011-01-01

335

Potential Predictability in the NCEP CPC Dynamical Seasonal Forecast System.  

NASA Astrophysics Data System (ADS)

Monthly and seasonal predictions of mean atmospheric states have traditionally been viewed as a boundary forcing problem, with little regard for the role of atmospheric initial conditions (IC). The potential predictability of these mean states is investigated using hindcasted monthly mean January (JAN) and seasonal mean January February March (JFM) 200-hPa geopotential heights from the National Centers for Environmental Prediction Climate Prediction Center (NCEP CPC) Dynamical Seasonal Prediction System along with the corresponding data from the NCEP National Center for Atmospheric Research (NCAR) reanalysis for the period 1980 2000. With lead times ranging from 1 to 4 months, analyses of variance tests are employed to separate the total variability into an unpredictable internal component, due to atmospheric dynamics, and a potentially predictable external component, due to the boundary forcing. These components represent the noise and signal, respectively, and areas where the signal exceeds the noise designate where time averages could be potentially predicted with some degree of skill. Temporal anomaly correlations (ACs) between ensemble-averaged model height anomalies and reanalysis height anomalies also provide a measure of the model skill.Comparisons between the results of these tests for the different initialization times confirm that, for this model, the atmospheric initial conditions have little effect on the monthly and seasonal means for lead times of one month or more. The model proves to be highly skillful in the Tropics, as expected. Signal-to-noise ratios (SNRs) and ACs also show four areas in the extratropics displaying significant skill: the South Pacific Ocean, Southern Ocean, Southeast Asia, and the Pacific North America (PNA) region. The skill found in the extratropics outside of the PNA region is highly encouraging. SNRs for JFM are approximately twice those for JAN, suggesting that seasonal forecasts are more reliable than monthly forecasts. Anomaly correlations for El Niño Southern Oscillation (ENSO) warm and cold events are markedly higher than correlations for both the period 1980 2000 and the subset of ENSO neutral events. The model's ability to accurately capture changes in the atmosphere in response to changes in sea surface temperatures (SSTs) suggests that accurate forecasting of SSTs in the ocean could lead to more accurate forecasts of atmospheric conditions associated with ENSO warm and cold events.


Phelps, Michael W.; Kumar, Arun; O'Brien, James J.

2004-10-01

336

Genetic divergence does not predict change in ornament expression among populations of stalk-eyed flies  

Microsoft Academic Search

Stalk-eyed flies (Diptera: Diopsidae) possess eyes at the ends of elongated peduncles, and exhibit dramatic variation in eye span, relative to body length, among species. In some sexually dimorphic species, evidence indicates that eye span is under both intra- and intersexual selection. Theory predicts that isolated populations should evolve differences in sexually selected traits due to drift. To determine if

JOHN G. S WALLOW; LISA E. W ALLACE; SARAH J. C HRISTIANSON; PHILIP M. J OHNS; GERALD S. W ILKINSON

2005-01-01

337

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

ERIC Educational Resources Information Center

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

Alloway, Tracy Packiam; Gregory, David

2013-01-01

338

Carotid plaque burden predicts cardiovascular death: A prospective, population-based cohort study  

Microsoft Academic Search

Background: Ultrasonographic assessment of plaque in the carotid artery is a recognized non-invasive technique to reveal atherosclerosis. The aim of this study was to investigate whether plaque in the carotid arteries predicted cardiovascular (CV) death independently of traditional CV risk factors in the general population.Methods: In 1993 to 1994, a random sample of 2651 men and women, aged 41, 51,

Marina K. Christensen; Michael H. Olsen; Lars T. Jensen; Hans Ibsen

2005-01-01

339

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

ERIC Educational Resources Information Center

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

Goodman, Anna; Goodman, Robert

2011-01-01

340

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

EPA Science Inventory

The US EPA National Exposure Research Laboratory (NERL) is currently developing an integrated human exposure source-to-dose modeling system (HES2D). This modeling system will incorporate models that use a probabilistic approach to predict population exposures to environmental ...

341

Predicting the acoustic response of a microbubble population for contrast imaging in medical ultrasound  

Microsoft Academic Search

Although the behavior of a bubble in an acoustic field has been studied extensively, few theoretical treatments to date have been applied to simulate the acoustic response of a real population of variably sized microbubbles in a finite-width sound beam. In this paper, we present a modified Trilling equation for single bubble dynamics that has been solved numerically for different

Chien Ting Chin; Peter N. Burns

2000-01-01

342

Transmembrane topology and signal peptide prediction using dynamic bayesian networks.  

PubMed

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

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

2008-11-01

343

Cooperative Bacterial Growth Dynamics Predict the Evolution of Antibiotic Resistance  

NASA Astrophysics Data System (ADS)

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.

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

2011-03-01

344

Water-level fluctuations and metapopulation dynamics as drivers of genetic diversity in populations of three Tanganyikan cichlid fish species  

PubMed Central

Understanding how genetic variation is generated and maintained in natural populations, and how this process unfolds in a changing environment, remains a central issue in biological research. In this work, we analysed patterns of genetic diversity from several populations of three cichlid species from Lake Tanganyika in parallel, using the mitochondrial DNA control region. We sampled populations inhabiting the littoral rocky habitats in both very deep and very shallow areas of the lake. We hypothesized that the former would constitute relatively older, more stable and genetically more diverse populations, because they should have been less severely affected by the well-documented episodes of dramatic water-level fluctuations. In agreement with our predictions, populations of all three species sampled in very shallow shorelines showed traces of stronger population growth than populations of the same species inhabiting deep shorelines. However, contrary to our working hypothesis, we found a significant trend towards increased genetic diversity in the younger, demographically less stable populations inhabiting shallow areas, in comparison with the older and more stable populations inhabiting the deep shorelines. We interpret this finding as the result of the establishment of metapopulation dynamics in the former shorelines, by the frequent perturbation and reshuffling of individuals between populations due to the lake-level fluctuations. The repeated succession of periods of allopatric separation and secondary contact is likely to have further increased the rapid pace of speciation in lacustrine cichlids. PMID:23837841

Nevado, B; Mautner, S; Sturmbauer, C; Verheyen, E

2013-01-01

345

Water-level fluctuations and metapopulation dynamics as drivers of genetic diversity in populations of three Tanganyikan cichlid fish species.  

PubMed

Understanding how genetic variation is generated and maintained in natural populations, and how this process unfolds in a changing environment, remains a central issue in biological research. In this work, we analysed patterns of genetic diversity from several populations of three cichlid species from Lake Tanganyika in parallel, using the mitochondrial DNA control region. We sampled populations inhabiting the littoral rocky habitats in both very deep and very shallow areas of the lake. We hypothesized that the former would constitute relatively older, more stable and genetically more diverse populations, because they should have been less severely affected by the well-documented episodes of dramatic water-level fluctuations. In agreement with our predictions, populations of all three species sampled in very shallow shorelines showed traces of stronger population growth than populations of the same species inhabiting deep shorelines. However, contrary to our working hypothesis, we found a significant trend towards increased genetic diversity in the younger, demographically less stable populations inhabiting shallow areas, in comparison with the older and more stable populations inhabiting the deep shorelines. We interpret this finding as the result of the establishment of metapopulation dynamics in the former shorelines, by the frequent perturbation and reshuffling of individuals between populations due to the lake-level fluctuations. The repeated succession of periods of allopatric separation and secondary contact is likely to have further increased the rapid pace of speciation in lacustrine cichlids. PMID:23837841

Nevado, B; Mautner, S; Sturmbauer, C; Verheyen, E

2013-08-01

346

Predicting physical time series using dynamic ridge polynomial neural networks.  

