OSSOS: X. How to use a Survey Simulator: Statistical Testing of Dynamical Models Against the Real Kuiper Belt

NASA Astrophysics Data System (ADS)

Lawler, Samantha M.; Kavelaars, J. J.; Alexandersen, Mike; Bannister, Michele T.; Gladman, Brett; Petit, Jean-Marc; Shankman, Cory

2018-05-01

All surveys include observational biases, which makes it impossible to directly compare properties of discovered trans-Neptunian Objects (TNOs) with dynamical models. However, by carefully keeping track of survey pointings on the sky, detection limits, tracking fractions, and rate cuts, the biases from a survey can be modelled in Survey Simulator software. A Survey Simulator takes an intrinsic orbital model (from, for example, the output of a dynamical Kuiper belt emplacement simulation) and applies the survey biases, so that the biased simulated objects can be directly compared with real discoveries. This methodology has been used with great success in the Outer Solar System Origins Survey (OSSOS) and its predecessor surveys. In this chapter, we give four examples of ways to use the OSSOS Survey Simulator to gain knowledge about the true structure of the Kuiper Belt. We demonstrate how to statistically compare different dynamical model outputs with real TNO discoveries, how to quantify detection biases within a TNO population, how to measure intrinsic population sizes, and how to use upper limits from non-detections. We hope this will provide a framework for dynamical modellers to statistically test the validity of their models.

Recasting a model atomistic glassformer as a system of icosahedra

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pinney, Rhiannon; Bristol Centre for Complexity Science, University of Bristol, Bristol BS8 1TS; Liverpool, Tanniemola B.

2015-12-28

We consider a binary Lennard-Jones glassformer whose super-Arrhenius dynamics are correlated with the formation of icosahedral structures. Upon cooling, these icosahedra organize into mesoclusters. We recast this glassformer as an effective system of icosahedra which we describe with a population dynamics model. This model we parameterize with data from the temperature regime accessible to molecular dynamics simulations. We then use the model to determine the population of icosahedra in mesoclusters at arbitrary temperature. Using simulation data to incorporate dynamics into the model, we predict relaxation behavior at temperatures inaccessible to conventional approaches. Our model predicts super-Arrhenius dynamics whose relaxation timemore » remains finite for non-zero temperature.« less

Computer simulation of the coffee leaf miner using sexual Penna aging model

NASA Astrophysics Data System (ADS)

de Oliveira, A. C. S.; Martins, S. G. F.; Zacarias, M. S.

2008-01-01

Forecast models based on climatic conditions are of great interest in Integrated Pest Management (IPM) programs. The success of these models depends, among other factors, on the knowledge of the temperature effect on the pests’ population dynamics. In this direction, a computer simulation was made for the population dynamics of the coffee leaf miner, L. coffeella, at different temperatures, considering experimental data relative to the pest. The age structure was inserted into the dynamics through sexual Penna Model. The results obtained, such as life expectancy, growth rate and annual generations’ number, in agreement to those in laboratory and field conditions, show that the simulation can be used as a forecast model for controlling L. coffeella.

Population Dynamics of Early Human Migration in Britain

PubMed Central

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

2016-01-01

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

Climate-based models for West Nile Culex mosquito vectors in the Northeastern US

NASA Astrophysics Data System (ADS)

Gong, Hongfei; Degaetano, Arthur T.; Harrington, Laura C.

2011-05-01

Climate-based models simulating Culex mosquito population abundance in the Northeastern US were developed. Two West Nile vector species, Culex pipiens and Culex restuans, were included in model simulations. The model was optimized by a parameter-space search within biological bounds. Mosquito population dynamics were driven by major environmental factors including temperature, rainfall, evaporation rate and photoperiod. The results show a strong correlation between the timing of early population increases (as early warning of West Nile virus risk) and decreases in late summer. Simulated abundance was highly correlated with actual mosquito capture in New Jersey light traps and validated with field data. This climate-based model simulates the population dynamics of both the adult and immature mosquito life stage of Culex arbovirus vectors in the Northeastern US. It is expected to have direct and practical application for mosquito control and West Nile prevention programs.

Robust state preparation in quantum simulations of Dirac dynamics

NASA Astrophysics Data System (ADS)

Song, Xue-Ke; Deng, Fu-Guo; Lamata, Lucas; Muga, J. G.

2017-02-01

A nonrelativistic system such as an ultracold trapped ion may perform a quantum simulation of a Dirac equation dynamics under specific conditions. The resulting Hamiltonian and dynamics are highly controllable, but the coupling between momentum and internal levels poses some difficulties to manipulate the internal states accurately in wave packets. We use invariants of motion to inverse engineer robust population inversion processes with a homogeneous, time-dependent simulated electric field. This exemplifies the usefulness of inverse-engineering techniques to improve the performance of quantum simulation protocols.

Disease dynamics in a dynamic social network

NASA Astrophysics Data System (ADS)

Christensen, Claire; Albert, István; Grenfell, Bryan; Albert, Réka

2010-07-01

We develop a framework for simulating a realistic, evolving social network (a city) into which a disease is introduced. We compare our results to prevaccine era measles data for England and Wales, and find that they capture the quantitative and qualitative features of epidemics in populations spanning two orders of magnitude. Our results provide unique insight into how and why the social topology of the contact network influences the propagation of the disease through the population. We argue that network simulation is suitable for concurrently probing contact network dynamics and disease dynamics in ways that prior modeling approaches cannot and it can be extended to the study of less well-documented diseases.

The cultural implications of growth: Modeling nonlinear interaction of trait selection and population dynamics

NASA Astrophysics Data System (ADS)

Antoci, Angelo; Galeotti, Marcello; Russu, Paolo; Luigi Sacco, Pier

2018-05-01

In this paper, we study a nonlinear model of the interaction between trait selection and population dynamics, building on previous work of Ghirlanda et al. [Theor. Popul. Biol. 77, 181-188 (2010)] and Antoci et al. [Commun. Nonlinear Sci. Numer. Simul. 58, 92-106 (2018)]. We establish some basic properties of the model dynamics and present some simulations of the fine-grained structure of alternative dynamic regimes for chosen combinations of parameters. The role of the parameters that govern the reinforcement/corruption of maladaptive vs. adaptive traits is of special importance in determining the model's dynamic evolution. The main implication of this result is the need to pay special attention to the structural forces that may favor the emergence and consolidation of maladaptive traits in contemporary socio-economies, as it is the case, for example, for the stimulation of dysfunctional consumption habits and lifestyles in the pursuit of short-term profits.

The cultural implications of growth: Modeling nonlinear interaction of trait selection and population dynamics.

PubMed

Antoci, Angelo; Galeotti, Marcello; Russu, Paolo; Luigi Sacco, Pier

2018-05-01

In this paper, we study a nonlinear model of the interaction between trait selection and population dynamics, building on previous work of Ghirlanda et al. [Theor. Popul. Biol. 77, 181-188 (2010)] and Antoci et al. [Commun. Nonlinear Sci. Numer. Simul. 58, 92-106 (2018)]. We establish some basic properties of the model dynamics and present some simulations of the fine-grained structure of alternative dynamic regimes for chosen combinations of parameters. The role of the parameters that govern the reinforcement/corruption of maladaptive vs. adaptive traits is of special importance in determining the model's dynamic evolution. The main implication of this result is the need to pay special attention to the structural forces that may favor the emergence and consolidation of maladaptive traits in contemporary socio-economies, as it is the case, for example, for the stimulation of dysfunctional consumption habits and lifestyles in the pursuit of short-term profits.

Generating a Dynamic Synthetic Population – Using an Age-Structured Two-Sex Model for Household Dynamics

PubMed Central

Namazi-Rad, Mohammad-Reza; Mokhtarian, Payam; Perez, Pascal

2014-01-01

Generating a reliable computer-simulated synthetic population is necessary for knowledge processing and decision-making analysis in agent-based systems in order to measure, interpret and describe each target area and the human activity patterns within it. In this paper, both synthetic reconstruction (SR) and combinatorial optimisation (CO) techniques are discussed for generating a reliable synthetic population for a certain geographic region (in Australia) using aggregated- and disaggregated-level information available for such an area. A CO algorithm using the quadratic function of population estimators is presented in this paper in order to generate a synthetic population while considering a two-fold nested structure for the individuals and households within the target areas. The baseline population in this study is generated from the confidentialised unit record files (CURFs) and 2006 Australian census tables. The dynamics of the created population is then projected over five years using a dynamic micro-simulation model for individual- and household-level demographic transitions. This projection is then compared with the 2011 Australian census. A prediction interval is provided for the population estimates obtained by the bootstrapping method, by which the variability structure of a predictor can be replicated in a bootstrap distribution. PMID:24733522

A DYNAMIC MODEL OF AN ESTUARINE INVASION BY A NON-NATIVE SEAGRASS

EPA Science Inventory

Mathematical and simulation models provide an excellent tool for examining and predicting biological invasions in time and space; however, traditional models do not incorporate dynamic rates of population growth, which limits their realism. We developed a spatially explicit simul...

Simulation of Population Processes with a Programmable Pocket Calculator.

ERIC Educational Resources Information Center

Kidd, N. A. C.

1979-01-01

Presents a set of simulation models for use in teaching population dynamics. These models are designed specifically for use with a programmable pocket calculator, and can be used to demonstrate growth of populations with discrete or overlapping generations and also to explore effects of density-dependent and -independent mortality. (Author/CS)

Modeled response of the West Nile virus vector Culex quinquefasciatus to changing climate using the dynamic mosquito simulation model

NASA Astrophysics Data System (ADS)

Morin, Cory W.; Comrie, Andrew C.

2010-09-01

Climate can strongly influence the population dynamics of disease vectors and is consequently a key component of disease ecology. Future climate change and variability may alter the location and seasonality of many disease vectors, possibly increasing the risk of disease transmission to humans. The mosquito species Culex quinquefasciatus is a concern across the southern United States because of its role as a West Nile virus vector and its affinity for urban environments. Using established relationships between atmospheric variables (temperature and precipitation) and mosquito development, we have created the Dynamic Mosquito Simulation Model (DyMSiM) to simulate Cx. quinquefasciatus population dynamics. The model is driven with climate data and validated against mosquito count data from Pasco County, Florida and Coachella Valley, California. Using 1-week and 2-week filters, mosquito trap data are reproduced well by the model ( P < 0.0001). Dry environments in southern California produce different mosquito population trends than moist locations in Florida. Florida and California mosquito populations are generally temperature-limited in winter. In California, locations are water-limited through much of the year. Using future climate projection data generated by the National Center for Atmospheric Research CCSM3 general circulation model, we applied temperature and precipitation offsets to the climate data at each location to evaluate mosquito population sensitivity to possible future climate conditions. We found that temperature and precipitation shifts act interdependently to cause remarkable changes in modeled mosquito population dynamics. Impacts include a summer population decline from drying in California due to loss of immature mosquito habitats, and in Florida a decrease in late-season mosquito populations due to drier late summer conditions.

Fast stochastic algorithm for simulating evolutionary population dynamics

NASA Astrophysics Data System (ADS)

Tsimring, Lev; Hasty, Jeff; Mather, William

2012-02-01

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

Dynamics of the GB3 loop regions from MD simulation: how much of it is real?

PubMed

Li, Tong; Jing, Qingqing; Yao, Lishan

2011-04-07

A total of 1.1 μs of molecular dynamics (MD) simulations were performed to study the structure and dynamics of protein GB3. The simulation motional amplitude of the loop regions is generally overestimated in comparison with the experimental backbone N-H order parameters S(2). Two-state behavior is observed for several residues in these regions, with the minor state population in the range of 3-13%. Further inspection suggests that the (φ, ψ) dihedral angles of the minor states deviate from the GB3 experimental values, implying the existence of nonnative states. After fitting the MD trajectories of these residues to the NMR RDCs, the minor state populations are significantly reduced by at least 80%, suggesting that MD simulations are strongly biased toward the minor states, thus overestimating the dynamics of the loop regions. The optimized trajectories produce intra, sequential H(N)-H(α) RDCs and intra (3)J(HNHα) that are not included in the trajectories fitting for these residues that are closer to the experimental data. Unlike GB3, 0.55 μs MD simulations of protein ubiquitin do not show distinctive minor states, and the derived NMR order parameters are better converged. Our findings indicate that the artifacts of the simulations depend on the specific system studied and that one should be cautious interpreting the enhanced dihedral dynamics from long MD simulations.

Human population dynamics in Europe over the Last Glacial Maximum.

PubMed

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

2015-07-07

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

Human population dynamics in Europe over the Last Glacial Maximum

PubMed Central

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

2015-01-01

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

A dynamic model of the marriage market-Part 2: simulation of marital states and application to empirical data.

PubMed

Matthews, A P; Garenne, M L

2013-09-01

A dynamic, two-sex, age-structured marriage model is presented. Part 1 focused on first marriage only and described a marriage market matching algorithm. In Part 2 the model is extended to include divorce, widowing, and remarriage. The model produces a self-consistent set of marital states distributed by age and sex in a stable population by means of a gender-symmetric numerical method. The model is compared with empirical data for the case of Zambia. Furthermore, a dynamic marriage function for a changing population is demonstrated in simulations of three hypothetical scenarios of elevated mortality in young to middle adulthood. The marriage model has its primary application to simulation of HIV-AIDS epidemics in African countries. Copyright © 2013 Elsevier Inc. All rights reserved.

Simulations for designing and interpreting intervention trials in infectious diseases.

PubMed

Halloran, M Elizabeth; Auranen, Kari; Baird, Sarah; Basta, Nicole E; Bellan, Steven E; Brookmeyer, Ron; Cooper, Ben S; DeGruttola, Victor; Hughes, James P; Lessler, Justin; Lofgren, Eric T; Longini, Ira M; Onnela, Jukka-Pekka; Özler, Berk; Seage, George R; Smith, Thomas A; Vespignani, Alessandro; Vynnycky, Emilia; Lipsitch, Marc

2017-12-29

Interventions in infectious diseases can have both direct effects on individuals who receive the intervention as well as indirect effects in the population. In addition, intervention combinations can have complex interactions at the population level, which are often difficult to adequately assess with standard study designs and analytical methods. Herein, we urge the adoption of a new paradigm for the design and interpretation of intervention trials in infectious diseases, particularly with regard to emerging infectious diseases, one that more accurately reflects the dynamics of the transmission process. In an increasingly complex world, simulations can explicitly represent transmission dynamics, which are critical for proper trial design and interpretation. Certain ethical aspects of a trial can also be quantified using simulations. Further, after a trial has been conducted, simulations can be used to explore the possible explanations for the observed effects. Much is to be gained through a multidisciplinary approach that builds collaborations among experts in infectious disease dynamics, epidemiology, statistical science, economics, simulation methods, and the conduct of clinical trials.

Modelling and observing the role of wind in Anopheles population dynamics around a reservoir.

PubMed

Endo, Noriko; Eltahir, Elfatih A B

2018-01-25

Wind conditions, as well as other environmental conditions, are likely to influence malaria transmission through the behaviours of Anopheles mosquitoes, especially around water-resource reservoirs. Wind-induced waves in a reservoir impose mortality on aquatic-stage mosquitoes. Mosquitoes' host-seeking activity is also influenced by wind through dispersion of [Formula: see text]. However, no malaria transmission model exists to date that simulated those impacts of wind mechanistically. A modelling framework for simulating the three important effects of wind on the behaviours of mosquito is developed: attraction of adult mosquitoes through dispersion of [Formula: see text] ([Formula: see text] attraction), advection of adult mosquitoes (advection), and aquatic-stage mortality due to wind-induced surface waves (waves). The framework was incorporated in a mechanistic malaria transmission simulator, HYDREMATS. The performance of the extended simulator was compared with the observed population dynamics of the Anopheles mosquitoes at a village adjacent to the Koka Reservoir in Ethiopia. The observed population dynamics of the Anopheles mosquitoes were reproduced with some reasonable accuracy in HYDREMATS that includes the representation of the wind effects. HYDREMATS without the wind model failed to do so. Offshore wind explained the increase in Anopheles population that cannot be expected from other environmental conditions alone. Around large water bodies such as reservoirs, the role of wind in the dynamics of Anopheles population, hence in malaria transmission, can be significant. Modelling the impacts of wind on the behaviours of Anopheles mosquitoes aids in reproducing the seasonality of malaria transmission and in estimation of the risk of malaria around reservoirs.

Modeling the Population Dynamics of Antibiotic-Resistant Bacteria:. AN Agent-Based Approach

NASA Astrophysics Data System (ADS)

Murphy, James T.; Walshe, Ray; Devocelle, Marc

The response of bacterial populations to antibiotic treatment is often a function of a diverse range of interacting factors. In order to develop strategies to minimize the spread of antibiotic resistance in pathogenic bacteria, a sound theoretical understanding of the systems of interactions taking place within a colony must be developed. The agent-based approach to modeling bacterial populations is a useful tool for relating data obtained at the molecular and cellular level with the overall population dynamics. Here we demonstrate an agent-based model, called Micro-Gen, which has been developed to simulate the growth and development of bacterial colonies in culture. The model also incorporates biochemical rules and parameters describing the kinetic interactions of bacterial cells with antibiotic molecules. Simulations were carried out to replicate the development of methicillin-resistant S. aureus (MRSA) colonies growing in the presence of antibiotics. The model was explored to see how the properties of the system emerge from the interactions of the individual bacterial agents in order to achieve a better mechanistic understanding of the population dynamics taking place. Micro-Gen provides a good theoretical framework for investigating the effects of local environmental conditions and cellular properties on the response of bacterial populations to antibiotic exposure in the context of a simulated environment.

Potential impact of harvesting on the population dynamics of two epiphytic bromeliads

NASA Astrophysics Data System (ADS)

Toledo-Aceves, Tarin; Hernández-Apolinar, Mariana; Valverde, Teresa

2014-08-01

Large numbers of epiphytes are extracted from cloud forests for ornamental use and illegal trade in Latin America. We examined the potential effects of different harvesting regimes on the population dynamics of the epiphytic bromeliads Tillandsia multicaulis and Tillandsia punctulata. The population dynamics of these species were studied over a 2-year period in a tropical montane cloud forest in Veracruz, Mexico. Prospective and retrospective analyses were used to identify which demographic processes and life-cycle stages make the largest relative contribution to variation in population growth rate (λ). The effect of simulated harvesting levels on population growth rates was analysed for both species. λ of both populations was highly influenced by survival (stasis), to a lesser extent by growth, and only slightly by fecundity. Vegetative growth played a central role in the population dynamics of these organisms. The λ value of the studied populations did not differ significantly from unity: T. multicaulis λ (95% confidence interval) = 0.982 (0.897-1.060) and T. punctulata λ = 0.967 (0.815-1.051), suggesting population stability. However, numerical simulation of different levels of extraction showed that λ would drop substantially even under very low (2%) harvesting levels. Matrix analysis revealed that T. multicaulis and T. punctulata populations are likely to decline and therefore commercial harvesting would be unsustainable. Based on these findings, management recommendations are outlined.

Distinguishing Antimicrobial Models with Different Resistance Mechanisms via Population Pharmacodynamic Modeling

PubMed Central

Jacobs, Matthieu; Grégoire, Nicolas; Couet, William; Bulitta, Jurgen B.

2016-01-01

Semi-mechanistic pharmacokinetic-pharmacodynamic (PK-PD) modeling is increasingly used for antimicrobial drug development and optimization of dosage regimens, but systematic simulation-estimation studies to distinguish between competing PD models are lacking. This study compared the ability of static and dynamic in vitro infection models to distinguish between models with different resistance mechanisms and support accurate and precise parameter estimation. Monte Carlo simulations (MCS) were performed for models with one susceptible bacterial population without (M1) or with a resting stage (M2), a one population model with adaptive resistance (M5), models with pre-existing susceptible and resistant populations without (M3) or with (M4) inter-conversion, and a model with two pre-existing populations with adaptive resistance (M6). For each model, 200 datasets of the total bacterial population were simulated over 24h using static antibiotic concentrations (256-fold concentration range) or over 48h under dynamic conditions (dosing every 12h; elimination half-life: 1h). Twelve-hundred random datasets (each containing 20 curves for static or four curves for dynamic conditions) were generated by bootstrapping. Each dataset was estimated by all six models via population PD modeling to compare bias and precision. For M1 and M3, most parameter estimates were unbiased (<10%) and had good imprecision (<30%). However, parameters for adaptive resistance and inter-conversion for M2, M4, M5 and M6 had poor bias and large imprecision under static and dynamic conditions. For datasets that only contained viable counts of the total population, common statistical criteria and diagnostic plots did not support sound identification of the true resistance mechanism. Therefore, it seems advisable to quantify resistant bacteria and characterize their MICs and resistance mechanisms to support extended simulations and translate from in vitro experiments to animal infection models and ultimately patients. PMID:26967893

Evolutionary dynamics with fluctuating population sizes and strong mutualism.

PubMed

Chotibut, Thiparat; Nelson, David R

2015-08-01

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

Evolutionary dynamics with fluctuating population sizes and strong mutualism

NASA Astrophysics Data System (ADS)

Chotibut, Thiparat; Nelson, David R.

2015-08-01

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

Turnover of Village Chickens Undermines Vaccine Coverage to Control HPAI H5N1.

PubMed

Villanueva-Cabezas, J P; Campbell, P T; McCaw, J M; Durr, P A; McVernon, J

2017-02-01

Highly pathogenic avian influenza (HPAI) subtype H5N1 remains an enzootic disease of village chickens in Indonesia, posing ongoing risk at the animal-human interface. Previous modelling showed that the fast natural turnover of chicken populations might undermine herd immunity after vaccination, although actual details of how this effect applies to Indonesia's village chicken population have not been determined. We explored the turnover effect in Indonesia's scavenging and mixed populations of village chickens using an extended Leslie matrix model parameterized with data collected from village chicken flocks in Java region, Indonesia. Population dynamics were simulated for 208 weeks; the turnover effect was simulated for 16 weeks after vaccination in two 'best case' scenarios, where the whole population (scenario 1), or birds aged over 14 days (scenario 2), were vaccinated. We found that the scavenging and mixed populations have different productive traits. When steady-state dynamics are reached, both populations are dominated by females (54.5%), and 'growers' and 'chicks' represent the most abundant age stages with 39% and 38% in the scavenging, and 60% and 25% in the mixed population, respectively. Simulations showed that the population turnover might reduce the herd immunity below the critical threshold that prevents the re-emergence of HPAI H5N1 4-8 weeks (scavenging) and 6-9 weeks (mixed population) after vaccination in scenario 1, and 2-6 weeks (scavenging) and 4-7 weeks (mixed population) after vaccination in scenario 2. In conclusion, we found that Indonesia's village chicken population does not have a unique underlying population dynamic and therefore, different turnover effects on herd immunity may be expected after vaccination; nonetheless, our simulations carried out in best case scenarios highlight the limitations of current vaccine technologies to control HPAI H5N1. This suggests that the improvements and complementary strategies are necessary and must be explored. © 2016 Blackwell Verlag GmbH.

Nonlinear absorption dynamics using field-induced surface hopping: zinc porphyrin in water.

PubMed

Röhr, Merle I S; Petersen, Jens; Wohlgemuth, Matthias; Bonačić-Koutecký, Vlasta; Mitrić, Roland

2013-05-10

We wish to present the application of our field-induced surface-hopping (FISH) method to simulate nonlinear absorption dynamics induced by strong nonresonant laser fields. We provide a systematic comparison of the FISH approach with exact quantum dynamics simulations on a multistate model system and demonstrate that FISH allows for accurate simulations of nonlinear excitation processes including multiphoton electronic transitions. In particular, two different approaches for simulating two-photon transitions are compared. The first approach is essentially exact and involves the solution of the time-dependent Schrödinger equation in an extended manifold of excited states, while in the second one only transiently populated nonessential states are replaced by an effective quadratic coupling term, and dynamics is performed in a considerably smaller manifold of states. We illustrate the applicability of our method to complex molecular systems by simulating the linear and nonlinear laser-driven dynamics in zinc (Zn) porphyrin in the gas phase and in water. For this purpose, the FISH approach is connected with the quantum mechanical-molecular mechanical approach (QM/MM) which is generally applicable to large classes of complex systems. Our findings that multiphoton absorption and dynamics increase the population of higher excited states of Zn porphyrin in the nonlinear regime, in particular in solution, provides a means for manipulating excited-state properties, such as transient absorption dynamics and electronic relaxation. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2016-01-01

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

Folding molecular dynamics simulations accurately predict the effect of mutations on the stability and structure of a vammin-derived peptide.

PubMed

Koukos, Panagiotis I; Glykos, Nicholas M

2014-08-28

Folding molecular dynamics simulations amounting to a grand total of 4 μs of simulation time were performed on two peptides (with native and mutated sequences) derived from loop 3 of the vammin protein and the results compared with the experimentally known peptide stabilities and structures. The simulations faithfully and accurately reproduce the major experimental findings and show that (a) the native peptide is mostly disordered in solution, (b) the mutant peptide has a well-defined and stable structure, and (c) the structure of the mutant is an irregular β-hairpin with a non-glycine β-bulge, in excellent agreement with the peptide's known NMR structure. Additionally, the simulations also predict the presence of a very small β-hairpin-like population for the native peptide but surprisingly indicate that this population is structurally more similar to the structure of the native peptide as observed in the vammin protein than to the NMR structure of the isolated mutant peptide. We conclude that, at least for the given system, force field, and simulation protocol, folding molecular dynamics simulations appear to be successful in reproducing the experimentally accessible physical reality to a satisfactory level of detail and accuracy.

A Markov model for the temporal dynamics of balanced random networks of finite size

PubMed Central

Lagzi, Fereshteh; Rotter, Stefan

2014-01-01

The balanced state of recurrent networks of excitatory and inhibitory spiking neurons is characterized by fluctuations of population activity about an attractive fixed point. Numerical simulations show that these dynamics are essentially nonlinear, and the intrinsic noise (self-generated fluctuations) in networks of finite size is state-dependent. Therefore, stochastic differential equations with additive noise of fixed amplitude cannot provide an adequate description of the stochastic dynamics. The noise model should, rather, result from a self-consistent description of the network dynamics. Here, we consider a two-state Markovian neuron model, where spikes correspond to transitions from the active state to the refractory state. Excitatory and inhibitory input to this neuron affects the transition rates between the two states. The corresponding nonlinear dependencies can be identified directly from numerical simulations of networks of leaky integrate-and-fire neurons, discretized at a time resolution in the sub-millisecond range. Deterministic mean-field equations, and a noise component that depends on the dynamic state of the network, are obtained from this model. The resulting stochastic model reflects the behavior observed in numerical simulations quite well, irrespective of the size of the network. In particular, a strong temporal correlation between the two populations, a hallmark of the balanced state in random recurrent networks, are well represented by our model. Numerical simulations of such networks show that a log-normal distribution of short-term spike counts is a property of balanced random networks with fixed in-degree that has not been considered before, and our model shares this statistical property. Furthermore, the reconstruction of the flow from simulated time series suggests that the mean-field dynamics of finite-size networks are essentially of Wilson-Cowan type. We expect that this novel nonlinear stochastic model of the interaction between neuronal populations also opens new doors to analyze the joint dynamics of multiple interacting networks. PMID:25520644

Evolution of the stellar mass function in multiple-population globular clusters

NASA Astrophysics Data System (ADS)

Vesperini, Enrico; Hong, Jongsuk; Webb, Jeremy J.; D'Antona, Franca; D'Ercole, Annibale

2018-05-01

We present the results of a survey of N-body simulations aimed at studying the effects of the long-term dynamical evolution on the stellar mass function (MF) of multiple stellar populations in globular clusters. Our simulations show that if first-(1G) and second-generation (2G) stars have the same initial MF (IMF), the global MFs of the two populations are affected similarly by dynamical evolution and no significant differences between the 1G and 2G MFs arise during the cluster's evolution. If the two populations have different IMFs, dynamical effects do not completely erase memory of the initial differences. Should observations find differences between the global 1G and 2G MFs, these would reveal the fingerprints of differences in their IMFs. Irrespective of whether the 1G and 2G populations have the same global IMF or not, dynamical effects can produce differences between the local (measured at various distances from the cluster centre) 1G and 2G MFs; these differences are a manifestation of the process of mass segregation in populations with different initial structural properties. In dynamically old and spatially mixed clusters, however, differences between the local 1G and 2G MFs can reveal differences between the 1G and 2G global MFs. In general, for clusters with any dynamical age, large differences between the local 1G and 2G MFs are more likely to be associated with differences in the global MF. Our study also reveals a dependence of the spatial mixing rate on the stellar mass, another dynamical consequence of the multiscale nature of multiple-population clusters.

Modeling wildlife populations with HexSim

EPA Science Inventory

HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications including population viability analysis for on...

Model reduction for agent-based social simulation: coarse-graining a civil violence model.

PubMed

Zou, Yu; Fonoberov, Vladimir A; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G

2012-06-01

Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

Model reduction for agent-based social simulation: Coarse-graining a civil violence model

NASA Astrophysics Data System (ADS)

Zou, Yu; Fonoberov, Vladimir A.; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G.

2012-06-01

Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

Simple deterministic models and applications. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Yang, Hyun Mo

2015-12-01

Currently, discrete modellings are largely accepted due to the access to computers with huge storage capacity and high performance processors and easy implementation of algorithms, allowing to develop and simulate increasingly sophisticated models. Wang et al. [7] present a review of dynamics in complex networks, focusing on the interaction between disease dynamics and human behavioral and social dynamics. By doing an extensive review regarding to the human behavior responding to disease dynamics, the authors briefly describe the complex dynamics found in the literature: well-mixed populations networks, where spatial structure can be neglected, and other networks considering heterogeneity on spatially distributed populations. As controlling mechanisms are implemented, such as social distancing due 'social contagion', quarantine, non-pharmaceutical interventions and vaccination, adaptive behavior can occur in human population, which can be easily taken into account in the dynamics formulated by networked populations.

Parameter sensitivity analysis for pesticide impacts on honeybee colonies

EPA Science Inventory

We employ Monte Carlo simulation and linear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed that simulate hive population trajectories, taking into account queen strength, foraging success, weather, colo...

Particle tagging and its implications for stellar population dynamics

NASA Astrophysics Data System (ADS)

Le Bret, Theo; Pontzen, Andrew; Cooper, Andrew P.; Frenk, Carlos; Zolotov, Adi; Brooks, Alyson M.; Governato, Fabio; Parry, Owen H.

2017-07-01

We establish a controlled comparison between the properties of galactic stellar haloes obtained with hydrodynamical simulations and with 'particle tagging'. Tagging is a fast way to obtain stellar population dynamics: instead of tracking gas and star formation, it 'paints' stars directly on to a suitably defined subset of dark matter particles in a collisionless, dark-matter-only simulation. Our study shows that 'live' particle tagging schemes, where stellar masses are painted on to the dark matter particles dynamically throughout the simulation, can generate good fits to the hydrodynamical stellar density profiles of a central Milky Way-like galaxy and its most prominent substructure. Energy diffusion processes are crucial to reshaping the distribution of stars in infalling spheroidal systems and hence the final stellar halo. We conclude that the success of any particular tagging scheme hinges on this diffusion being taken into account, and discuss the role of different subgrid feedback prescriptions in driving this diffusion.

Femtosecond excitation tuning and site energy memory of population transfer in poly(p-phenylenevinylene): Gated luminescence experiments and simulation

NASA Astrophysics Data System (ADS)

Sperling, J.; Milota, F.; Tortschanoff, A.; Warmuth, Ch.; Mollay, B.; Bässler, H.; Kauffmann, H. F.

2002-12-01

We present a comprehensive experimental and computational study on fs-relaxational dynamics of optical excitations in the conjugated polymer poly(p-phenylenevinylene) (PPV) under selective excitation tuning conditions into the long-wavelength, low-vibrational S1ν=0-density-of-states (DOS). The dependence of single-wavelength luminescence kinetics and time-windowed spectral transients on distinct, initial excitation boundaries at 1.4 K and at room temperature was measured applying the luminescence up-conversion technique. The typical energy-dispersive intra-DOS energy transfer was simulated by a combination of static Monte Carlo method with a dynamical algorithm for solving the energy-space transport Master-Equation in population-space. For various, selective excitations that give rise to specific S1-population distributions in distinct spatial and energetic subspaces inside the DOS, simulations confirm the experimental results and show that the subsequent, energy-dissipative, multilevel relaxation is hierarchically constrained, and reveals a pronounced site-energy memory effect with a migration-threshold, characteristic of the (dressed) excitation dynamics in the disordered PPV many-body system.

Spatial-temporal population dynamics across species range: from centre to margin

Treesearch

Qinfeng Guo; Mark Taper; Michele Schoenberger; J. Brandle

2005-01-01

Understanding the boundaries of species'rangs and the variations in population dynamics from the centre to margin of a species' range is critical. This study simulated spatial-tamporal patterns of birth and death rates and migration across a species' range in different seasons. Our results demonstrated the importance of dispersal and migration in...

Automated sampling assessment for molecular simulations using the effective sample size

PubMed Central

Zhang, Xin; Bhatt, Divesh; Zuckerman, Daniel M.

2010-01-01

To quantify the progress in the development of algorithms and forcefields used in molecular simulations, a general method for the assessment of the sampling quality is needed. Statistical mechanics principles suggest the populations of physical states characterize equilibrium sampling in a fundamental way. We therefore develop an approach for analyzing the variances in state populations, which quantifies the degree of sampling in terms of the effective sample size (ESS). The ESS estimates the number of statistically independent configurations contained in a simulated ensemble. The method is applicable to both traditional dynamics simulations as well as more modern (e.g., multi–canonical) approaches. Our procedure is tested in a variety of systems from toy models to atomistic protein simulations. We also introduce a simple automated procedure to obtain approximate physical states from dynamic trajectories: this allows sample–size estimation in systems for which physical states are not known in advance. PMID:21221418

A mapping variable ring polymer molecular dynamics study of condensed phase proton-coupled electron transfer

NASA Astrophysics Data System (ADS)

Pierre, Sadrach; Duke, Jessica R.; Hele, Timothy J. H.; Ananth, Nandini

2017-12-01

We investigate the mechanisms of condensed phase proton-coupled electron transfer (PCET) using Mapping-Variable Ring Polymer Molecular Dynamics (MV-RPMD), a recently developed method that employs an ensemble of classical trajectories to simulate nonadiabatic excited state dynamics. Here, we construct a series of system-bath model Hamiltonians for the PCET, where four localized electron-proton states are coupled to a thermal bath via a single solvent mode, and we employ MV-RPMD to simulate state population dynamics. Specifically, for each model, we identify the dominant PCET mechanism, and by comparing against rate theory calculations, we verify that our simulations correctly distinguish between concerted PCET, where the electron and proton transfer together, and sequential PCET, where either the electron or the proton transfers first. This work represents a first application of MV-RPMD to multi-level condensed phase systems; we introduce a modified MV-RPMD expression that is derived using a symmetric rather than asymmetric Trotter discretization scheme and an initialization protocol that uses a recently derived population estimator to constrain trajectories to a dividing surface. We also demonstrate that, as expected, the PCET mechanisms predicted by our simulations are robust to an arbitrary choice of the initial dividing surface.

A BASIC Program for Use in Teaching Population Dynamics.

ERIC Educational Resources Information Center

Kidd, N. A. C.