PubMed

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

Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir

2014-01-01

347

Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks  

PubMed Central

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

Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir

2014-01-01

348

Seasonal forcing on the dynamics of Clethrionomys rufocanus : Modeling geographic gradients in population dynamics  

Microsoft Academic Search

We interpret gradients in population dynamics of the gray-sided vole from the southwestern part of the island of Hokkaido\\u000a to its northeastern part within the framework of a phenomenological model involving the relative length of summer and winter.\\u000a In Hokkaido, as in other northern regions, both spring and fall is considered as short transition periods between the two\\u000a main seasons

Nils Chr Stenseth; Ottar N. Bjørnstad; Takashi Saitoh

1998-01-01

349

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

PubMed Central

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

?erná, Lucie; Münzbergová, Zuzana

2013-01-01

350

Dynamical evolution and spatial mixing of multiple population globular clusters  

NASA Astrophysics Data System (ADS)

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.

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

2013-03-01

351

Diabetes risk scores and death: predictability and practicability in two different populations.  

PubMed

The aim was to examine the capacity of commonly used type 2 diabetes mellitus (T2DM) risk scores to predict overall mortality. The US-based NHANES III (n = 3138; 982 deaths) and the Swiss-based CoLaus study (n = 3946; 191 deaths) were used. The predictive value of eight T2DM risk scores regarding overall mortality was tested. The Griffin score, based on few self-reported parameters, presented the best (NHANES III) and second best (CoLaus) predictive capacity. Generally, the predictive capacity of scores based on clinical (anthropometrics, lifestyle, history) and biological (blood parameters) data was not better than of scores based solely on clinical self-reported data. T2DM scores can be validly used to predict mortality risk in general populations without diabetes. Comparison with other scores could further show whether such scores also suit as a screening tool for quick overall health risk assessment. PMID:25085474

Faeh, David; Marques-Vidal, Pedro; Brändle, Michael; Braun, Julia; Rohrmann, Sabine

2015-02-01

352

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

PubMed Central

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

Jager, Tjalling; Klok, Chris

2010-01-01

353

Population dynamics of three early seral herb species in Pacific Northwest forests.  

E-print Network

??I investigated the population dynamics of fireweed (Epilobium angustfolium), foxglove (Digitalis purpurea) , and woodland groundsel (Senecio sylvaticus) to understand their colonization, persistence, and extirpation… (more)

Hanson, D. Eric

1998-01-01

354

Predictions of Native American Population Structure Using Linguistic Covariates in a Hidden Regression Framework  

PubMed Central

Background The mainland of the Americas is home to a remarkable diversity of languages, and the relationships between genes and languages have attracted considerable attention in the past. Here we investigate to which extent geography and languages can predict the genetic structure of Native American populations. Methodology/Principal Findings Our approach is based on a Bayesian latent cluster regression model in which cluster membership is explained by geographic and linguistic covariates. After correcting for geographic effects, we find that the inclusion of linguistic information improves the prediction of individual membership to genetic clusters. We further compare the predictive power of Greenberg's and The Ethnologue classifications of Amerindian languages. We report that The Ethnologue classification provides a better genetic proxy than Greenberg's classification at the stock and at the group levels. Although high predictive values can be achieved from The Ethnologue classification, we nevertheless emphasize that Choco, Chibchan and Tupi linguistic families do not exhibit a univocal correspondence with genetic clusters. Conclusions/Significance The Bayesian latent class regression model described here is efficient at predicting population genetic structure using geographic and linguistic information in Native American populations. PMID:21305006

Jay, Flora; François, Olivier; Blum, Michael G. B.

2011-01-01

355

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

PubMed

Understanding how climate change, exploitation and eutrophication will affect populations and ecosystems of the Baltic Sea can be facilitated with models which realistically combine these forcings into common frameworks. Here, we evaluate sensitivity of fish recruitment and population dynamics to past and future environmental forcings provided by three ocean-biogeochemical models of the Baltic Sea. Modeled temperature explained nearly as much variability in reproductive success of sprat (Sprattus sprattus; Clupeidae) as measured temperatures during 1973-2005, and both the spawner biomass and the temperature have influenced recruitment for at least 50 years. The three Baltic Sea models estimate relatively similar developments (increases) in biomass and fishery yield during twenty-first century climate change (ca. 28 % range among models). However, this uncertainty is exceeded by the one associated with the fish population model, and by the source of global climate data used by regional models. Knowledge of processes and biases could reduce these uncertainties. PMID:22926884

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

2012-09-01

356

Disease dynamics during wildlife translocations: disruptions to the host population and potential  

E-print Network

complications due to disease (reviewed in Cunningham, 1996; Kock et al., 2010)Disease dynamics during wildlife translocations: disruptions to the host population and potential Research Center, U.S. Geological Survey, Henderson, NV, USA 2 Center for Infectious Disease Dynamics

Bansal, Shweta

357

Accuracy of genomic prediction within and across populations for nematode resistance and body weight traits in sheep.  

PubMed

Genomic prediction utilizes single nucleotide polymorphism (SNP) chip data to predict animal genetic merit. It has the advantage of potentially capturing the effects of the majority of loci that contribute to genetic variation in a trait, even when the effects of the individual loci are very small. To implement genomic prediction, marker effects are estimated with a training set, including individuals with marker genotypes and trait phenotypes; subsequently, genomic estimated breeding values (GEBV) for any genotyped individual in the population can be calculated using the estimated marker effects. In this study, we aimed to: (i) evaluate the potential of genomic prediction to predict GEBV for nematode resistance traits and BW in sheep, within and across populations; (ii) evaluate the accuracy of these predictions through within-population cross-validation; and (iii) explore the impact of population structure on the accuracy of prediction. Four data sets comprising 752 lambs from a Scottish Blackface population, 2371 from a Sarda×Lacaune backcross population, 1000 from a Martinik Black-Belly×Romane backcross population and 64 from a British Texel population were used in this study. Traits available for the analysis were faecal egg count for Nematodirus and Strongyles and BW at different ages or as average effect, depending on the population. Moreover, immunoglobulin A was also available for the Scottish Blackface population. Results show that GEBV had moderate to good within-population predictive accuracy, whereas across-population predictions had accuracies close to zero. This can be explained by our finding that in most cases the accuracy estimates were mostly because of additive genetic relatedness between animals, rather than linkage disequilibrium between SNP and quantitative trait loci. Therefore, our results suggest that genomic prediction for nematode resistance and BW may be of value in closely related animals, but that with the current SNP chip genomic predictions are unlikely to work across breeds. PMID:24636823

Riggio, V; Abdel-Aziz, M; Matika, O; Moreno, C R; Carta, A; Bishop, S C

2014-04-01

358

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

PubMed

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

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

2014-05-01

359

Dynamics of Populations of Planetary Systems (IAU C197)  

NASA Astrophysics Data System (ADS)

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

Knezevic, Zoran; Milani, Andrea

2005-05-01

360

Genomic predictions based on a joint reference population for the Nordic Red cattle breeds.  

PubMed

The main aim of this study was to compare accuracies of imputation and genomic predictions based on single and joint reference populations for Norwegian Red (NRF) and a composite breed (DFS) consisting of Danish Red, Finnish Ayrshire, and Swedish Red. The single nucleotide polymorphism (SNP) data for NRF consisted of 2 data sets: one including 25,000 markers (NRF25K) and the other including 50,000 markers (NRF50K). The NRF25K data set had 2,572 bulls, and the NRF50K data set had 1,128 bulls. Four hundred forty-two bulls were genotyped in both data sets (double-genotyped bulls). The DFS data set (DSF50K) included 50,000 markers of 13,472 individuals, of which around 4,700 were progeny-tested bulls. The NRF25K data set was imputed to 50,000 density using the software Beagle. The average error rate for the imputation of NRF25K decreased slightly from 0.023 to 0.021, and the correlation between observed and imputed genotypes changed from 0.935 to 0.936 when comparing the NRF50K reference and the NRF50K-DFS50K joint reference imputations. A genomic BLUP (GBLUP) model and a Bayesian 4-component mixture model were used to predict genomic breeding values for the NRF and DFS bulls based on the single and joint NRF and DFS reference populations. In the multiple population predictions, accuracies of genomic breeding values increased for the 3 production traits (milk, fat, and protein yields) for both NRF and DFS. Accuracies increased by 6 and 1.3 percentage points, on average, for the NRF and DFS bulls, respectively, using the GBLUP model, and by 9.3 and 1.3 percentage points, on average, using the Bayesian 4-component mixture model. However, accuracies for health or reproduction traits did not increase from the multiple population predictions. Among the 3 DFS populations, Swedish Red gained most in accuracies from the multiple population predictions, presumably because Swedish Red has a closer genetic relationship with NRF than Danish Red and Finnish Ayrshire. The Bayesian 4-component mixture model performed better than the GBLUP model for most production traits for both NRF and DFS, whereas no advantage was found for health or reproduction traits. In general, combining NRF and DFS reference populations was useful in genomic predictions for both the NRF and DFS bulls. PMID:24792791

Zhou, L; Heringstad, B; Su, G; Guldbrandtsen, B; Meuwissen, T H E; Svendsen, M; Grove, H; Nielsen, U S; Lund, M S

2014-07-01

361

Non-linear population dynamics in chemostats associated with live-dead cell cycling in Escherichia coli strain K12-MG1655.  

PubMed

Bacterial populations conditionally display non-linear dynamic behaviour in bioreactors with steady inputs, which is often attributed to varying habitat conditions or shifting intracellular metabolic activity. However, mathematical modelling has predicted that such dynamics also might simply result from staggered birth, growth, and death events of groups of cells within the population, causing density oscillations and the cycling of live and dead cells within the system. To assess this prediction, laboratory experiments were performed on Escherichia coli strain K12-MG1655 grown in chemostats to first define fine-scale population dynamics over time (minutes) and then determine whether the dynamics correlate with live-dead cell cycles in the system. E. coli populations displayed consistent oscillatory behaviour in all experiments. However, close synchronisation between OD??? and live-dead cell oscillations (within ~33-38 min cycles) only became statistically significant (p?predicted by the model and also consistent with recent observations that death is non-stochastic in such populations. These data show that oscillatory dynamic behaviour is intrinsic in bioreactor populations, which has implications to process operations in biotechnology. PMID:20890753

Chi Fru, Ernest; Ofi?eru, Irina Dana; Lavric, Vasile; Graham, David W

2011-02-01

362

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

PubMed

Synfire waves are propagating spike packets in synfire chains, which are feedforward chains embedded in random networks. Although synfire waves have proved to be effective quantification for network activity with clear relations to network structure, their utilities are largely limited to feedforward networks with low background activity. To overcome these shortcomings, we describe a novel generalisation of synfire waves, and define 'synconset wave' as a cascade of first spikes within a synchronisation event. Synconset waves would occur in 'synconset chains', which are feedforward chains embedded in possibly heavily recurrent networks with heavy background activity. We probed the utility of synconset waves using simulation of single compartment neuron network models with biophysically realistic conductances, and demonstrated that the spread of synconset waves directly follows from the network connectivity matrix and is modulated by top-down inputs and the resultant oscillations. Such synconset profiles lend intuitive insights into network organisation in terms of connection probabilities between various network regions rather than an adjacency matrix. To test this intuition, we develop a Bayesian likelihood function that quantifies the probability that an observed synfire wave was caused by a given network. Further, we demonstrate it's utility in the inverse problem of identifying the network that caused a given synfire wave. This method was effective even in highly subsampled networks where only a small subset of neurons were accessible, thus showing it's utility in experimental estimation of connectomes in real neuronal-networks. Together, we propose synconset chains/waves as an effective framework for understanding the impact of network structure on function, and as a step towards developing physiology-driven network identification methods. Finally, as synconset chains extend the utilities of synfire chains to arbitrary networks, we suggest utilities of our framework to several aspects of network physiology including cell assemblies, population codes, and oscillatory synchrony. PMID:24116018

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

2013-01-01

363

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

PubMed

Environmental variability has important influences on mosquito life cycles and understanding the spatial and temporal patterns of mosquito populations is critical for mosquito control and vector-borne disease prevention. Meteorological data used for model-based predictions of mosquito abundance and life cycle dynamics are typically acquired from ground-based weather stations; however, data availability and completeness are often limited by sparse networks and resource availability. In contrast, environmental measurements from satellite remote sensing are more spatially continuous and can be retrieved automatically. This study compared environmental measurements from the NASA Advanced Microwave Scanning Radiometer on EOS (AMSR-E) and in situ weather station data to examine their ability to predict the abundance of two important mosquito species (Aedes vexans and Culex tarsalis) in Sioux Falls, South Dakota, USA from 2005 to 2010. The AMSR-E land parameters included daily surface water inundation fraction, surface air temperature, soil moisture, and microwave vegetation opacity. The AMSR-E derived models had better fits and higher forecasting accuracy than models based on weather station data despite the relatively coarse (25-km) spatial resolution of the satellite data. In the AMSR-E models, air temperature and surface water fraction were the best predictors of Aedes vexans, whereas air temperature and vegetation opacity were the best predictors of Cx. tarsalis abundance. The models were used to extrapolate spatial, seasonal, and interannual patterns of climatic suitability for mosquitoes across eastern South Dakota. Our findings demonstrate that environmental metrics derived from satellite passive microwave radiometry are suitable for predicting mosquito population dynamics and can potentially improve the effectiveness of mosquito-borne disease early warning systems. PMID:23049143

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

2012-10-01

364

Transcriptome dynamics-based operon prediction in prokaryotes  

PubMed Central

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

2014-01-01

365

Usefulness of multiparental populations of maize (Zea mays L.) for genome-based prediction.  