1984-01-01

Describes an interactive simulation model which can be used to demonstrate population growth with discrete or overlapping populations and the effects of random, constant, or density-dependent mortality. The program listing (for Commodore PET 4032 microcomputer) is included. (Author/DH)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vassilevska, Tanya

This is the first code, designed to run on a desktop, which models the intracellular replication and the cell-to-cell infection and demonstrates virus evolution at the molecular level. This code simulates the infection of a population of "idealized biological cells" (represented as objects that do not divide or have metabolism) with "virus" (represented by its genetic sequence), the replication and simultaneous mutation of the virus which leads to evolution of the population of genetically diverse viruses. The code is built to simulate single-stranded RNA viruses. The input for the code is 1. the number of biological cells in the culture,more » 2. the initial composition of the virus population, 3. the reference genome of the RNA virus, 4. the coordinates of the genome regions and their significance and, 5. parameters determining the dynamics of virus replication, such as the mutation rate. The simulation ends when all cells have been infected or when no more infections occurs after a given number of attempts. The code has the ability to simulate the evolution of the virus in serial passage of cell "cultures", i.e. after the end of a simulation, a new one is immediately scheduled with a new culture of infected cells. The code outputs characteristics of the resulting virus population dynamics and genetic composition of the virus population, such as the top dominant genomes, percentage of a genome with specific characteristics.« less

BIOACCUMULATION AND AQUATIC SYSTEM SIMULATOR (BASS) USER'S MANUAL BETA TEST VERSION 2.1

EPA Science Inventory

BASS (Bioaccumulation and Aquatic System Simulator) is a Fortran 95 simulation program that predicts the population and bioaccumulation dynamics of age-structured fish assemblages that are exposed to hydrophobic organic pollutants and class B and borderline metals that complex wi...

Obesity trend in the United States and economic intervention options to change it: A simulation study linking ecological epidemiology and system dynamics modeling.

PubMed

Chen, H-J; Xue, H; Liu, S; Huang, T T K; Wang, Y C; Wang, Y

2018-05-29

To study the country-level dynamics and influences between population weight status and socio-economic distribution (employment status and family income) in the US and to project the potential impacts of socio-economic-based intervention options on obesity prevalence. Ecological study and simulation. Using the longitudinal data from the 2001-2011 Medical Expenditure Panel Survey (N = 88,453 adults), we built and calibrated a system dynamics model (SDM) capturing the feedback loops between body weight status and socio-economic status distribution and simulated the effects of employment- and income-based intervention options. The SDM-based simulation projected rising overweight/obesity prevalence in the US in the future. Improving people's income from lower to middle-income group would help control the rising prevalence, while only creating jobs for the unemployed did not show such effect. Improving people from low- to middle-income levels may be effective, instead of solely improving reemployment rate, in curbing the rising obesity trend in the US adult population. This study indicates the value of the SDM as a virtual laboratory to evaluate complex distributive phenomena of the interplay between population health and economy. Copyright © 2018 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Huntington II Simulation Program - RATS. Student Workbook, Teacher's Guide, and Resource Handbook.

ERIC Educational Resources Information Center

Frishman, Austin

Presented are instructions for the use of "RATS," a model simulating the dynamics of a rat population in either a city or an apartment house. The student controls the conditions of growth and sets the points at which the computer program prints reports. The rat population is controlled by variables including garbage levels selected for the site,…

Fixation Times in Deme Structured, Finite Populations with Rare Migration

NASA Astrophysics Data System (ADS)

Hauert, Christoph; Chen, Yu-Ting; Imhof, Lorens A.

2014-08-01

Population structure affects both the outcome and the speed of evolutionary dynamics. Here we consider a finite population that is divided into subpopulations called demes. The dynamics within the demes are stochastic and frequency-dependent. Individuals can adopt one of two strategic types, or . The fitness of each individual is determined by interactions with other individuals in the same deme. With small probability, proportional to fitness, individuals migrate to other demes. The outcome of these dynamics has been studied earlier by analyzing the fixation probability of a single mutant in an otherwise homogeneous population. These results give only a partial picture of the dynamics, because the time when fixation occurs can be exceedingly large. In this paper, we study the impact of deme structures on the speed of evolution. We derive analytical approximations of fixation times in the limit of rare migration and rare mutation. In this limit, the conditional fixation time of a single mutant in a population is the same as that of a single in an population. For the prisoner's dilemma game, simulation results fit very well with our analytical predictions and demonstrate that fixation takes place in a moderate amount of time as compared to the expected waiting time until a mutant successfully invades and fixates. The simulations also confirm that the conditional fixation time of a single cooperator is indeed the same as that of a single defector.

Implementing and Simulating Dynamic Traffic Assignment with Intelligent Transportation Systems in Cube Avenue

NASA Technical Reports Server (NTRS)

Foytik, Peter; Robinson, Mike

2010-01-01

As urban populations and traffic congestion levels increase, effective use of information and communication tools and intelligent transportation systems as becoming increasingly important in order to maximize the efficiency of transportation networks. The appropriate placement and employment of these tools within a network is critical to their effectiveness. This presentation proposes and demonstrates the use of a commercial transportation simulation tool to simulate dynamic traffic assignment and rerouting to model route modifications as a result of traffic information.

Simulated population responses of common carp to commercial exploitation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weber, Michael J.; Hennen, Matthew J.; Brown, Michael L.

2011-12-01

Common carp Cyprinus carpio is a widespread invasive species that can become highly abundant and impose deleterious ecosystem effects. Thus, aquatic resource managers are interested in controlling common carp populations. Control of invasive common carp populations is difficult, due in part to the inherent uncertainty of how populations respond to exploitation. To understand how common carp populations respond to exploitation, we evaluated common carp population dynamics (recruitment, growth, and mortality) in three natural lakes in eastern South Dakota. Common carp exhibited similar population dynamics across these three systems that were characterized by consistent recruitment (ages 3 to 15 years present),more » fast growth (K = 0.37 to 0.59), and low mortality (A = 1 to 7%). We then modeled the effects of commercial exploitation on size structure, abundance, and egg production to determine its utility as a management tool to control populations. All three populations responded similarly to exploitation simulations with a 575-mm length restriction, representing commercial gear selectivity. Simulated common carp size structure modestly declined (9 to 37%) in all simulations. Abundance of common carp declined dramatically (28 to 56%) at low levels of exploitation (0 to 20%) but exploitation >40% had little additive effect and populations were only reduced by 49 to 79% despite high exploitation (>90%). Maximum lifetime egg production was reduced from 77 to 89% at a moderate level of exploitation (40%), indicating the potential for recruitment overfishing. Exploitation further reduced common carp size structure, abundance, and egg production when simulations were not size selective. Our results provide insights to how common carp populations may respond to exploitation. Although commercial exploitation may be able to partially control populations, an integrated removal approach that removes all sizes of common carp has a greater chance of controlling population abundance and reducing perturbations induced by this invasive species.« less

Simulating ungulate herbivory across forest landscapes: A browsing extension for LANDIS-II

USGS Publications Warehouse

DeJager, Nathan R.; Drohan, Patrick J.; Miranda, Brian M.; Sturtevant, Brian R.; Stout, Susan L.; Royo, Alejandro; Gustafson, Eric J.; Romanski, Mark C.

2017-01-01

Browsing ungulates alter forest productivity and vegetation succession through selective foraging on species that often dominate early succession. However, the long-term and large-scale effects of browsing on forest succession are not possible to project without the use of simulation models. To explore the effects of ungulates on succession in a spatially explicit manner, we developed a Browse Extension that simulates the effects of browsing ungulates on the growth and survival of plant species cohorts within the LANDIS-II spatially dynamic forest landscape simulation model framework. We demonstrate the capabilities of the new extension and explore the spatial effects of ungulates on forest composition and dynamics using two case studies. The first case study examined the long-term effects of persistently high white-tailed deer browsing rates in the northern hardwood forests of the Allegheny National Forest, USA. In the second case study, we incorporated a dynamic ungulate population model to simulate interactions between the moose population and boreal forest landscape of Isle Royale National Park, USA. In both model applications, browsing reduced total aboveground live biomass and caused shifts in forest composition. Simulations that included effects of browsing resulted in successional patterns that were more similar to those observed in the study regions compared to simulations that did not incorporate browsing effects. Further, model estimates of moose population density and available forage biomass were similar to previously published field estimates at Isle Royale and in other moose-boreal forest systems. Our simulations suggest that neglecting effects of browsing when modeling forest succession in ecosystems known to be influenced by ungulates may result in flawed predictions of aboveground biomass and tree species composition.

Prediction of time-integrated activity coefficients in PRRT using simulated dynamic PET and a pharmacokinetic model.

PubMed

Hardiansyah, Deni; Attarwala, Ali Asgar; Kletting, Peter; Mottaghy, Felix M; Glatting, Gerhard

2017-10-01

To investigate the accuracy of predicted time-integrated activity coefficients (TIACs) in peptide-receptor radionuclide therapy (PRRT) using simulated dynamic PET data and a physiologically based pharmacokinetic (PBPK) model. PBPK parameters were estimated using biokinetic data of 15 patients after injection of (152±15)MBq of 111 In-DTPAOC (total peptide amount (5.78±0.25)nmol). True mathematical phantoms of patients (MPPs) were the PBPK model with the estimated parameters. Dynamic PET measurements were simulated as being done after bolus injection of 150MBq 68 Ga-DOTATATE using the true MPPs. Dynamic PET scans around 35min p.i. (P 1 ), 4h p.i. (P 2 ) and the combination of P 1 and P 2 (P 3 ) were simulated. Each measurement was simulated with four frames of 5min each and 2 bed positions. PBPK parameters were fitted to the PET data to derive the PET-predicted MPPs. Therapy was simulated assuming an infusion of 5.1GBq of 90 Y-DOTATATE over 30min in both true and PET-predicted MPPs. TIACs of simulated therapy were calculated, true MPPs (true TIACs) and predicted MPPs (predicted TIACs) followed by the calculation of variabilities v. For P 1 and P 2 the population variabilities of kidneys, liver and spleen were acceptable (v<10%). For the tumours and the remainders, the values were large (up to 25%). For P 3 , population variabilities for all organs including the remainder further improved, except that of the tumour (v>10%). Treatment planning of PRRT based on dynamic PET data seems possible for the kidneys, liver and spleen using a PBPK model and patient specific information. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Approximate probabilistic cellular automata for the dynamics of single-species populations under discrete logisticlike growth with and without weak Allee effects.

PubMed

Mendonça, J Ricardo G; Gevorgyan, Yeva

2017-05-01

We investigate one-dimensional elementary probabilistic cellular automata (PCA) whose dynamics in first-order mean-field approximation yields discrete logisticlike growth models for a single-species unstructured population with nonoverlapping generations. Beginning with a general six-parameter model, we find constraints on the transition probabilities of the PCA that guarantee that the ensuing approximations make sense in terms of population dynamics and classify the valid combinations thereof. Several possible models display a negative cubic term that can be interpreted as a weak Allee factor. We also investigate the conditions under which a one-parameter PCA derived from the more general six-parameter model can generate valid population growth dynamics. Numerical simulations illustrate the behavior of some of the PCA found.

Numeric, Agent-based or System Dynamics Model? Which Modeling Approach is the Best for Vast Population Simulation?

PubMed

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

2018-01-01

Alzheimer's disease is one of the most common mental illnesses. It is posited that more than 25% of the population is affected by some mental disease during their lifetime. Treatment of each patient draws resources from the economy concerned. Therefore, it is important to quantify the potential economic impact. Agent-based, system dynamics and numerical approaches to dynamic modeling of the population of the European Union and its patients with Alzheimer's disease are presented in this article. Simulations, their characteristics, and the results from different modeling tools are compared. The results of these approaches are compared with EU population growth predictions from the statistical office of the EU by Eurostat. The methodology of a creation of the models is described and all three modeling approaches are compared. The suitability of each modeling approach for the population modeling is discussed. In this case study, all three approaches gave us the results corresponding with the EU population prediction. Moreover, we were able to predict the number of patients with AD and, based on the modeling method, we were also able to monitor different characteristics of the population. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Evolutionary Dynamics of Fearfulness and Boldness: A Stochastic Simulation Model

PubMed Central

Lu, Nan; Ji, Ting; Zhang, Jia-Hua; Sun, Yue-Hua; Tao, Yi

2012-01-01

A stochastic simulation model is investigated for the evolution of anti-predator behavior in birds. The main goal is to reveal the effects of population size, predation threats, and energy lost per escape on the evolutionary dynamics of fearfulness and boldness. Two pure strategies, fearfulness and boldness, are assumed to have different responses for the predator attacks and nonlethal disturbance. On the other hand, the co-existence mechanism of fearfulness and boldness is also considered. For the effects of total population size, predation threats, and energy lost per escape, our main results show that: (i) the fearful (bold) individuals will be favored in a small (large) population, i.e. in a small (large) population, the fearfulness (boldness) can be considered to be an ESS; (ii) in a population with moderate size, fearfulness would be favored under moderate predator attacks; and (iii) although the total population size is the most important factor for the evolutionary dynamics of both fearful and bold individuals, the small energy lost per escape enables the fearful individuals to have the ability to win the advantage even in a relatively large population. Finally, we show also that the co-existence of fearful and bold individuals is possible when the competitive interactions between individuals are introduced. PMID:22412859

Evolutionary dynamics of fearfulness and boldness: a stochastic simulation model.

PubMed

Lu, Nan; Ji, Ting; Zhang, Jia-Hua; Sun, Yue-Hua; Tao, Yi

2012-01-01

A stochastic simulation model is investigated for the evolution of anti-predator behavior in birds. The main goal is to reveal the effects of population size, predation threats, and energy lost per escape on the evolutionary dynamics of fearfulness and boldness. Two pure strategies, fearfulness and boldness, are assumed to have different responses for the predator attacks and nonlethal disturbance. On the other hand, the co-existence mechanism of fearfulness and boldness is also considered. For the effects of total population size, predation threats, and energy lost per escape, our main results show that: (i) the fearful (bold) individuals will be favored in a small (large) population, i.e. in a small (large) population, the fearfulness (boldness) can be considered to be an ESS; (ii) in a population with moderate size, fearfulness would be favored under moderate predator attacks; and (iii) although the total population size is the most important factor for the evolutionary dynamics of both fearful and bold individuals, the small energy lost per escape enables the fearful individuals to have the ability to win the advantage even in a relatively large population. Finally, we show also that the co-existence of fearful and bold individuals is possible when the competitive interactions between individuals are introduced.

Model structure of the stream salmonid simulator (S3)—A dynamic model for simulating growth, movement, and survival of juvenile salmonids

USGS Publications Warehouse

Perry, Russell W.; Plumb, John M.; Jones, Edward C.; Som, Nicholas A.; Hetrick, Nicholas J.; Hardy, Thomas B.

2018-04-06

Fisheries and water managers often use population models to aid in understanding the effect of alternative water management or restoration actions on anadromous fish populations. We developed the Stream Salmonid Simulator (S3) to help resource managers evaluate the effect of management alternatives on juvenile salmonid populations. S3 is a deterministic stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily time series of discharge, water temperature, and usable habitat area or carrying capacity. The physical characteristics of each habitat unit and the number of fish occupying each unit, in turn, drive survival and growth within each habitat unit and movement of fish among habitat units.The purpose of this report is to outline the underlying general structure of the S3 model that is common among different applications of the model. We have developed applications of the S3 model for juvenile fall Chinook salmon (Oncorhynchus tshawytscha) in the lower Klamath River. Thus, this report is a companion to current application of the S3 model to the Trinity River (in review). The general S3 model structure provides a biological and physical framework for the salmonid freshwater life cycle. This framework captures important demographics of juvenile salmonids aimed at translating management alternatives into simulated population responses. Although the S3 model is built on this common framework, the model has been constructed to allow much flexibility in application of the model to specific river systems. The ability for practitioners to include system-specific information for the physical stream structure, survival, growth, and movement processes ensures that simulations provide results that are relevant to the questions asked about the population under study.

Stereodynamics in state-resolved scattering at the gas–liquid interface

PubMed Central

Perkins, Bradford G.; Nesbitt, David J.

2008-01-01

Stereodynamics at the gas–liquid interface provides insight into the important physical interactions that directly influence heterogeneous chemistry at the surface and within the bulk liquid. We investigate molecular beam scattering of CO2 from a liquid perfluoropolyether (PFPE) surface in vacuum [incident energy Einc = 10.6(8) kcal/mol, incident angle θinc = 60°] to specifically reveal rotational angular-momentum directions for scattered molecules. Experimentally, internal quantum state populations and MJ distributions are probed by high-resolution polarization-modulated infrared laser spectroscopy. Analysis of J-state populations reveals dual-channel scattering dynamics characterized by a two-temperature Boltzmann distribution for trapping–desorption and impulsive scattering. In addition, molecular dynamics simulations of CO2 + fluorinated self-assembled monolayers have been used to model CO2 + PFPE dynamics. Experimental results and molecular dynamics simulations reveal highly oriented CO2 distributions that preferentially scatter with “top spin” as a strongly increasing function of J state. PMID:18678907

Potential-based dynamical reweighting for Markov state models of protein dynamics.

PubMed

Weber, Jeffrey K; Pande, Vijay S

2015-06-09

As simulators attempt to replicate the dynamics of large cellular components in silico, problems related to sampling slow, glassy degrees of freedom in molecular systems will be amplified manyfold. It is tempting to augment simulation techniques with external biases to overcome such barriers with ease; biased simulations, however, offer little utility unless equilibrium properties of interest (both kinetic and thermodynamic) can be recovered from the data generated. In this Article, we present a general scheme that harnesses the power of Markov state models (MSMs) to extract equilibrium kinetic properties from molecular dynamics trajectories collected on biased potential energy surfaces. We first validate our reweighting protocol on a simple two-well potential, and we proceed to test our method on potential-biased simulations of the Trp-cage miniprotein. In both cases, we find that equilibrium populations, time scales, and dynamical processes are reliably reproduced as compared to gold standard, unbiased data sets. We go on to discuss the limitations of our dynamical reweighting approach, and we suggest auspicious target systems for further application.

Studies on the population dynamics of a rumor-spreading model in online social networks

NASA Astrophysics Data System (ADS)

Dong, Suyalatu; Fan, Feng-Hua; Huang, Yong-Chang

2018-02-01

This paper sets up a rumor spreading model in online social networks based on the European fox rabies SIR model. The model considers the impact of changing number of online social network users, combines the transmission dynamics to set up a population dynamics of rumor spreading model in online social networks. Simulation is carried out on online social network, and results show that the new rumor spreading model is in accordance with the real propagation characteristics in online social networks.

CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics

USGS Publications Warehouse

Landguth, Erin L; Bearlin, Andrew; Day, Casey; Dunham, Jason B.

2016-01-01

1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications.2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers.3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

EpiPOD : community vaccination and dispensing model user's guide.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berry, M.; Samsa, M.; Walsh, D.

EpiPOD is a modeling system that enables local, regional, and county health departments to evaluate and refine their plans for mass distribution of antiviral and antibiotic medications and vaccines. An intuitive interface requires users to input as few or as many plan specifics as are available in order to simulate a mass treatment campaign. Behind the input interface, a system dynamics model simulates pharmaceutical supply logistics, hospital and first-responder personnel treatment, population arrival dynamics and treatment, and disease spread. When the simulation is complete, users have estimates of the number of illnesses in the population at large, the number ofmore » ill persons seeking treatment, and queuing and delays within the mass treatment system--all metrics by which the plan can be judged.« less

Population Simulation, AKA: Grahz, Rahbitz and Fawkzes

NASA Technical Reports Server (NTRS)

Bangert, Tyler R.

2008-01-01

In an effort to give students a more visceral experience of science and instill a deeper working knowledge of concepts, activities that utilize hands-on, laboratory and simulated experiences are recommended because these activities have a greater impact on student learning, especially for Native American students. Because it is not usually feasible to take large and/or multiple classes of high school science students into the field to count numbers of organisms of a particular species, especially over a long period of time and covering a large area of an environment, the population simulation presented in this paper was created to aid students in understanding population dynamics by working with a simulated environment, which can be done in the classroom. Students create an environment and populate the environment with imaginary species. Then, using a sequence of "rules" that allow organisms to eat, reproduce, move and age, students see how the population of a species changes over time. In particular, students practice collecting data, summarizing information, plotting graphs, and interpreting graphs for such information as carrying capacity, predator prey relationships, and how specific species factors impact population and the environment. Students draw conclusions from their results and suggest further research, which may involve changes in simulation parameters, prediction of outcomes, and testing predictions. The population Simulation has demonstrated success in the above student activities using a "board game" version of the population simulation. A computer version of the population simulation needs more testing, but preliminary runs are promising. A second - and more complicated - computer simulation will simulate the same things and will add simulated population genetics.

A Dynamic Simulation Model of Land-Use, Population, and Rural Livelihoods in the Central Rift Valley of Ethiopia

NASA Astrophysics Data System (ADS)

Garedew, Efrem; Sandewall, Mats; Soderberg, Ulf

2012-01-01

The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years and to improve our understanding of the interactions among them. The modeling output is characterized by rapid population growth, declining farm size and household incomes, deteriorating woody vegetation cover and worsening land degradation if current conditions remain. However, through integrated intervention strategies (including forest increase, micro-finance, family planning, health and education) the woody vegetation cover is likely to increase in the landscape, population growth is likely to slow down and households' income is likely to improve. A validation assessment of the simulation model based on historical data on land-use and population from 1973 to 2006 showed that the model is relatively robust. We conclude that as a supporting tool, the simulation model can contribute to the decision making process.

Modeling tradeoffs in avian life history traits and consequences for population growth

USGS Publications Warehouse

Clark, M.E.; Martin, T.E.

2007-01-01

Variation in population dynamics is inherently related to life history characteristics of species, which vary markedly even within phylogenetic groups such as passerine birds. We computed the finite rate of population change (??) from a matrix projection model and from mark-recapture observations for 23 bird species breeding in northern Arizona. We used sensitivity analyses and a simulation model to separate contributions of different life history traits to population growth rate. In particular we focused on contrasting effects of components of reproduction (nest success, clutch size, number of clutches, and juvenile survival) versus adult survival on ??. We explored how changes in nest success or adult survival coupled to costs in other life history parameters affected ?? over a life history gradient provided by our 23 Arizona species, as well as a broader sample of 121 North American passerine species. We further examined these effects for more than 200 passeriform and piciform populations breeding across North America. Model simulations indicate nest success and juvenile survival exert the largest effects on population growth in species with moderate to high reproductive output, whereas adult survival contributed more to population growth in long-lived species. Our simulations suggest that monitoring breeding success in populations across a broad geographic area provides an important index for identifying neotropical migratory populations at risk of serious population declines and a potential method for identifying large-scale mechanisms regulating population dynamics. ?? 2007 Elsevier B.V. All rights reserved.

Dispersive models describing mosquitoes’ population dynamics

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

Clustering Effect on the Dynamics in a Spatial Rock-Paper-Scissors System

NASA Astrophysics Data System (ADS)

Hashimoto, Tsuyoshi; Sato, Kazunori; Ichinose, Genki; Miyazaki, Rinko; Tainaka, Kei-ichi

2018-01-01

The lattice dynamics for rock-paper-scissors games is related to population theories in ecology. In most cases, simulations are performed by local and global interactions. It is known in the former case that the dynamics is usually stable. We find two types of non-random distributions in the stationary state. One is a cluster formation of endangered species: when the density of a species approaches zero, its clumping degree diverges to infinity. The other is the strong aggregations of high-density species. Such spatial pattern formations play important roles in population dynamics.

A multi-model framework for simulating wildlife population response to land-use and climate change

USGS Publications Warehouse

McRae, B.H.; Schumaker, N.H.; McKane, R.B.; Busing, R.T.; Solomon, A.M.; Burdick, C.A.

2008-01-01

Reliable assessments of how human activities will affect wildlife populations are essential for making scientifically defensible resource management decisions. A principle challenge of predicting effects of proposed management, development, or conservation actions is the need to incorporate multiple biotic and abiotic factors, including land-use and climate change, that interact to affect wildlife habitat and populations through time. Here we demonstrate how models of land-use, climate change, and other dynamic factors can be integrated into a coherent framework for predicting wildlife population trends. Our framework starts with land-use and climate change models developed for a region of interest. Vegetation changes through time under alternative future scenarios are predicted using an individual-based plant community model. These predictions are combined with spatially explicit animal habitat models to map changes in the distribution and quality of wildlife habitat expected under the various scenarios. Animal population responses to habitat changes and other factors are then projected using a flexible, individual-based animal population model. As an example application, we simulated animal population trends under three future land-use scenarios and four climate change scenarios in the Cascade Range of western Oregon. We chose two birds with contrasting habitat preferences for our simulations: winter wrens (Troglodytes troglodytes), which are most abundant in mature conifer forests, and song sparrows (Melospiza melodia), which prefer more open, shrubby habitats. We used climate and land-use predictions from previously published studies, as well as previously published predictions of vegetation responses using FORCLIM, an individual-based forest dynamics simulator. Vegetation predictions were integrated with other factors in PATCH, a spatially explicit, individual-based animal population simulator. Through incorporating effects of landscape history and limited dispersal, our framework predicted population changes that typically exceeded those expected based on changes in mean habitat suitability alone. Although land-use had greater impacts on habitat quality than did climate change in our simulations, we found that small changes in vital rates resulting from climate change or other stressors can have large consequences for population trajectories. The ability to integrate bottom-up demographic processes like these with top-down constraints imposed by climate and land-use in a dynamic modeling environment is a key advantage of our approach. The resulting framework should allow researchers to synthesize existing empirical evidence, and to explore complex interactions that are difficult or impossible to capture through piecemeal modeling approaches. ?? 2008 Elsevier B.V.

An advection-diffusion-reaction size-structured fish population dynamics model combined with a statistical parameter estimation procedure: application to the Indian ocean skipjack tuna fishery.

PubMed

Faugeras, Blaise; Maury, Olivier

2005-10-01

We develop an advection-diffusion size-structured fish population dynamics model and apply it to simulate the skipjack tuna population in the Indian Ocean. The model is fully spatialized, and movements are parameterized with oceanographical and biological data; thus it naturally reacts to environment changes. We first formulate an initial-boundary value problem and prove existence of a unique positive solution. We then discuss the numerical scheme chosen for the integration of the simulation model. In a second step we address the parameter estimation problem for such a model. With the help of automatic differentiation, we derive the adjoint code which is used to compute the exact gradient of a Bayesian cost function measuring the distance between the outputs of the model and catch and length frequency data. A sensitivity analysis shows that not all parameters can be estimated from the data. Finally twin experiments in which pertubated parameters are recovered from simulated data are successfully conducted.

[Are simple time lags responsible for cyclic variation of population density? : A comparison of laboratory population dynamics of Brachionus calyciflorus pallas (rotatoria) with computer simulations].

PubMed

Halbach, Udo; Burkhardt, Heinz Jürgen

1972-09-01

Laboratory populations of the rotifer Brachionus calyciflorus were cultured at different temperatures (25, 20, 15°C) but otherwise at constant conditions. The population densities showed relatively constant oscillations (Figs. 1 to 3A-C). Amplitudes and frequencies of the oscillations were positively correlated with temperature (Table 1). A test was made, whether the logistic growth function with simple time lag is able to describe the population curves. There are strong similarities between the simulations (Figs. 1-3E) and the real population dynamics if minor adjustments of the empirically determined parameters are made. There-fore it is suggested that time lags are responsible for the observed oscillations. However, the actual time lags probably do not act in the simple manner of the model, because birth and death rates react with different time lags, and both parameters are dependent on individual age and population density. A more complex model, which incorporates these modifications, should lead to a more realistic description of the observed oscillations.

Dispersal responses override density effects on genetic diversity during post-disturbance succession

PubMed Central

Landguth, Erin L.; Bull, C. Michael; Banks, Sam C.; Gardner, Michael G.; Driscoll, Don A.

2016-01-01

Dispersal fundamentally influences spatial population dynamics but little is known about dispersal variation in landscapes where spatial heterogeneity is generated predominantly by disturbance and succession. We tested the hypothesis that habitat succession following fire inhibits dispersal, leading to declines over time in genetic diversity in the early successional gecko Nephrurus stellatus. We combined a landscape genetics field study with a spatially explicit simulation experiment to determine whether successional patterns in genetic diversity were driven by habitat-mediated dispersal or demographic effects (declines in population density leading to genetic drift). Initial increases in genetic structure following fire were likely driven by direct mortality and rapid population expansion. Subsequent habitat succession increased resistance to gene flow and decreased dispersal and genetic diversity in N. stellatus. Simulated changes in population density alone did not reproduce these results. Habitat-mediated reductions in dispersal, combined with changes in population density, were essential to drive the field-observed patterns. Our study provides a framework for combining demographic, movement and genetic data with simulations to discover the relative influence of demography and dispersal on patterns of landscape genetic structure. Our results suggest that succession can inhibit connectivity among individuals, opening new avenues for understanding how disturbance regimes influence spatial population dynamics. PMID:27009225

REVIEW OF SIMULATION METHODS FOR SPATIALLY-EXPLICIT POPULATION-LEVEL RISK ASSESSMENT

EPA Science Inventory

Factors that significantly impact population dynamics, such as resource availability and exposure to stressors, frequently vary over space and thereby determine the heterogeneous spatial distributions of organisms. Considering this fact, the US Environmental Protection Agency's ...

The dynamic influence of human resources on evidence-based intervention sustainability and population outcomes: an agent-based modeling approach.

PubMed

McKay, Virginia R; Hoffer, Lee D; Combs, Todd B; Margaret Dolcini, M

2018-06-05

Sustaining evidence-based interventions (EBIs) is an ongoing challenge for dissemination and implementation science in public health and social services. Characterizing the relationship among human resource capacity within an agency and subsequent population outcomes is an important step to improving our understanding of how EBIs are sustained. Although human resource capacity and population outcomes are theoretically related, examining them over time within real-world experiments is difficult. Simulation approaches, especially agent-based models, offer advantages that complement existing methods. We used an agent-based model to examine the relationships among human resources, EBI delivery, and population outcomes by simulating provision of an EBI through a hypothetical agency and its staff. We used data from existing studies examining a widely implemented HIV prevention intervention to inform simulation design, calibration, and validity. Once we developed a baseline model, we used the model as a simulated laboratory by systematically varying three human resource variables: the number of staff positions, the staff turnover rate, and timing in training. We tracked the subsequent influence on EBI delivery and the level of population risk over time to describe the overall and dynamic relationships among these variables. Higher overall levels of human resource capacity at an agency (more positions) led to more extensive EBI delivery over time and lowered population risk earlier in time. In simulations representing the typical human resource investments, substantial influences on population risk were visible after approximately 2 years and peaked around 4 years. Human resources, especially staff positions, have an important impact on EBI sustainability and ultimately population health. A minimum level of human resources based on the context (e.g., size of the initial population and characteristics of the EBI) is likely needed for an EBI to have a meaningful impact on population outcomes. Furthermore, this model demonstrates how ABMs may be leveraged to inform research design and assess the impact of EBI sustainability in practice.

Sobol’ sensitivity analysis for stressor impacts on honeybee colonies

EPA Science Inventory

We employ Monte Carlo simulation and nonlinear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed of hive population trajectories, taking into account queen strength, foraging success, mite impacts, weather...

Effects of glyphosate formulations on the population dynamics of two freshwater cladoceran species.

PubMed

Reno, U; Doyle, S R; Momo, F R; Regaldo, L; Gagneten, A M

2018-02-05

The general objective of this work is to experimentally assess the effects of acute glyphosate pollution on two freshwater cladoceran species (Daphnia magna and Ceriodaphnia dubia) and to use this information to predict the population dynamics and the potential for recovery of exposed organisms. Five to six concentrations of four formulations of glyphosate (4-Gly) (Eskoba ® , Panzer Gold ® , Roundup Ultramax ® and Sulfosato Touchdown ® ) were evaluated in both cladoceran species through acute tests and 15-day recovery tests in order to estimate the population dynamics of microcrustaceans. The endpoints of the recovery test were: survival, growth (number of molts), fecundity, and the intrinsic population growth rate (r). A matrix population model (MPM) was applied to r of the survivor individuals of the acute tests, followed by a Monte Carlo simulation study. Among the 4-Gly tested, Sulfosato Touchdown ® was the one that showed higher toxicity, and C. dubia was the most sensitive species. The Monte Carlo simulation study showed an average value of λ always <1 for D. magna, indicating that its populations would not be able to survive under natural environmental conditions after an acute Gly exposure between 0.25 and 35 a.e. mg L -1 . The average value of λ for C. dubia was also <1 after exposure to Roundup Ultramax ® : 1.30 and 1.20 for 1.21 and 2.5 mg a.e. L -1 ,respectively. The combined methodology-recovery tests and the later analysis through MPM with a Monte Carlo simulation study-is proposed to integrate key demographic parameters and predict the possible fate of microcrustacean populations after being exposed to acute 4-Gly contamination events.

Conformational ensembles of RNA oligonucleotides from integrating NMR and molecular simulations.

PubMed

Bottaro, Sandro; Bussi, Giovanni; Kennedy, Scott D; Turner, Douglas H; Lindorff-Larsen, Kresten

2018-05-01

RNA molecules are key players in numerous cellular processes and are characterized by a complex relationship between structure, dynamics, and function. Despite their apparent simplicity, RNA oligonucleotides are very flexible molecules, and understanding their internal dynamics is particularly challenging using experimental data alone. We show how to reconstruct the conformational ensemble of four RNA tetranucleotides by combining atomistic molecular dynamics simulations with nuclear magnetic resonance spectroscopy data. The goal is achieved by reweighting simulations using a maximum entropy/Bayesian approach. In this way, we overcome problems of current simulation methods, as well as in interpreting ensemble- and time-averaged experimental data. We determine the populations of different conformational states by considering several nuclear magnetic resonance parameters and point toward properties that are not captured by state-of-the-art molecular force fields. Although our approach is applied on a set of model systems, it is fully general and may be used to study the conformational dynamics of flexible biomolecules and to detect inaccuracies in molecular dynamics force fields.

Inference of Epidemiological Dynamics Based on Simulated Phylogenies Using Birth-Death and Coalescent Models

PubMed Central

Boskova, Veronika; Bonhoeffer, Sebastian; Stadler, Tanja

2014-01-01

Quantifying epidemiological dynamics is crucial for understanding and forecasting the spread of an epidemic. The coalescent and the birth-death model are used interchangeably to infer epidemiological parameters from the genealogical relationships of the pathogen population under study, which in turn are inferred from the pathogen genetic sequencing data. To compare the performance of these widely applied models, we performed a simulation study. We simulated phylogenetic trees under the constant rate birth-death model and the coalescent model with a deterministic exponentially growing infected population. For each tree, we re-estimated the epidemiological parameters using both a birth-death and a coalescent based method, implemented as an MCMC procedure in BEAST v2.0. In our analyses that estimate the growth rate of an epidemic based on simulated birth-death trees, the point estimates such as the maximum a posteriori/maximum likelihood estimates are not very different. However, the estimates of uncertainty are very different. The birth-death model had a higher coverage than the coalescent model, i.e. contained the true value in the highest posterior density (HPD) interval more often (2–13% vs. 31–75% error). The coverage of the coalescent decreases with decreasing basic reproductive ratio and increasing sampling probability of infecteds. We hypothesize that the biases in the coalescent are due to the assumption of deterministic rather than stochastic population size changes. Both methods performed reasonably well when analyzing trees simulated under the coalescent. The methods can also identify other key epidemiological parameters as long as one of the parameters is fixed to its true value. In summary, when using genetic data to estimate epidemic dynamics, our results suggest that the birth-death method will be less sensitive to population fluctuations of early outbreaks than the coalescent method that assumes a deterministic exponentially growing infected population. PMID:25375100

Quantitative sampling of conformational heterogeneity of a DNA hairpin using molecular dynamics simulations and ultrafast fluorescence spectroscopy

PubMed Central

Voltz, Karine; Léonard, Jérémie; Touceda, Patricia Tourón; Conyard, Jamie; Chaker, Ziyad; Dejaegere, Annick; Godet, Julien; Mély, Yves; Haacke, Stefan; Stote, Roland H.