PubMed

The efficiency of marker-assisted prediction of phenotypes has been studied intensively for different types of plant breeding populations. However, one remaining question is how to incorporate and counterbalance information from biparental and multiparental populations into model training for genome-wide prediction. To address this question, we evaluated testcross performance of 1652 doubled-haploid maize (Zea mays L.) lines that were genotyped with 56,110 single nucleotide polymorphism markers and phenotyped for five agronomic traits in four to six European environments. The lines are arranged in two diverse half-sib panels representing two major European heterotic germplasm pools. The data set contains 10 related biparental dent families and 11 related biparental flint families generated from crosses of maize lines important for European maize breeding. With this new data set we analyzed genome-based best linear unbiased prediction in different validation schemes and compositions of estimation and test sets. Further, we theoretically and empirically investigated marker linkage phases across multiparental populations. In general, predictive abilities similar to or higher than those within biparental families could be achieved by combining several half-sib families in the estimation set. For the majority of families, 375 half-sib lines in the estimation set were sufficient to reach the same predictive performance of biomass yield as an estimation set of 50 full-sib lines. In contrast, prediction across heterotic pools was not possible for most cases. Our findings are important for experimental design in genome-based prediction as they provide guidelines for the genetic structure and required sample size of data sets used for model training. PMID:25236445

Lehermeier, Christina; Krämer, Nicole; Bauer, Eva; Bauland, Cyril; Camisan, Christian; Campo, Laura; Flament, Pascal; Melchinger, Albrecht E; Menz, Monica; Meyer, Nina; Moreau, Laurence; Moreno-González, Jesús; Ouzunova, Milena; Pausch, Hubert; Ranc, Nicolas; Schipprack, Wolfgang; Schönleben, Manfred; Walter, Hildrun; Charcosset, Alain; Schön, Chris-Carolin

2014-09-01

366

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

PubMed

It has been shown that plant genotype can strongly affect not only individual herbivore performance, but also community composition and ecosystem function. Few studies, however, have addressed how plant genotype affects herbivore population dynamics. In this paper, we used a simulation modeling approach to ask how the genetic composition of a forest influences pest outbreak dynamics, using the example of aspen (Populus tremuloides) and forest tent caterpillars (FTC; Malacosoma disstria). Specifically, we examined how plant genotype, the relative size of genotypic patches, and the rate of insect dispersal between them, affect the frequency, amplitude, and duration of outbreaks. We found that coupling two different genotypes does not necessarily result in an averaging of insect dynamics. Instead, depending on the ratio of patch sizes, when dispersal rates are moderate, outbreaks in the two-genotype case may be more or less severe than in forests of either genotype alone. Thresholds for different dynamic behaviors were similar for all genotypic combinations. Thus, the qualitative behavior of a stand of two different genotypes can be predicted based on the response of the insect to each genotype, the relative sizes of the two patches, and the scale of insect dispersal. PMID:24597225

Moran, Emily V; Bewick, Sharon; Cobbold, Christina A

2013-12-01

367

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

PubMed Central

Although molecular chaperones are essential components of protein homeostatic machinery, their mechanism of action and impact on adaptation and evolutionary dynamics remain controversial. Here we developed a physics-based ab initio multi-scale model of a living cell for population dynamics simulations to elucidate the effect of chaperones on adaptive evolution. The 6-loci genomes of model cells encode model proteins, whose folding and interactions in cellular milieu can be evaluated exactly from their genome sequences. A genotype-phenotype relationship that is based on a simple yet non-trivially postulated protein-protein interaction (PPI) network determines the cell division rate. Model proteins can exist in native and molten globule states and participate in functional and all possible promiscuous non-functional PPIs. We find that an active chaperone mechanism, whereby chaperones directly catalyze protein folding, has a significant impact on the cellular fitness and the rate of evolutionary dynamics, while passive chaperones, which just maintain misfolded proteins in soluble complexes have a negligible effect on the fitness. We find that by partially releasing the constraint on protein stability, active chaperones promote a deeper exploration of sequence space to strengthen functional PPIs, and diminish the non-functional PPIs. A key experimentally testable prediction emerging from our analysis is that down-regulation of chaperones that catalyze protein folding significantly slows down the adaptation dynamics. PMID:24244114

Çetinba?, Murat; Shakhnovich, Eugene I.

2013-01-01

368

Population structure in the native range predicts the spread of introduced marine species.  

PubMed

Forecasting invasion success remains a fundamental challenge in invasion biology. The effort to identify universal characteristics that predict which species become invasive has faltered in part because of the diversity of taxa and systems considered. Here, we use an alternative approach focused on the spread stage of invasions. FST, a measure of alternative fixation of alleles, is a common proxy for realized dispersal among natural populations, summarizing the combined influences of life history, behaviour, habitat requirements, population size, history and ecology. We test the hypothesis that population structure in the native range (FST) is negatively correlated with the geographical extent of spread of marine species in an introduced range. An analysis of the available data (29 species, nine phyla) revealed a significant negative correlation (R(2) = 0.245-0.464) between FST and the extent of spread of non-native species. Mode FST among pairwise comparisons between populations in the native range demonstrated the highest predictive power (R(2) = 0.464, p < 0.001). There was significant improvement when marker type was considered, with mtDNA datasets providing the strongest relationship (n = 21, R(2) = 0.333-0.516). This study shows that FST can be used to make qualitative predictions concerning the geographical extent to which a non-native marine species will spread once established in a new area. PMID:23595272

Gaither, Michelle R; Bowen, Brian W; Toonen, Robert J

2013-06-01

369

The population and evolutionary dynamics of phage and bacteria with CRISPR-mediated immunity.  

PubMed

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), together with associated genes (cas), form the CRISPR-cas adaptive immune system, which can provide resistance to viruses and plasmids in bacteria and archaea. Here, we use mathematical models, population dynamic experiments, and DNA sequence analyses to investigate the host-phage interactions in a model CRISPR-cas system, Streptococcus thermophilus DGCC7710 and its virulent phage 2972. At the molecular level, the bacteriophage-immune mutant bacteria (BIMs) and CRISPR-escape mutant phage (CEMs) obtained in this study are consistent with those anticipated from an iterative model of this adaptive immune system: resistance by the addition of novel spacers and phage evasion of resistance by mutation in matching sequences or flanking motifs. While CRISPR BIMs were readily isolated and CEMs generated at high rates (frequencies in excess of 10(-6)), our population studies indicate that there is more to the dynamics of phage-host interactions and the establishment of a BIM-CEM arms race than predicted from existing assumptions about phage infection and CRISPR-cas immunity. Among the unanticipated observations are: (i) the invasion of phage into populations of BIMs resistant by the acquisition of one (but not two) spacers, (ii) the survival of sensitive bacteria despite the presence of high densities of phage, and (iii) the maintenance of phage-limited communities due to the failure of even two-spacer BIMs to become established in populations with wild-type bacteria and phage. We attribute (i) to incomplete resistance of single-spacer BIMs. Based on the results of additional modeling and experiments, we postulate that (ii) and (iii) can be attributed to the phage infection-associated production of enzymes or other compounds that induce phenotypic phage resistance in sensitive bacteria and kill resistant BIMs. We present evidence in support of these hypotheses and discuss the implications of these results for the ecology and (co)evolution of bacteria and phage. PMID:23516369

Levin, Bruce R; Moineau, Sylvain; Bushman, Mary; Barrangou, Rodolphe

2013-01-01

370

The Population and Evolutionary Dynamics of Phage and Bacteria with CRISPR–Mediated Immunity  

PubMed Central

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), together with associated genes (cas), form the CRISPR–cas adaptive immune system, which can provide resistance to viruses and plasmids in bacteria and archaea. Here, we use mathematical models, population dynamic experiments, and DNA sequence analyses to investigate the host–phage interactions in a model CRISPR–cas system, Streptococcus thermophilus DGCC7710 and its virulent phage 2972. At the molecular level, the bacteriophage-immune mutant bacteria (BIMs) and CRISPR–escape mutant phage (CEMs) obtained in this study are consistent with those anticipated from an iterative model of this adaptive immune system: resistance by the addition of novel spacers and phage evasion of resistance by mutation in matching sequences or flanking motifs. While CRISPR BIMs were readily isolated and CEMs generated at high rates (frequencies in excess of 10?6), our population studies indicate that there is more to the dynamics of phage–host interactions and the establishment of a BIM–CEM arms race than predicted from existing assumptions about phage infection and CRISPR–cas immunity. Among the unanticipated observations are: (i) the invasion of phage into populations of BIMs resistant by the acquisition of one (but not two) spacers, (ii) the survival of sensitive bacteria despite the presence of high densities of phage, and (iii) the maintenance of phage-limited communities due to the failure of even two-spacer BIMs to become established in populations with wild-type bacteria and phage. We attribute (i) to incomplete resistance of single-spacer BIMs. Based on the results of additional modeling and experiments, we postulate that (ii) and (iii) can be attributed to the phage infection-associated production of enzymes or other compounds that induce phenotypic phage resistance in sensitive bacteria and kill resistant BIMs. We present evidence in support of these hypotheses and discuss the implications of these results for the ecology and (co)evolution of bacteria and phage. PMID:23516369

Levin, Bruce R.; Moineau, Sylvain; Bushman, Mary; Barrangou, Rodolphe

2013-01-01

371

Dynamic wake prediction and visualization with uncertainty analysis  

NASA Technical Reports Server (NTRS)

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.

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

2005-01-01

372

Montane refugia predict population genetic structure in the Large-blotched Ensatina salamander.  

PubMed

Understanding the biotic consequences of Pleistocene range shifts and fragmentation remains a fundamental goal in historical biogeography and evolutionary biology. Here, we combine species distribution models (SDM) from the present and two late Quaternary time periods with multilocus genetic data (mitochondrial DNA and microsatellites) to evaluate the effect of climate-induced habitat shifts on population genetic structure in the Large-blotched Ensatina (Ensatina eschscholtzii klauberi), a plethodontid salamander endemic to middle and high-elevation conifer forest in the Transverse and Peninsular Ranges of southern California and northern Baja California. A composite SDM representing the range through time predicts two disjunct refugia, one in southern California encompassing the core of the species range and the other in the Sierra San Pedro Mártir of northern Baja California at the southern limit of the species range. Based on our spatial model, we would expect a pattern of high connectivity among populations within the northern refugium and, conversely, a pattern of isolation due to long-term persistence of the Sierra San Pedro Mártir population. Our genetic results are consistent with these predictions based on the hypothetical refugia in that (i) historical measures of population connectivity among stable areas are correlated with gene flow estimates; and (ii) there is strong geographical structure between separate refugia. These results provide evidence for the role of recent climatic change in shaping patterns of population persistence and connectivity within the Transverse and Peninsular Ranges, an evolutionary hotspot. PMID:23379992

Devitt, Thomas J; Devitt, Susan E Cameron; Hollingsworth, Bradford D; McGuire, Jimmy A; Moritz, Craig

2013-03-01

373

Winter rainfall predicts phenology in widely separated populations of a migrant songbird.  

PubMed

Climate change is affecting behaviour and phenology in many animals. In migratory birds, weather patterns both at breeding and at non-breeding sites can influence the timing of spring migration and breeding. However, variation in responses to weather across a species range has rarely been studied, particularly among populations that may winter in different locations. We used prior knowledge of migratory connectivity to test the influence of weather from predicted non-breeding sites on bird phenology in two breeding populations of a long-distance migratory bird species separated by 3,000 km. We found that winter rainfall showed similar associations with arrival and egg-laying dates in separate breeding populations on an east-west axis: greater rainfall in Jamaica and eastern Mexico was generally associated with advanced American redstart (Setophaga ruticilla) phenology in Ontario and Alberta, respectively. In Ontario, these patterns of response could largely be explained by changes in the behaviour of individual birds, i.e., phenotypic plasticity. By explicitly incorporating migratory connectivity into responses to climate, our data suggest that widely separated breeding populations can show independent and geographically specific associations with changing weather conditions. The tendency of individuals to delay migration and breeding following dry winters could result in population declines due to predicted drying trends in tropical areas and the tight linkage between early arrival/breeding and reproductive success in long-distance migrants. PMID:23161154

McKellar, Ann E; Marra, Peter P; Hannon, Susan J; Studds, Colin E; Ratcliffe, Laurene M

2013-06-01

374

Comparison of individual-based modeling and population approaches for prediction of foodborne pathogens growth.  

PubMed

Individual-based modeling (IBM) approach combined with the microenvironment modeling of vacuum-packed cold-smoked salmon was more effective to describe the variability of the growth of a few Listeria monocytogenes cells contaminating irradiated salmon slices than the traditional population models. The IBM approach was particularly relevant to predict the absence of growth in 25% (5 among 20) of artificially contaminated cold-smoked salmon samples stored at 8 °C. These results confirmed similar observations obtained with smear soft cheese (Ferrier et al., 2013). These two different food models were used to compare the IBM/microscale and population/macroscale modeling approaches in more global exposure and risk assessment frameworks taking into account the variability and/or the uncertainty of the factors influencing the growth of L. monocytogenes. We observed that the traditional population models significantly overestimate exposure and risk estimates in comparison to IBM approach when contamination of foods occurs with a low number of cells (<100 per serving). Moreover, the exposure estimates obtained with the population model were characterized by a great uncertainty. The overestimation was mainly linked to the ability of IBM to predict no growth situations rather than the consideration of microscale environment. On the other hand, when the aim of quantitative risk assessment studies is only to assess the relative impact of changes in control measures affecting the growth of foodborne bacteria, the two modeling approach gave similar results and the simplest population approach was suitable. PMID:25500386

Augustin, Jean-Christophe; Ferrier, Rachel; Hezard, Bernard; Lintz, Adrienne; Stahl, Valérie

2015-02-01

375

Evaluating physiological dynamics via synchrosqueezing: prediction of ventilator weaning.  