2016-01-01

Molecular dynamics (MD) simulations and time resolved fluorescence (TRF) spectroscopy were combined to quantitatively describe the conformational landscape of the DNA primary binding sequence (PBS) of the HIV-1 genome, a short hairpin targeted by retroviral nucleocapsid proteins implicated in the viral reverse transcription. Three 2-aminopurine (2AP) labeled PBS constructs were studied. For each variant, the complete distribution of fluorescence lifetimes covering 5 orders of magnitude in timescale was measured and the populations of conformers experimentally observed to undergo static quenching were quantified. A binary quantification permitted the comparison of populations from experimental lifetime amplitudes to populations of aromatically stacked 2AP conformers obtained from simulation. Both populations agreed well, supporting the general assumption that quenching of 2AP fluorescence results from pi-stacking interactions with neighboring nucleobases and demonstrating the success of the proposed methodology for the combined analysis of TRF and MD data. Cluster analysis of the latter further identified predominant conformations that were consistent with the fluorescence decay times and amplitudes, providing a structure-based rationalization for the wide range of fluorescence lifetimes. Finally, the simulations provided evidence of local structural perturbations induced by 2AP. The approach presented is a general tool to investigate fine structural heterogeneity in nucleic acid and nucleoprotein assemblies. PMID:26896800

The role of density-dependent individual growth in the persistence of freshwater salmonid populations.

PubMed

Vincenzi, Simone; Crivelli, Alain J; Jesensek, Dusan; De Leo, Giulio A

2008-06-01

Theoretical and empirical models of populations dynamics have paid little attention to the implications of density-dependent individual growth on the persistence and regulation of small freshwater salmonid populations. We have therefore designed a study aimed at testing our hypothesis that density-dependent individual growth is a process that enhances population recovery and reduces extinction risk in salmonid populations in a variable environment subject to disturbance events. This hypothesis was tested in two newly introduced marble trout (Salmo marmoratus) populations living in Slovenian streams (Zakojska and Gorska) subject to severe autumn floods. We developed a discrete-time stochastic individual-based model of population dynamics for each population with demographic parameters and compensatory responses tightly calibrated on data from individually tagged marble trout. The occurrence of severe flood events causing population collapses was explicitly accounted for in the model. We used the model in a population viability analysis setting to estimate the quasi-extinction risk and demographic indexes of the two marble trout populations when individual growth was density-dependent. We ran a set of simulations in which the effect of floods on population abundance was explicitly accounted for and another set of simulations in which flood events were not included in the model. These simulation results were compared with those of scenarios in which individual growth was modelled with density-independent Von Bertalanffy growth curves. Our results show how density-dependent individual growth may confer remarkable resilience to marble trout populations in case of major flood events. The resilience to flood events shown by the simulation results can be explained by the increase in size-dependent fecundity as a consequence of the drop in population size after a severe flood, which allows the population to quickly recover to the pre-event conditions. Our results suggest that density-dependent individual growth plays a potentially powerful role in the persistence of freshwater salmonids living in streams subject to recurrent yet unpredictable flood events.

Modelling the spread of innovation in wild birds.

PubMed

Shultz, Thomas R; Montrey, Marcel; Aplin, Lucy M

2017-06-01

We apply three plausible algorithms in agent-based computer simulations to recent experiments on social learning in wild birds. Although some of the phenomena are simulated by all three learning algorithms, several manifestations of social conformity bias are simulated by only the approximate majority (AM) algorithm, which has roots in chemistry, molecular biology and theoretical computer science. The simulations generate testable predictions and provide several explanatory insights into the diffusion of innovation through a population. The AM algorithm's success raises the possibility of its usefulness in studying group dynamics more generally, in several different scientific domains. Our differential-equation model matches simulation results and provides mathematical insights into the dynamics of these algorithms. © 2017 The Author(s).

Integral projection models for finite populations in a stochastic environment.

PubMed

Vindenes, Yngvild; Engen, Steinar; Saether, Bernt-Erik

2011-05-01

Continuous types of population structure occur when continuous variables such as body size or habitat quality affect the vital parameters of individuals. These structures can give rise to complex population dynamics and interact with environmental conditions. Here we present a model for continuously structured populations with finite size, including both demographic and environmental stochasticity in the dynamics. Using recent methods developed for discrete age-structured models we derive the demographic and environmental variance of the population growth as functions of a continuous state variable. These two parameters, together with the expected population growth rate, are used to define a one-dimensional diffusion approximation of the population dynamics. Thus, a substantial reduction in complexity is achieved as the dynamics of the complex structured model can be described by only three population parameters. We provide methods for numerical calculation of the model parameters and demonstrate the accuracy of the diffusion approximation by computer simulation of specific examples. The general modeling framework makes it possible to analyze and predict future dynamics and extinction risk of populations with various types of structure, and to explore consequences of changes in demography caused by, e.g., climate change or different management decisions. Our results are especially relevant for small populations that are often of conservation concern.

Stochastic dynamics of dengue epidemics.

PubMed

de Souza, David R; Tomé, Tânia; Pinho, Suani T R; Barreto, Florisneide R; de Oliveira, Mário J

2013-01-01

We use a stochastic Markovian dynamics approach to describe the spreading of vector-transmitted diseases, such as dengue, and the threshold of the disease. The coexistence space is composed of two structures representing the human and mosquito populations. The human population follows a susceptible-infected-recovered (SIR) type dynamics and the mosquito population follows a susceptible-infected-susceptible (SIS) type dynamics. The human infection is caused by infected mosquitoes and vice versa, so that the SIS and SIR dynamics are interconnected. We develop a truncation scheme to solve the evolution equations from which we get the threshold of the disease and the reproductive ratio. The threshold of the disease is also obtained by performing numerical simulations. We found that for certain values of the infection rates the spreading of the disease is impossible, for any death rate of infected mosquitoes.

New Editions for the Apple II of the Chelsea Science Simulations.

ERIC Educational Resources Information Center

Pipeline, 1983

1983-01-01

Ten computer simulations for the Apple II are described. Subject areas of programs include: population dynamics, plant competition, enzyme kinetics, evolution and natural selection, genetic mapping, ammonia synthesis, reaction kinetics, wave interference/diffraction, satellite orbits, and particle scattering. (JN)

SIMULATING FISH ASSEMBLAGE DYNAMICS IN RIVER NETWORKS

EPA Science Inventory

My recently retired colleague, Joan Baker, and I have developed a prototype computer simulation model for studying the effects of human and non-human alterations of habitats and species availability on fish assemblage populations. The fish assemblage model, written in R, is a sp...

Coupled stream and population dynamics: Modeling the role beaver (Castor canadensis) play in generating juvenile steelhead (Oncorhynchus mykiss) habitat

NASA Astrophysics Data System (ADS)

Jordan, C.; Bouwes, N.; Wheaton, J. M.; Pollock, M.

2013-12-01

Over the past several centuries, the population of North American Beaver has been dramatically reduced through fur trapping. As a result, the geomorphic impacts long-term beaver occupancy and activity can have on fluvial systems have been lost, both from the landscape and from our collective memory such that physical and biological models of floodplain system function neither consider nor have the capacity to incorporate the role beaver can play in structuring the dynamics of streams. Concomitant with the decline in beaver populations was an increasing pressure on streams and floodplains through human activity, placing numerous species of stream rearing fishes in peril, most notably the ESA listing of trout and salmon populations across the entirety of the Western US. The rehabilitation of stream systems is seen as one of the primary means by which population and ecosystem recovery can be achieved, yet the methods of stream rehabilitation are applied almost exclusively with the expected outcome of a static idealized stream planform, occasionally with an acknowledgement of restoring processes rather than form and only rarely with the goal of a beaver dominated riverscape. We have constructed an individual based model of trout and beaver populations that allows the exploration of fish population dynamics as a function of stream habitat quality and quantity. We based the simulation tool on Bridge Creek (John Day River basin, Oregon) where we have implemented a large-scale restoration experiment using wooden posts to provide beavers with stable platforms for dam building and to simulate the dams themselves. Extensive monitoring captured geomorphic and riparian changes, as well as fish and beaver population responses; information we use to parameterize the model as to the geomorphic and fish response to dam building beavers. In the simulation environment, stream habitat quality and quantity can be manipulated directly through rehabilitation actions and indirectly through the dynamics of the co-occurring beaver population. The model allowed to us to ask questions critical for designing restoration strategies based on dam building beaver activity, such as what beaver population growth rate is required to develop and maintain floodplain connectivity in an incised system, or what beaver population size is required to increase juvenile steelhead production? The model was sensitive to several variables including beaver colony size, dams and colony dynamics and site fidelity, and thus highlights further research needs to fill critical information gaps.

And So It Grows: Using a Computer-Based Simulation of a Population Growth Model to Integrate Biology & Mathematics

ERIC Educational Resources Information Center

Street, Garrett M.; Laubach, Timothy A.

2013-01-01

We provide a 5E structured-inquiry lesson so that students can learn more of the mathematics behind the logistic model of population biology. By using models and mathematics, students understand how population dynamics can be influenced by relatively simple changes in the environment.

Dynamics of buckbrush populations under simulated forest restoration alternatives

Treesearch

David W. Huffman; Margaret M. Moore

2008-01-01

Plant population models are valuable tools for assessing ecological tradeoffs between forest management approaches. In addition, these models can provide insight on plant life history patterns and processes important for persistence and recovery of populations in changing environments. In this study, we evaluated a set of ecological restoration alternatives for their...

Dynamics of buckbrush populations under simulated forest restoration alternatives (P-53)

Treesearch

David W. Huffman; Margaret M. Moore

2008-01-01

Plant population models are valuable tools for assessing ecological tradeoffs between forest management approaches. In addition, these models can provide insight on plant life history patterns and processes important for persistence and recovery of populations in changing environments. In this study, we evaluated a set of ecological restoration alternatives for their...

Stability and robustness analysis of cooperation cycles driven by destructive agents in finite populations

NASA Astrophysics Data System (ADS)

Requejo, Rubén J.; Camacho, Juan; Cuesta, José A.; Arenas, Alex

2012-08-01

The emergence and promotion of cooperation are two of the main issues in evolutionary game theory, as cooperation is amenable to exploitation by defectors, which take advantage of cooperative individuals at no cost, dooming them to extinction. It has been recently shown that the existence of purely destructive agents (termed jokers) acting on the common enterprises (public goods games) can induce stable limit cycles among cooperation, defection, and destruction when infinite populations are considered. These cycles allow for time lapses in which cooperators represent a relevant fraction of the population, providing a mechanism for the emergence of cooperative states in nature and human societies. Here we study analytically and through agent-based simulations the dynamics generated by jokers in finite populations for several selection rules. Cycles appear in all cases studied, thus showing that the joker dynamics generically yields a robust cyclic behavior not restricted to infinite populations. We also compute the average time in which the population consists mostly of just one strategy and compare the results with numerical simulations.

Stellar metallicity variations across spiral arms in disk galaxies with multiple populations

NASA Astrophysics Data System (ADS)

Khoperskov, S.; Di Matteo, P.; Haywood, M.; Combes, F.

2018-03-01

This Letter studies the formation of azimuthal metallicity variations in the disks of spiral galaxies in the absence of initial radial metallicity gradients. Using high-resolution N-body simulations, we model composite stellar discs, made of kinematically cold and hot stellar populations, and study their response to spiral arm perturbations. We find that, as expected, disk populations with different kinematics respond differently to a spiral perturbation, with the tendency for dynamically cooler populations to show a larger fractional contribution to spiral arms than dynamically hotter populations. By assuming a relation between kinematics and metallicity, namely the hotter the population, the more metal-poor it is, this differential response to the spiral arm perturbations naturally leads to azimuthal variations in the mean metallicity of stars in the simulated disk. Thus, azimuthal variations in the mean metallicity of stars across a spiral galaxy are not necessarily a consequence of the reshaping, by radial migration, of an initial radial metallicity gradient. They indeed arise naturally also in stellar disks which have initially only a negative vertical metallicity gradient.

Constraint methods that accelerate free-energy simulations of biomolecules.

PubMed

Perez, Alberto; MacCallum, Justin L; Coutsias, Evangelos A; Dill, Ken A

2015-12-28

Atomistic molecular dynamics simulations of biomolecules are critical for generating narratives about biological mechanisms. The power of atomistic simulations is that these are physics-based methods that satisfy Boltzmann's law, so they can be used to compute populations, dynamics, and mechanisms. But physical simulations are computationally intensive and do not scale well to the sizes of many important biomolecules. One way to speed up physical simulations is by coarse-graining the potential function. Another way is to harness structural knowledge, often by imposing spring-like restraints. But harnessing external knowledge in physical simulations is problematic because knowledge, data, or hunches have errors, noise, and combinatoric uncertainties. Here, we review recent principled methods for imposing restraints to speed up physics-based molecular simulations that promise to scale to larger biomolecules and motions.

Pre-Whaling Genetic Diversity and Population Ecology in Eastern Pacific Gray Whales: Insights from Ancient DNA and Stable Isotopes

PubMed Central

Alter, S. Elizabeth; Newsome, Seth D.; Palumbi, Stephen R.

2012-01-01

Commercial whaling decimated many whale populations, including the eastern Pacific gray whale, but little is known about how population dynamics or ecology differed prior to these removals. Of particular interest is the possibility of a large population decline prior to whaling, as such a decline could explain the ∼5-fold difference between genetic estimates of prior abundance and estimates based on historical records. We analyzed genetic (mitochondrial control region) and isotopic information from modern and prehistoric gray whales using serial coalescent simulations and Bayesian skyline analyses to test for a pre-whaling decline and to examine prehistoric genetic diversity, population dynamics and ecology. Simulations demonstrate that significant genetic differences observed between ancient and modern samples could be caused by a large, recent population bottleneck, roughly concurrent with commercial whaling. Stable isotopes show minimal differences between modern and ancient gray whale foraging ecology. Using rejection-based Approximate Bayesian Computation, we estimate the size of the population bottleneck at its minimum abundance and the pre-bottleneck abundance. Our results agree with previous genetic studies suggesting the historical size of the eastern gray whale population was roughly three to five times its current size. PMID:22590499

An open-population hierarchical distance sampling model

USGS Publications Warehouse

Sollmann, Rachel; Beth Gardner,; Richard B Chandler,; Royle, J. Andrew; T Scott Sillett,

2015-01-01

Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

An open-population hierarchical distance sampling model.

PubMed

Sollmann, Rahel; Gardner, Beth; Chandler, Richard B; Royle, J Andrew; Sillett, T Scott

2015-02-01

Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for Island Scrub-Jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying numbers of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

Fundamental population-productivity relationships can be modified through density-dependent feedbacks of life-history evolution.

PubMed

Kuparinen, Anna; Stenseth, Nils Christian; Hutchings, Jeffrey A

2014-12-01

The evolution of life histories over contemporary time scales will almost certainly affect population demography. One important pathway for such eco-evolutionary interactions is the density-dependent regulation of population dynamics. Here, we investigate how fisheries-induced evolution (FIE) might alter density-dependent population-productivity relationships. To this end, we simulate the eco-evolutionary dynamics of an Atlantic cod (Gadus morhua) population under fishing, followed by a period of recovery in the absence of fishing. FIE is associated with increases in juvenile production, the ratio of juveniles to mature population biomass, and the ratio of the mature population biomass relative to the total population biomass. In contrast, net reproductive rate (R 0 ) and per capita population growth rate (r) decline concomitantly with evolution. Our findings suggest that FIE can substantially modify the fundamental population-productivity relationships that underlie density-dependent population regulation and that form the primary population-dynamical basis for fisheries stock-assessment projections. From a conservation and fisheries-rebuilding perspective, we find that FIE reduces R 0 and r, the two fundamental correlates of population recovery ability and inversely extinction probability.

Parameterization and Sensitivity Analysis of a Complex Simulation Model for Mosquito Population Dynamics, Dengue Transmission, and Their Control

PubMed Central

Ellis, Alicia M.; Garcia, Andres J.; Focks, Dana A.; Morrison, Amy C.; Scott, Thomas W.

2011-01-01

Models can be useful tools for understanding the dynamics and control of mosquito-borne disease. More detailed models may be more realistic and better suited for understanding local disease dynamics; however, evaluating model suitability, accuracy, and performance becomes increasingly difficult with greater model complexity. Sensitivity analysis is a technique that permits exploration of complex models by evaluating the sensitivity of the model to changes in parameters. Here, we present results of sensitivity analyses of two interrelated complex simulation models of mosquito population dynamics and dengue transmission. We found that dengue transmission may be influenced most by survival in each life stage of the mosquito, mosquito biting behavior, and duration of the infectious period in humans. The importance of these biological processes for vector-borne disease models and the overwhelming lack of knowledge about them make acquisition of relevant field data on these biological processes a top research priority. PMID:21813844

Implications of Stellar Feedback for Dynamical Modeling of the Milky Way and Dwarf Galaxies

NASA Astrophysics Data System (ADS)

Wetzel, Andrew

2018-04-01

I will present recent results on dynamical modeling of stellar populations from the FIRE cosmological zoom-in baryonic simulations of Milky Way-like and dwarf galaxies. First, I will discuss the dynamical formation of the Milky Way, including the origin of thin+thick stellar disk morphology. I also will discuss the curious origin of metal-rich stars on halo-like orbits near the Sun, as recently measured by Gaia, with new insights from FIRE simulations on stellar radial migration/heating. Next, I will discuss role of stellar feedback in generating non-equilibrium fluctuations of the gravitational potential in low-mass 'dwarf' galaxies, which can explain the origin of cores in their dark-matter density profiles. In particular, we predict significant observable effects on stellar dynamics, including radial migration, size fluctuations, and population gradients, which can provide observational tests of feedback-driven core formation. Finally, this scenario can explain the formation of newly discovered 'ultra-diffuse' galaxies.

Simulating Population Dynamics in an Ecosystem Context Using Coupled Eulerian-Lagrangian Hybrid Models (CEL HYBRID Models)

DTIC Science & Technology

2000-04-01

natural systems (King 1993). Population modelers have used certain difference equations, sometimes called the Lotka - Volterra system of equations...environment 28 Step 5 - Simulate the hydraulic and/or water quality field 29 Step 6 - Generate biota response data for decision support 29 Step 7...Quality and Contaminant Modeling Branch (WQCMB), and Mr. R. Andrew Goodwin, contract student, WQCMB, under the general supervision of Dr. Mark S. Dortch

Modelling the dynamics of feral alfalfa populations and its management implications.

PubMed

Bagavathiannan, Muthukumar V; Begg, Graham S; Gulden, Robert H; Van Acker, Rene C

2012-01-01

Feral populations of cultivated crops can pose challenges to novel trait confinement within agricultural landscapes. Simulation models can be helpful in investigating the underlying dynamics of feral populations and determining suitable management options. We developed a stage-structured matrix population model for roadside feral alfalfa populations occurring in southern Manitoba, Canada. The model accounted for the existence of density-dependence and recruitment subsidy in feral populations. We used the model to investigate the long-term dynamics of feral alfalfa populations, and to evaluate the effectiveness of simulated management strategies such as herbicide application and mowing in controlling feral alfalfa. Results suggest that alfalfa populations occurring in roadside habitats can be persistent and less likely to go extinct under current roadverge management scenarios. Management attempts focused on controlling adult plants alone can be counterproductive due to the presence of density-dependent effects. Targeted herbicide application, which can achieve complete control of seedlings, rosettes and established plants, will be an effective strategy, but the seedbank population may contribute to new recruits. In regions where roadside mowing is regularly practiced, devising a timely mowing strategy (early- to mid-August for southern Manitoba), one that can totally prevent seed production, will be a feasible option for managing feral alfalfa populations. Feral alfalfa populations can be persistent in roadside habitats. Timely mowing or regular targeted herbicide application will be effective in managing feral alfalfa populations and limit feral-population-mediated gene flow in alfalfa. However, in the context of novel trait confinement, the extent to which feral alfalfa populations need to be managed will be dictated by the tolerance levels established by specific production systems for specific traits. The modelling framework outlined in this paper could be applied to other perennial herbaceous plants with similar life-history characteristics.

Differential influences of local subpopulations on regional diversity and differentiation for greater sage-grouse (Centrocercus urophasianus)

USGS Publications Warehouse

Row, Jeffery R.; Oyler-McCance, Sara J.; Fedy, Brad C.

2016-01-01

The distribution of spatial genetic variation across a region can shape evolutionary dynamics and impact population persistence. Local population dynamics and among-population dispersal rates are strong drivers of this spatial genetic variation, yet for many species we lack a clear understanding of how these population processes interact in space to shape within-species genetic variation. Here, we used extensive genetic and demographic data from 10 subpopulations of greater sage-grouse to parameterize a simulated approximate Bayesian computation (ABC) model and (i) test for regional differences in population density and dispersal rates for greater sage-grouse subpopulations in Wyoming, and (ii) quantify how these differences impact subpopulation regional influence on genetic variation. We found a close match between observed and simulated data under our parameterized model and strong variation in density and dispersal rates across Wyoming. Sensitivity analyses suggested that changes in dispersal (via landscape resistance) had a greater influence on regional differentiation, whereas changes in density had a greater influence on mean diversity across all subpopulations. Local subpopulations, however, varied in their regional influence on genetic variation. Decreases in the size and dispersal rates of central populations with low overall and net immigration (i.e. population sources) had the greatest negative impact on genetic variation. Overall, our results provide insight into the interactions among demography, dispersal and genetic variation and highlight the potential of ABC to disentangle the complexity of regional population dynamics and project the genetic impact of changing conditions.

Coevolutionary dynamics in large, but finite populations

NASA Astrophysics Data System (ADS)

Traulsen, Arne; Claussen, Jens Christian; Hauert, Christoph

2006-07-01

Coevolving and competing species or game-theoretic strategies exhibit rich and complex dynamics for which a general theoretical framework based on finite populations is still lacking. Recently, an explicit mean-field description in the form of a Fokker-Planck equation was derived for frequency-dependent selection with two strategies in finite populations based on microscopic processes [A. Traulsen, J. C. Claussen, and C. Hauert, Phys. Rev. Lett. 95, 238701 (2005)]. Here we generalize this approach in a twofold way: First, we extend the framework to an arbitrary number of strategies and second, we allow for mutations in the evolutionary process. The deterministic limit of infinite population size of the frequency-dependent Moran process yields the adjusted replicator-mutator equation, which describes the combined effect of selection and mutation. For finite populations, we provide an extension taking random drift into account. In the limit of neutral selection, i.e., whenever the process is determined by random drift and mutations, the stationary strategy distribution is derived. This distribution forms the background for the coevolutionary process. In particular, a critical mutation rate uc is obtained separating two scenarios: above uc the population predominantly consists of a mixture of strategies whereas below uc the population tends to be in homogeneous states. For one of the fundamental problems in evolutionary biology, the evolution of cooperation under Darwinian selection, we demonstrate that the analytical framework provides excellent approximations to individual based simulations even for rather small population sizes. This approach complements simulation results and provides a deeper, systematic understanding of coevolutionary dynamics.

A computational framework for testing arrhythmia marker sensitivities to model parameters in functionally calibrated populations of atrial cells

NASA Astrophysics Data System (ADS)

Vagos, Márcia R.; Arevalo, Hermenegild; de Oliveira, Bernardo Lino; Sundnes, Joakim; Maleckar, Mary M.

2017-09-01

Models of cardiac cell electrophysiology are complex non-linear systems which can be used to gain insight into mechanisms of cardiac dynamics in both healthy and pathological conditions. However, the complexity of cardiac models can make mechanistic insight difficult. Moreover, these are typically fitted to averaged experimental data which do not incorporate the variability in observations. Recently, building populations of models to incorporate inter- and intra-subject variability in simulations has been combined with sensitivity analysis (SA) to uncover novel ionic mechanisms and potentially clarify arrhythmogenic behaviors. We used the Koivumäki human atrial cell model to create two populations, representing normal Sinus Rhythm (nSR) and chronic Atrial Fibrillation (cAF), by varying 22 key model parameters. In each population, 14 biomarkers related to the action potential and dynamic restitution were extracted. Populations were calibrated based on distributions of biomarkers to obtain reasonable physiological behavior, and subjected to SA to quantify correlations between model parameters and pro-arrhythmia markers. The two populations showed distinct behaviors under steady state and dynamic pacing. The nSR population revealed greater variability, and more unstable dynamic restitution, as compared to the cAF population, suggesting that simulated cAF remodeling rendered cells more stable to parameter variation and rate adaptation. SA revealed that the biomarkers depended mainly on five ionic currents, with noted differences in sensitivities to these between nSR and cAF. Also, parameters could be selected to produce a model variant with no alternans and unaltered action potential morphology, highlighting that unstable dynamical behavior may be driven by specific cell parameter settings. These results ultimately suggest that arrhythmia maintenance in cAF may not be due to instability in cell membrane excitability, but rather due to tissue-level effects which promote initiation and maintenance of reentrant arrhythmia.

A dynamic simulation model of land-use, population, and rural livelihoods in the Central Rift Valley of Ethiopia.

PubMed

Garedew, Efrem; Sandewall, Mats; Soderberg, Ulf

2012-01-01

The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years and to improve our understanding of the interactions among them. The modeling output is characterized by rapid population growth, declining farm size and household incomes, deteriorating woody vegetation cover and worsening land degradation if current conditions remain. However, through integrated intervention strategies (including forest increase, micro-finance, family planning, health and education) the woody vegetation cover is likely to increase in the landscape, population growth is likely to slow down and households' income is likely to improve. A validation assessment of the simulation model based on historical data on land-use and population from 1973 to 2006 showed that the model is relatively robust. We conclude that as a supporting tool, the simulation model can contribute to the decision making process.

Persistence and diversity of directional landscape connectivity improves biomass pulsing in expanding and contracting wetlands

USGS Publications Warehouse

Yurek, Simeon; DeAngelis, Donald L.; Trexler, Joel C.; Klassen, Stephen; Larsen, Laurel G.

2016-01-01

In flood-pulsed ecosystems, hydrology and landscape structure mediate transfers of energy up the food chain by expanding and contracting in area, enabling spatial expansion and growth of fish populations during rising water levels, and subsequent concentration during the drying phase. Connectivity of flooded areas is dynamic as waters rise and fall, and is largely determined by landscape geomorphology and anisotropy. We developed a methodology for simulating fish dispersal and concentration on spatially-explicit, dynamic floodplain wetlands with pulsed food web dynamics, to evaluate how changes in connectivity through time contribute to the concentration of fish biomass that is essential for higher trophic levels. The model also tracks a connectivity index (DCI) over different compass directions to see if fish biomass dynamics can be related in a simple way to topographic pattern. We demonstrate the model for a seasonally flood-pulsed, oligotrophic system, the Everglades, where flow regimes have been greatly altered. Three dispersing populations of functional fish groups were simulated with empirically-based dispersal rules on two landscapes, and two twelve-year time series of managed water levels for those areas were applied. The topographies of the simulations represented intact and degraded ridge-and-slough landscapes (RSL). Simulation results showed large pulses of biomass concentration forming during the onset of the drying phase, when water levels were falling and fish began to converge into the sloughs. As water levels fell below the ridges, DCI declined over different directions, closing down dispersal lanes, and fish density spiked. Persistence of intermediate levels of connectivity on the intact RSL enabled persistent concentration events throughout the drying phase. The intact landscape also buffered effects of wet season population growth. Water level reversals on both landscapes negatively affected fish densities by depleting fish populations without allowing enough time for them to regenerate. Testable, spatiotemporal predictions of the timing, location, duration, and magnitude of fish concentration pulses were produced by the model, and can be applied to restoration planning.

Peptide crystal simulations reveal hidden dynamics

PubMed Central

Janowski, Pawel A.; Cerutti, David S.; Holton, James; Case, David A.

2013-01-01

Molecular dynamics simulations of biomolecular crystals at atomic resolution have the potential to recover information on dynamics and heterogeneity hidden in the X-ray diffraction data. We present here 9.6 microseconds of dynamics in a small helical peptide crystal with 36 independent copies of the unit cell. The average simulation structure agrees with experiment to within 0.28 Å backbone and 0.42 Å all-atom rmsd; a model refined against the average simulation density agrees with the experimental structure to within 0.20 Å backbone and 0.33 Å all-atom rmsd. The R-factor between the experimental structure factors and those derived from this unrestrained simulation is 23% to 1.0 Å resolution. The B-factors for most heavy atoms agree well with experiment (Pearson correlation of 0.90), but B-factors obtained by refinement against the average simulation density underestimate the coordinate fluctuations in the underlying simulation where the simulation samples alternate conformations. A dynamic flow of water molecules through channels within the crystal lattice is observed, yet the average water density is in remarkable agreement with experiment. A minor population of unit cells is characterized by reduced water content, 310 helical propensity and a gauche(−) side-chain rotamer for one of the valine residues. Careful examination of the experimental data suggests that transitions of the helices are a simulation artifact, although there is indeed evidence for alternate valine conformers and variable water content. This study highlights the potential for crystal simulations to detect dynamics and heterogeneity in experimental diffraction data, as well as to validate computational chemistry methods. PMID:23631449

Sequence selection by dynamical symmetry breaking in an autocatalytic binary polymer model

NASA Astrophysics Data System (ADS)

Fellermann, Harold; Tanaka, Shinpei; Rasmussen, Steen

2017-12-01

Template-directed replication of nucleic acids is at the essence of all living beings and a major milestone for any origin of life scenario. We present an idealized model of prebiotic sequence replication, where binary polymers act as templates for their autocatalytic replication, thereby serving as each others reactants and products in an intertwined molecular ecology. Our model demonstrates how autocatalysis alters the qualitative and quantitative system dynamics in counterintuitive ways. Most notably, numerical simulations reveal a very strong intrinsic selection mechanism that favors the appearance of a few population structures with highly ordered and repetitive sequence patterns when starting from a pool of monomers. We demonstrate both analytically and through simulation how this "selection of the dullest" is caused by continued symmetry breaking through random fluctuations in the transient dynamics that are amplified by autocatalysis and eventually propagate to the population level. The impact of these observations on related prebiotic mathematical models is discussed.

Simulating anchovy's full life cycle in the northern Aegean Sea (eastern Mediterranean): A coupled hydro-biogeochemical-IBM model

NASA Astrophysics Data System (ADS)

Politikos, D.; Somarakis, S.; Tsiaras, K. P.; Giannoulaki, M.; Petihakis, G.; Machias, A.; Triantafyllou, G.

2015-11-01

A 3-D full life cycle population model for the North Aegean Sea (NAS) anchovy stock is presented. The model is two-way coupled with a hydrodynamic-biogeochemical model (POM-ERSEM). The anchovy life span is divided into seven life stages/age classes. Embryos and early larvae are passive particles, but subsequent stages exhibit active horizontal movements based on specific rules. A bioenergetics model simulates the growth in both the larval and juvenile/adult stages, while the microzooplankton and mesozooplankton fields of the biogeochemical model provide the food for fish consumption. The super-individual approach is adopted for the representation of the anchovy population. A dynamic egg production module, with an energy allocation algorithm, is embedded in the bioenergetics equation and produces eggs based on a new conceptual model for anchovy vitellogenesis. A model simulation for the period 2003-2006 with realistic initial conditions reproduced well the magnitude of population biomass and daily egg production estimated from acoustic and daily egg production method (DEPM) surveys, carried out in the NAS during June 2003-2006. Model simulated adult and egg habitats were also in good agreement with observed spatial distributions of acoustic biomass and egg abundance in June. Sensitivity simulations were performed to investigate the effect of different formulations adopted for key processes, such as reproduction and movement. The effect of the anchovy population on plankton dynamics was also investigated, by comparing simulations adopting a two-way or a one-way coupling of the fish with the biogeochemical model.

Early dynamical evolution of young substructured clusters

NASA Astrophysics Data System (ADS)

Dorval, Julien; Boily, Christian

2017-03-01

Stellar clusters form with a high level of substructure, inherited from the molecular cloud and the star formation process. Evidence from observations and simulations also indicate the stars in such young clusters form a subvirial system. The subsequent dynamical evolution can cause important mass loss, ejecting a large part of the birth population in the field. It can also imprint the stellar population and still be inferred from observations of evolved clusters. Nbody simulations allow a better understanding of these early twists and turns, given realistic initial conditions. Nowadays, substructured, clumpy young clusters are usually obtained through pseudo-fractal growth and velocity inheritance. We introduce a new way to create clumpy initial conditions through a ''Hubble expansion'' which naturally produces self consistent clumps, velocity-wise. In depth analysis of the resulting clumps shows consistency with hydrodynamical simulations of young star clusters. We use these initial conditions to investigate the dynamical evolution of young subvirial clusters. We find the collapse to be soft, with hierarchical merging leading to a high level of mass segregation. The subsequent evolution is less pronounced than the equilibrium achieved from a cold collapse formation scenario.

Effects of dynamical grouping on cooperation in N-person evolutionary snowdrift game

NASA Astrophysics Data System (ADS)

Ji, M.; Xu, C.; Hui, P. M.

2011-09-01

A population typically consists of agents that continually distribute themselves into different groups at different times. This dynamic grouping has recently been shown to be essential in explaining many features observed in human activities including social, economic, and military activities. We study the effects of dynamic grouping on the level of cooperation in a modified evolutionary N-person snowdrift game. Due to the formation of dynamical groups, the competition takes place in groups of different sizes at different times and players of different strategies are mixed by the grouping dynamics. It is found that the level of cooperation is greatly enhanced by the dynamic grouping of agents, when compared with a static population of the same size. As a parameter β, which characterizes the relative importance of the reward and cost, increases, the fraction of cooperative players fC increases and it is possible to achieve a fully cooperative state. Analytically, we present a dynamical equation that incorporates the effects of the competing game and group size distribution. The distribution of cooperators in different groups is assumed to be a binomial distribution, which is confirmed by simulations. Results from the analytic equation are in good agreement with numerical results from simulations. We also present detailed simulation results of fC over the parameter space spanned by the probabilities of group coalescence νm and group fragmentation νp in the grouping dynamics. A high νm and low νp promotes cooperation, and a favorable reward characterized by a high β would lead to a fully cooperative state.