PubMed

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

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

2014-03-01

376

The influence of spatio-temporal resource fluctuations on insular rat population dynamics  

PubMed Central

Local spatio-temporal resource variations can strongly influence the population dynamics of small mammals. This is particularly true on islands which are bottom-up driven systems, lacking higher order predators and with high variability in resource subsidies. The influence of resource fluctuations on animal survival may be mediated by individual movement among habitat patches, but simultaneously analysing survival, resource availability and habitat selection requires sophisticated analytical methods. We use a Bayesian multi-state capture–recapture model to estimate survival and movement probabilities of non-native black rats (Rattus rattus) across three habitats seasonally varying in resource availability. We find that survival varies most strongly with temporal rainfall patterns, overwhelming minor spatial variation among habitats. Surprisingly for a generalist forager, movement between habitats was rare, suggesting individuals do not opportunistically respond to spatial resource subsidy variations. Climate is probably the main driver of rodent population dynamics on islands, and even substantial habitat and seasonal spatial subsidies are overwhelmed in magnitude by predictable annual patterns in resource pulses. Marked variation in survival and capture has important implications for the timing of rat control. PMID:21775327

Russell, James C.; Ruffino, Lise

2012-01-01

377

Predictive capacity of carbamazepine pharmacokinetic parameters in a Portuguese outpatient population.  

PubMed

The individualization of anticonvulsant therapy regimens can contribute to the implementation of appropriate carbamazepine (CBZ) maintenance doses in epileptic patients. An accurate method for the prediction of concentrations based on a determination of parameters and serum concentrations could be of clinical relevance in the management of epilepsy. In this study, we retrospectively evaluated the predictive performance in an adult outpatient population of six different methods, representing six sets of CBZ pharmacokinetic parameters selected according to the literature using a Bayesian computer program (PKS System; Abbott Laboratories, Abbott Park, IL, USA). The study involved 50 patients with two or more available concentrations selected under several inclusion criteria. The patients were taking CBZ (between 200 and 1600 mg/d) in monotherapy or polytherapy regimens and had no hepatic or renal disease. Steady state concentrations were predicted according to the use of prior information and using one and two feedback patient concentrations. Accuracy and precision were assessed by mean prediction error (ME), mean squared prediction error (MSE) and root mean squared prediction error (RMSE). The analysis showed CL = 0.067 L/hour/kg and Vd = 1.19 L/kg as the most accurate and precise set of pharmacokinetic parameters, presenting the highest percentage of clinically acceptable estimates (error < 2 microg/mL). Additionally, predictions based on one measured feedback concentration were found to be more accurate and precise than prior population-based predictions; the use of two previous patient concentrations further improved predictive capacity but failed to show a significant difference when compared with predictions based on one measured feedback concentration. In conclusion, the adoption of the previously mentioned set of parameters as population estimates and the use of at least one feedback concentration through the Bayesian approach seems to be essential for a better CBZ use in clinical practice. Finally, despite the obtained results, we believe that the Portuguese pharmacokinetic parameter determination of antiepileptics should be carried out to improve the rationale and cost-effectiveness of anticonvulsant therapy. PMID:10217344

Falcão, A C; de Almeida, A M; Leitão, F; Santos, J; Sales, F; Caramona, M M

1999-04-01

378

Evolution of discrete populations and the canonical diffusion of adaptive dynamics  

Microsoft Academic Search

The biological theory of adaptive dynamics proposes a description of the long-term evolution of a structured asexual population. It is based on the assumptions of large population, rare mutations and small mutation steps, that lead to a deterministic ODE describing the evolution of the dominant type, called the ``canonical equation of adaptive dynamics.'' Here, in order to include the effect

Nicolas Champagnat; Amaury Lambert

2006-01-01

379

PLANT GENOTYPE AFFECTS LONG-TERM HERBIVORE POPULATION DYNAMICS AND EXTINCTION: CONSERVATION IMPLICATIONS  

Microsoft Academic Search

Few studies have linked long-term herbivore population dynamics with plant genetics. In this study we present evidence that plant genotype and hybridization influence the population dynamics of the poplar bud gall mite, Aceria parapopuli. Using experimental transfers and a five-year data set on mite abundance on two cottonwood species (Populus fremontii and P. angustifolia) and their naturally occurring hybrids, we

Patrick J. McIntyre; Thomas G. Whitham

2003-01-01

380

Population Dynamics of Common Carp in Eastern South Dakota Glacial Lakes Quinton E. Phelps  

E-print Network

precision among four alternative structures compared to otoliths for 139 common carp collected from fivePopulation Dynamics of Common Carp in Eastern South Dakota Glacial Lakes By Quinton E. Phelps and Fisheries Sciences South Dakota State University 2006 #12;11 Population Dynamics of Common Carp in Eastern

381

Winter weather affects asp viper Vipera aspis population dynamics through susceptible juveniles  

E-print Network

Winter weather affects asp viper Vipera aspis population dynamics through susceptible juveniles Res. and Flatt, T. 2005. Winter weather affects asp viper Vipera aspis population dynamics through susceptible European snake, the asp viper (Vipera aspis), over six to 17 years. Survival was lowest among juvenile

Altwegg, Res

382

Dynamics and Predictability of Deep Propagating Atmospheric Gravity Waves  

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

383

Predicting hemorrhage and obstruction in the elderly population using thromboelastographic indices  

PubMed Central

Objective To estimate the value of the different thromboelastogram indices for predicting hemorrhage and vascular obstruction in an elderly population. Methods This was a prospective cohort study of patients 65 years and older without hemato-logic disorders who received thromboelastography (TEG) examination at the Chinese People’s Liberation Army General Hospital from January 2007 to December 2010. Detailed information was collected at recruitment including their TEG test results. Subjects were then followed during outpatient visits and hospitalization. The primary outcome measures were hemorrhage and vascular obstruction. Receiver-operating characteristics (ROC) curves were used to compare the predictive value of the four TEG indices, reaction time (R), clot formation time (K), maximal amplitude (MA), alpha angle (ANGLE) and their combination for predicting hemorrhage and vascular obstruction. The maximal Youden’s index was used to estimate optimal cut-off values for the indices. Areas under the ROC curves were used to estimate overall predictive accuracies. Results A total of 403 elderly patients met inclusion criteria and were included: 373 male and 30 females with mean age 83.0 ± 7.3 years and range of 65–103 years. Hemorrhage occurred in 25 (6.2%) patients and vascular obstruction in 78 (19.4%) patients during the 2-year follow up. The currently recommended TEG cut-off values were poorly predictive of vascular obstruction and modestly predictive of hemorrhage. Based on maximal Youden’s, the optimal cutoffs of the TEG indices for predicting vascular obstruction were: R = 7, K = 1.5, MA = 63.5, and ANGLE = 67.1. A combination of all four showed the best predictive value (area under the ROC curve of 0.60, sensitivity 85.9%, and specificity 34.7%). The optimal cut-off values for predicting hemorrhage were: R = 7.8, K = 2.3, MA = 50.5, ANGLE = 53.7. A combination of R and MA was also most predictive of hemorrhage (area under ROC curve 0.66, sensitivity 60%, and specificity 71.7%). Conclusion The currently adopted cut-off values for TEG indices are poorly and modestly predictive of hemorrhage and obstruction, respectively, in the elderly population. Optimal cutoff values determined by ROC curve analysis improved the prediction of vascular obstruction and hemorrhage. PMID:24204130

Zheng, Qiwen; Fu, Shuhong; Chen, Dafang; Li, Xiaoxia; Li, Yuru; Li, Yanyan; Yu, Jihong; Gong, Meiliang; Bai, Jie

2013-01-01

384

Population dynamics of a South American rodent: seasonal structure interacting with climate, density dependence and predator effects.  

PubMed Central

Understanding the role of interactions between intrinsic feedback loops and external climatic forces is one of the central challenges within the field of population ecology. For rodent dynamics, the seasonal structure of the environment necessitates changes between two stages: reproductive and non-reproductive. Nevertheless, the interactions between seasonality, climate, density dependence and predators have been generally ignored. We demonstrate that direct climate effects, the nonlinear effect of predators and the nonlinear first-order feedback embedded in a seasonal structure are key elements underlying the large and irregular fluctuations in population numbers exhibited by a small rodent in a semi-arid region of central Chile. We found that factors influencing population growth rates clearly differ between breeding and non-breeding seasons. In addition, we detected nonlinear density dependencies as well as nonlinear and differential effects of generalist and specialist predators. Recent climatic changes may account for dramatic perturbations of the rodent's population dynamics. Changes in the predator guild induced by climate are likely to result, through the food web, in a large impact on small rodent demography and population dynamics. Assuming such interactions to be typical of ecological systems, we conclude that appropriate predictions of the ecological consequences of climate change will depend on having an in-depth understanding of the community-weather system. PMID:12573073

Lima, Mauricio; Stenseth, Nils Chr; Jaksic, Fabian M

2002-01-01

385

A Dynamic Method to Estimate Source Emission Rate and Predict Contaminant Concentrations  

Microsoft Academic Search

It is very important to develop a method to predict contaminant concentrations in an enclosed space. The key technology is source emission rate estimation and dynamic concentration prediction. This paper presented a new method to estimate source emission rate and predict contaminant concentrations dynamically. A variable-structural contaminant concentration model was built, and then the extended Kalman filter was used to

Qu Hongquan; Pang Liping

2009-01-01

386

Aspiration dynamics in structured population acts as if in a well-mixed one  

PubMed Central

Understanding the evolution of human interactive behaviors is important. Recent experimental results suggest that human cooperation in spatial structured population is not enhanced as predicted in previous works, when payoff-dependent imitation updating rules are used. This constraint opens up an avenue to shed light on how humans update their strategies in real life. Studies via simulations show that, instead of comparison rules, self-evaluation driven updating rules may explain why spatial structure does not alter the evolutionary outcome. Though inspiring, there is a lack of theoretical result to show the existence of such evolutionary updating rule. Here we study the aspiration dynamics, and show that it does not alter the evolutionary outcome in various population structures. Under weak selection, by analytical approximation, we find that the favored strategy in regular graphs is invariant. Further, we show that this is because the criterion under which a strategy is favored is the same as that of a well-mixed population. By simulation, we show that this holds for random networks. Although how humans update their strategies is an open question to be studied, our results provide a theoretical foundation of the updating rules that may capture the real human updating rules. PMID:25619664

Du, Jinming; Wu, Bin; Wang, Long

2015-01-01

387

Effects of Nano-Titanium Dioxide on Freshwater Algal Population Dynamics  

PubMed Central

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

Kulacki, Konrad J.; Cardinale, Bradley J.

2012-01-01

388

Population dynamics in changing environments: the case of an eruptive forest pest species.  

PubMed

In recent decades we have seen rapid and co-occurring changes in landscape structure, species distributions and even climate as consequences of human activity. Such changes affect the dynamics of the interaction between major forest pest species, such as bark beetles (Coleoptera: Curculionidae, Scolytinae), and their host trees. Normally breeding mostly in broken or severely stressed spruce; at high population densities some bark beetle species can colonise and kill healthy trees on scales ranging from single trees in a stand to multi-annual landscape-wide outbreaks. In Eurasia, the largest outbreaks are caused by the spruce bark beetle, Ips typographus (Linnaeus), which is common and shares a wide distribution with its main host, Norway spruce (Picea abies Karst.). A large literature is now available, from which this review aims to synthesize research relevant for the population dynamics of I. typographus and co-occurring species under changing conditions. We find that spruce bark beetle population dynamics tend to be metastable, but that mixed-species and age-heterogeneous forests with good site-matching tend to be less susceptible to large-scale outbreaks. While large accumulations of logs should be removed and/or debarked before the next swarming period, intensive removal of all coarse dead wood may be counterproductive, as it reduces the diversity of predators that in some areas may play a role in keeping I. typographus populations below the outbreak threshold, and sanitary logging frequently causes edge effects and root damage, reducing the resistance of remaining trees. It is very hard to predict the outcome of interspecific interactions due to invading beetle species or I. typographus establishing outside its current range, as they can be of varying sign and strength and may fluctuate depending on environmental factors and population phase. Most research indicates that beetle outbreaks will increase in frequency and magnitude as temperature, wind speed and precipitation variability increases, and that mitigating forestry practices should be adopted as soon as possible considering the time lags involved. PMID:21557798

Kausrud, Kyrre; Okland, Bjørn; Skarpaas, Olav; Grégoire, Jean-Claude; Erbilgin, Nadir; Stenseth, Nils Chr

2012-02-01

389

Reinvasion dynamics of northern pocket gopher ( Thomomys talpoides) populations in removal areas  

Microsoft Academic Search

This study was designed to test the hypothesis that continuous removal of northern pocket gophers (Thomomys talpoides) from natural habitats and tree fruit orchards would result in successful population reduction. A secondary objective was a detailed analysis of demographic responses (reinvasion dynamics) of gopher populations in control and removal sites. Pocket gopher populations were intensively live-trapped in replicate control and

Thomas P. Sullivan; Druscilla S. Sullivan; Eugene J. Hogue

2001-01-01

390

Evolutionary game dynamics in a finite asymmetric two-deme population and emergence of cooperation  

E-print Network

by natural selection in a finite population. The Prisoner's Dilemma (PD) (Axelrod and Hamilton, 1981Evolutionary game dynamics in a finite asymmetric two-deme population and emergence of cooperation in a finite population subdivided into two demes with both unequal deme sizes and different migration rates