Swarming Patterns in a Two-Dimensional Kinematic Model for Biological Groups

NASA Astrophysics Data System (ADS)

Topaz, Chad

2004-03-01

We construct a continuum model for the motion of biological organisms experiencing social interactions and study its pattern-forming behavior. The model takes the form of a conservation law in two spatial dimensions. Social interactions are modeled in the velocity term, which is nonlocal in the population density. The dynamics of the model may be uniquely decomposed into incompressible motion and potential motion. For the purely incompressible case, the model resembles that for fluid dynamical vortex patches. There exist solutions that have constant population density and compact support for all time. Numerical simulations produce rotating structures with circular cores and spiral arms, reminiscent of naturally observed swarms such as ant mills. For the purely potential case, the model resembles a nonlocal (forwards or backwards) porous media equation, describing aggregation or dispersion of the population. For the aggregative case, the population clumps into regions of high and low density with a predictable characteristic length scale that is confirmed by numerical simulations.

The effect of area size and predation on the time to extinction of prairie vole populations. simulation studies via SERDYCA: a Spatially-Explicit Individual-Based Model of Rodent Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostova, T; Carlsen, T

2003-11-21

We present a spatially-explicit individual-based computational model of rodent dynamics, customized for the prairie vole species, M. Ochrogaster. The model is based on trophic relationships and represents important features such as territorial competition, mating behavior, density-dependent predation and dispersal out of the modeled spatial region. Vegetation growth and vole fecundity are dependent on climatic components. The results of simulations show that the model correctly predicts the overall temporal dynamics of the population density. Time-series analysis shows a very good match between the periods corresponding to the peak population density frequencies predicted by the model and the ones reported in themore » literature. The model is used to study the relation between persistence, landscape area and predation. We introduce the notions of average time to extinction (ATE) and persistence frequency to quantify persistence. While the ATE decreases with decrease of area, it is a bell-shaped function of the predation level: increasing for 'small' and decreasing for 'large' predation levels.« less

NMR Spectroscopy and Molecular Dynamics Simulation of r(CCGCUGCGG)2 Reveal a Dynamic UU Internal Loop Found in Myotonic Dystrophy Type 1†

PubMed Central

Parkesh, Raman; Fountain, Matthew; Disney, Matthew D.

2011-01-01

The NMR structure of an RNA with a copy of the 5′CUG/3′GUC motif found in the triplet repeating disorder myotonic dystrophy type 1 (DM1) is disclosed. The lowest energy conformation of the UU pair is a single hydrogen bonded structure; however, the UU protons undergo exchange indicating structural dynamics. Molecular dynamics simulations show that the single hydrogen bonded structure is the most populated one but the UU pair interconverts between 0, 1, and 2 hydrogen bonded pairs. These studies have implications for the recognition of the DM1 RNA by small molecules and proteins. PMID:21204525

Population dynamics in the presence of quasispecies effects and changing environments

NASA Astrophysics Data System (ADS)

Forster, Robert Burke

2006-12-01

This thesis explores how natural selection acts on organisms such as viruses that have either highly error-prone reproduction or face variable environmental conditions or both. By modeling population dynamics under these conditions, we gain a better understanding of the selective forces at work, both in our simulations and hopefully also in real organisms. With an understanding of the important factors in natural selection we can forecast not only the immediate fate of an existing population but also in what directions such a population might evolve in the future. We demonstrate that the concept of a quasispecies is relevant to evolution in a neutral fitness landscape. Motivated by RNA viruses such as HIV, we use RNA secondary structure as our model system and find that quasispecies effects arise both rapidly and in realistically small populations. We discover that the evolutionary effects of neutral drift, punctuated equilibrium and the selection for mutational robustness extend to the concept of a quasispecies. In our study of periodic environments, we consider the tradeoffs faced by quasispecies in adapting to environmental change. We develop an analytical model to predict whether evolution favors short-term or long-term adaptation and validate our model through simulation. Our results bear directly on the population dynamics of viruses such as West Nile that alternate between two host species. More generally, we discover that a selective pressure exists under these conditions to fuse or split genes with complementary environmental functions. Lastly, we study the general effects of frequency-dependent selection on two strains competing in a periodic environment. Under very general assumptions, we prove that stable coexistence rather than extinction is the likely outcome. The population dynamics of this system may be as simple as stable equilibrium or as complex as deterministic chaos.

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

PubMed

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

2008-11-07

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

Quantitative sampling of conformational heterogeneity of a DNA hairpin using molecular dynamics simulations and ultrafast fluorescence spectroscopy.

PubMed

Voltz, Karine; Léonard, Jérémie; Touceda, Patricia Tourón; Conyard, Jamie; Chaker, Ziyad; Dejaegere, Annick; Godet, Julien; Mély, Yves; Haacke, Stefan; Stote, Roland H

2016-04-20

Molecular dynamics (MD) simulations and time resolved fluorescence (TRF) spectroscopy were combined to quantitatively describe the conformational landscape of the DNA primary binding sequence (PBS) of the HIV-1 genome, a short hairpin targeted by retroviral nucleocapsid proteins implicated in the viral reverse transcription. Three 2-aminopurine (2AP) labeled PBS constructs were studied. For each variant, the complete distribution of fluorescence lifetimes covering 5 orders of magnitude in timescale was measured and the populations of conformers experimentally observed to undergo static quenching were quantified. A binary quantification permitted the comparison of populations from experimental lifetime amplitudes to populations of aromatically stacked 2AP conformers obtained from simulation. Both populations agreed well, supporting the general assumption that quenching of 2AP fluorescence results from pi-stacking interactions with neighboring nucleobases and demonstrating the success of the proposed methodology for the combined analysis of TRF and MD data. Cluster analysis of the latter further identified predominant conformations that were consistent with the fluorescence decay times and amplitudes, providing a structure-based rationalization for the wide range of fluorescence lifetimes. Finally, the simulations provided evidence of local structural perturbations induced by 2AP. The approach presented is a general tool to investigate fine structural heterogeneity in nucleic acid and nucleoprotein assemblies. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Metamodels for Transdisciplinary Analysis of Wildlife Population Dynamics

PubMed Central

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

2013-01-01

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

A Dynamic Bayesian Network model for long-term simulation of clinical complications in type 1 diabetes.

PubMed

Marini, Simone; Trifoglio, Emanuele; Barbarini, Nicola; Sambo, Francesco; Di Camillo, Barbara; Malovini, Alberto; Manfrini, Marco; Cobelli, Claudio; Bellazzi, Riccardo

2015-10-01

The increasing prevalence of diabetes and its related complications is raising the need for effective methods to predict patient evolution and for stratifying cohorts in terms of risk of developing diabetes-related complications. In this paper, we present a novel approach to the simulation of a type 1 diabetes population, based on Dynamic Bayesian Networks, which combines literature knowledge with data mining of a rich longitudinal cohort of type 1 diabetes patients, the DCCT/EDIC study. In particular, in our approach we simulate the patient health state and complications through discretized variables. Two types of models are presented, one entirely learned from the data and the other partially driven by literature derived knowledge. The whole cohort is simulated for fifteen years, and the simulation error (i.e. for each variable, the percentage of patients predicted in the wrong state) is calculated every year on independent test data. For each variable, the population predicted in the wrong state is below 10% on both models over time. Furthermore, the distributions of real vs. simulated patients greatly overlap. Thus, the proposed models are viable tools to support decision making in type 1 diabetes. Copyright © 2015 Elsevier Inc. All rights reserved.

Sobol' sensitivity analysis for stressor impacts on honeybee ...

EPA Pesticide Factsheets

We employ Monte Carlo simulation and nonlinear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed of hive population trajectories, taking into account queen strength, foraging success, mite impacts, weather, colony resources, population structure, and other important variables. This allows us to test the effects of defined pesticide exposure scenarios versus controlled simulations that lack pesticide exposure. The daily resolution of the model also allows us to conditionally identify sensitivity metrics. We use the variancebased global decomposition sensitivity analysis method, Sobol’, to assess firstand secondorder parameter sensitivities within VarroaPop, allowing us to determine how variance in the output is attributed to each of the input variables across different exposure scenarios. Simulations with VarroaPop indicate queen strength, forager life span and pesticide toxicity parameters are consistent, critical inputs for colony dynamics. Further analysis also reveals that the relative importance of these parameters fluctuates throughout the simulation period according to the status of other inputs. Our preliminary results show that model variability is conditional and can be attributed to different parameters depending on different timescales. By using sensitivity analysis to assess model output and variability, calibrations of simulation models can be better informed to yield more

Synchronization and survival of connected bacterial populations

NASA Astrophysics Data System (ADS)

Gokhale, Shreyas; Conwill, Arolyn; Ranjan, Tanvi; Gore, Jeff

Migration plays a vital role in controlling population dynamics of species occupying distinct habitat patches. While local populations are vulnerable to extinction due to demographic or environmental stochasticity, migration from neighboring habitat patches can rescue these populations through colonization of uninhabited regions. However, a large migratory flux can synchronize the population dynamics in connected patches, thereby enhancing the risk of global extinction during periods of depression in population size. Here, we investigate this trade-off between local rescue and global extinction experimentally using laboratory populations of E. coli bacteria. Our model system consists of co-cultures of ampicillin resistant and chloramphenicol resistant strains that form a cross-protection mutualism and exhibit period-3 oscillations in the relative population density in the presence of both antibiotics. We quantify the onset of synchronization of oscillations in a pair of co-cultures connected by migration and demonstrate that period-3 oscillations can be disturbed for moderate rates of migration. These features are consistent with simulations of a mechanistic model of antibiotic deactivation in our system. The simulations further predict that the probability of survival of connected populations in high concentrations of antibiotics is maximized at intermediate migration rates. We verify this prediction experimentally and show that survival is enhanced through a combination of disturbance of period-3 oscillations and stochastic re-colonization events.

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

PubMed Central

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

2012-01-01

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

AN INDIVIDUAL-BASED SIMULATION MODEL FOR MOTTLED SCULPIN (COTTUS BAIRDI) IN A SOUTHERN APPALACHIAN STREAM

EPA Science Inventory

We describe and analyze a spatially explicit, individual-based model for the local population dynamics of mottled sculpin (Cottus bairdi). The model simulated daily growth, mortality, movement and spawning of individuals within a reach of stream. Juvenile and adult growth was bas...

Lectures and Simulation Laboratories to Improve Learners' Conceptual Understanding

ERIC Educational Resources Information Center

Brophy, Sean P.; Magana, Alejandra J.; Strachan, Alejandro

2013-01-01

We studied the use of online molecular dynamics simulations (MD) to enhance student abilities to understand the atomic processes governing plastic deformation in materials. The target population included a second-year undergraduate engineering course in the School of Materials Engineering at Purdue University. The objectives of the study were to…

Microbial Community Dynamics of a Simulated Chloraminated Drinking Water Distribution System Subjected to Episodes of Nitrification

EPA Science Inventory

Bacterial populations were examined in a simulated chloraminated drinking water distribution system (i.e. loop). The loop (BW-AB-I) received chlorinated municipal water (BW-C) amended with ammonia (2mg/L monochloramine). After six years of continuous operation, the operational ...

Simulation of MAD Cow Disease Propagation

NASA Astrophysics Data System (ADS)

Magdoń-Maksymowicz, M. S.; Maksymowicz, A. Z.; Gołdasz, J.

Computer simulation of dynamic of BSE disease is presented. Both vertical (to baby) and horizontal (to neighbor) mechanisms of the disease spread are considered. The game takes place on a two-dimensional square lattice Nx×Ny = 1000×1000 with initial population randomly distributed on the net. The disease may be introduced either with the initial population or by a spontaneous development of BSE in an item, at a small frequency. Main results show a critical probability of the BSE transmission above which the disease is present in the population. This value is vulnerable to possible spatial clustering of the population and it also depends on the mechanism responsible for the disease onset, evolution and propagation. A threshold birth rate below which the population is extinct is seen. Above this threshold the population is disease free at equilibrium until another birth rate value is reached when the disease is present in population. For typical model parameters used for the simulation, which may correspond to the mad cow disease, we are close to the BSE-free case.

Slow and fast dynamics model of a Malaria with Sickle-Cell genetic disease with multi-stage infections of the mosquitoes population

NASA Astrophysics Data System (ADS)

Dewi Siawanta, Shanti; Adi-Kusumo, Fajar; Irwan Endrayanto, Aluicius

2018-03-01

Malaria, which is caused by Plasmodium, is a common disease in tropical areas. There are three types of Plasmodium i.e. Plasmodium Vivax, Plasmodium Malariae, and Plasmodium Falciparum. The most dangerous cases of the Malaria are mainly caused by the Plasmodium Falciparum. One of the important characteristics for the Plasmodium infection is due to the immunity of erythrocyte that contains HbS (Haemoglobin Sickle-cell) genes. The individuals who has the HbS gene has better immunity against the disease. In this paper, we consider a model that shows the spread of malaria involving the interaction between the mosquitos population, the human who has HbS genes population and the human with normal gene population. We do some analytical and numerical simulation to study the basic reproduction ratio and the slow-fast dynamics of the phase-portrait. The slow dynamics in our model represents the response of the human population with HbS gene to the Malaria disease while the fast dynamics show the response of the human population with the normal gene to the disease. The slow and fast dynamics phenomena are due to the fact that the population of the individuals who have HbS gene is much smaller than the individuals who has normal genes.

Elevated nonlinearity as an indicator of shifts in the dynamics of populations under stress.

PubMed

Dakos, Vasilis; Glaser, Sarah M; Hsieh, Chih-Hao; Sugihara, George

2017-03-01

Populations occasionally experience abrupt changes, such as local extinctions, strong declines in abundance or transitions from stable dynamics to strongly irregular fluctuations. Although most of these changes have important ecological and at times economic implications, they remain notoriously difficult to detect in advance. Here, we study changes in the stability of populations under stress across a variety of transitions. Using a Ricker-type model, we simulate shifts from stable point equilibrium dynamics to cyclic and irregular boom-bust oscillations as well as abrupt shifts between alternative attractors. Our aim is to infer the loss of population stability before such shifts based on changes in nonlinearity of population dynamics. We measure nonlinearity by comparing forecast performance between linear and nonlinear models fitted on reconstructed attractors directly from observed time series. We compare nonlinearity to other suggested leading indicators of instability (variance and autocorrelation). We find that nonlinearity and variance increase in a similar way prior to the shifts. By contrast, autocorrelation is strongly affected by oscillations. Finally, we test these theoretical patterns in datasets of fisheries populations. Our results suggest that elevated nonlinearity could be used as an additional indicator to infer changes in the dynamics of populations under stress. © 2017 The Author(s).

Vibrational population relaxation of carbon monoxide in the heme pocket of photolyzed carbonmonoxy myoglobin: Comparison of time-resolved mid-IR absorbance experiments and molecular dynamics simulations

PubMed Central

Sagnella, Diane E.; Straub, John E.; Jackson, Timothy A.; Lim, Manho; Anfinrud, Philip A.

1999-01-01

The vibrational energy relaxation of carbon monoxide in the heme pocket of sperm whale myoglobin was studied by using molecular dynamics simulation and normal mode analysis methods. Molecular dynamics trajectories of solvated myoglobin were run at 300 K for both the δ- and ɛ-tautomers of the distal His-64. Vibrational population relaxation times of 335 ± 115 ps for the δ-tautomer and 640 ± 185 ps for the ɛ-tautomer were estimated by using the Landau–Teller model. Normal mode analysis was used to identify those protein residues that act as the primary “doorway” modes in the vibrational relaxation of the oscillator. Although the CO relaxation rates in both the ɛ- and δ-tautomers are similar in magnitude, the simulations predict that the vibrational relaxation of the CO is faster in the δ-tautomer with the distal His playing an important role in the energy relaxation mechanism. Time-resolved mid-IR absorbance measurements were performed on photolyzed carbonmonoxy hemoglobin (Hb13CO). From these measurements, a T1 time of 600 ± 150 ps was determined. The simulation and experimental estimates are compared and discussed. PMID:10588704

Clinical study and numerical simulation of brain cancer dynamics under radiotherapy

NASA Astrophysics Data System (ADS)

Nawrocki, S.; Zubik-Kowal, B.

2015-05-01

We perform a clinical and numerical study of the progression of brain cancer tumor growth dynamics coupled with the effects of radiotherapy. We obtained clinical data from a sample of brain cancer patients undergoing radiotherapy and compare it to our numerical simulations to a mathematical model of brain tumor cell population growth influenced by radiation treatment. We model how the body biologically receives a physically delivered dose of radiation to the affected tumorous area in the form of a generalized LQ model, modified to account for the conversion process of sublethal lesions into lethal lesions at high radiation doses. We obtain good agreement between our clinical data and our numerical simulations of brain cancer progression given by the mathematical model, which couples tumor growth dynamics and the effect of irradiation. The correlation, spanning a wide dataset, demonstrates the potential of the mathematical model to describe the dynamics of brain tumor growth influenced by radiotherapy.

Counter-diabatic driving for Dirac dynamics

NASA Astrophysics Data System (ADS)

Fan, Qi-Zhen; Cheng, Xiao-Hang; Chen, Xi

2018-03-01

In this paper, we investigate the fast quantum control of Dirac equation dynamics by counter-diabatic driving, sharing the concept of shortcut to adiabaticity. We systematically calculate the counter-diabatic terms in different Dirac systems, like graphene and trapped ions. Specially, the fast and robust population inversion processes are achieved in Dirac system, taking into account the quantum simulation with trapped ions. In addition, the population transfer between two bands can be suppressed by counter-diabatic driving in graphene system, which might have potential applications in opt-electric devices.

A Simulation Environment for the Dynamic Evaluation of Disaster Preparedness Policies and Interventions

PubMed Central

Lewis, Bryan; Swarup, Samarth; Bisset, Keith; Eubank, Stephen; Marathe, Madhav; Barrett, Chris

2013-01-01

Disasters affect a society at many levels. Simulation based studies often evaluate the effectiveness of one or two response policies in isolation and are unable to represent impact of the policies to coevolve with others. Similarly, most in-depth analyses are based on a static assessment of the “aftermath” rather than capturing dynamics. We have developed a data-centric simulation environment for applying a systems approach to a dynamic analysis of complex combinations of disaster responses. We analyze an improvised nuclear detonation in Washington DC with this environment. The simulated blast affects the transportation system, communications infrastructure, electrical power system, behaviors and motivations of population, and health status of survivors. The effectiveness of partially restoring wireless communications capacity is analyzed in concert with a range of other disaster response policies. Despite providing a limited increase in cell phone communication, overall health was improved. PMID:23903394

New insights into the nonadiabatic state population dynamics of model proton-coupled electron transfer reactions from the mixed quantum-classical Liouville approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shakib, Farnaz A.; Hanna, Gabriel, E-mail: gabriel.hanna@ualberta.ca

In a previous study [F. A. Shakib and G. Hanna, J. Chem. Phys. 141, 044122 (2014)], we investigated a model proton-coupled electron transfer (PCET) reaction via the mixed quantum-classical Liouville (MQCL) approach and found that the trajectories spend the majority of their time on the mean of two coherently coupled adiabatic potential energy surfaces. This suggested a need for mean surface evolution to accurately simulate observables related to ultrafast PCET processes. In this study, we simulate the time-dependent populations of the three lowest adiabatic states in the ET-PT (i.e., electron transfer preceding proton transfer) version of the same PCET modelmore » via the MQCL approach and compare them to the exact quantum results and those obtained via the fewest switches surface hopping (FSSH) approach. We find that the MQCL population profiles are in good agreement with the exact quantum results and show a significant improvement over the FSSH results. All of the mean surfaces are shown to play a direct role in the dynamics of the state populations. Interestingly, our results indicate that the population transfer to the second-excited state can be mediated by dynamics on the mean of the ground and second-excited state surfaces, as part of a sequence of nonadiabatic transitions that bypasses the first-excited state surface altogether. This is made possible through nonadiabatic transitions between different mean surfaces, which is the manifestation of coherence transfer in MQCL dynamics. We also investigate the effect of the strength of the coupling between the proton/electron and the solvent coordinate on the state population dynamics. Drastic changes in the population dynamics are observed, which can be understood in terms of the changes in the potential energy surfaces and the nonadiabatic couplings. Finally, we investigate the state population dynamics in the PT-ET (i.e., proton transfer preceding electron transfer) and concerted versions of the model. The PT-ET results confirm the participation of all of the mean surfaces, albeit in different proportions compared to the ET-PT case, while the concerted results indicate that the mean of the ground- and first-excited state surfaces only plays a role, due to the large energy gaps between the ground- and second-excited state surfaces.« less

Dynamics of water bound to crystalline cellulose

DOE Office of Scientific and Technical Information (OSTI.GOV)

O’Neill, Hugh; Pingali, Sai Venkatesh; Petridis, Loukas

Interactions of water with cellulose are of both fundamental and technological importance. Here, we characterize the properties of water associated with cellulose using deuterium labeling, neutron scattering and molecular dynamics simulation. Quasi-elastic neutron scattering provided quantitative details about the dynamical relaxation processes that occur and was supported by structural characterization using small-angle neutron scattering and X-ray diffraction. We can unambiguously detect two populations of water associated with cellulose. The first is “non-freezing bound” water that gradually becomes mobile with increasing temperature and can be related to surface water. The second population is consistent with confined water that abruptly becomes mobilemore » at ~260 K, and can be attributed to water that accumulates in the narrow spaces between the microfibrils. Quantitative analysis of the QENS data showed that, at 250 K, the water diffusion coefficient was 0.85 ± 0.04 × 10-10 m2sec-1 and increased to 1.77 ± 0.09 × 10-10 m2sec-1 at 265 K. MD simulations are in excellent agreement with the experiments and support the interpretation that water associated with cellulose exists in two dynamical populations. Our results provide clarity to previous work investigating the states of bound water and provide a new approach for probing water interactions with lignocellulose materials.« less

On the use of satellite-based estimates of rainfall temporal distribution to simulate the potential for malaria transmission in rural Africa

NASA Astrophysics Data System (ADS)

Yamana, Teresa K.; Eltahir, Elfatih A. B.

2011-02-01

This paper describes the use of satellite-based estimates of rainfall to force the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS), a hydrology-based mechanistic model of malaria transmission. We first examined the temporal resolution of rainfall input required by HYDREMATS. Simulations conducted over Banizoumbou village in Niger showed that for reasonably accurate simulation of mosquito populations, the model requires rainfall data with at least 1 h resolution. We then investigated whether HYDREMATS could be effectively forced by satellite-based estimates of rainfall instead of ground-based observations. The Climate Prediction Center morphing technique (CMORPH) precipitation estimates distributed by the National Oceanic and Atmospheric Administration are available at a 30 min temporal resolution and 8 km spatial resolution. We compared mosquito populations simulated by HYDREMATS when the model is forced by adjusted CMORPH estimates and by ground observations. The results demonstrate that adjusted rainfall estimates from satellites can be used with a mechanistic model to accurately simulate the dynamics of mosquito populations.

Using a full annual cycle model to evaluate long-term population viability of the conservation-reliant Kirtland's warbler after successful recovery

USGS Publications Warehouse

Brown, Donald J.; Ribic, Christine; Donner, Deahn M.; Nelson, Mark D.; Bocetti, Carol I.; Deloria-Sheffield, Christie M.

2017-01-01

Long-term management planning for conservation-reliant migratory songbirds is particularly challenging because habitat quality in different stages and geographic locations of the annual cycle can have direct and carry-over effects that influence the population dynamics. The Neotropical migratory songbird Kirtland's warbler Setophaga kirtlandii (Baird 1852) is listed as endangered under the U.S. Endangered Species Act and Near Threatened under the IUCN Red List. This conservation-reliant species is being considered for U.S. federal delisting because the species has surpassed the designated 1000 breeding pairs recovery threshold since 2001.To help inform the delisting decision and long-term management efforts, we developed a population simulation model for the Kirtland's warbler that incorporated both breeding and wintering grounds habitat dynamics, and projected population viability based on current environmental conditions and potential future management scenarios. Future management scenarios included the continuation of current management conditions, reduced productivity and carrying capacity due to the changes in habitat suitability from the creation of experimental jack pine Pinus banksiana (Lamb.) plantations, and reduced productivity from alteration of the brown-headed cowbird Molothrus ater (Boddaert 1783) removal programme.Linking wintering grounds precipitation to productivity improved the accuracy of the model for replicating past observed population dynamics. Our future simulations indicate that the Kirtland's warbler population is stable under two potential future management scenarios: (i) continuation of current management practices and (ii) spatially restricting cowbird removal to the core breeding area, assuming that cowbirds reduce productivity in the remaining patches by ≤41%. The additional future management scenarios we assessed resulted in population declines.Synthesis and applications. Our study indicates that the Kirtland's warbler population is stable under current management conditions and that the jack pine plantation and cowbird removal programmes continue to be necessary for the long-term persistence of the species. This study represents one of the first attempts to incorporate full annual cycle dynamics into a population viability analysis for a migratory bird, and our results indicate that incorporating wintering grounds dynamics improved the model performance.

Documentation and user guides for SPBLOB: a computer simulation model of the join population dynamics for loblolly pine and the southern pine beetle

Treesearch

John Bishir; James Roberds; Brian Strom; Xiaohai Wan

2009-01-01

SPLOB is a computer simulation model for the interaction between loblolly pine (Pinus taeda L.), the economically most important forest crop in the United States, and the southern pine beetle (SPB: Dendroctonus frontalis Zimm.), the major insect pest for this species. The model simulates loblolly pine stands from time of planting...

A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology.

PubMed

Tompkins, Adrian M; Ermert, Volker

2013-02-18

The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions.

A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology

PubMed Central

2013-01-01

Background The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. Methods A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Results Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. Conclusions A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions. PMID:23419192

Disease-emergence dynamics and control in a socially-structured wildlife species

NASA Astrophysics Data System (ADS)

Pepin, Kim M.; Vercauteren, Kurt C.

2016-04-01

Once a pathogen is introduced in a population, key factors governing rate of spread include contact structure, supply of susceptible individuals and pathogen life-history. We examined the interplay of these factors on emergence dynamics and efficacy of disease prevention and response. We contrasted transmission dynamics of livestock viruses with different life-histories in hypothetical populations of feral swine with different contact structures (homogenous, metapopulation, spatial and network). Persistence probability was near 0 for the FMDV-like case under a wide range of parameter values and contact structures, while persistence was probable for the CSFV-like case. There were no sets of conditions where the FMDV-like pathogen persisted in every stochastic simulation. Even when population growth rates were up to 300% annually, the FMDV-like pathogen persisted in <25% of simulations regardless of transmission probabilities and contact structure. For networks and spatial contact structure, persistence probability of the FMDV-like pathogen was always <10%. Because of its low persistence probability, even very early response to the FMDV-like pathogen in feral swine was unwarranted while response to the CSFV-like pathogen was generally effective. When pre-emergence culling of feral swine caused population declines, it was effective at decreasing outbreak size of both diseases by ≥80%.

Accounting for system dynamics in reserve design.

PubMed

Leroux, Shawn J; Schmiegelow, Fiona K A; Cumming, Steve G; Lessard, Robert B; Nagy, John

2007-10-01

Systematic conservation plans have only recently considered the dynamic nature of ecosystems. Methods have been developed to incorporate climate change, population dynamics, and uncertainty in reserve design, but few studies have examined how to account for natural disturbance. Considering natural disturbance in reserve design may be especially important for the world's remaining intact areas, which still experience active natural disturbance regimes. We developed a spatially explicit, dynamic simulation model, CONSERV, which simulates patch dynamics and fire, and used it to evaluate the efficacy of hypothetical reserve networks in northern Canada. We designed six networks based on conventional reserve design methods, with different conservation targets for woodland caribou habitat, high-quality wetlands, vegetation, water bodies, and relative connectedness. We input the six reserve networks into CONSERV and tracked the ability of each to maintain initial conservation targets through time under an active natural disturbance regime. None of the reserve networks maintained all initial targets, and some over-represented certain features, suggesting that both effectiveness and efficiency of reserve design could be improved through use of spatially explicit dynamic simulation during the planning process. Spatial simulation models of landscape dynamics are commonly used in natural resource management, but we provide the first illustration of their potential use for reserve design. Spatial simulation models could be used iteratively to evaluate competing reserve designs and select targets that have a higher likelihood of being maintained through time. Such models could be combined with dynamic planning techniques to develop a general theory for reserve design in an uncertain world.

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

The western spruce budworm model: structure and content.

Treesearch

K.A. Sheehan; W.P. Kemp; J.J. Colbert; N.L. Crookston

1989-01-01

The Budworm Model predicts the amounts of foliage destroyed annually by the western spruce budworm, Choristoneura occidentalis Freeman, in a forest stand. The model may be used independently, or it may be linked to the Stand Prognosis Model to simulate the dynamics of forest stands. Many processes that affect budworm population dynamics are...

Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

PubMed

Heinonen, Johannes P M; Palmer, Stephen C F; Redpath, Steve M; Travis, Justin M J

2014-01-01

Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.

Modelling Hen Harrier Dynamics to Inform Human-Wildlife Conflict Resolution: A Spatially-Realistic, Individual-Based Approach

PubMed Central

Heinonen, Johannes P. M.; Palmer, Stephen C. F.; Redpath, Steve M.; Travis, Justin M. J.

2014-01-01

Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions. PMID:25405860

Anticipating the unintended consequences of security dynamics.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Backus, George A.; Overfelt, James Robert; Malczynski, Leonard A.

2010-01-01

In a globalized world, dramatic changes within any one nation causes ripple or even tsunamic effects within neighbor nations and nations geographically far removed. Multinational interventions to prevent or mitigate detrimental changes can easily cause secondary unintended consequences more detrimental and enduring than the feared change instigating the intervention. This LDRD research developed the foundations for a flexible geopolitical and socioeconomic simulation capability that focuses on the dynamic national security implications of natural and man-made trauma for a nation-state and the states linked to it through trade or treaty. The model developed contains a database for simulating all 229 recognizedmore » nation-states and sovereignties with the detail of 30 economic sectors including consumers and natural resources. The model explicitly simulates the interactions among the countries and their governments. Decisions among governments and populations is based on expectation formation. In the simulation model, failed expectations are used as a key metric for tension across states, among ethnic groups, and between population factions. This document provides the foundational documentation for the model.« less

Non-radiative relaxation dynamics of pyrrole following excitation in the range 249.5-200 nm

NASA Astrophysics Data System (ADS)

Kirkby, Oliver M.; Parkes, Michael A.; Neville, Simon P.; Worth, Graham A.; Fielding, Helen H.

2017-09-01

The non-radiative relaxation dynamics of pyrrole have been investigated using time-resolved photoelectron spectroscopy and quantum dynamics simulations. Following excitation of the A2 (11 πσ∗) state, we observe population flow out of the Franck-Condon region on a ≲ 50 fs timescale. Following excitation of the B2 (21 ππ∗) state, we observe population being transferred to the A2 (11 πσ∗) state on a <50 fs timescale and subsequently out of the Franck-Condon region, also on a <50 fs timescale. Quantum dynamics calculations suggest that population is transferred from the B2 (21 ππ∗) state through the A2 (1 π 3pz) state to the B1 (21 πσ∗) state before being transferred to the A2 (11 πσ∗) state.

Monte Carlo simulation for kinetic chemotaxis model: An application to the traveling population wave

NASA Astrophysics Data System (ADS)

Yasuda, Shugo

2017-02-01

A Monte Carlo simulation of chemotactic bacteria is developed on the basis of the kinetic model and is applied to a one-dimensional traveling population wave in a microchannel. In this simulation, the Monte Carlo method, which calculates the run-and-tumble motions of bacteria, is coupled with a finite volume method to calculate the macroscopic transport of the chemical cues in the environment. The simulation method can successfully reproduce the traveling population wave of bacteria that was observed experimentally and reveal the microscopic dynamics of bacterium coupled with the macroscopic transports of the chemical cues and bacteria population density. The results obtained by the Monte Carlo method are also compared with the asymptotic solution derived from the kinetic chemotaxis equation in the continuum limit, where the Knudsen number, which is defined by the ratio of the mean free path of bacterium to the characteristic length of the system, vanishes. The validity of the Monte Carlo method in the asymptotic behaviors for small Knudsen numbers is numerically verified.

Using spatiotemporal statistical models to estimate animal abundance and infer ecological dynamics from survey counts

USGS Publications Warehouse

Conn, Paul B.; Johnson, Devin S.; Ver Hoef, Jay M.; Hooten, Mevin B.; London, Joshua M.; Boveng, Peter L.

2015-01-01

Ecologists often fit models to survey data to estimate and explain variation in animal abundance. Such models typically require that animal density remains constant across the landscape where sampling is being conducted, a potentially problematic assumption for animals inhabiting dynamic landscapes or otherwise exhibiting considerable spatiotemporal variation in density. We review several concepts from the burgeoning literature on spatiotemporal statistical models, including the nature of the temporal structure (i.e., descriptive or dynamical) and strategies for dimension reduction to promote computational tractability. We also review several features as they specifically relate to abundance estimation, including boundary conditions, population closure, choice of link function, and extrapolation of predicted relationships to unsampled areas. We then compare a suite of novel and existing spatiotemporal hierarchical models for animal count data that permit animal density to vary over space and time, including formulations motivated by resource selection and allowing for closed populations. We gauge the relative performance (bias, precision, computational demands) of alternative spatiotemporal models when confronted with simulated and real data sets from dynamic animal populations. For the latter, we analyze spotted seal (Phoca largha) counts from an aerial survey of the Bering Sea where the quantity and quality of suitable habitat (sea ice) changed dramatically while surveys were being conducted. Simulation analyses suggested that multiple types of spatiotemporal models provide reasonable inference (low positive bias, high precision) about animal abundance, but have potential for overestimating precision. Analysis of spotted seal data indicated that several model formulations, including those based on a log-Gaussian Cox process, had a tendency to overestimate abundance. By contrast, a model that included a population closure assumption and a scale prior on total abundance produced estimates that largely conformed to our a priori expectation. Although care must be taken to tailor models to match the study population and survey data available, we argue that hierarchical spatiotemporal statistical models represent a powerful way forward for estimating abundance and explaining variation in the distribution of dynamical populations.

Population dynamics and the economics of invasive species management: the greenhouse whitefly in California-grown strawberries.

PubMed

McKee, Gregory J; Goodhue, Rachael E; Zalom, Frank G; Carter, Colin A; Chalfant, James A

2009-01-01

In agriculture, relatively few efficacious control measures may be available for an invasive pest. In the case of a new insect pest, insecticide use decisions are affected by regulations associated with its registration, insect population dynamics, and seasonal market price cycles. We assess the costs and benefits of environmental regulations designed to regulate insecticide applications on an invasive species. We construct a bioeconomic model, based on detailed scientific data, of management decisions for a specific invasion: greenhouse whiteflies in California-grown strawberries. The empirical model integrates whitefly population dynamics, the effect of whitefly feeding on strawberry yields, and weekly strawberry price. We use the model to assess the optimality of alternative treatment programs on a simulated greenhouse whitefly population. Our results show that regulations may lead growers to "under-spray" when placed in an economic context, and provide some general lessons about the design of optimal invasive species control policies.

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

PubMed

Orr, Mark G; Thrush, Roxanne; Plaut, David C

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

The Theory of Reasoned Action as Parallel Constraint Satisfaction: Towards a Dynamic Computational Model of Health Behavior

PubMed Central

Orr, Mark G.; Thrush, Roxanne; Plaut, David C.