Lessard, Sabin

391

Nash Certainty Equivalence in Large Population Stochastic Dynamic Games: Connections with the  

E-print Network

Nash Certainty Equivalence in Large Population Stochastic Dynamic Games: Connections;Brief Historic Background: Prisoner's Dilemma A Very Simple Model with a Rich Structure: Two criminal(n): the population driving term z(n) = 1 n n i=1 zi ui: control wi: noise (a standard Wiener process) n: population

Huang, Minyi

392

Population dynamics and production of Daphnia hyalina Leydig and Daphnia cucullata Sars in Tjeukemeer  

Microsoft Academic Search

As part of a research programme on the food chains in Tjeukemeer, the Daphnia hyalina and Daphnia cucullata populations were studied for three successive years. To analyse the factors regulating the production of these two species, their population parameters (density, size distribution, fecundity) and population dynamics (birth rate, mortality rate) were studied and related to environmental factors. Since Daphnia in

J. Vijverberg; A. F. Richter

1982-01-01

393

Population Dynamics and Tropical Deforestation: State of the Debate and Conceptual Challenges  

E-print Network

Population Dynamics and Tropical Deforestation: State of the Debate and Conceptual Challenges David is the role of population in driving deforestation? This question was put forth as a discussion topic diverse backgrounds weighed in on the discussion, citing key factors in the population-deforestation nexus

Lopez-Carr, David

394

Human-caused mortality influences spatial population dynamics: Pumas in landscapes with varying mortality risks  

E-print Network

Available online 22 January 2013 Keywords: Dispersal Population contribution Puma concolor Source to basic and applied ecology. Puma (Puma concolor) populations are expected to be influenced by interHuman-caused mortality influences spatial population dynamics: Pumas in landscapes with varying

Mitchell, Mike

395

Surprising migration and population size dynamics in ancient Iberian brown bears (Ursus arctos)  

E-print Network

Surprising migration and population size dynamics in ancient Iberian brown bears (Ursus arctos, 2008 (sent for review December 10, 2007) The endangered brown bear populations (Ursus arctos) in Iberia have been suggested to be the last fragments of the brown bear population that served as recolonization

396

Weed populations and crop rotations : Exploring dynamics of a structured periodic system  

Microsoft Academic Search

The periodic growing of a certain set of crops in a prescribed order, called a crop rotation, is considered to be an important tool for managing weed populations. Nevertheless, the effects of crop rotations on weed population dynamics are not well understood. Explanations for rotation effects on weed populations usually invoke the diversity of environments caused by different crops that

Shana K. Mertens; Frank van den Bosch

2002-01-01

397

T-wave alternans predicts mortality in a population undergoing a clinically indicated exercise test  

Microsoft Academic Search

Aims As a part of the Finnish Cardiovascular Study, we tested the hypothesis that T-wave alternans (TWA) predicts mortality in a general population of patients referred for a clinical exercise test. Methods and results A total of 1037 consecutive patients (mean age+SD of 58+13 years, 673 men and 364 women) with a clinically indicated exercise test and with technically successful

Tuomo Nieminen; Terho Lehtimaki; Jari Viik; Rami Lehtinen; Kjell Nikus; Tiit Koobi; Kari Niemela; V ainoTurjanmaa; Willi Kaiser; Heini Huhtala; Richard L. Verrier; Heikki Huikuri; Mika Kahonen

2007-01-01

398

Structural Prediction of Dynamic Bayesian Network With Partial Prior Information.  

PubMed

The prediction of the structure of a hidden Dynamic Bayesian Network (DBN) from a noisy dataset is an important and challenging task. This work presents a generalized framework to infer the DBN network structure with partial prior information. In the proposed framework, the partial information about the network structure is provided in the form of prior. The proposed method makes use of the prior information regarding the presence and as well as absence of some of the edges. Using the noisy dataset and partial prior information, this method is able to infer nearly accurate structure of the network. The proposed method is validated using simulated datasets. In addition, two real biological datasets are used to infer hidden biological interaction networks. PMID:25314704

Maiti, Aniruddha; Reddy, Ramakanth; Mukherjee, Anirban

2014-10-13

399

Methods for evaluating the predictive accuracy of structural dynamic models  

NASA Technical Reports Server (NTRS)

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.

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

1990-01-01

400

Prediction of dynamic blade loading of the Francis-99 turbine  

NASA Astrophysics Data System (ADS)

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.

Nicolle, J.; Cupillard, S.

2015-01-01

401

Population dynamics a source of diversity Zdenek Pospisil  

E-print Network

of subsistence increase, · the superior power of population is repressed, and the actual population kept equal (1927) food chain, ecological niche, pyramid of numbers #12;A bit of history Introduction A bit

Pospí�il, Zdenek

402

Population dynamics of Trigoniulus lumbricinus ( gerst ) (Diplopoda: Trigoniulidae)  

Microsoft Academic Search

Summary  The number of the diplopod,Trigoniulus lumbricinus (Gerst) in the leaf litter varies between months. The annual population peak is reached during May to July after which the population\\u000a declines. The seasonal population change is statistically correlated with the rainfall, but a causal relationship is difficult\\u000a to establish: there is no indication that the population is regulated by any density related

Barundeb Banerjee

1974-01-01

403

Mosquito population dynamic (Diptera: Culicidae) in a eutrophised dam.  

PubMed

This study observed the mosquito population in a rural eutrophised dam. Larvae of L3 and L4 stages and pupae were dipped out during twelve month collections and the reared to the adult stage for identification. The collections were done along nine metres from the edge of the dam divided in three parts (P1, P2 and P3), each part being 3 m long. P1 did not have vegetation (grass) along its edge,which would reach or sink into the water to promote some shade on the marginal water. A total of 217 adults of four species was identified with the following constancies and frequencies: Culex quinquefasciatus (Say, 1823) (83% and 40.6%), Anopheles (Nyssorhynchus) evansae (Brèthes, 1926) (92% and 26.7%), Anopheles (Nyssorhynchus) rangeli (Gabaldon, Cova Garcia and Lopez, 1940) (83% and 14.3%) and Culex nigripalpus (Theobald, 1901) (33% and 18.4%). C. quinquefasciatus, A. evansae, A. rangeli and C. nigripalpus were more frequent in the quarters Nov./Dec./Jan. (85.7%), May/June/July (75%), Aug./Sept./Oct. (29.4%) and Aug./Sept./Oct. (23.5%) particularly in the months of December (88.4%) Sept.tember (48.94), (38.3) and August (47.62) respectively. The presence of C. quinquefasciatus and the high incidence of Daphinia sp. and also the levels of Organic Nitrogen (0.28 mg/L) and of total Phosphorus (0.02 mg/L) are indications of the eutrophication of the dam. There was a difference regarding the total of Anopheles (A. avansae + A. rangeli) and Culex species (C. quinquefasciatus + C. nigripalpis) between P1 and P2 (?(2) = 0.0097),