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual’s pre-existing belief structure and the beliefs of others in the individual’s social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics. PMID:23671603

Intraspecific Competition and Population Dynamics of Aedes aegypti

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Simulating Heterogeneous Tumor Cell Populations

PubMed Central

Bar-Sagi, Dafna; Mishra, Bud

2016-01-01

Certain tumor phenomena, like metabolic heterogeneity and local stable regions of chronic hypoxia, signify a tumor’s resistance to therapy. Although recent research has shed light on the intracellular mechanisms of cancer metabolic reprogramming, little is known about how tumors become metabolically heterogeneous or chronically hypoxic, namely the initial conditions and spatiotemporal dynamics that drive these cell population conditions. To study these aspects, we developed a minimal, spatially-resolved simulation framework for modeling tissue-scale mixed populations of cells based on diffusible particles the cells consume and release, the concentrations of which determine their behavior in arbitrarily complex ways, and on stochastic reproduction. We simulate cell populations that self-sort to facilitate metabolic symbiosis, that grow according to tumor-stroma signaling patterns, and that give rise to stable local regions of chronic hypoxia near blood vessels. We raise two novel questions in the context of these results: (1) How will two metabolically symbiotic cell subpopulations self-sort in the presence of glucose, oxygen, and lactate gradients? We observe a robust pattern of alternating striations. (2) What is the proper time scale to observe stable local regions of chronic hypoxia? We observe the stability is a function of the balance of three factors related to O2—diffusion rate, local vessel release rate, and viable and hypoxic tumor cell consumption rate. We anticipate our simulation framework will help researchers design better experiments and generate novel hypotheses to better understand dynamic, emergent whole-tumor behavior. PMID:28030620

The effect of gas dynamics on semi-analytic modelling of cluster galaxies

NASA Astrophysics Data System (ADS)

Saro, A.; De Lucia, G.; Dolag, K.; Borgani, S.

2008-12-01

We study the degree to which non-radiative gas dynamics affect the merger histories of haloes along with subsequent predictions from a semi-analytic model (SAM) of galaxy formation. To this aim, we use a sample of dark matter only and non-radiative smooth particle hydrodynamics (SPH) simulations of four massive clusters. The presence of gas-dynamical processes (e.g. ram pressure from the hot intra-cluster atmosphere) makes haloes more fragile in the runs which include gas. This results in a 25 per cent decrease in the total number of subhaloes at z = 0. The impact on the galaxy population predicted by SAMs is complicated by the presence of `orphan' galaxies, i.e. galaxies whose parent substructures are reduced below the resolution limit of the simulation. In the model employed in our study, these galaxies survive (unaffected by the tidal stripping process) for a residual merging time that is computed using a variation of the Chandrasekhar formula. Due to ram-pressure stripping, haloes in gas simulations tend to be less massive than their counterparts in the dark matter simulations. The resulting merging times for satellite galaxies are then longer in these simulations. On the other hand, the presence of gas influences the orbits of haloes making them on average more circular and therefore reducing the estimated merging times with respect to the dark matter only simulation. This effect is particularly significant for the most massive satellites and is (at least in part) responsible for the fact that brightest cluster galaxies in runs with gas have stellar masses which are about 25 per cent larger than those obtained from dark matter only simulations. Our results show that gas dynamics has only a marginal impact on the statistical properties of the galaxy population, but that its impact on the orbits and merging times of haloes strongly influences the assembly of the most massive galaxies.

Linking Crystal Populations to Dynamic States: Crystal Dissolution and Growth During an Open-System Event

NASA Astrophysics Data System (ADS)

Bergantz, G. W.; Schleicher, J.; Burgisser, A.

2016-12-01

The identification of shared characteristics in zoned crystals has motivated the definition of crystal populations. These populations reflect the simultaneous transport of crystals, heat and composition during open-system events. An obstacle to interpreting the emergence of a population is the absence of a way to correlate specific dynamic conditions with the characteristic attributes of a population. By combining a boundary-layer diffusion controlled model for crystal growth/dissolution with discrete-element magma dynamics simulations of crystal-bearing magmas, the creation of populations can be simulated. We have implemented a method that decomposes the chemical potential into the thermal and compositional contributions to crystal dissolution/growth. This allows for the explicit treatment of thermal inertia and thermal-compositional decoupling as fluid circulation stirs the system during an open-system event. We have identified three distinct dynamic states producing crystal populations. They are based on the volume fraction of crystals. In a mushy system, thermal and compositional states are tightly linked as the volume involved in the mixing is constrained by the so-called mixing bowl (Bergantz et al., 2015). The mixing bowl volume is a function of the visco-plastic response of the mush and the intrusion width, not by the progressive entrainment of the new intrusion as commonly assumed. Crystal dissolution is the dominate response to input of more primitive magma. At the other endmember, under very dilute conditions, thermal and compositional conditions can become decoupled, and the in-coming magma forms a double-diffusive low-Re jet. This can allow for both dissolution and growth as crystals circulate widely into an increasingly stratified system. A middle range of crystal concentration produces a very complex feedback, as sedimenting crystals form fingers and chains that interact with the incoming magma, break-up the entrainment with chaotic stirring and add a second length scale to the mixing. It simultaneously forms a small mixing bowl in the pile of crystals sedimenting at the base. This can produce very complex populations even in a simple open-system event. Bergantz et al., 2015, Open-system dynamics and mixing in magma mushes, Nature Geosci., DOI: 10.1038/NGEO2534

Modelling population dynamics and response to management options in the poultry red mite Dermanyssus gallinae (Acari: Dermanyssidae).

PubMed

Huber, K; Zenner, L; Bicout, D J

2011-02-28

The poultry red mite Dermanyssus gallinae is a major pest and widespread ectoparasite of laying hens and other domestic and wild birds. Under optimal conditions, D. gallinae can complete its lifecycle in less than 10 days, leading to rapid proliferation of populations in poultry systems. This paper focuses on developing a theoretical model framework to describe the population dynamics of D. gallinae. This model is then used to test the efficacy and residual effect of different control options for managing D. gallinae. As well as allowing comparison between treatment options, the model also allows comparison of treatment efficacies to different D. gallinae life stages. Three different means for controlling D. gallinae populations were subjected to the model using computer simulations: mechanical cleaning (killing once at a given time all accessible population stages), sanitary clearance (starving the mite population for a given duration, e.g. between flocks) and acaricide treatment (killing a proportion of nymphs and adults during the persistence of the treatment). Simulations showed that mechanical cleaning and sanitary clearance alone could not eradicate the model D. gallinae population, although these methods did delay population establishment. In contrast, the complete eradication of the model D. gallinae population was achieved by several successive acaricide treatments in close succession, even when a relatively low treatment level was used. Copyright © 2010 Elsevier B.V. All rights reserved.

Thermodynamics of urban population flows.

PubMed

Hernando, A; Plastino, A

2012-12-01

Orderliness, reflected via mathematical laws, is encountered in different frameworks involving social groups. Here we show that a thermodynamics can be constructed that macroscopically describes urban population flows. Microscopic dynamic equations and simulations with random walkers underlie the macroscopic approach. Our results might be regarded, via suitable analogies, as a step towards building an explicit social thermodynamics.

Mainstreaming Modeling and Simulation to Accelerate Public Health Innovation

PubMed Central

Sepulveda, Martin-J.; Mabry, Patricia L.

2014-01-01

Dynamic modeling and simulation are systems science tools that examine behaviors and outcomes resulting from interactions among multiple system components over time. Although there are excellent examples of their application, they have not been adopted as mainstream tools in population health planning and policymaking. Impediments to their use include the legacy and ease of use of statistical approaches that produce estimates with confidence intervals, the difficulty of multidisciplinary collaboration for modeling and simulation, systems scientists’ inability to communicate effectively the added value of the tools, and low funding for population health systems science. Proposed remedies include aggregation of diverse data sets, systems science training for public health and other health professionals, changing research incentives toward collaboration, and increased funding for population health systems science projects. PMID:24832426

Simulated bat populations erode when exposed to climate change projections for western North America

PubMed Central

Adams, Rick A.

2017-01-01

Recent research has demonstrated that temperature and precipitation conditions correlate with successful reproduction in some insectivorous bat species that live in arid and semiarid regions, and that hot and dry conditions correlate with reduced lactation and reproductive output by females of some species. However, the potential long-term impacts of climate-induced reproductive declines on bat populations in western North America are not well understood. We combined results from long-term field monitoring and experiments in our study area with information on vital rates to develop stochastic age-structured population dynamics models and analyzed how simulated fringed myotis (Myotis thysanodes) populations changed under projected future climate conditions in our study area near Boulder, Colorado (Boulder Models) and throughout western North America (General Models). Each simulation consisted of an initial population of 2,000 females and an approximately stable age distribution at the beginning of the simulation. We allowed each population to be influenced by the mean annual temperature and annual precipitation for our study area and a generalized range-wide model projected through year 2086, for each of four carbon emission scenarios (representative concentration pathways RCP2.6, RCP4.5, RCP6.0, RCP8.5). Each population simulation was repeated 10,000 times. Of the 8 Boulder Model simulations, 1 increased (+29.10%), 3 stayed approximately stable (+2.45%, +0.05%, -0.03%), and 4 simulations decreased substantially (-44.10%, -44.70%, -44.95%, -78.85%). All General Model simulations for western North America decreased by >90% (-93.75%, -96.70%, -96.70%, -98.75%). These results suggest that a changing climate in western North America has the potential to quickly erode some forest bat populations including species of conservation concern, such as fringed myotis. PMID:28686737

Simulated bat populations erode when exposed to climate change projections for western North America.

PubMed

Hayes, Mark A; Adams, Rick A

2017-01-01

Recent research has demonstrated that temperature and precipitation conditions correlate with successful reproduction in some insectivorous bat species that live in arid and semiarid regions, and that hot and dry conditions correlate with reduced lactation and reproductive output by females of some species. However, the potential long-term impacts of climate-induced reproductive declines on bat populations in western North America are not well understood. We combined results from long-term field monitoring and experiments in our study area with information on vital rates to develop stochastic age-structured population dynamics models and analyzed how simulated fringed myotis (Myotis thysanodes) populations changed under projected future climate conditions in our study area near Boulder, Colorado (Boulder Models) and throughout western North America (General Models). Each simulation consisted of an initial population of 2,000 females and an approximately stable age distribution at the beginning of the simulation. We allowed each population to be influenced by the mean annual temperature and annual precipitation for our study area and a generalized range-wide model projected through year 2086, for each of four carbon emission scenarios (representative concentration pathways RCP2.6, RCP4.5, RCP6.0, RCP8.5). Each population simulation was repeated 10,000 times. Of the 8 Boulder Model simulations, 1 increased (+29.10%), 3 stayed approximately stable (+2.45%, +0.05%, -0.03%), and 4 simulations decreased substantially (-44.10%, -44.70%, -44.95%, -78.85%). All General Model simulations for western North America decreased by >90% (-93.75%, -96.70%, -96.70%, -98.75%). These results suggest that a changing climate in western North America has the potential to quickly erode some forest bat populations including species of conservation concern, such as fringed myotis.

Dissipative dynamics at conical intersections: simulations with the hierarchy equations of motion method.

PubMed

Chen, Lipeng; Gelin, Maxim F; Chernyak, Vladimir Y; Domcke, Wolfgang; Zhao, Yang

2016-12-16

The effect of a dissipative environment on the ultrafast nonadiabatic dynamics at conical intersections is analyzed for a two-state two-mode model chosen to represent the S 2 (ππ*)-S 1 (nπ*) conical intersection in pyrazine (the system) which is bilinearly coupled to infinitely many harmonic oscillators in thermal equilibrium (the bath). The system-bath coupling is modeled by the Drude spectral function. The equation of motion for the reduced density matrix of the system is solved numerically exactly with the hierarchy equation of motion method using graphics-processor-unit (GPU) technology. The simulations are valid for arbitrary strength of the system-bath coupling and arbitrary bath memory relaxation time. The present computational studies overcome the limitations of weak system-bath coupling and short memory relaxation time inherent in previous simulations based on multi-level Redfield theory [A. Kühl and W. Domcke, J. Chem. Phys. 2002, 116, 263]. Time evolutions of electronic state populations and time-dependent reduced probability densities of the coupling and tuning modes of the conical intersection have been obtained. It is found that even weak coupling to the bath effectively suppresses the irregular fluctuations of the electronic populations of the isolated two-mode conical intersection. While the population of the upper adiabatic electronic state (S 2 ) is very efficiently quenched by the system-bath coupling, the population of the diabatic ππ* electronic state exhibits long-lived oscillations driven by coherent motion of the tuning mode. Counterintuitively, the coupling to the bath can lead to an enhanced lifetime of the coherence of the tuning mode as a result of effective damping of the highly excited coupling mode, which reduces the strong mode-mode coupling inherent to the conical intersection. The present results extend previous studies of the dissipative dynamics at conical intersections to the nonperturbative regime of system-bath coupling. They pave the way for future first-principles simulations of femtosecond time-resolved four-wave-mixing spectra of chromophores in condensed phases which are nonperturbative in the system dynamics, the system-bath coupling as well as the field-matter coupling.

Solvation of fluoro-acetonitrile in water by 2D-IR spectroscopy: A combined experimental-computational study

NASA Astrophysics Data System (ADS)

Cazade, Pierre-André; Tran, Halina; Bereau, Tristan; Das, Akshaya K.; Kläsi, Felix; Hamm, Peter; Meuwly, Markus

2015-06-01

The solvent dynamics around fluorinated acetonitrile is characterized by 2-dimensional infrared spectroscopy and atomistic simulations. The lineshape of the linear infrared spectrum is better captured by semiempirical (density functional tight binding) mixed quantum mechanical/molecular mechanics simulations, whereas force field simulations with multipolar interactions yield lineshapes that are significantly too narrow. For the solvent dynamics, a relatively slow time scale of 2 ps is found from the experiments and supported by the mixed quantum mechanical/molecular mechanics simulations. With multipolar force fields fitted to the available thermodynamical data, the time scale is considerably faster—on the 0.5 ps time scale. The simulations provide evidence for a well established CF-HOH hydrogen bond (population of 25%) which is found from the radial distribution function g(r) from both, force field and quantum mechanics/molecular mechanics simulations.

New insights into photodissociation dynamics of cyclobutanone from the AIMS dynamic simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Lihong; Fang, Wei-Hai, E-mail: fangwh@bnu.edu.cn

2016-04-14

In this work, the combined electronic structure calculations and non-adiabatic dynamics simulations were performed for understanding mechanistic photodissociation of cyclobutanone at ∼248 nm. Besides the stationary and intersection structures reported before, two new conical intersections between the ground (S{sub 0}) and the first excited singlet (S{sub 1}) states were determined in the present study, which were confirmed to be the new S{sub 1} → S{sub 0} funnels by the ab initio multiple spawning dynamic simulation, giving rise to products in the S{sub 0} state selectively. The time evolution of the S{sub 1} electronic population was fitted with the pure exponentialmore » formulae, from which the S{sub 1} lifetime was estimated to be 484.0 fs. The time constant for the S{sub 1} α-cleavage is calculated to be 176.6 fs, which is based on the present dynamics simulation. As a result of the ultrafast S{sub 1} processes, the statistical distribution of the excess energies is prevented in the S{sub 1} state. The S{sub 1} dynamic effect (the nonergodic behavior) was predicted to be an important factor that is responsible for the wavelength dependence of the branching ratio of photodissociation products, which will be discussed in detail.« less

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

PubMed Central

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

2008-01-01

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

Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth.

PubMed

Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

2016-01-01

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

An analytical approach to top predator interference on the dynamics of a food chain model

NASA Astrophysics Data System (ADS)

Senthamarai, R.; Vijayalakshmi, T.

2018-04-01

In this paper, a nonlinear mathematical model is proposed and analyzed to study of top predator interference on the dynamics of a food chain model. The mathematical model is formulated using the system of non-linear ordinary differential equations. In this model, there are three state dimensionless variables, viz, size of prey population x, size of intermediate predator y and size of top predator population z. The analytical results are compared with the numerical simulation using MATLAB software and satisfactory results are noticed.

Computationally-efficient stochastic cluster dynamics method for modeling damage accumulation in irradiated materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoang, Tuan L.; Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, CA 94550; Marian, Jaime, E-mail: jmarian@ucla.edu

2015-11-01

An improved version of a recently developed stochastic cluster dynamics (SCD) method (Marian and Bulatov, 2012) [6] is introduced as an alternative to rate theory (RT) methods for solving coupled ordinary differential equation (ODE) systems for irradiation damage simulations. SCD circumvents by design the curse of dimensionality of the variable space that renders traditional ODE-based RT approaches inefficient when handling complex defect population comprised of multiple (more than two) defect species. Several improvements introduced here enable efficient and accurate simulations of irradiated materials up to realistic (high) damage doses characteristic of next-generation nuclear systems. The first improvement is a proceduremore » for efficiently updating the defect reaction-network and event selection in the context of a dynamically expanding reaction-network. Next is a novel implementation of the τ-leaping method that speeds up SCD simulations by advancing the state of the reaction network in large time increments when appropriate. Lastly, a volume rescaling procedure is introduced to control the computational complexity of the expanding reaction-network through occasional reductions of the defect population while maintaining accurate statistics. The enhanced SCD method is then applied to model defect cluster accumulation in iron thin films subjected to triple ion-beam (Fe{sup 3+}, He{sup +} and H{sup +}) irradiations, for which standard RT or spatially-resolved kinetic Monte Carlo simulations are prohibitively expensive.« less

Computationally-efficient stochastic cluster dynamics method for modeling damage accumulation in irradiated materials

NASA Astrophysics Data System (ADS)

Hoang, Tuan L.; Marian, Jaime; Bulatov, Vasily V.; Hosemann, Peter

2015-11-01

An improved version of a recently developed stochastic cluster dynamics (SCD) method (Marian and Bulatov, 2012) [6] is introduced as an alternative to rate theory (RT) methods for solving coupled ordinary differential equation (ODE) systems for irradiation damage simulations. SCD circumvents by design the curse of dimensionality of the variable space that renders traditional ODE-based RT approaches inefficient when handling complex defect population comprised of multiple (more than two) defect species. Several improvements introduced here enable efficient and accurate simulations of irradiated materials up to realistic (high) damage doses characteristic of next-generation nuclear systems. The first improvement is a procedure for efficiently updating the defect reaction-network and event selection in the context of a dynamically expanding reaction-network. Next is a novel implementation of the τ-leaping method that speeds up SCD simulations by advancing the state of the reaction network in large time increments when appropriate. Lastly, a volume rescaling procedure is introduced to control the computational complexity of the expanding reaction-network through occasional reductions of the defect population while maintaining accurate statistics. The enhanced SCD method is then applied to model defect cluster accumulation in iron thin films subjected to triple ion-beam (Fe3+, He+ and H+) irradiations, for which standard RT or spatially-resolved kinetic Monte Carlo simulations are prohibitively expensive.

An individual-based simulation model for mottled sculpin (Cottus bairdi) in a southern Appalachian stream

Treesearch

Brenda Rashleigh; Gary D. Grossman

2005-01-01

We describe and analyze a spatially explicit, individual-based model for the local population dynamics of mottled sculpin (Cottus bairdi). The model simulated daily growth, mortality, movement and spawning of individuals within a reach of stream. Juvenile and adult growth was based on consumption bioenergetics of benthic macroinvertebrate prey;...

Evaluations of alternative methods for monitoring and estimating responses of salmon productivity in the North Pacific to future climatic change and other processes: A simulation study

EPA Science Inventory

Estimation of the relative influence of climate change, compared to other human activities, on dynamics of Pacific salmon (Oncorhynchus spp.) populations can help management agencies take appropriate management actions. We used empirically based simulation modelling of 48 sockeye...

A system dynamics simulation model for sustainable water resources management and agricultural development in the Volta River Basin, Ghana.

PubMed

Kotir, Julius H; Smith, Carl; Brown, Greg; Marshall, Nadine; Johnstone, Ron

2016-12-15

In a rapidly changing water resources system, dynamic models based on the notion of systems thinking can serve as useful analytical tools for scientists and policy-makers to study changes in key system variables over time. In this paper, an integrated system dynamics simulation model was developed using a system dynamics modelling approach to examine the feedback processes and interaction between the population, the water resource, and the agricultural production sub-sectors of the Volta River Basin in West Africa. The objective of the model is to provide a learning tool for policy-makers to improve their understanding of the long-term dynamic behaviour of the basin, and as a decision support tool for exploring plausible policy scenarios necessary for sustainable water resource management and agricultural development. Structural and behavioural pattern tests, and statistical test were used to evaluate and validate the performance of the model. The results showed that the simulated outputs agreed well with the observed reality of the system. A sensitivity analysis also indicated that the model is reliable and robust to uncertainties in the major parameters. Results of the business as usual scenario showed that total population, agricultural, domestic, and industrial water demands will continue to increase over the simulated period. Besides business as usual, three additional policy scenarios were simulated to assess their impact on water demands, crop yield, and net-farm income. These were the development of the water infrastructure (scenario 1), cropland expansion (scenario 2) and dry conditions (scenario 3). The results showed that scenario 1 would provide the maximum benefit to people living in the basin. Overall, the model results could help inform planning and investment decisions within the basin to enhance food security, livelihoods development, socio-economic growth, and sustainable management of natural resources. Copyright © 2016 Elsevier B.V. All rights reserved.

[Spatial structure analysis and distribution simulation of Therioaphis trifolii population based on geostatistics and GIS].

PubMed

Zhang, Rong; Leng, Yun-fa; Zhu, Meng-meng; Wang, Fang

2007-11-01

Based on geographic information system and geostatistics, the spatial structure of Therioaphis trifolii population of different periods in Yuanzhou district of Guyuan City, the southern Ningxia Province, was analyzed. The spatial distribution of Therioaphis trifolii population was also simulated by ordinary Kriging interpretation. The results showed that Therioaphis trifolii population of different periods was correlated spatially in the study area. The semivariograms of Therioaphis trifolii could be described by exponential model, indicating an aggregated spatial arrangement. The spatial variance varied from 34.13%-48.77%, and the range varied from 8.751-12.049 km. The degree and direction of aggregation showed that the trend was increased gradually from southwest to northeast. The dynamic change of Therioaphis trifolii population in different periods could be analyzed intuitively on the simulated maps of the spatial distribution from the two aspects of time and space, The occurrence position and degree of Therioaphis trifolii to a state of certain time could be determined easily.

The evolution of wealth transmission in human populations: a stochastic model

NASA Astrophysics Data System (ADS)

Augustins, G.; Etienne, L.; Ferdy, J.-B.; Ferrer, R.; Godelle, B.; Pitard, E.; Rousset, F.

2014-03-01

Reproductive success and survival are influenced by wealth in human populations. Wealth is transmitted to offsprings and strategies of transmission vary over time and among populations, the main variation being how equally wealth is transmitted to children. Here we propose a model where we simulate both the dynamics of wealth in a population and the evolution of a trait that determines how wealth is transmitted from parents to offspring, in a darwinian context.

A parallel algorithm for step- and chain-growth polymerization in molecular dynamics.

PubMed

de Buyl, Pierre; Nies, Erik

2015-04-07

Classical Molecular Dynamics (MD) simulations provide insight into the properties of many soft-matter systems. In some situations, it is interesting to model the creation of chemical bonds, a process that is not part of the MD framework. In this context, we propose a parallel algorithm for step- and chain-growth polymerization that is based on a generic reaction scheme, works at a given intrinsic rate and produces continuous trajectories. We present an implementation in the ESPResSo++ simulation software and compare it with the corresponding feature in LAMMPS. For chain growth, our results are compared to the existing simulation literature. For step growth, a rate equation is proposed for the evolution of the crosslinker population that compares well to the simulations for low crosslinker functionality or for short times.

A parallel algorithm for step- and chain-growth polymerization in molecular dynamics

NASA Astrophysics Data System (ADS)

de Buyl, Pierre; Nies, Erik

2015-04-01

Classical Molecular Dynamics (MD) simulations provide insight into the properties of many soft-matter systems. In some situations, it is interesting to model the creation of chemical bonds, a process that is not part of the MD framework. In this context, we propose a parallel algorithm for step- and chain-growth polymerization that is based on a generic reaction scheme, works at a given intrinsic rate and produces continuous trajectories. We present an implementation in the ESPResSo++ simulation software and compare it with the corresponding feature in LAMMPS. For chain growth, our results are compared to the existing simulation literature. For step growth, a rate equation is proposed for the evolution of the crosslinker population that compares well to the simulations for low crosslinker functionality or for short times.

Dynamics of water bound to crystalline cellulose.

PubMed

O'Neill, Hugh; Pingali, Sai Venkatesh; Petridis, Loukas; He, Junhong; Mamontov, Eugene; Hong, Liang; Urban, Volker; Evans, Barbara; Langan, Paul; Smith, Jeremy C; Davison, Brian H

2017-09-19

Interactions of water with cellulose are of both fundamental and technological importance. Here, we characterize the properties of water associated with cellulose using deuterium labeling, neutron scattering and molecular dynamics simulation. Quasi-elastic neutron scattering provided quantitative details about the dynamical relaxation processes that occur and was supported by structural characterization using small-angle neutron scattering and X-ray diffraction. We can unambiguously detect two populations of water associated with cellulose. The first is "non-freezing bound" water that gradually becomes mobile with increasing temperature and can be related to surface water. The second population is consistent with confined water that abruptly becomes mobile at ~260 K, and can be attributed to water that accumulates in the narrow spaces between the microfibrils. Quantitative analysis of the QENS data showed that, at 250 K, the water diffusion coefficient was 0.85 ± 0.04 × 10 -10  m 2 sec -1 and increased to 1.77 ± 0.09 × 10 -10  m 2 sec -1 at 265 K. MD simulations are in excellent agreement with the experiments and support the interpretation that water associated with cellulose exists in two dynamical populations. Our results provide clarity to previous work investigating the states of bound water and provide a new approach for probing water interactions with lignocellulose materials.

Complex Population Dynamics and the Coalescent Under Neutrality

PubMed Central

Volz, Erik M.

2012-01-01

Estimates of the coalescent effective population size Ne can be poorly correlated with the true population size. The relationship between Ne and the population size is sensitive to the way in which birth and death rates vary over time. The problem of inference is exacerbated when the mechanisms underlying population dynamics are complex and depend on many parameters. In instances where nonparametric estimators of Ne such as the skyline struggle to reproduce the correct demographic history, model-based estimators that can draw on prior information about population size and growth rates may be more efficient. A coalescent model is developed for a large class of populations such that the demographic history is described by a deterministic nonlinear dynamical system of arbitrary dimension. This class of demographic model differs from those typically used in population genetics. Birth and death rates are not fixed, and no assumptions are made regarding the fraction of the population sampled. Furthermore, the population may be structured in such a way that gene copies reproduce both within and across demes. For this large class of models, it is shown how to derive the rate of coalescence, as well as the likelihood of a gene genealogy with heterochronous sampling and labeled taxa, and how to simulate a coalescent tree conditional on a complex demographic history. This theoretical framework encapsulates many of the models used by ecologists and epidemiologists and should facilitate the integration of population genetics with the study of mathematical population dynamics. PMID:22042576

Early dynamical evolution of substructured stellar clusters

NASA Astrophysics Data System (ADS)

Dorval, Julien; Boily, Christian

2015-08-01

It is now widely accepted that stellar clusters form with a high level of substructure (Kuhn et al. 2014, Bate 2009), inherited from the molecular cloud and the star formation process. Evidence from observations and simulations also indicate the stars in such young clusters form a subvirial system (Kirk et al. 2007, Maschberger et al. 2010). The subsequent dynamical evolution can cause important mass loss, ejecting a large part of the birth population in the field. It can also imprint the stellar population and still be inferred from observations of evolved clusters. Nbody simulations allow a better understanding of these early twists and turns, given realistic initial conditions. Nowadays, substructured, clumpy young clusters are usually obtained through pseudo-fractal growth (Goodwin et al. 2004) and velocity inheritance. Such models are visually realistics and are very useful, they are however somewhat artificial in their velocity distribution. I introduce a new way to create clumpy initial conditions through a "Hubble expansion" which naturally produces self consistent clumps, velocity-wise. A velocity distribution analysis shows the new method produces realistic models, consistent with the dynamical state of the newly created cores in hydrodynamic simulation of cluster formation (Klessen & Burkert 2000). I use these initial conditions to investigate the dynamical evolution of young subvirial clusters, up to 80000 stars. I find an overall soft evolution, with hierarchical merging leading to a high level of mass segregation. I investigate the influence of the mass function on the fate of the cluster, specifically on the amount of mass loss induced by the early violent relaxation. Using a new binary detection algorithm, I also find a strong processing of the native binary population.

HIV competition dynamics over sexual networks: first comer advantage conserves founder effects.

PubMed

Ferdinandy, Bence; Mones, Enys; Vicsek, Tamás; Müller, Viktor

2015-02-01

Outside Africa, the global phylogeography of HIV is characterized by compartmentalized local epidemics that are typically dominated by a single subtype, which indicates strong founder effects. We hypothesized that the competition of viral strains at the epidemic level may involve an advantage of the resident strain that was the first to colonize a population. Such an effect would slow down the invasion of new strains, and thus also the diversification of the epidemic. We developed a stochastic modelling framework to simulate HIV epidemics over dynamic contact networks. We simulated epidemics in which the second strain was introduced into a population where the first strain had established a steady-state epidemic, and assessed whether, and on what time scale, the second strain was able to spread in the population. Simulations were parameterized based on empirical data; we tested scenarios with varying levels of overall prevalence. The spread of the second strain occurred on a much slower time scale compared with the initial expansion of the first strain. With strains of equal transmission efficiency, the second strain was unable to invade on a time scale relevant for the history of the HIV pandemic. To become dominant over a time scale of decades, the second strain needed considerable (>25%) advantage in transmission efficiency over the resident strain. The inhibition effect was weaker if the second strain was introduced while the first strain was still in its growth phase. We also tested how possible mechanisms of interference (inhibition of superinfection, depletion of highly connected hubs in the network, one-time acute peak of infectiousness) contribute to the inhibition effect. Our simulations confirmed a strong first comer advantage in the competition dynamics of HIV at the population level, which may explain the global phylogeography of the virus and may influence the future evolution of the pandemic.

Observing Stellar Clusters in the Computer

NASA Astrophysics Data System (ADS)

Borch, A.; Spurzem, R.; Hurley, J.

2006-08-01

We present a new approach to combine direct N-body simulations to stellar population synthesis modeling in order to model the dynamical evolution and color evolution of globular clusters at the same time. This allows us to model the spectrum, colors and luminosities of each star in the simulated cluster. For this purpose the NBODY6++ code (Spurzem 1999) is used, which is a parallel version of the NBODY code. J. Hurley implemented simple recipes to follow the changes of stellar masses, radii, and luminosities due to stellar evolution into the NBODY6++ code (Hurley et al. 2001), in the sense that each simulation particle represents one star. These prescriptions cover all evolutionary phases and solar to globular cluster metallicities. We used the stellar parameters obtained by this stellar evolution routine and coupled them to the stellar library BaSeL 2.0 (Lejeune et al. 1997). As a first application we investigated the integrated broad band colors of simulated clusters. We modeled tidally disrupted globular clusters and compared the results with isolated globular clusters. Due to energy equipartition we expected a relative blueing of tidally disrupted clusters, because of the higher escape probability of red, low-mass stars. This behaviour we actually observe for concentrated globular clusters. The mass-to-light ratio of isolated clusters follows exactly a color-M/L correlation, similar as described in Bell and de Jong (2001) in the case of spiral galaxies. At variance to this correlation, in tidally disrupted clusters the M/L ratio becomes significantly lower at the time of cluster dissolution. Hence, for isolated clusters the behavior of the stellar population is not influenced by dynamical evolution, whereas the stellar population of tidally disrupted clusters is strongly influenced by dynamical effects.

SLiM 2: Flexible, Interactive Forward Genetic Simulations.

PubMed

Haller, Benjamin C; Messer, Philipp W

2017-01-01

Modern population genomic datasets hold immense promise for revealing the evolutionary processes operating in natural populations, but a crucial prerequisite for this goal is the ability to model realistic evolutionary scenarios and predict their expected patterns in genomic data. To that end, we present SLiM 2: an evolutionary simulation framework that combines a powerful, fast engine for forward population genetic simulations with the capability of modeling a wide variety of complex evolutionary scenarios. SLiM achieves this flexibility through scriptability, which provides control over most aspects of the simulated evolutionary scenarios with a simple R-like scripting language called Eidos. An example SLiM simulation is presented to illustrate the power of this approach. SLiM 2 also includes a graphical user interface for simulation construction, interactive runtime control, and dynamic visualization of simulation output, facilitating easy and fast model development with quick prototyping and visual debugging. We conclude with a performance comparison between SLiM and two other popular forward genetic simulation packages. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Combining Computational Fluid Dynamics and Agent-Based Modeling: A New Approach to Evacuation Planning

PubMed Central

Epstein, Joshua M.; Pankajakshan, Ramesh; Hammond, Ross A.

2011-01-01

We introduce a novel hybrid of two fields—Computational Fluid Dynamics (CFD) and Agent-Based Modeling (ABM)—as a powerful new technique for urban evacuation planning. CFD is a predominant technique for modeling airborne transport of contaminants, while ABM is a powerful approach for modeling social dynamics in populations of adaptive individuals. The hybrid CFD-ABM method is capable of simulating how large, spatially-distributed populations might respond to a physically realistic contaminant plume. We demonstrate the overall feasibility of CFD-ABM evacuation design, using the case of a hypothetical aerosol release in Los Angeles to explore potential effectiveness of various policy regimes. We conclude by arguing that this new approach can be powerfully applied to arbitrary population centers, offering an unprecedented preparedness and catastrophic event response tool. PMID:21687788

Restoration ecology: two-sex dynamics and cost minimization.

PubMed

Molnár, Ferenc; Caragine, Christina; Caraco, Thomas; Korniss, Gyorgy

2013-01-01

We model a spatially detailed, two-sex population dynamics, to study the cost of ecological restoration. We assume that cost is proportional to the number of individuals introduced into a large habitat. We treat dispersal as homogeneous diffusion in a one-dimensional reaction-diffusion system. The local population dynamics depends on sex ratio at birth, and allows mortality rates to differ between sexes. Furthermore, local density dependence induces a strong Allee effect, implying that the initial population must be sufficiently large to avert rapid extinction. We address three different initial spatial distributions for the introduced individuals; for each we minimize the associated cost, constrained by the requirement that the species must be restored throughout the habitat. First, we consider spatially inhomogeneous, unstable stationary solutions of the model's equations as plausible candidates for small restoration cost. Second, we use numerical simulations to find the smallest rectangular cluster, enclosing a spatially homogeneous population density, that minimizes the cost of assured restoration. Finally, by employing simulated annealing, we minimize restoration cost among all possible initial spatial distributions of females and males. For biased sex ratios, or for a significant between-sex difference in mortality, we find that sex-specific spatial distributions minimize the cost. But as long as the sex ratio maximizes the local equilibrium density for given mortality rates, a common homogeneous distribution for both sexes that spans a critical distance yields a similarly low cost.

Restoration Ecology: Two-Sex Dynamics and Cost Minimization

PubMed Central

Molnár, Ferenc; Caragine, Christina; Caraco, Thomas; Korniss, Gyorgy

2013-01-01

We model a spatially detailed, two-sex population dynamics, to study the cost of ecological restoration. We assume that cost is proportional to the number of individuals introduced into a large habitat. We treat dispersal as homogeneous diffusion in a one-dimensional reaction-diffusion system. The local population dynamics depends on sex ratio at birth, and allows mortality rates to differ between sexes. Furthermore, local density dependence induces a strong Allee effect, implying that the initial population must be sufficiently large to avert rapid extinction. We address three different initial spatial distributions for the introduced individuals; for each we minimize the associated cost, constrained by the requirement that the species must be restored throughout the habitat. First, we consider spatially inhomogeneous, unstable stationary solutions of the model’s equations as plausible candidates for small restoration cost. Second, we use numerical simulations to find the smallest rectangular cluster, enclosing a spatially homogeneous population density, that minimizes the cost of assured restoration. Finally, by employing simulated annealing, we minimize restoration cost among all possible initial spatial distributions of females and males. For biased sex ratios, or for a significant between-sex difference in mortality, we find that sex-specific spatial distributions minimize the cost. But as long as the sex ratio maximizes the local equilibrium density for given mortality rates, a common homogeneous distribution for both sexes that spans a critical distance yields a similarly low cost. PMID:24204810

Discontinuous Galerkin finite element method for solving population density functions of cortical pyramidal and thalamic neuronal populations.

PubMed

Huang, Chih-Hsu; Lin, Chou-Ching K; Ju, Ming-Shaung

2015-02-01

Compared with the Monte Carlo method, the population density method is efficient for modeling collective dynamics of neuronal populations in human brain. In this method, a population density function describes the probabilistic distribution of states of all neurons in the population and it is governed by a hyperbolic partial differential equation. In the past, the problem was mainly solved by using the finite difference method. In a previous study, a continuous Galerkin finite element method was found better than the finite difference method for solving the hyperbolic partial differential equation; however, the population density function often has discontinuity and both methods suffer from a numerical stability problem. The goal of this study is to improve the numerical stability of the solution using discontinuous Galerkin finite element method. To test the performance of the new approach, interaction of a population of cortical pyramidal neurons and a population of thalamic neurons was simulated. The numerical results showed good agreement between results of discontinuous Galerkin finite element and Monte Carlo methods. The convergence and accuracy of the solutions are excellent. The numerical stability problem could be resolved using the discontinuous Galerkin finite element method which has total-variation-diminishing property. The efficient approach will be employed to simulate the electroencephalogram or dynamics of thalamocortical network which involves three populations, namely, thalamic reticular neurons, thalamocortical neurons and cortical pyramidal neurons. Copyright © 2014 Elsevier Ltd. All rights reserved.

Rabies disease dynamics in naïve dog populations in Australia.

PubMed

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

2016-09-01

Currently, Australia is free from terrestrial rabies but an incursion from nearby Indonesia, where the virus is endemic, is a feasible threat. Here, we aimed to determine whether the response to a simulated rabies incursion would vary between three extant Australian dog populations; free-roaming domestic dogs from a remote indigenous community in northern Australia, and free-roaming domestic and wild dogs in peri-urban areas of north-east New South Wales. We further sought to predict how different management strategies impacted disease dynamics in these populations. We used simple stochastic state-transition models and dog demographic and contact rate data from the three dog populations to simulate rabies spread, and used global and local sensitivity analyses to determine effects of model parameters. To identify the most effective control options, dog removal and vaccination strategies were also simulated. Responses to simulated rabies incursions varied between the dog populations. Free-roaming domestic dogs from north-east New South Wales exhibited the lowest risk for rabies maintenance and spread. Due to low containment and high contact rates, rabies progressed rapidly through free-roaming dogs from the remote indigenous community in northern Australia. In contrast, rabies remained at relatively low levels within the north-east New South Wales wild dog population for over a year prior to an epidemic. Across all scenarios, sensitivity analyses revealed that contact rates and the probability of transmission were the most important drivers of the number of infectious individuals within a population. The number of infectious individuals was less sensitive to birth and death rates. Removal of dogs as a control strategy was not effective for any population modelled, while vaccination rates in excess of 70% of the population resulted in significant reductions in disease progression. The variability in response between these distinct dog groups to a rabies incursion, suggests that a blanket approach to management would not be effective or feasible to control rabies in Australia. Control strategies that take into account the different population and behavioural characteristics of these dog groups will maximise the likelihood of effective and efficient rabies control in Australia. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Acceptability of the Kalman filter to monitor pronghorn population size

Treesearch

Raymond L. Czaplewski

1986-01-01

Pronghorn antelope are important components of grassland and steppe ecosystems in Wyoming. Monitoring data on the size and population dynamics of these herds are expensive and gathered only a few times each year. Reliable data include estimates of animals harvested and proportion of bucks, does, and fawns. A deterministic simulation model has been used to improve...

Modeling the Impact of Baryons on Subhalo Populations with Machine Learning

NASA Astrophysics Data System (ADS)

Nadler, Ethan O.; Mao, Yao-Yuan; Wechsler, Risa H.; Garrison-Kimmel, Shea; Wetzel, Andrew

2018-06-01

We identify subhalos in dark matter–only (DMO) zoom-in simulations that are likely to be disrupted due to baryonic effects by using a random forest classifier trained on two hydrodynamic simulations of Milky Way (MW)–mass host halos from the Latte suite of the Feedback in Realistic Environments (FIRE) project. We train our classifier using five properties of each disrupted and surviving subhalo: pericentric distance and scale factor at first pericentric passage after accretion and scale factor, virial mass, and maximum circular velocity at accretion. Our five-property classifier identifies disrupted subhalos in the FIRE simulations with an 85% out-of-bag classification score. We predict surviving subhalo populations in DMO simulations of the FIRE host halos, finding excellent agreement with the hydrodynamic results; in particular, our classifier outperforms DMO zoom-in simulations that include the gravitational potential of the central galactic disk in each hydrodynamic simulation, indicating that it captures both the dynamical effects of a central disk and additional baryonic physics. We also predict surviving subhalo populations for a suite of DMO zoom-in simulations of MW-mass host halos, finding that baryons impact each system consistently and that the predicted amount of subhalo disruption is larger than the host-to-host scatter among the subhalo populations. Although the small size and specific baryonic physics prescription of our training set limits the generality of our results, our work suggests that machine-learning classification algorithms trained on hydrodynamic zoom-in simulations can efficiently predict realistic subhalo populations.

Population dynamics in non-homogeneous environments

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

Dynamic and thermodynamic crossover scenarios in the Kob-Andersen mixture: Insights from multi-CPU and multi-GPU simulations.

PubMed

Coslovich, Daniele; Ozawa, Misaki; Kob, Walter

2018-05-17

The physical behavior of glass-forming liquids presents complex features of both dynamic and thermodynamic nature. Some studies indicate the presence of thermodynamic anomalies and of crossovers in the dynamic properties, but their origin and degree of universality is difficult to assess. Moreover, conventional simulations are barely able to cover the range of temperatures at which these crossovers usually occur. To address these issues, we simulate the Kob-Andersen Lennard-Jones mixture using efficient protocols based on multi-CPU and multi-GPU parallel tempering. Our setup enables us to probe the thermodynamics and dynamics of the liquid at equilibrium well below the critical temperature of the mode-coupling theory, [Formula: see text]. We find that below [Formula: see text] the analysis is hampered by partial crystallization of the metastable liquid, which nucleates extended regions populated by large particles arranged in an fcc structure. By filtering out crystalline samples, we reveal that the specific heat grows in a regular manner down to [Formula: see text] . Possible thermodynamic anomalies suggested by previous studies can thus occur only in a region of the phase diagram where the system is highly metastable. Using the equilibrium configurations obtained from the parallel tempering simulations, we perform molecular dynamics and Monte Carlo simulations to probe the equilibrium dynamics down to [Formula: see text]. A temperature-derivative analysis of the relaxation time and diffusion data allows us to assess different dynamic scenarios around [Formula: see text]. Hints of a dynamic crossover come from analysis of the four-point dynamic susceptibility. Finally, we discuss possible future numerical strategies to clarify the nature of crossover phenomena in glass-forming liquids.

Stochastic Simulation of Biomolecular Networks in Dynamic Environments

PubMed Central

Voliotis, Margaritis; Thomas, Philipp; Grima, Ramon; Bowsher, Clive G.

2016-01-01

Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate—using decision-making by a large population of quorum sensing bacteria—that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits. PMID:27248512

Systematic Validation of Protein Force Fields against Experimental Data

PubMed Central

Eastwood, Michael P.; Dror, Ron O.; Shaw, David E.

2012-01-01

Molecular dynamics simulations provide a vehicle for capturing the structures, motions, and interactions of biological macromolecules in full atomic detail. The accuracy of such simulations, however, is critically dependent on the force field—the mathematical model used to approximate the atomic-level forces acting on the simulated molecular system. Here we present a systematic and extensive evaluation of eight different protein force fields based on comparisons of experimental data with molecular dynamics simulations that reach a previously inaccessible timescale. First, through extensive comparisons with experimental NMR data, we examined the force fields' abilities to describe the structure and fluctuations of folded proteins. Second, we quantified potential biases towards different secondary structure types by comparing experimental and simulation data for small peptides that preferentially populate either helical or sheet-like structures. Third, we tested the force fields' abilities to fold two small proteins—one α-helical, the other with β-sheet structure. The results suggest that force fields have improved over time, and that the most recent versions, while not perfect, provide an accurate description of many structural and dynamical properties of proteins. PMID:22384157

Nonadiabatic Ab Initio Molecular Dynamics with the Floating Occupation Molecular Orbital-Complete Active Space Configuration Interaction Method [Non-Adiabatic Ab Initio Molecular Dynamics with Floating Occupation Molecular Orbitals CASCI Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hollas, Daniel; Sistik, Lukas; Hohenstein, Edward G.

Here, we show that the floating occupation molecular orbital complete active space configuration interaction (FOMO-CASCI) method is a promising alternative to the widely used complete active space self-consistent field (CASSCF) method in direct nonadiabatic dynamics simulations. We have simulated photodynamics of three archetypal molecules in photodynamics: ethylene, methaniminium cation, and malonaldehyde. We compared the time evolution of electronic populations and reaction mechanisms as revealed by the FOMO-CASCI and CASSCF approaches. Generally, the two approaches provide similar results. Some dynamical differences are observed, but these can be traced back to energetically minor differences in the potential energy surfaces. We suggest thatmore » the FOMO-CASCI method represents, due to its efficiency and stability, a promising approach for direct ab initio dynamics in the excited state.« less

Dynamics of epidemic spreading with vaccination: Impact of social pressure and engagement

NASA Astrophysics Data System (ADS)

Pires, Marcelo A.; Crokidakis, Nuno

2017-02-01

In this work we consider a model of epidemic spreading coupled with an opinion dynamics in a fully-connected population. Regarding the opinion dynamics, the individuals may be in two distinct states, namely in favor or against a vaccination campaign. Individuals against the vaccination follow a standard SIS model, whereas the pro-vaccine individuals can also be in a third compartment, namely Vaccinated. In addition, the opinions change according to the majority-rule dynamics in groups with three individuals. We also consider that the vaccine can give permanent or temporary immunization to the individuals. By means of analytical calculations and computer simulations, we show that the opinion dynamics can drastically affect the disease propagation, and that the engagement of the pro-vaccine individuals can be crucial for stopping the epidemic spreading. The full numerical code for simulating the model is available from the authors' webpage.

Modelling the Dynamics of Post-Vaccination Immunity Rate in a Population of Sahelian Sheep after a Vaccination Campaign against Peste des Petits Ruminants Virus

PubMed Central

Lancelot, Renaud; Lesnoff, Matthieu

2016-01-01

Background Peste des petits ruminants (PPR) is an acute infectious viral disease affecting domestic small ruminants (sheep and goats) and some wild ruminant species in Africa, the Middle East and Asia. A global PPR control strategy based on mass vaccination—in regions where PPR is endemic—was recently designed and launched by international organizations. Sahelian Africa is one of the most challenging endemic regions for PPR control. Indeed, strong seasonal and annual variations in mating, mortality and offtake rates result in a complex population dynamics which might in turn alter the population post-vaccination immunity rate (PIR), and thus be important to consider for the implementation of vaccination campaigns. Methods In a context of preventive vaccination in epidemiological units without PPR virus transmission, we developed a predictive, dynamic model based on a seasonal matrix population model to simulate PIR dynamics. This model was mostly calibrated with demographic and epidemiological parameters estimated from a long-term follow-up survey of small ruminant herds. We used it to simulate the PIR dynamics following a single PPR vaccination campaign in a Sahelian sheep population, and to assess the effects of (i) changes in offtake rate related to the Tabaski (a Muslim feast following the lunar calendar), and (ii) the date of implementation of the vaccination campaigns. Results The persistence of PIR was not influenced by the Tabaski date. Decreasing the vaccination coverage from 100 to 80% had limited effects on PIR. However, lower vaccination coverage did not provide sufficient immunity rates (PIR < 70%). As a trade-off between model predictions and other considerations like animal physiological status, and suitability for livestock farmers, we would suggest to implement vaccination campaigns in September-October. This model is a first step towards better decision support for animal health authorities. It might be adapted to other species, livestock farming systems or diseases. PMID:27603710

Rethinking the logistic approach for population dynamics of mutualistic interactions.

PubMed

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

2014-12-21

Mutualistic communities have an internal structure that makes them resilient to external perturbations. Late research has focused on their stability and the topology of the relations between the different organisms to explain the reasons of the system robustness. Much less attention has been invested in analyzing the systems dynamics. The main population models in use are modifications of the r-K formulation of logistic equation with additional terms to account for the benefits produced by the interspecific interactions. These models have shortcomings as the so-called r-K formulation diverges under some conditions. In this work, we introduce a model for population dynamics under mutualism that preserves the original logistic formulation. It is mathematically simpler than the widely used type II models, although it shows similar complexity in terms of fixed points and stability of the dynamics. We perform an analytical stability analysis and numerical simulations to study the model behavior in general interaction scenarios including tests of the resilience of its dynamics under external perturbations. Despite its simplicity, our results indicate that the model dynamics shows an important richness that can be used to gain further insights in the dynamics of mutualistic communities. Copyright © 2014 Elsevier Ltd. All rights reserved.

Gene surfing in expanding populations.

PubMed

Hallatschek, Oskar; Nelson, David R

2008-02-01

Large scale genomic surveys are partly motivated by the idea that the neutral genetic variation of a population may be used to reconstruct its migration history. However, our ability to trace back the colonization pathways of a species from their genetic footprints is limited by our understanding of the genetic consequences of a range expansion. Here, we study, by means of simulations and analytical methods, the neutral dynamics of gene frequencies in an asexual population undergoing a continual range expansion in one dimension. During such a colonization period, lineages can fix at the wave front by means of a "surfing" mechanism [Edmonds, C.A., Lillie, A.S., Cavalli-Sforza, L.L., 2004. Mutations arising in the wave front of an expanding population. Proc. Natl. Acad. Sci. 101, 975-979]. We quantify this phenomenon in terms of (i) the spatial distribution of lineages that reach fixation and, closely related, (ii) the continual loss of genetic diversity (heterozygosity) at the wave front, characterizing the approach to fixation. Our stochastic simulations show that an effective population size can be assigned to the wave that controls the (observable) gradient in heterozygosity left behind the colonization process. This effective population size is markedly higher in the presence of cooperation between individuals ("pushed waves") than when individuals proliferate independently ("pulled waves"), and increases only sub-linearly with deme size. To explain these and other findings, we develop a versatile analytical approach, based on the physics of reaction-diffusion systems, that yields simple predictions for any deterministic population dynamics. Our analytical theory compares well with the simulation results for pushed waves, but is less accurate in the case of pulled waves when stochastic fluctuations in the tip of the wave are important.

An agent-based modeling framework for evaluating hypotheses on risks for developing autism: effects of the gut microbial environment.

PubMed

Weston, Bronson; Fogal, Benjamin; Cook, Daniel; Dhurjati, Prasad

2015-04-01

The number of cases diagnosed with Autism Spectrum Disorders is rising at an alarming rate with the Centers for Disease Control estimating the 2014 incidence rate as 1 in 68. Recently, it has been hypothesized that gut bacteria may contribute to the development of autism. Specifically, the relative balances between the inflammatory microbes clostridia and desulfovibrio and the anti-inflammatory microbe bifidobacteria may become destabilized prior to autism development. The imbalance leads to a leaky gut, characterized by a more porous epithelial membrane resulting in microbial toxin release into the blood, which may contribute to brain inflammation and autism development. To test how changes in population dynamics of the gut microbiome may lead to the imbalanced microbial populations associated with autism patients, we constructed a novel agent-based model of clostridia, desulfovibrio, and bifidobacteria population interactions in the gut. The model demonstrates how changing physiological conditions in the gut can affect the population dynamics of the microbiome. Simulations using our agent-based model indicate that despite large perturbations to initial levels of bacteria, the populations robustly achieve a single steady-state given similar gut conditions. These simulation results suggests that disturbance such as a prebiotic or antibiotic treatment may only transiently affect the gut microbiome. However, sustained prebiotic treatments may correct low population counts of bifidobacteria. Furthermore, our simulations suggest that clostridia growth rate is a key determinant of risk of autism development. Treatment of high-risk infants with supra-physiological levels of lysozymes may suppress clostridia growth rate, resulting in a steep decrease in the clostridia population and therefore reduced risk of autism development. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dynamical equivalence, the origin of the Galactic field stellar and binary population, and the initial radius-mass relation of embedded clusters

NASA Astrophysics Data System (ADS)

Belloni, Diogo; Kroupa, Pavel; Rocha-Pinto, Helio J.; Giersz, Mirek

2018-03-01

In order to allow a better understanding of the origin of Galactic field populations, dynamical equivalence of stellar-dynamical systems has been postulated by Kroupa and Belloni et al. to allow mapping of solutions of the initial conditions of embedded clusters such that they yield, after a period of dynamical processing, the Galactic field population. Dynamically equivalent systems are defined to initially and finally have the same distribution functions of periods, mass ratios and eccentricities of binary stars. Here, we search for dynamically equivalent clusters using the MOCCA code. The simulations confirm that dynamically equivalent solutions indeed exist. The result is that the solution space is next to identical to the radius-mass relation of Marks & Kroupa, ( r_h/pc )= 0.1^{+0.07}_{-0.04} ( M_ecl/M_{⊙} )^{0.13± 0.04}. This relation is in good agreement with the oIMF. This is achieved by applying a similar procedurebserved density of molecular cloud clumps. According to the solutions, the time-scale to reach dynamical equivalence is about 0.5 Myr which is, interestingly, consistent with the lifetime of ultra-compact H II regions and the time-scale needed for gas expulsion to be active in observed very young clusters as based on their dynamical modelling.

Enhanced sampling by multiple molecular dynamics trajectories: carbonmonoxy myoglobin 10 micros A0-->A(1-3) transition from ten 400 picosecond simulations.

PubMed

Loccisano, Anne E; Acevedo, Orlando; DeChancie, Jason; Schulze, Brita G; Evanseck, Jeffrey D

2004-05-01

The utility of multiple trajectories to extend the time scale of molecular dynamics simulations is reported for the spectroscopic A-states of carbonmonoxy myoglobin (MbCO). Experimentally, the A0-->A(1-3) transition has been observed to be 10 micros at 300 K, which is beyond the time scale of standard molecular dynamics simulations. To simulate this transition, 10 short (400 ps) and two longer time (1.2 ns) molecular dynamics trajectories, starting from five different crystallographic and solution phase structures with random initial velocities centered in a 37 A radius sphere of water, have been used to sample the native-fold of MbCO. Analysis of the ensemble of structures gathered over the cumulative 5.6 ns reveals two biomolecular motions involving the side chains of His64 and Arg45 to explain the spectroscopic states of MbCO. The 10 micros A0-->A(1-3) transition involves the motion of His64, where distance between His64 and CO is found to vary up to 8.8 +/- 1.0 A during the transition of His64 from the ligand (A(1-3)) to bulk solvent (A0). The His64 motion occurs within a single trajectory only once, however the multiple trajectories populate the spectroscopic A-states fully. Consequently, multiple independent molecular dynamics simulations have been found to extend biomolecular motion from 5 ns of total simulation to experimental phenomena on the microsecond time scale.

Alternative Stable States, Coral Reefs, and Smooth Dynamics with a Kick.

PubMed

Ippolito, Stephen; Naudot, Vincent; Noonburg, Erik G

2016-03-01

We consider a computer simulation, which was found to be faithful to time series data for Caribbean coral reefs, and an analytical model to help understand the dynamics of the simulation. The analytical model is a system of ordinary differential equations (ODE), and the authors claim this model demonstrates the existence of alternative stable states. The existence of an alternative stable state should consider a sudden shift in coral and macroalgae populations, while the grazing rate remains constant. The results of such shifts, however, are often confounded by changes in grazing rate. Although the ODE suggest alternative stable states, the ODE need modification to explicitly account for shifts or discrete events such as hurricanes. The goal of this paper will be to study the simulation dynamics through a simplified analytical representation. We proceed by modifying the original analytical model through incorporating discrete changes into the ODE. We then analyze the resulting dynamics and their bifurcations with respect to changes in grazing rate and hurricane frequency. In particular, a "kick" enabling the ODE to consider impulse events is added. Beyond adding a "kick" we employ the grazing function that is suggested by the simulation. The extended model was fit to the simulation data to support its use and predicts the existence cycles depending nonlinearly on grazing rates and hurricane frequency. These cycles may bring new insights into consideration for reef health, restoration and dynamics.

The effect of social alliances on wolf population on their survival under hunting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cebrat, S.; Kakol, J.

1997-04-01

We have introduced the modified Verhulst factor to simulate the dynamics of wolves` population. The new factor enlarges the capacity of environment for organisms living in organized groups. Under this factor, social behavior allows the population to reach the larger size in the same ecological niche. The other effect of the introduced factor is that additional non-selective killing factors limit the population size not only directly but also by shrinking the effective ecological niche capacity.

The Effect of Social Alliances on Wolf Population on Their Survival Under Hunting

NASA Astrophysics Data System (ADS)

Cebrat, Stanisław; Kakol, Jerzy

We have introduced the modified Verhulst factor to simulate the dynamics of wolves' population. The new factor enlarges the capacity of environment for organisms living in organized groups. Under this factor, social behavior allows the population to reach the larger size in the same ecological niche. The other effect of the introduced factor is that additional non-selective killing factors limit the population size not only directly but also by shrinking the effective ecological niche capacity.

Computer simulation of vasectomy for wolf control

USGS Publications Warehouse

Haight, R.G.; Mech, L.D.

1997-01-01

Recovering gray wolf (Canis lupus) populations in the Lake Superior region of the United States are prompting state management agencies to consider strategies to control population growth. In addition to wolf removal, vasectomy has been proposed. To predict the population effects of different sterilization and removal strategies, we developed a simulation model of wolf dynamics using simple rules for demography and dispersal. Simulations suggested that the effects of vasectomy and removal in a disjunct population depend largely on the degree of annual immigration. With low immigration, periodic sterilization reduced pup production and resulted in lower rates of territory recolonization. Consequently, average pack size, number of packs, and population size were significantly less than those for an untreated population. Periodically removing a proportion of the population produced roughly the same trends as did sterilization; however, more than twice as many wolves had to be removed than sterilized. With high immigration, periodic sterilization reduced pup production but not territory recolonization and produced only moderate reductions in population size relative to an untreated population. Similar reductions in population size were obtained by periodically removing large numbers of wolves. Our analysis does not address the possible effects of vasectomy on larger wolf populations, but it suggests that the subject should be considered through modeling or field testing.

The demographic consequences of mutualism: ants increase host-plant fruit production but not population growth.

PubMed

Ford, Kevin R; Ness, Joshua H; Bronstein, Judith L; Morris, William F

2015-10-01

The impact of mutualists on a partner's demography depends on how they affect the partner's multiple vital rates and how those vital rates, in turn, affect population growth. However, mutualism studies rarely measure effects on multiple vital rates or integrate them to assess the ultimate impact on population growth. We used vital rate data, population models and simulations of long-term population dynamics to quantify the demographic impact of a guild of ant species on the plant Ferocactus wislizeni. The ants feed at the plant's extrafloral nectaries and attack herbivores attempting to consume reproductive organs. Ant-guarded plants produced significantly more fruit, but ants had no significant effect on individual growth or survival. After integrating ant effects across these vital rates, we found that projected population growth was not significantly different between unguarded and ant-guarded plants because population growth was only weakly influenced by differences in fruit production (though strongly influenced by differences in individual growth and survival). However, simulations showed that ants could positively affect long-term plant population dynamics through services provided during rare but important events (herbivore outbreaks that reduce survival or years of high seedling recruitment associated with abundant precipitation). Thus, in this seemingly clear example of mutualism, the interaction may actually yield no clear benefit to plant population growth, or if it does, may only do so through the actions of the ants during rare events. These insights demonstrate the value of taking a demographic approach to studying the consequences of mutualism.

Simulation of emotional contagion using modified SIR model: A cellular automaton approach

NASA Astrophysics Data System (ADS)

Fu, Libi; Song, Weiguo; Lv, Wei; Lo, Siuming

2014-07-01

Emotion plays an important role in the decision-making of individuals in some emergency situations. The contagion of emotion may induce either normal or abnormal consolidated crowd behavior. This paper aims to simulate the dynamics of emotional contagion among crowds by modifying the epidemiological SIR model to a cellular automaton approach. This new cellular automaton model, entitled the “CA-SIRS model”, captures the dynamic process ‘susceptible-infected-recovered-susceptible', which is based on SIRS contagion in epidemiological theory. Moreover, in this new model, the process is integrated with individual movement. The simulation results of this model show that multiple waves and dynamical stability around a mean value will appear during emotion spreading. It was found that the proportion of initial infected individuals had little influence on the final stable proportion of infected population in a given system, and that infection frequency increased with an increase in the average crowd density. Our results further suggest that individual movement accelerates the spread speed of emotion and increases the stable proportion of infected population. Furthermore, decreasing the duration of an infection and the probability of reinfection can markedly reduce the number of infected individuals. It is hoped that this study will be helpful in crowd management and evacuation organization.

A stochastic simulator of birth-death master equations with application to phylodynamics.

PubMed

Vaughan, Timothy G; Drummond, Alexei J

2013-06-01

In this article, we present a versatile new software tool for the simulation and analysis of stochastic models of population phylodynamics and chemical kinetics. Models are specified via an expressive and human-readable XML format and can be used as the basis for generating either single population histories or large ensembles of such histories. Importantly, phylogenetic trees or networks can be generated alongside the histories they correspond to, enabling investigations into the interplay between genealogies and population dynamics. Summary statistics such as means and variances can be recorded in place of the full ensemble, allowing for a reduction in the amount of memory used--an important consideration for models including large numbers of individual subpopulations or demes. In the case of population size histories, the resulting simulation output is written to disk in the flexible JSON format, which is easily read into numerical analysis environments such as R for visualization or further processing. Simulated phylogenetic trees can be recorded using the standard Newick or NEXUS formats, with extensions to these formats used for non-tree-like inheritance relationships.

A Stochastic Simulator of Birth–Death Master Equations with Application to Phylodynamics

PubMed Central

Vaughan, Timothy G.; Drummond, Alexei J.

2013-01-01

In this article, we present a versatile new software tool for the simulation and analysis of stochastic models of population phylodynamics and chemical kinetics. Models are specified via an expressive and human-readable XML format and can be used as the basis for generating either single population histories or large ensembles of such histories. Importantly, phylogenetic trees or networks can be generated alongside the histories they correspond to, enabling investigations into the interplay between genealogies and population dynamics. Summary statistics such as means and variances can be recorded in place of the full ensemble, allowing for a reduction in the amount of memory used—an important consideration for models including large numbers of individual subpopulations or demes. In the case of population size histories, the resulting simulation output is written to disk in the flexible JSON format, which is easily read into numerical analysis environments such as R for visualization or further processing. Simulated phylogenetic trees can be recorded using the standard Newick or NEXUS formats, with extensions to these formats used for non-tree-like inheritance relationships. PMID:23505043

Towards a complex systems approach in sports injury research: simulating running-related injury development with agent-based modelling.

PubMed

Hulme, Adam; Thompson, Jason; Nielsen, Rasmus Oestergaard; Read, Gemma J M; Salmon, Paul M

2018-06-18

There have been recent calls for the application of the complex systems approach in sports injury research. However, beyond theoretical description and static models of complexity, little progress has been made towards formalising this approach in way that is practical to sports injury scientists and clinicians. Therefore, our objective was to use a computational modelling method and develop a dynamic simulation in sports injury research. Agent-based modelling (ABM) was used to model the occurrence of sports injury in a synthetic athlete population. The ABM was developed based on sports injury causal frameworks and was applied in the context of distance running-related injury (RRI). Using the acute:chronic workload ratio (ACWR), we simulated the dynamic relationship between changes in weekly running distance and RRI through the manipulation of various 'athlete management tools'. The findings confirmed that building weekly running distances over time, even within the reported ACWR 'sweet spot', will eventually result in RRI as athletes reach and surpass their individual physical workload limits. Introducing training-related error into the simulation and the modelling of a 'hard ceiling' dynamic resulted in a higher RRI incidence proportion across the population at higher absolute workloads. The presented simulation offers a practical starting point to further apply more sophisticated computational models that can account for the complex nature of sports injury aetiology. Alongside traditional forms of scientific inquiry, the use of ABM and other simulation-based techniques could be considered as a complementary and alternative methodological approach in sports injury research. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Inferring infection hazard in wildlife populations by linking data across individual and population scales.

PubMed

Pepin, Kim M; Kay, Shannon L; Golas, Ben D; Shriner, Susan S; Gilbert, Amy T; Miller, Ryan S; Graham, Andrea L; Riley, Steven; Cross, Paul C; Samuel, Michael D; Hooten, Mevin B; Hoeting, Jennifer A; Lloyd-Smith, James O; Webb, Colleen T; Buhnerkempe, Michael G

2017-03-01

Our ability to infer unobservable disease-dynamic processes such as force of infection (infection hazard for susceptible hosts) has transformed our understanding of disease transmission mechanisms and capacity to predict disease dynamics. Conventional methods for inferring FOI estimate a time-averaged value and are based on population-level processes. Because many pathogens exhibit epidemic cycling and FOI is the result of processes acting across the scales of individuals and populations, a flexible framework that extends to epidemic dynamics and links within-host processes to FOI is needed. Specifically, within-host antibody kinetics in wildlife hosts can be short-lived and produce patterns that are repeatable across individuals, suggesting individual-level antibody concentrations could be used to infer time since infection and hence FOI. Using simulations and case studies (influenza A in lesser snow geese and Yersinia pestis in coyotes), we argue that with careful experimental and surveillance design, the population-level FOI signal can be recovered from individual-level antibody kinetics, despite substantial individual-level variation. In addition to improving inference, the cross-scale quantitative antibody approach we describe can reveal insights into drivers of individual-based variation in disease response, and the role of poorly understood processes such as secondary infections, in population-level dynamics of disease. © 2017 John Wiley & Sons Ltd/CNRS.

Inferring infection hazard in wildlife populations by linking data across individual and population scales

USGS Publications Warehouse

Pepin, Kim M.; Kay, Shannon L.; Golas, Ben D.; Shriner, Susan A.; Gilbert, Amy T.; Miller, Ryan S.; Graham, Andrea L.; Riley, Steven; Cross, Paul C.; Samuel, Michael D.; Hooten, Mevin B.; Hoeting, Jennifer A.; Lloyd-Smith, James O.; Webb, Colleen T.; Buhnerkempe, Michael G.

2017-01-01

Our ability to infer unobservable disease-dynamic processes such as force of infection (infection hazard for susceptible hosts) has transformed our understanding of disease transmission mechanisms and capacity to predict disease dynamics. Conventional methods for inferring FOI estimate a time-averaged value and are based on population-level processes. Because many pathogens exhibit epidemic cycling and FOI is the result of processes acting across the scales of individuals and populations, a flexible framework that extends to epidemic dynamics and links within-host processes to FOI is needed. Specifically, within-host antibody kinetics in wildlife hosts can be short-lived and produce patterns that are repeatable across individuals, suggesting individual-level antibody concentrations could be used to infer time since infection and hence FOI. Using simulations and case studies (influenza A in lesser snow geese and Yersinia pestis in coyotes), we argue that with careful experimental and surveillance design, the population-level FOI signal can be recovered from individual-level antibody kinetics, despite substantial individual-level variation. In addition to improving inference, the cross-scale quantitative antibody approach we describe can reveal insights into drivers of individual-based variation in disease response, and the role of poorly understood processes such as secondary infections, in population-level dynamics of disease.

An overview of the utility of population simulation software in molecular ecology.

PubMed

Hoban, Sean

2014-05-01

Stochastic simulation software that simultaneously model genetic, population and environmental processes can inform many topics in molecular ecology. These include forecasting species and community response to environmental change, inferring dispersal ecology, revealing cryptic mating, quantifying past population dynamics, assessing in situ management options and monitoring neutral and adaptive biodiversity change. Advances in population demographic-genetic simulation software, especially with respect to individual life history, landscapes and genetic processes, are transforming and expanding the ways that molecular data can be used. The aim of this review is to explain the roles that such software can play in molecular ecology studies (whether as a principal component or a supporting function) so that researchers can decide whether, when and precisely how simulations can be incorporated into their work. First, I use seven case studies to demonstrate how simulations are employed, their specific advantage/necessity and what alternative or complementary (nonsimulation) approaches are available. I also explain how simulations can be integrated with existing spatial, environmental, historical and genetic data sets. I next describe simulation features that may be of interest to molecular ecologists, such as spatial and behavioural considerations and species' interactions, to provide guidance on how particular simulation capabilities can serve particular needs. Lastly, I discuss the prospect of simulation software in emerging challenges (climate change, biodiversity monitoring, population exploitation) and opportunities (genomics, ancient DNA), in order to emphasize that the scope of simulation-based work is expanding. I also suggest practical considerations, priorities and elements of best practice. This should accelerate the uptake of simulation approaches and firmly embed them as a versatile tool in the molecular ecologist's toolbox. © 2014 John Wiley & Sons Ltd.

Sustainable and Smart City Planning Using Spatial Data in Wallonia

NASA Astrophysics Data System (ADS)

Stephenne, N.; Beaumont, B.; Hallot, E.; Wolff, E.; Poelmans, L.; Baltus, C.

2016-09-01

Simulating population distribution and land use changes in space and time offer opportunities for smart city planning. It provides a holistic and dynamic vision of fast changing urban environment to policy makers. Impacts, such as environmental and health risks or mobility issues, of policies can be assessed and adapted consequently. In this paper, we suppose that "Smart" city developments should be sustainable, dynamic and participative. This paper addresses these three smart objectives in the context of urban risk assessment in Wallonia, Belgium. The sustainable, dynamic and participative solution includes (i) land cover and land use mapping using remote sensing and GIS, (ii) population density mapping using dasymetric mapping, (iii) predictive modelling of land use changes and population dynamics and (iv) risk assessment. The comprehensive and long-term vision of the territory should help to draw sustainable spatial planning policies, to adapt remote sensing acquisition, to update GIS data and to refine risk assessment from regional to city scale.

A parallel implementation of an off-lattice individual-based model of multicellular populations

NASA Astrophysics Data System (ADS)

Harvey, Daniel G.; Fletcher, Alexander G.; Osborne, James M.; Pitt-Francis, Joe

2015-07-01

As computational models of multicellular populations include ever more detailed descriptions of biophysical and biochemical processes, the computational cost of simulating such models limits their ability to generate novel scientific hypotheses and testable predictions. While developments in microchip technology continue to increase the power of individual processors, parallel computing offers an immediate increase in available processing power. To make full use of parallel computing technology, it is necessary to develop specialised algorithms. To this end, we present a parallel algorithm for a class of off-lattice individual-based models of multicellular populations. The algorithm divides the spatial domain between computing processes and comprises communication routines that ensure the model is correctly simulated on multiple processors. The parallel algorithm is shown to accurately reproduce the results of a deterministic simulation performed using a pre-existing serial implementation. We test the scaling of computation time, memory use and load balancing as more processes are used to simulate a cell population of fixed size. We find approximate linear scaling of both speed-up and memory consumption on up to 32 processor cores. Dynamic load balancing is shown to provide speed-up for non-regular spatial distributions of cells in the case of a growing population.

Integrating association data and disease dynamics: an illustration using African Buffalo in Kruger National Park

USGS Publications Warehouse

Cross, Paul C.; James O, Lloyd-Smith; Bowers, Justin A.; Hay, Craig T.; Hofmeyr, Markus; Getz, Wayne M.

2004-01-01

Recognition is a prerequisite for non-random association amongst individuals. We explore how non-random association patterns (i.e. who spends time with whom) affect disease dynamics. We estimated the amount of time individuals spent together per month using radio-tracking data from African buffalo and incorporated these data into a dynamic social network model. The dynamic nature of the network has a strong influence on simulated disease dynamics particularly for diseases with shorter infectious periods. Cluster analyses of the association data demonstrated that buffalo herds were not as well defined as previously thought. Associations were more tightly clustered in 2002 than 2003, perhaps due to drier conditions in 2003. As a result, diseases may spread faster during drought conditions due to increased population mixing. Association data are often collected but this is the first use of empirical data in a network disease model in a wildlife population.

How does selfing affect the dynamics of selfish transposable elements?

PubMed

Boutin, Thibaud S; Le Rouzic, Arnaud; Capy, Pierre

2012-03-07

Many theoretical models predicting the dynamics of transposable elements (TEs) in genomes, populations, and species have already been proposed. However, most of them only focus on populations of sexual diploid individuals, and TE dynamics in populations partly composed by autogamous individuals remains poorly investigated. To estimate the impact of selfing on TE dynamics, the short- and long-term evolution of TEs was simulated in outcrossing populations with various proportions of selfing individuals. Selfing has a deep impact on TE dynamics: the higher the selfing rate, the lower the probability of invasion. Already known non-equilibrium dynamics (complete loss, domestication, cyclical invasion of TEs) can all be described whatever the mating system. However, their pattern and their respective frequencies greatly depend on the selfing rate. For instance, in cyclical dynamics resulting from interactions between autonomous and non-autonomous copies, cycles are faster when the selfing rate increases. Interestingly, an abrupt change in the mating system from sexuality to complete asexuality leads to the loss of all the elements over a few hundred generations. In general, for intermediate selfing rates, the transposition activity remains maintained. Our theoretical results evidence that a clear and systematic contrast in TE content according to the mating system is expected, with a smooth transition for intermediate selfing rates. Several parameters impact the TE copy number, and all dynamics described in allogamous populations can be also observed in partly autogamous species. This study thus provides new insights to understand the complex signal from empirical comparison of closely related species with different mating systems.

Modeling structured population dynamics using data from unmarked individuals

USGS Publications Warehouse

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

2014-01-01

The study of population dynamics requires unbiased, precise estimates of abundance and vital rates that account for the demographic structure inherent in all wildlife and plant populations. Traditionally, these estimates have only been available through approaches that rely on intensive mark–recapture data. We extended recently developed N-mixture models to demonstrate how demographic parameters and abundance can be estimated for structured populations using only stage-structured count data. Our modeling framework can be used to make reliable inferences on abundance as well as recruitment, immigration, stage-specific survival, and detection rates during sampling. We present a range of simulations to illustrate the data requirements, including the number of years and locations necessary for accurate and precise parameter estimates. We apply our modeling framework to a population of northern dusky salamanders (Desmognathus fuscus) in the mid-Atlantic region (USA) and find that the population is unexpectedly declining. Our approach represents a valuable advance in the estimation of population dynamics using multistate data from unmarked individuals and should additionally be useful in the development of integrated models that combine data from intensive (e.g., mark–recapture) and extensive (e.g., counts) data sources.

Spatial-temporal population dynamics across species range: from center to margin

USGS Publications Warehouse

Guo, Q.; Taper, M.L.; Schoenberger, M.; Brandl, J.

2005-01-01

Understanding the boundaries of species' ranges and the variations in population dynamics from the centre to margin of a species' range is critical. This study simulated spatial-temporal patterns of birth and death rates and migration across a species' range in different seasons. Our results demonstrated the importance of dispersal and migration in altering birth and death rates, balancing source and sink habitats, and governing expansion or contraction of species' ranges in changing environments. We also showed that the multiple equilibria of metapopulations across a species' range could be easily broken following climatic changes or physical disturbances either or local or regional. Although we refer to our models as describing the population dynamics across whole species' range, they should also apply to small-scale habitats (metapopulations) in which species abundance follows a humped pattern or to any ecosystem or landscape where strong central-marginal (C-M) environmental gradients exist. Conservation of both central and marginal populations would therefore be equally important considerations in making management decisions.

Spatial-temporal population dynamics across species range: From centre to margin

USGS Publications Warehouse

Guo, Q.; Taper, M.; Schoenberger, M.; Brandle, J.

2005-01-01

Understanding the boundaries of species' ranges and the variations in population dynamics from the centre to margin of a species' range is critical. This study simulated spatial-temporal patterns of birth and death rates and migration across a species' range in different seasons. Our results demonstrated the importance of dispersal and migration in altering birth and death rates, balancing source and sink habitats, and governing expansion or contraction of species' ranges in changing environments. We also showed that the multiple equilibria of metapopulations across a species' range could be easily broken following climatic changes or physical disturbances either local or regional. Although we refer to our models as describing the population dynamics across whole species' range, they should also apply to small-scale habitats (metapopulations) in which species abundance follows a humped pattern or to any ecosystem or landscape where strong central-marginal (C-M) environmental gradients exist. Conservation of both central and marginal populations would therefore be equally important considerations in making management decisions.

Scale-invariance underlying the logistic equation and its social applications

NASA Astrophysics Data System (ADS)

Hernando, A.; Plastino, A.

2013-01-01

On the basis of dynamical principles we i) advance a derivation of the Logistic Equation (LE), widely employed (among multiple applications) in the simulation of population growth, and ii) demonstrate that scale-invariance and a mean-value constraint are sufficient and necessary conditions for obtaining it. We also generalize the LE to multi-component systems and show that the above dynamical mechanisms underlie a large number of scale-free processes. Examples are presented regarding city-populations, diffusion in complex networks, and popularity of technological products, all of them obeying the multi-component logistic equation in an either stochastic or deterministic way.

A Mathematical Model of Economic Population Dynamics in a Country That Has Optimal Zakat Management

NASA Astrophysics Data System (ADS)

Subhan, M.

2018-04-01

Zakat is the main tools against two issues in Islamic economy: economic justice and helping the poor. However, no government of Islamic countries can solve the economic disparity today. A mathematical model could give some understanding about this phenomenon. The goal of this research is to obtain a mathematical model that can describe the dynamic of economic group population. The research is theoretical based on relevance references. From the analytical and numerical simulation, we conclude that well-manage zakat and full comitment of the wealthy can achieve wealth equilibrium that represents minimum poverty.

Big-leaf mahogany Swietenia macrophylla population dynamics and implications for sustainable management

Treesearch

James Grogan; R. Matthew Landis; Christopher M. Free; Mark D. Schulze; Marco Lentini; Mark S. Ashton

2014-01-01

Summary 1. The impacts of selective harvesting in tropical forests on population recovery and future timber yields by high-value species remain largely unknown for lack of demographic data spanning all phases of life history, from seed to senescence. In this study, we use an individual- based model parameterized using 15 years of annual census data to simulate...

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

PubMed

Du, Jinming; Wu, Bin; Wang, Long

2015-01-26

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.

Chloroplast microsatellites reveal colonization and metapopulation dynamics in the Canary Island pine

PubMed Central

Navascués, Miguel; Vaxevanidou, Zafeiro; González-Martínez, Santiago C; Climent, José; Gil, Luis; Emerson, Brent C

2006-01-01

Chloroplast microsatellites are becoming increasingly popular markers for population genetic studies in plants, but there has been little focus on their potential for demographic inference. In this work the utility of chloroplast microsatellites for the study of population expansions was explored. First, we investigated the power of mismatch distribution analysis and the FS test with coalescent simulations of different demographic scenarios. We then applied those methods to empirical data obtained for the Canary Island pine (Pinus canariensis). The results of the simulations showed that chloroplast microsatellites are sensitive to sudden population growth. The power of the FS test and accuracy of demographic parameter estimates, such as the time of expansion, were reduced proportionally to the level of homoplasy within the data. The analysis of Canary Island pine chloroplast microsatellite data indicated population expansions for almost all sample localities. Demographic expansions at the island level can be explained by the colonisation of the archipelago by the pine, while population expansions of different ages in different localities within an island appear to be the result of local extinctions and recolonisation dynamics. Comparable mitochondrial DNA sequence data from a parasite of P. canariensis, the weevil Brachyderes rugatus, supports this scenario, suggesting a key role for volcanism in the evolution of pine forest communities in the Canary Islands. PMID:16911194

Effects of dispersal on total biomass in a patchy, heterogeneous system: analysis and experiment.

USGS Publications Warehouse

Zhang, Bo; Liu, Xin; DeAngelis, Donald L.; Ni, Wei-Ming; Wang, G Geoff

2015-01-01

An intriguing recent result from mathematics is that a population diffusing at an intermediate rate in an environment in which resources vary spatially will reach a higher total equilibrium biomass than the population in an environment in which the same total resources are distributed homogeneously. We extended the current mathematical theory to apply to logistic growth and also showed that the result applies to patchy systems with dispersal among patches, both for continuous and discrete time. This allowed us to make specific predictions, through simulations, concerning the biomass dynamics, which were verified by a laboratory experiment. The experiment was a study of biomass growth of duckweed (Lemna minor Linn.), where the resources (nutrients added to water) were distributed homogeneously among a discrete series of water-filled containers in one treatment, and distributed heterogeneously in another treatment. The experimental results showed that total biomass peaked at an intermediate, relatively low, diffusion rate, higher than the total carrying capacity of the system and agreeing with the simulation model. The implications of the experiment to dynamics of source, sink, and pseudo-sink dynamics are discussed.

On the accuracy of the LSC-IVR approach for excitation energy transfer in molecular aggregates

NASA Astrophysics Data System (ADS)

Teh, Hung-Hsuan; Cheng, Yuan-Chung

2017-04-01

We investigate the applicability of the linearized semiclassical initial value representation (LSC-IVR) method to excitation energy transfer (EET) problems in molecular aggregates by simulating the EET dynamics of a dimer model in a wide range of parameter regime and comparing the results to those obtained from a numerically exact method. It is found that the LSC-IVR approach yields accurate population relaxation rates and decoherence rates in a broad parameter regime. However, the classical approximation imposed by the LSC-IVR method does not satisfy the detailed balance condition, generally leading to incorrect equilibrium populations. Based on this observation, we propose a post-processing algorithm to solve the long time equilibrium problem and demonstrate that this long-time correction method successfully removed the deviations from exact results for the LSC-IVR method in all of the regimes studied in this work. Finally, we apply the LSC-IVR method to simulate EET dynamics in the photosynthetic Fenna-Matthews-Olson complex system, demonstrating that the LSC-IVR method with long-time correction provides excellent description of coherent EET dynamics in this typical photosynthetic pigment-protein complex.

Modeling Selection and Extinction Mechanisms of Biological Systems

NASA Astrophysics Data System (ADS)

Amirjanov, Adil

In this paper, the behavior of a genetic algorithm is modeled to enhance its applicability as a modeling tool of biological systems. A new description model for selection mechanism is introduced which operates on a portion of individuals of population. The extinction and recolonization mechanism is modeled, and solving the dynamics analytically shows that the genetic drift in the population with extinction/recolonization is doubled. The mathematical analysis of the interaction between selection and extinction/recolonization processes is carried out to assess the dynamics of motion of the macroscopic statistical properties of population. Computer simulations confirm that the theoretical predictions of described models are in good approximations. A mathematical model of GA dynamics was also examined, which describes the anti-predator vigilance in an animal group with respect to a known analytical solution of the problem, and showed a good agreement between them to find the evolutionarily stable strategies.

Mapping the ecological networks of microbial communities.

PubMed

Xiao, Yandong; Angulo, Marco Tulio; Friedman, Jonathan; Waldor, Matthew K; Weiss, Scott T; Liu, Yang-Yu

2017-12-11

Mapping the ecological networks of microbial communities is a necessary step toward understanding their assembly rules and predicting their temporal behavior. However, existing methods require assuming a particular population dynamics model, which is not known a priori. Moreover, those methods require fitting longitudinal abundance data, which are often not informative enough for reliable inference. To overcome these limitations, here we develop a new method based on steady-state abundance data. Our method can infer the network topology and inter-taxa interaction types without assuming any particular population dynamics model. Additionally, when the population dynamics is assumed to follow the classic Generalized Lotka-Volterra model, our method can infer the inter-taxa interaction strengths and intrinsic growth rates. We systematically validate our method using simulated data, and then apply it to four experimental data sets. Our method represents a key step towards reliable modeling of complex, real-world microbial communities, such as the human gut microbiota.

The origin of ultra diffuse galaxies: stellar feedback and quenching

NASA Astrophysics Data System (ADS)

Chan, T. K.; Kereš, D.; Wetzel, A.; Hopkins, P. F.; Faucher-Giguère, C.-A.; El-Badry, K.; Garrison-Kimmel, S.; Boylan-Kolchin, M.

2018-05-01

We test if the cosmological zoom-in simulations of isolated galaxies from the FIRE project reproduce the properties of ultra diffuse galaxies (UDGs). We show that outflows that dynamically heat galactic stars, together with a passively aging stellar population after imposed quenching, naturally reproduce the observed population of red UDGs, without the need for high spin halos, or dynamical influence from their host cluster. We reproduce the range of surface brightness, radius and absolute magnitude of the observed red UDGs by quenching simulated galaxies at a range of different times. They represent a mostly uniform population of dark matter-dominated dwarf galaxies with M* ˜ 108 M⊙, low metallicity and a broad range of ages; the more massive the UDGs, the older they are. The most massive red UDG in our sample (M* ˜ 3 × 108M⊙) requires quenching at z ˜ 3 when its halo reached Mh ˜ 1011 M⊙. Our simulated UDGs form with normal stellar-to-halo ratios and match the central enclosed masses and the velocity dispersions of the observed UDGs. Enclosed masses remain largely fixed across a broad range of quenching times because the central regions of their dark matter halos complete their growth early. If our simulated dwarfs are not quenched, they evolve into bluer low-surface brightness galaxies with M/L similar to observed field dwarfs. While our simulation sample covers a limited range of formation histories and halo masses, we predict that UDG is a common, and perhaps even dominant, galaxy type around M* ˜ 108 M⊙, both in the field and in clusters.

The origin of ultra diffuse galaxies: stellar feedback and quenching

NASA Astrophysics Data System (ADS)

Chan, T. K.; Kereš, D.; Wetzel, A.; Hopkins, P. F.; Faucher-Giguère, C.-A.; El-Badry, K.; Garrison-Kimmel, S.; Boylan-Kolchin, M.

2018-07-01

We test if the cosmological zoom-in simulations of isolated galaxies from the FIRE project reproduce the properties of ultra diffuse galaxies (UDGs). We show that outflows that dynamically heat galactic stars, together with a passively aging stellar population after imposed quenching, naturally reproduce the observed population of red UDGs, without the need for high spin haloes, or dynamical influence from their host cluster. We reproduce the range of surface brightness, radius, and absolute magnitude of the observed red UDGs by quenching simulated galaxies at a range of different times. They represent a mostly uniform population of dark matter-dominated dwarf galaxies with M* ˜ 108 M⊙, low metallicity, and a broad range of ages; the more massive the UDGs, the older they are. The most massive red UDG in our sample (M* ˜ 3 × 108 M⊙) requires quenching at z ˜ 3 when its halo reached Mh ˜ 1011 M⊙. Our simulated UDGs form with normal stellar-to-halo ratios and match the central enclosed masses and the velocity dispersions of the observed UDGs. Enclosed masses remain largely fixed across a broad range of quenching times because the central regions of their dark matter haloes complete their growth early. If our simulated dwarfs are not quenched, they evolve into bluer low surface brightness galaxies with M/L similar to observed field dwarfs. While our simulation sample covers a limited range of formation histories and halo masses, we predict that UDG is a common, and perhaps even dominant, galaxy type around M* ˜ 108 M⊙, both in the field and in clusters.

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

PubMed

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

2017-05-01

Social networks provide an established tool to implement heterogeneous contact structures in epidemiological models. Dynamic temporal changes in contact structure and ranging behaviour of wildlife may impact disease dynamics. A consensus has yet to emerge, however, concerning the conditions in which network dynamics impact model outcomes, as compared to static approximations that average contact rates over longer time periods. Furthermore, as many pathogens can be transmitted both environmentally and via close contact, it is important to investigate the relative influence of both transmission routes in real-world populations. Here, we use empirically derived networks from a population of wild primates, Verreaux's sifakas (Propithecus verreauxi), and simulated networks to investigate pathogen spread in dynamic vs. static social networks. First, we constructed a susceptible-exposed-infected-recovered model of Cryptosporidium spread in wild Verreaux's sifakas. We incorporated social and environmental transmission routes and parameterized the model for two different climatic seasons. Second, we used simulated networks and greater variation in epidemiological parameters to investigate the conditions in which dynamic networks produce larger outbreak sizes than static networks. We found that average outbreak size of Cryptosporidium infections in sifakas was larger when the disease was introduced in the dry season than in the wet season, driven by an increase in home range overlap towards the end of the dry season. Regardless of season, dynamic networks always produced larger average outbreak sizes than static networks. Larger outbreaks in dynamic models based on simulated networks occurred especially when the probability of transmission and recovery were low. Variation in tie strength in the dynamic networks also had a major impact on outbreak size, while network modularity had a weaker influence than epidemiological parameters that determine transmission and recovery. Our study adds to emerging evidence that dynamic networks can change predictions of disease dynamics, especially if the disease shows low transmissibility and a long infectious period, and when environmental conditions lead to enhanced between-group contact after an infectious agent has been introduced. © 2016 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

Simulating range-wide population and breeding habitat dynamics for an endangered woodland warbler in the face of uncertainty

USGS Publications Warehouse

Adam Duarte,; Hatfield, Jeffrey; Todd M. Swannack,; Michael R. J. Forstner,; M. Clay Green,; Floyd W. Weckerly,

2015-01-01

Population viability analyses provide a quantitative approach that seeks to predict the possible future status of a species of interest under different scenarios and, therefore, can be important components of large-scale species’ conservation programs. We created a model and simulated range-wide population and breeding habitat dynamics for an endangered woodland warbler, the golden-cheeked warbler (Setophaga chrysoparia). Habitat-transition probabilities were estimated across the warbler's breeding range by combining National Land Cover Database imagery with multistate modeling. Using these estimates, along with recently published demographic estimates, we examined if the species can remain viable into the future given the current conditions. Lastly, we evaluated if protecting a greater amount of habitat would increase the number of warblers that can be supported in the future by systematically increasing the amount of protected habitat and comparing the estimated terminal carrying capacity at the end of 50 years of simulated habitat change. The estimated habitat-transition probabilities supported the hypothesis that habitat transitions are unidirectional, whereby habitat is more likely to diminish than regenerate. The model results indicated population viability could be achieved under current conditions, depending on dispersal. However, there is considerable uncertainty associated with the population projections due to parametric uncertainty. Model results suggested that increasing the amount of protected lands would have a substantial impact on terminal carrying capacities at the end of a 50-year simulation. Notably, this study identifies the need for collecting the data required to estimate demographic parameters in relation to changes in habitat metrics and population density in multiple regions, and highlights the importance of establishing a common definition of what constitutes protected habitat, what management goals are suitable within those protected areas, and a standard operating procedure to identify areas of priority for habitat conservation efforts. Therefore, we suggest future efforts focus on these aspects of golden-cheeked warbler conservation and ecology.

In silico modelling of drug–polymer interactions for pharmaceutical formulations

PubMed Central

Ahmad, Samina; Johnston, Blair F.; Mackay, Simon P.; Schatzlein, Andreas G.; Gellert, Paul; Sengupta, Durba; Uchegbu, Ijeoma F.

2010-01-01

Selecting polymers for drug encapsulation in pharmaceutical formulations is usually made after extensive trial and error experiments. To speed up excipient choice procedures, we have explored coarse-grained computer simulations (dissipative particle dynamics (DPD) and coarse-grained molecular dynamics using the MARTINI force field) of polymer–drug interactions to study the encapsulation of prednisolone (log p = 1.6), paracetamol (log p = 0.3) and isoniazid (log p = −1.1) in poly(l-lactic acid) (PLA) controlled release microspheres, as well as the encapsulation of propofol (log p = 4.1) in bioavailability enhancing quaternary ammonium palmitoyl glycol chitosan (GCPQ) micelles. Simulations have been compared with experimental data. DPD simulations, in good correlation with experimental data, correctly revealed that hydrophobic drugs (prednisolone and paracetamol) could be encapsulated within PLA microspheres and predicted the experimentally observed paracetamol encapsulation levels (5–8% of the initial drug level) in 50 mg ml−1 PLA microspheres, but only when initial paracetamol levels exceeded 5 mg ml−1. However, the mesoscale technique was unable to model the hydrophilic drug (isoniazid) encapsulation (4–9% of the initial drug level) which was observed in experiments. Molecular dynamics simulations using the MARTINI force field indicated that the self-assembly of GCPQ is rapid, with propofol residing at the interface between micellar hydrophobic and hydrophilic groups, and that there is a heterogeneous distribution of propofol within the GCPQ micelle population. GCPQ–propofol experiments also revealed a population of relatively empty and drug-filled GCPQ particles. PMID:20519214

Simulation and evaluation on the eco-industrial system of Changchun economic and technological development zone, China.

PubMed

Zhao, Yan; Shang, Jin-cheng; Chen, Chong; Wu, He-nan

2008-04-01

Reasonable structure, adaptive patterns and effective regulation of society, economy and environment subsystems should be taken into account in order to obtain harmonious development of urban eco-industrial system. We simulated and evaluated a redesigned eco-industrial system in Changchun Economic and Technological Development Zone (CCETDZ) in the present work using system dynamics and grey cluster methods. Four typical development strategies were simulated during 2005-2020 via standard system dynamic models. Furthermore, analytic hierarchy process and grey cluster allowed for the eco-industrial system evaluation and scenarios optimizing. Our dynamic simulation and statistical analysis revealed that: (1) CCETDZ would have different development scenarios under different strategies. The total population in scenario 2 grew most rapidly and reached 3.28 x 10(5) in 2020, exceeding its long-term planning expected population. And the GDP differences among these four scenarios would amount to 6.41 x 10(10) RMB. On the other hand, environmental pollution would become serious along with economy increasing. As a restriction factor, positive or negative increment of water resource will occur according to the selected strategy. (2) The fourth strategy would have the best efficiency, which means that the most efficiently development of CCETDZ required to take science, technology, environment progress and economy increase into account at the same time. (3) Positive environment protection measures, such as cleaner production, green manufacture, production life cycle management and environment friendly industries, should be attached great importance the same as economy development during 2005-2020 in CCETDZ.

Odour-impact assessment around a landfill site from weather-type classification, complaint inventory and numerical simulation.

PubMed

Chemel, C; Riesenmey, C; Batton-Hubert, M; Vaillant, H

2012-01-01

Gases released from landfill sites into the atmosphere have the potential to cause olfactory nuisances within the surrounding communities. Landfill sites are often located over complex topography for convenience mainly related to waste disposal and environmental masking. Dispersion of odours is strongly conditioned by local atmospheric dynamics. Assessment of odour impacts needs to take into account the variability of local atmospheric dynamics. In this study, we discuss a method to assess odour impacts around a landfill site located over complex terrain in order to provide information to be used subsequently to identify management strategies to reduce olfactory nuisances in the residential neighbourhoods. A weather-type classification is defined in order to identify meteorological conditions under which olfactory nuisances are to be expected. A non-steady state Gaussian model and a full-physics meteorological model are used to predict olfactory nuisances, for both the winter and summer scenarios that lead to the majority of complaints in neighbourhoods surrounding the landfill site. Simulating representative scenarios rather than full years make a high resolution simulation of local atmospheric dynamics in space and time possible. Results underline the key role of local atmospheric dynamics in driving the dispersion of odours. The odour concentration simulated by the full-physics meteorological model is combined with the density of the population in order to calculate an average population exposure for the two scenarios. Results of this study are expected to provide helpful information to develop technical solutions for an effective management of landfill operations, which would reduce odour impacts within the surrounding communities. Copyright © 2011 Elsevier Ltd. All rights reserved.

Optimal control of the population dynamics of the ground vibrational state of a polyatomic molecule

NASA Astrophysics Data System (ADS)

de Clercq, Ludwig E.; Botha, Lourens R.; Rohwer, Erich G.; Uys, Hermann; Du Plessis, Anton

2011-03-01

Simulating coherent control with femtosecond pulses on a polyatomic molecule with anharmonic splitting was demonstrated. The simulation mimicked pulse shaping of a Spatial Light Modulator (SLM) and the interaction was described with the Von Neumann equation. A transform limited pulse with a fluence of 600 J/m2 produced 18% of the population in an arbitrarily chosen upper vibrational state, n =2. Phase only and amplitude only shaped pulse produced optimum values of 60% and 40% respectively, of the population in the vibrational state, n=2, after interaction with the ultra short pulse. The combination of phase and amplitude shaping produced the best results, 80% of the population was in the targeted vibrational state, n=2, after interaction. These simulations were carried out with all the population initially in the ground vibrational level. It was found that even at room temperatures (300 Kelvin) that the population in the selected level is comparable with the case where all population is initially in the ground vibrational state. With a 10% noise added to the amplitude and phase masks, selective excitation of the targeted vibrational state is still possible.

Conservation biology for suites of species: Demographic modeling for Pacific island kingfishers

USGS Publications Warehouse

Kesler, D.C.; Haig, S.M.

2007-01-01

Conservation practitioners frequently extrapolate data from single-species investigations when managing critically endangered populations. However, few researchers initiate work with the intent of making findings useful to conservation efforts for other species. We presented and explored the concept of conducting conservation-oriented research for suites of geographically separated populations with similar natural histories, resource needs, and extinction threats. An example was provided in the form of an investigation into the population demography of endangered Micronesian kingfishers (Todiramphus cinnamominus). We provided the first demographic parameter estimates for any of the 12 endangered Pacific Todiramphus species, and used results to develop a population projection matrix model for management throughout the insular Pacific. Further, we used the model for elasticity and simulation analyses with demographic values that randomly varied across ranges that might characterize congener populations. Results from elasticity and simulation analyses indicated that changes in breeding adult survival exerted the greatest magnitude of influence on population dynamics. However, changes in nestling survival were more consistently correlated with population dynamics as demographic rates were randomly altered. We concluded that conservation practitioners working with endangered Pacific kingfishers should primarily focus efforts on factors affecting nestling and breeder survival, and secondarily address fledgling juveniles and helpers. Further, we described how the generalized base model might be changed to focus on individual populations and discussed the potential application of multi-species models to other conservation situations. ?? 2007 Elsevier Ltd. All rights reserved.

Multi-agent Simulations of Population Behavior: A Promising Tool for Systems Biology.

PubMed

Colosimo, Alfredo

2018-01-01

This contribution reports on the simulation of some dynamical events observed in the collective behavior of different kinds of populations, ranging from shape-changing cells in a Petri dish to functionally correlated brain areas in vivo. The unifying methodological approach, based upon a Multi-Agent Simulation (MAS) paradigm as incorporated in the NetLogo™ interpreter, is a direct consequence of the cornerstone that simple, individual actions within a population of interacting agents often give rise to complex, collective behavior.The discussion will mainly focus on the emergence and spreading of synchronous activities within the population, as well as on the modulation of the collective behavior exerted by environmental force-fields. A relevant section of this contribution is dedicated to the extension of the MAS paradigm to Brain Network models. In such a general framework some recent applications taken from the direct experience of the author, and exploring the activation patterns characteristic of specific brain functional states, are described, and their impact on the Systems-Biology universe underlined.

Epidemic Process over the Commute Network in a Metropolitan Area

PubMed Central

Yashima, Kenta; Sasaki, Akira

2014-01-01

An understanding of epidemiological dynamics is important for prevention and control of epidemic outbreaks. However, previous studies tend to focus only on specific areas, indicating that application to another area or intervention strategy requires a similar time-consuming simulation. Here, we study the epidemic dynamics of the disease-spread over a commute network, using the Tokyo metropolitan area as an example, in an attempt to elucidate the general properties of epidemic spread over a commute network that could be used for a prediction in any metropolitan area. The model is formulated on the basis of a metapopulation network in which local populations are interconnected by actual commuter flows in the Tokyo metropolitan area and the spread of infection is simulated by an individual-based model. We find that the probability of a global epidemic as well as the final epidemic sizes in both global and local populations, the timing of the epidemic peak, and the time at which the epidemic reaches a local population are mainly determined by the joint distribution of the local population sizes connected by the commuter flows, but are insensitive to geographical or topological structure of the network. Moreover, there is a strong relation between the population size and the time that the epidemic reaches this local population and we are able to determine the reason for this relation as well as its dependence on the commute network structure and epidemic parameters. This study shows that the model based on the connection between the population size classes is sufficient to predict both global and local epidemic dynamics in metropolitan area. Moreover, the clear relation of the time taken by the epidemic to reach each local population can be used as a novel measure for intervention; this enables efficient intervention strategies in each local population prior to the actual arrival. PMID:24905831

Modeling the Impact of Baryons on Subhalo Populations with Machine Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nadler, Ethan O.; Mao, Yao -Yuan; Wechsler, Risa H.

Here, we identify subhalos in dark matter–only (DMO) zoom-in simulations that are likely to be disrupted due to baryonic effects by using a random forest classifier trained on two hydrodynamic simulations of Milky Way (MW)–mass host halos from the Latte suite of the Feedback in Realistic Environments (FIRE) project. We train our classifier using five properties of each disrupted and surviving subhalo: pericentric distance and scale factor at first pericentric passage after accretion and scale factor, virial mass, and maximum circular velocity at accretion. Our five-property classifier identifies disrupted subhalos in the FIRE simulations with an 85% out-of-bag classification score.more » We predict surviving subhalo populations in DMO simulations of the FIRE host halos, finding excellent agreement with the hydrodynamic results; in particular, our classifier outperforms DMO zoom-in simulations that include the gravitational potential of the central galactic disk in each hydrodynamic simulation, indicating that it captures both the dynamical effects of a central disk and additional baryonic physics. We also predict surviving subhalo populations for a suite of DMO zoom-in simulations of MW-mass host halos, finding that baryons impact each system consistently and that the predicted amount of subhalo disruption is larger than the host-to-host scatter among the subhalo populations. Although the small size and specific baryonic physics prescription of our training set limits the generality of our results, our work suggests that machine-learning classification algorithms trained on hydrodynamic zoom-in simulations can efficiently predict realistic subhalo populations.« less

Modeling the Impact of Baryons on Subhalo Populations with Machine Learning

DOE PAGES

Nadler, Ethan O.; Mao, Yao -Yuan; Wechsler, Risa H.; ...

2018-06-01

Here, we identify subhalos in dark matter–only (DMO) zoom-in simulations that are likely to be disrupted due to baryonic effects by using a random forest classifier trained on two hydrodynamic simulations of Milky Way (MW)–mass host halos from the Latte suite of the Feedback in Realistic Environments (FIRE) project. We train our classifier using five properties of each disrupted and surviving subhalo: pericentric distance and scale factor at first pericentric passage after accretion and scale factor, virial mass, and maximum circular velocity at accretion. Our five-property classifier identifies disrupted subhalos in the FIRE simulations with an 85% out-of-bag classification score.more » We predict surviving subhalo populations in DMO simulations of the FIRE host halos, finding excellent agreement with the hydrodynamic results; in particular, our classifier outperforms DMO zoom-in simulations that include the gravitational potential of the central galactic disk in each hydrodynamic simulation, indicating that it captures both the dynamical effects of a central disk and additional baryonic physics. We also predict surviving subhalo populations for a suite of DMO zoom-in simulations of MW-mass host halos, finding that baryons impact each system consistently and that the predicted amount of subhalo disruption is larger than the host-to-host scatter among the subhalo populations. Although the small size and specific baryonic physics prescription of our training set limits the generality of our results, our work suggests that machine-learning classification algorithms trained on hydrodynamic zoom-in simulations can efficiently predict realistic subhalo populations.« less

Modeling the spatial and temporal population dynamics of the copepod Centropages typicus in the northwestern Mediterranean Sea during the year 2001 using a 3D ecosystem model

NASA Astrophysics Data System (ADS)

Carlotti, F.; Eisenhauer, L.; Campbell, R.; Diaz, F.

2014-07-01

The spatio-temporal dynamics of a simulated Centropages typicus (Kröyer) population during the year 2001 at the regional scale of the northwestern Mediterranean Sea are addressed using a 3D coupled physical-biogeochemical model. The setup of the coupled biological model comprises a pelagic plankton ecosystem model and a stage-structured population model forced by the 3D velocity and temperature fields provided by an eddy-resolving regional circulation model. The population model for C. typicus (C. t. below) represents demographic processes through five groups of developmental stages, which depend on underlying individual growth and development processes and are forced by both biotic (prey and predator fields) and abiotic (temperature, advection) factors from the coupled physical-biogeochemical model. The objective is to characterize C. t. ontogenic habitats driven by physical and trophic processes. The annual dynamics are presented for two of the main oceanographic stations in the Gulf of Lions, which are representative of shelf and open sea conditions, while the spatial distributions over the whole area are presented for three dates during the year, in early and late spring and in winter. The simulated spatial patterns of C. t. developmental stages are closely related to mesoscale hydrodynamic features and circulation patterns. The seasonal and spatial distributions on the Gulf of Lions shelf depend on the seasonal interplay between the Rhône river plume, the mesoscale eddies on the shelf and the Northern Current acting as either as a dynamic barrier between the shelf and the open sea or allowing cross-shelf exchanges. In the central gyre of the northwestern Mediterranean Sea, the patchiness of plankton is tightly linked to mesoscale frontal systems, surface eddies and filaments and deep gradients. Due to its flexibility in terms of its diet, C. t. succeeds in maintaining its population in both coastal and offshore areas year round. The simulations suggest that the winte-spring food conditions are more favorable on the shelf for C. t., whereas in late summer and fall, the offshore depth-integrated food biomasses represent a larger resource for C. t., particularly when mesoscale structures and vertical discontinuities increase food patchiness. The development and reproduction of C. t. depend on the prey field within the mesoscale structures that induce a contrasting spatial distribution of successive developmental stages on a given observation date. In late fall and winter, the results of the model suggest the existence of three refuge areas where the population maintains winter generations near the coast and within the Rhone River plume, or offshore within canyons within the shelf break, or in the frontal system related to the Northern Current. The simulated spatial and temporal distributions as well as the life cycle and physiological features of C. t. are discussed in light of recent reviews on the dynamics of C. t. in the northwestern Mediterranean Sea.

Population rate dynamics and multineuron firing patterns in sensory cortex

PubMed Central

Okun, Michael; Yger, Pierre; Marguet, Stephan; Gerard-Mercier, Florian; Benucci, Andrea; Katzner, Steffen; Busse, Laura; Carandini, Matteo; Harris, Kenneth D.

2012-01-01

Cortical circuits encode sensory stimuli through the firing of neuronal ensembles, and also produce spontaneous population patterns in the absence of sensory drive. This population activity is often characterized experimentally by the distribution of multineuron “words” (binary firing vectors), and a match between spontaneous and evoked word distributions has been suggested to reflect learning of a probabilistic model of the sensory world. We analyzed multineuron word distributions in sensory cortex of anesthetized rats and cats, and found that they are dominated by fluctuations in population firing rate rather than precise interactions between individual units. Furthermore, cortical word distributions change when brain state shifts, and similar behavior is seen in simulated networks with fixed, random connectivity. Our results suggest that similarity or dissimilarity in multineuron word distributions could primarily reflect similarity or dissimilarity in population firing rate dynamics, and not necessarily the precise interactions between neurons that would indicate learning of sensory features. PMID:23197704

Allee effect and the uncertainty of population recovery.

PubMed

Kuparinen, Anna; Keith, David M; Hutchings, Jeffrey A

2014-06-01

Recovery of depleted populations is fundamentally important for conservation biology and sustainable resource harvesting. At low abundance, population growth rate, a primary determinant of population recovery, is generally assumed to be relatively fast because competition is low (i.e., negative density dependence). But population growth can be limited in small populations by an Allee effect. This is particularly relevant for collapsed populations or species that have not recovered despite large reductions in, or elimination of, threats. We investigated how an Allee effect can influence the dynamics of recovery. We used Atlantic cod (Gadus morhua) as the study organism and an empirically quantified Allee effect for the species to parameterize our simulations. We simulated recovery through an individual-based mechanistic simulation model and then compared recovery among scenarios incorporating an Allee effect, negative density dependence, and an intermediate scenario. Although an Allee effect significantly slowed recovery, such that population increase could be negligible even after 100 years or more, it also made the time required for biomass rebuilding much less predictable. Our finding that an Allee effect greatly increased the uncertainty in recovery time frames provides an empirically based explanation for why the removal of threat does not always result in the recovery of depleted populations or species. © 2014 Society for Conservation Biology.

Strategies to control a common carp population by pulsed commercial harvest

USGS Publications Warehouse

Colvin, Michael E.; Pierce, Clay; Stewart, Timothy W.; Grummer, Scott E.

2012-01-01

Commercial fisheries are commonly used to manage nuisance fishes in freshwater systems, but such efforts are often unsuccessful. Strategies for successfully controlling a nuisance population of common carp Cyprinus carpio by pulsed commercial harvest were evaluated with a combination of (1) field sampling, (2) population estimation and CPUE indexing, and (3) simulation using an exponential semidiscrete biomass dynamics model (SDBDM). The range of annual fishing mortalities (F) that resulted in successful control (F = 0.244–0.265) was narrow. Common carp biomass dynamics were sensitive to unintentional underharvest due to high rates of surplus production and a biomass doubling time of 2.7 years. Simulations indicated that biomanipulation never achieved successful control unless supplemental fishing mortality was imposed. Harvest of a majority of annual production was required to achieve successful control, as indicated by the ecotrophic coefficient (EC). Readily available biomass data and tools such as SDBDMs and ECs can be used in an adaptive management framework to successfully control common carp and other nuisance fishes by pulsed commercial fishing.

Spatially explicit dynamic N-mixture models

USGS Publications Warehouse

Zhao, Qing; Royle, Andy; Boomer, G. Scott

2017-01-01

Knowledge of demographic parameters such as survival, reproduction, emigration, and immigration is essential to understand metapopulation dynamics. Traditionally the estimation of these demographic parameters requires intensive data from marked animals. The development of dynamic N-mixture models makes it possible to estimate demographic parameters from count data of unmarked animals, but the original dynamic N-mixture model does not distinguish emigration and immigration from survival and reproduction, limiting its ability to explain important metapopulation processes such as movement among local populations. In this study we developed a spatially explicit dynamic N-mixture model that estimates survival, reproduction, emigration, local population size, and detection probability from count data under the assumption that movement only occurs among adjacent habitat patches. Simulation studies showed that the inference of our model depends on detection probability, local population size, and the implementation of robust sampling design. Our model provides reliable estimates of survival, reproduction, and emigration when detection probability is high, regardless of local population size or the type of sampling design. When detection probability is low, however, our model only provides reliable estimates of survival, reproduction, and emigration when local population size is moderate to high and robust sampling design is used. A sensitivity analysis showed that our model is robust against the violation of the assumption that movement only occurs among adjacent habitat patches, suggesting wide applications of this model. Our model can be used to improve our understanding of metapopulation dynamics based on count data that are relatively easy to collect in many systems.

MONITORING DECLINING METAPOPULATIONS: INSIGHTS FROM A MODEL SIMULATION

EPA Science Inventory

Pond-breeding amphibians, host-specialist butterflies, and a variety of other organisms have been shown to exhibit population structures and dynamics consistent with metapopulation theory. In recent years large-scale biodiversity monitoring efforts have been initiated in many reg...

Dengue fever spreading based on probabilistic cellular automata with two lattices

NASA Astrophysics Data System (ADS)

Pereira, F. M. M.; Schimit, P. H. T.

2018-06-01

Modeling and simulation of mosquito-borne diseases have gained attention due to a growing incidence in tropical countries in the past few years. Here, we study the dengue spreading in a population modeled by cellular automata, where there are two lattices to model the human-mosquitointeraction: one lattice for human individuals, and one lattice for mosquitoes in order to enable different dynamics in populations. The disease considered is the dengue fever with one, two or three different serotypes coexisting in population. Although many regions exhibit the incidence of only one serotype, here we set a complete framework to also study the occurrence of two and three serotypes at the same time in a population. Furthermore, the flexibility of the model allows its use to other mosquito-borne diseases, like chikungunya, yellow fever and malaria. An approximation of the cellular automata is proposed in terms of ordinary differential equations; the spreading of mosquitoes is studied and the influence of some model parameters are analyzed with numerical simulations. Finally, a method to combat dengue spreading is simulated based on a reduction of mosquito birth and mosquito bites in population.

Regulation of Cortical Dynamic Range by Background Synaptic Noise and Feedforward Inhibition

PubMed Central

Khubieh, Ayah; Ratté, Stéphanie; Lankarany, Milad; Prescott, Steven A.

2016-01-01

The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then staggered all-or-none recruitment of those neurons would be necessary for the population to achieve a broad dynamic range. Contrary to this explanation, we show here through dynamic clamp experiments in vitro and computer simulations that pyramidal neurons have a broad dynamic range under the noisy conditions that exist in the intact brain due to background synaptic input. Feedforward inhibition capitalizes on those noise effects to control neuronal gain and thereby regulates the population dynamic range. Importantly, noise allows neurons to be recruited gradually and occludes the staggered recruitment previously attributed to heterogeneous excitation. Feedforward inhibition protects spike timing against the disruptive effects of noise, meaning noise can enable the gain control required for rate coding without compromising the precise spike timing required for temporal coding. PMID:26209846

Coherent Dynamics of Open Quantum System in the Presence of Majorana Fermions

NASA Astrophysics Data System (ADS)

Assuncao, Maryzaura O.; Diniz, Ginetom S.; Vernek, Edson; Souza, Fabricio M.

In recent years the research on quantum coherent dynamics of open systems has attracted great attention due to its relevance for future implementation of quantum computers. In the present study we apply the Kadanoff-Baym formalism to simulate the population dynamics of a double-dot molecular system attached to both a superconductor and fermionic reservoirs. We solve both analytically and numerically a set of coupled differential equations that account for crossed Andreev reflection (CAR), intramolecular hopping and tunneling. We pay particular attention on how Majorana bound states can affect the population dynamics of the molecule. We investigate on how initial state configuration affects the dynamics. For instance, if one dot is occupied and the other one is empty, the dynamics is dictated by the inter dot tunneling. On the other hand, for initially empty dots, the CAR dominates. We also investigate how the source and drain currents evolve in time. This work was supporte by FAPEMIG, CNPq and CAPES.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE PAGES

Hagos, Samson; Feng, Zhe; Plant, Robert S.; ...

2018-02-20

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

NASA Astrophysics Data System (ADS)

Hagos, Samson; Feng, Zhe; Plant, Robert S.; Houze, Robert A.; Xiao, Heng

2018-02-01

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The approach used follows the non-equilibrium statistical mechanical approach through a master equation. The aim is to represent the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and mass flux is a non-linear function of convective cell area, mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated mass flux variability under diurnally varying forcing. Besides its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to be capable of providing alternative, non-equilibrium, closure formulations for spectral mass flux parameterizations.« less

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

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

PubMed Central

Santos, Sílvio B.; Carvalho, Carla; Azeredo, Joana; Ferreira, Eugénio C.

2014-01-01

The prevalence and impact of bacteriophages in the ecology of bacterial communities coupled with their ability to control pathogens turn essential to understand and predict the dynamics between phage and bacteria populations. To achieve this knowledge it is essential to develop mathematical models able to explain and simulate the population dynamics of phage and bacteria. We have developed an unstructured mathematical model using delay-differential equations to predict the interactions between a broad-host-range Salmonella phage and its pathogenic host. The model takes into consideration the main biological parameters that rule phage-bacteria interactions likewise the adsorption rate, latent period, burst size, bacterial growth rate, and substrate uptake rate, among others. The experimental validation of the model was performed with data from phage-interaction studies in a 5 L bioreactor. The key and innovative aspect of the model was the introduction of variations in the latent period and adsorption rate values that are considered as constants in previous developed models. By modelling the latent period as a normal distribution of values and the adsorption rate as a function of the bacterial growth rate it was possible to accurately predict the behaviour of the phage-bacteria population. The model was shown to predict simulated data with a good agreement with the experimental observations and explains how a lytic phage and its host bacteria are able to coexist. PMID:25051248

Network evolution induced by the dynamical rules of two populations

NASA Astrophysics Data System (ADS)

Platini, Thierry; Zia, R. K. P.

2010-10-01

We study the dynamical properties of a finite dynamical network composed of two interacting populations, namely extrovert (a) and introvert (b). In our model, each group is characterized by its size (Na and Nb) and preferred degree (κa and \\kappa_b\\ll \\kappa_a ). The network dynamics is governed by the competing microscopic rules of each population that consist of the creation and destruction of links. Starting from an unconnected network, we give a detailed analysis of the mean field approach which is compared to Monte Carlo simulation data. The time evolution of the restricted degrees langkbbrang and langkabrang presents three time regimes and a non-monotonic behavior well captured by our theory. Surprisingly, when the population sizes are equal Na = Nb, the ratio of the restricted degree θ0 = langkabrang/langkbbrang appears to be an integer in the asymptotic limits of the three time regimes. For early times (defined by t < t1 = κb) the total number of links presents a linear evolution, where the two populations are indistinguishable and where θ0 = 1. Interestingly, in the intermediate time regime (defined for t_1\\lt t\\lt t_2\\propto \\kappa_a and for which θ0 = 5), the system reaches a transient stationary state, where the number of contacts among introverts remains constant while the number of connections increases linearly in the extrovert population. Finally, due to the competing dynamics, the network presents a frustrated stationary state characterized by a ratio θ0 = 3.

Molecular dynamics simulations of viral RNA polymerases link conserved and correlated motions of functional elements to fidelity

PubMed Central

Moustafa, Ibrahim M.; Shen, Hujun; Morton, Brandon; Colina, Coray M.; Cameron, Craig E.

2011-01-01

The viral RNA-dependent RNA polymerase (RdRp) is essential for multiplication of all RNA viruses. The sequence diversity of an RNA virus population contributes to its ability to infect the host. This diversity emanates from errors made by the RdRp during RNA synthesis. The physical basis for RdRp fidelity is unclear but is linked to conformational changes occurring during the nucleotide-addition cycle. To understand RdRp dynamics that might influence RdRp function, we have analyzed all-atom molecular dynamics (MD) simulations on the nanosecond timescale of four RdRps from the picornavirus family that exhibit 30–74% sequence identity. Principal component analysis showed that the major motions observed during the simulations derived from conserved structural motifs and regions of known function. Dynamics of residues participating in the same biochemical property, for example RNA binding, nucleotide binding or catalysis, were correlated even when spatially distant on the RdRp structure. The conserved and correlated dynamics of functional, structural elements suggest co-evolution of dynamics with structure and function of the RdRp. Crystal structures of all picornavirus RdRps exhibit a template-nascent RNA duplex channel too small to fully accommodate duplex RNA. Simulations revealed opening and closing motions of the RNA and NTP channels, which might be relevant to NTP entry, PPi exit and translocation. A role for nanosecond timescale dynamics in RdRp fidelity is supported by altered dynamics of the high-fidelity G64S derivative of PV RdRp relative to wild-type enzyme. PMID:21575642

Nonadiabatic nuclear dynamics of the ammonia cation studied by surface hopping classical trajectory calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belyaev, Andrey K., E-mail: belyaev@herzen.spb.ru; Domcke, Wolfgang, E-mail: wolfgang.domcke@ch.tum.de; Lasser, Caroline, E-mail: classer@ma.tum.de

The Landau–Zener (LZ) type classical-trajectory surface-hopping algorithm is applied to the nonadiabatic nuclear dynamics of the ammonia cation after photoionization of the ground-state neutral molecule to the excited states of the cation. The algorithm employs a recently proposed formula for nonadiabatic LZ transition probabilities derived from the adiabatic potential energy surfaces. The evolution of the populations of the ground state and the two lowest excited adiabatic states is calculated up to 200 fs. The results agree well with quantum simulations available for the first 100 fs based on the same potential energy surfaces. Three different time scales are detected formore » the nuclear dynamics: Ultrafast Jahn–Teller dynamics between the excited states on a 5 fs time scale; fast transitions between the excited state and the ground state within a time scale of 20 fs; and relatively slow partial conversion of a first-excited-state population to the ground state within a time scale of 100 fs. Beyond 100 fs, the adiabatic electronic populations are nearly constant due to a dynamic equilibrium between the three states. The ultrafast nonradiative decay of the excited-state populations provides a qualitative explanation of the experimental evidence that the ammonia cation is nonfluorescent.« less

Spatially cascading effect of perturbations in experimental meta-ecosystems.

PubMed

Harvey, Eric; Gounand, Isabelle; Ganesanandamoorthy, Pravin; Altermatt, Florian

2016-09-14

Ecosystems are linked to neighbouring ecosystems not only by dispersal, but also by the movement of subsidy. Such subsidy couplings between ecosystems have important landscape-scale implications because perturbations in one ecosystem may affect community structure and functioning in neighbouring ecosystems via increased/decreased subsidies. Here, we combine a general theoretical approach based on harvesting theory and a two-patch protist meta-ecosystem experiment to test the effect of regional perturbations on local community dynamics. We first characterized the relationship between the perturbation regime and local population demography on detritus production using a mathematical model. We then experimentally simulated a perturbation gradient affecting connected ecosystems simultaneously, thus altering cross-ecosystem subsidy exchanges. We demonstrate that the perturbation regime can interact with local population dynamics to trigger unexpected temporal variations in subsidy pulses from one ecosystem to another. High perturbation intensity initially led to the highest level of subsidy flows; however, the level of perturbation interacted with population dynamics to generate a crash in subsidy exchange over time. Both theoretical and experimental results show that a perturbation regime interacting with local community dynamics can induce a collapse in population levels for recipient ecosystems. These results call for integrative management of human-altered landscapes that takes into account regional dynamics of both species and resource flows. © 2016 The Author(s).

Simulation of oceanic whitecaps and their reflectance characteristics in the short wavelength infrared.

PubMed

Schwenger, Frédéric; Repasi, Endre

2017-02-20

The knowledge of the spatial energy (or power) distribution of light beams reflected at the dynamic sea surface is of great practical interest in maritime environments. For the estimation of the light energy reflected into a specific spatial direction a lot of parameters need to be taken into account. Both whitecap coverage and its optical properties have a large impact upon the calculated value. In published literature, for applications considering vertical light propagation paths, such as bathymetric lidar, the reflectance of sea surface and whitecaps are approximated by constant values. For near-horizontal light propagation paths the optical properties of the sea surface and the whitecaps must be considered in greater detail. The calculated light energy reflected into a specific direction varies statistically and depends largely on the dynamics of the wavy sea surface and the dynamics of whitecaps. A 3D simulation of the dynamic sea surface populated with whitecaps is presented. The simulation considers the evolution of whitecaps depending on wind speed and fetch. The radiance calculation of the maritime scene (open sea/clear sky) populated with whitecaps is done in the short wavelength infrared spectral band. Wave hiding and shadowing, especially occurring at low viewing angles, are considered. The specular reflection of a light beam at the sea surface in the absence of whitecaps is modeled by an analytical statistical bidirectional reflectance distribution function (BRDF) of the sea surface. For whitecaps, a specific BRDF is used by taking into account their shadowing function. To ensure the credibility of the simulation, the whitecap coverage is determined from simulated image sequences for different wind speeds and compared to whitecap coverage functions from literature. The impact of whitecaps on the radiation balance for bistatic configuration of light source and receiver is calculated for a different incident (zenith/azimuth angles) of the light beam and is presented for two different wind speeds.

DengueME: A Tool for the Modeling and Simulation of Dengue Spatiotemporal Dynamics †

PubMed Central

de Lima, Tiago França Melo; Lana, Raquel Martins; de Senna Carneiro, Tiago Garcia; Codeço, Cláudia Torres; Machado, Gabriel Souza; Ferreira, Lucas Saraiva; de Castro Medeiros, Líliam César; Davis Junior, Clodoveu Augusto

2016-01-01

The prevention and control of dengue are great public health challenges for many countries, particularly since 2015, as other arboviruses have been observed to interact significantly with dengue virus. Different approaches and methodologies have been proposed and discussed by the research community. An important tool widely used is modeling and simulation, which help us to understand epidemic dynamics and create scenarios to support planning and decision making processes. With this aim, we proposed and developed DengueME, a collaborative open source platform to simulate dengue disease and its vector’s dynamics. It supports compartmental and individual-based models, implemented over a GIS database, that represent Aedes aegypti population dynamics, human demography, human mobility, urban landscape and dengue transmission mediated by human and mosquito encounters. A user-friendly graphical interface was developed to facilitate model configuration and data input, and a library of models was developed to support teaching-learning activities. DengueME was applied in study cases and evaluated by specialists. Other improvements will be made in future work, to enhance its extensibility and usability. PMID:27649226

Complex Dynamics of Wetland Ecosystem with Nonlinear Harvesting: Application to Chilika Lake in Odisha, India

NASA Astrophysics Data System (ADS)

Upadhyay, Ranjit Kumar; Tiwari, S. K.; Roy, Parimita

2015-06-01

In this paper, an attempt has been made to study the spatial and temporal dynamical interactions among the species of wetland ecosystem through a mathematical model. The model represents the population dynamics of phytoplankton, zooplankton and fish species found in Chilika lake, Odisha, India. Nonlinear stability analysis of both the temporal and spatial models has been carried out. Maximum sustainable yield and optimal harvesting policy have been studied for a nonspatial model system. Numerical simulation has been performed to figure out the parameters responsible for the complex dynamics of the wetland system. Significant outcomes of our numerical findings and their interpretations from an ecological point of view are provided in this paper. Numerical simulation of spatial model exhibits some interesting and beautiful patterns. We have also pointed out the parameters that are responsible for the good health of wetland ecosystem.

Linking river management to species conservation using dynamic landscape scale models

USGS Publications Warehouse

Freeman, Mary C.; Buell, Gary R.; Hay, Lauren E.; Hughes, W. Brian; Jacobson, Robert B.; Jones, John W.; Jones, S.A.; LaFontaine, Jacob H.; Odom, Kenneth R.; Peterson, James T.; Riley, Jeffrey W.; Schindler, J. Stephen; Shea, C.; Weaver, J.D.

2013-01-01

Efforts to conserve stream and river biota could benefit from tools that allow managers to evaluate landscape-scale changes in species distributions in response to water management decisions. We present a framework and methods for integrating hydrology, geographic context and metapopulation processes to simulate effects of changes in streamflow on fish occupancy dynamics across a landscape of interconnected stream segments. We illustrate this approach using a 482 km2 catchment in the southeastern US supporting 50 or more stream fish species. A spatially distributed, deterministic and physically based hydrologic model is used to simulate daily streamflow for sub-basins composing the catchment. We use geographic data to characterize stream segments with respect to channel size, confinement, position and connectedness within the stream network. Simulated streamflow dynamics are then applied to model fish metapopulation dynamics in stream segments, using hypothesized effects of streamflow magnitude and variability on population processes, conditioned by channel characteristics. The resulting time series simulate spatially explicit, annual changes in species occurrences or assemblage metrics (e.g. species richness) across the catchment as outcomes of management scenarios. Sensitivity analyses using alternative, plausible links between streamflow components and metapopulation processes, or allowing for alternative modes of fish dispersal, demonstrate large effects of ecological uncertainty on model outcomes and highlight needed research and monitoring. Nonetheless, with uncertainties explicitly acknowledged, dynamic, landscape-scale simulations may prove useful for quantitatively comparing river management alternatives with respect to species conservation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostova, T; Carlsen, T

We present a study, based on simulations with SERDYCA, a spatially-explicit individual based model of rodent dynamics, on the connection between population persistence and the presence of inhomogeneities in the habitat. We are specifically interested on the effect that inhomogeneities that do not fragment the environment, have on population persistence. Our results suggest that a certain percentage of inhomogeneities can increase the average time to extinction of the population. Inhomogeneities decrease the population density and can increase the ratio of juveniles in the population thus providing a better chance for the population to restore itself after a severe period withmore » critically low population density. We call this the ''inhomogeneity localization effect''.« less

Virtual Screening and Molecular Dynamics Simulations from a Bank of Molecules of the Amazon Region Against Functional NS3-4A Protease-Helicase Enzyme of Hepatitis C Virus.

PubMed

Pinheiro, Alan Sena; Duarte, Jaqueline Bianca Carvalho; Alves, Cláudio Nahum; de Molfetta, Fábio Alberto

2015-07-01

Hepatitis C virus (HCV) infection is a disease that affects approximately 3% of the global population and requires new therapeutic agents without the inconvenience associated with current anti-HCV treatment. This paper reports on a study of a virtual screening and a molecular dynamics simulation of compounds derived from natural products from the Amazon region that are potentially effective against the NS3-4A enzyme of HCV, which plays an important role in the replication process of this virus. According to the results of the molecular docking calculations and subsequent consensual analysis, the best scored compounds showed interactions between hydrogen and residues of the catalytic triad as well as interactions with residues that guide ligands to the active site of the enzyme. They also showed stability in the molecular dynamics simulation, as the structures preserved important interactions at the active site of the enzyme. The root mean square deviation (RMSD) values were stabilized at the end of the simulation time. Such compounds are considered promising as novel therapies against HCV.

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

PubMed Central

Dann, Benjamin

2016-01-01

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

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

PubMed

Michaels, Jonathan A; Dann, Benjamin; Scherberger, Hansjörg

2016-11-01

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

Suppression of Beneficial Mutations in Dynamic Microbial Populations

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Land Cover Applications, Landscape Dynamics, and Global Change

USGS Publications Warehouse

Tieszen, Larry L.

2007-01-01

The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains

PubMed Central

Poleszczuk, Jan; Enderling, Heiko

2014-01-01

Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We discuss tumor properties that favor the proposed high-performance design and present simulation results of the tumor growth model. We estimate to which parameters the model is the most sensitive, and show that tumor volume depends on a number of parameters in a non-monotonic manner. PMID:25346862

Detecting population-environmental interactions with mismatched time series data.

PubMed

Ferguson, Jake M; Reichert, Brian E; Fletcher, Robert J; Jager, Henriëtte I

2017-11-01

Time series analysis is an essential method for decomposing the influences of density and exogenous factors such as weather and climate on population regulation. However, there has been little work focused on understanding how well commonly collected data can reconstruct the effects of environmental factors on population dynamics. We show that, analogous to similar scale issues in spatial data analysis, coarsely sampled temporal data can fail to detect covariate effects when interactions occur on timescales that are fast relative to the survey period. We propose a method for modeling mismatched time series data that couples high-resolution environmental data to low-resolution abundance data. We illustrate our approach with simulations and by applying it to Florida's southern Snail kite population. Our simulation results show that our method can reliably detect linear environmental effects and that detecting nonlinear effects requires high-resolution covariate data even when the population turnover rate is slow. In the Snail kite analysis, our approach performed among the best in a suite of previously used environmental covariates explaining Snail kite dynamics and was able to detect a potential phenological shift in the environmental dependence of Snail kites. Our work provides a statistical framework for reliably detecting population-environment interactions from coarsely surveyed time series. An important implication of this work is that the low predictability of animal population growth by weather variables found in previous studies may be due, in part, to how these data are utilized as covariates. © 2017 by the Ecological Society of America.

Stochastic population dynamics under resource constraints

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gavane, Ajinkya S., E-mail: ajinkyagavane@gmail.com; Nigam, Rahul, E-mail: rahul.nigam@hyderabad.bits-pilani.ac.in

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

A quantitative dynamic systems model of health-related quality of life among older adults

PubMed Central

Roppolo, Mattia; Kunnen, E Saskia; van Geert, Paul L; Mulasso, Anna; Rabaglietti, Emanuela

2015-01-01

Health-related quality of life (HRQOL) is a person-centered concept. The analysis of HRQOL is highly relevant in the aged population, which is generally suffering from health decline. Starting from a conceptual dynamic systems model that describes the development of HRQOL in individuals over time, this study aims to develop and test a quantitative dynamic systems model, in order to reveal the possible dynamic trends of HRQOL among older adults. The model is tested in different ways: first, with a calibration procedure to test whether the model produces theoretically plausible results, and second, with a preliminary validation procedure using empirical data of 194 older adults. This first validation tested the prediction that given a particular starting point (first empirical data point), the model will generate dynamic trajectories that lead to the observed endpoint (second empirical data point). The analyses reveal that the quantitative model produces theoretically plausible trajectories, thus providing support for the calibration procedure. Furthermore, the analyses of validation show a good fit between empirical and simulated data. In fact, no differences were found in the comparison between empirical and simulated final data for the same subgroup of participants, whereas the comparison between different subgroups of people resulted in significant differences. These data provide an initial basis of evidence for the dynamic nature of HRQOL during the aging process. Therefore, these data may give new theoretical and applied insights into the study of HRQOL and its development with time in the aging population. PMID:26604722

USING ECO-EVOLUTIONARY INDIVIDUAL-BASED MODELS TO INVESTIGATE SPATIALLY-DEPENDENT PROCESSES IN CONSERVATION GENETICS

EPA Science Inventory

Eco-evolutionary population simulation models are powerful new forecasting tools for exploring management strategies for climate change and other dynamic disturbance regimes. Additionally, eco-evo individual-based models (IBMs) are useful for investigating theoretical feedbacks ...

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size.

PubMed

Schwalger, Tilo; Deger, Moritz; Gerstner, Wulfram

2017-04-01

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations.

Benchmarking novel approaches for modelling species range dynamics

PubMed Central

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H.; Moore, Kara A.; Zimmermann, Niklaus E.

2016-01-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species’ range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species’ response to climate change but also emphasise several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. PMID:26872305

Benchmarking novel approaches for modelling species range dynamics.

PubMed

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

2016-08-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. © 2016 John Wiley & Sons Ltd.

The Stochastic Multi-strain Dengue Model: Analysis of the Dynamics

NASA Astrophysics Data System (ADS)

Aguiar, Maíra; Stollenwerk, Nico; Kooi, Bob W.

2011-09-01

Dengue dynamics is well known to be particularly complex with large fluctuations of disease incidences. An epidemic multi-strain model motivated by dengue fever epidemiology shows deterministic chaos in wide parameter regions. The addition of seasonal forcing, mimicking the vectorial dynamics, and a low import of infected individuals, which is realistic in the dynamics of infectious diseases epidemics show complex dynamics and qualitatively a good agreement between empirical DHF monitoring data and the obtained model simulation. The addition of noise can explain the fluctuations observed in the empirical data and for large enough population size, the stochastic system can be well described by the deterministic skeleton.

Multi-fractal characterization of bacterial swimming dynamics: a case study on real and simulated Serratia marcescens

PubMed Central

Bogdan, Paul; Wei, Guopeng; Marculescu, Radu; Zhuang, Jiang; Carlsen, Rika Wright; Sitti, Metin

2017-01-01

To add to the current state of knowledge about bacterial swimming dynamics, in this paper, we study the fractal swimming dynamics of populations of Serratia marcescens bacteria both in vitro and in silico, while accounting for realistic conditions like volume exclusion, chemical interactions, obstacles and distribution of chemoattractant in the environment. While previous research has shown that bacterial motion is non-ergodic, we demonstrate that, besides the non-ergodicity, the bacterial swimming dynamics is multi-fractal in nature. Finally, we demonstrate that the multi-fractal characteristic of bacterial dynamics is strongly affected by bacterial density and chemoattractant concentration. PMID:28804259

Effects of aging in catastrophe on the steady state and dynamics of a microtubule population

NASA Astrophysics Data System (ADS)

Jemseena, V.; Gopalakrishnan, Manoj

2015-05-01

Several independent observations have suggested that the catastrophe transition in microtubules is not a first-order process, as is usually assumed. Recent in vitro observations by Gardner et al. [M. K. Gardner et al., Cell 147, 1092 (2011), 10.1016/j.cell.2011.10.037] showed that microtubule catastrophe takes place via multiple steps and the frequency increases with the age of the filament. Here we investigate, via numerical simulations and mathematical calculations, some of the consequences of the age dependence of catastrophe on the dynamics of microtubules as a function of the aging rate, for two different models of aging: exponential growth, but saturating asymptotically, and purely linear growth. The boundary demarcating the steady-state and non-steady-state regimes in the dynamics is derived analytically in both cases. Numerical simulations, supported by analytical calculations in the linear model, show that aging leads to nonexponential length distributions in steady state. More importantly, oscillations ensue in microtubule length and velocity. The regularity of oscillations, as characterized by the negative dip in the autocorrelation function, is reduced by increasing the frequency of rescue events. Our study shows that the age dependence of catastrophe could function as an intrinsic mechanism to generate oscillatory dynamics in a microtubule population, distinct from hitherto identified ones.

Population ecology, nonlinear dynamics, and social evolution. I. Associations among nonrelatives.

PubMed

Avilés, Leticia; Abbot, Patrick; Cutter, Asher D

2002-02-01

Using an individual-based and genetically explicit simulation model, we explore the evolution of sociality within a population-ecology and nonlinear-dynamics framework. Assuming that individual fitness is a unimodal function of group size and that cooperation may carry a relative fitness cost, we consider the evolution of one-generation breeding associations among nonrelatives. We explore how parameters such as the intrinsic rate of growth and group and global carrying capacities may influence social evolution and how social evolution may, in turn, influence and be influenced by emerging group-level and population-wide dynamics. We find that group living and cooperation evolve under a wide range of parameter values, even when cooperation is costly and the interactions can be defined as altruistic. Greater levels of cooperation, however, did evolve when cooperation carried a low or no relative fitness cost. Larger group carrying capacities allowed the evolution of larger groups but also resulted in lower cooperative tendencies. When the intrinsic rate of growth was not too small and control of the global population size was density dependent, the evolution of large cooperative tendencies resulted in dynamically unstable groups and populations. These results are consistent with the existence and typical group sizes of organisms ranging from the pleometrotic ants to the colonial birds and the global population outbreaks and crashes characteristic of organisms such as the migratory locusts and the tree-killing bark beetles.

Observation and control of coherent torsional dynamics in a quinquethiophene molecule.

PubMed

Cirmi, Giovanni; Brida, Daniele; Gambetta, Alessio; Piacenza, Manuel; Della Sala, Fabio; Favaretto, Laura; Cerullo, Giulio; Lanzani, Guglielmo

2010-07-28

By applying femtosecond pump-probe spectroscopy to a substituted quinquethiophene molecule in solution, we observe in the time domain the coherent torsional dynamics that drives planarization of the excited state. Our interpretation is based on numerical modeling of the ground and excited state potential energy surfaces and simulation of wavepacket dynamics, which reveals two symmetric excited state deactivation pathways per oscillation period. We use the acquired knowledge on torsional dynamics to coherently control the excited state population with a pump-dump scheme, exploiting the non-stationary Franck-Condon overlap between ground and excited states.

Tracing the Early Development of Harmful Algal Blooms on the West Florida Shelf with the Aid of Lagrangian Coherent Structures

PubMed Central

Olascoaga, M. J.; Beron-Vera, F. J.; Brand, L. E.; Koçak, H.

2008-01-01

Several theories have been proposed to explain the development of harmful algal blooms (HABs) produced by the toxic dinoflagellate Karenia brevis on the West Florida Shelf. However, because the early stages of HAB development are usually not detected, these theories have been so far very difficult to verify. In this paper we employ simulated Lagrangian coherent structures (LCSs) to trace potential early locations of the development of a HAB in late 2004 before it was transported to a region where it could be detected by satellite imagery. The LCSs, which are extracted from surface ocean currents produced by a data-assimilative HYCOM (HYbrid-Coordinate Ocean Model) simulation, constitute material fluid barriers that demarcate potential pathways for HAB evolution. Using a simplified population dynamics model we infer the factors that could possibly lead to the development of the HAB in question. The population dynamics model determines nitrogen in two components, nutrients and phytoplankton, which are assumed to be passively advected by surface ocean currents produced by the above HYCOM simulation. Two nutrient sources are inferred for the HAB whose evolution is found to be strongly tied to the simulated LCSs. These nutrient sources are found to be located nearshore and possibly due to land runoff. PMID:19137076

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation

PubMed Central

Sherfey, Jason S.; Soplata, Austin E.; Ardid, Salva; Roberts, Erik A.; Stanley, David A.; Pittman-Polletta, Benjamin R.; Kopell, Nancy J.

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community. PMID:29599715

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation.

PubMed

Sherfey, Jason S; Soplata, Austin E; Ardid, Salva; Roberts, Erik A; Stanley, David A; Pittman-Polletta, Benjamin R; Kopell, Nancy J

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community.

Convergence dynamics and pseudo almost periodicity of a class of nonautonomous RFDEs with applications

NASA Astrophysics Data System (ADS)

Fan, Meng; Ye, Dan

2005-09-01

This paper studies the dynamics of a system of retarded functional differential equations (i.e., RF=Es), which generalize the Hopfield neural network models, the bidirectional associative memory neural networks, the hybrid network models of the cellular neural network type, and some population growth model. Sufficient criteria are established for the globally exponential stability and the existence and uniqueness of pseudo almost periodic solution. The approaches are based on constructing suitable Lyapunov functionals and the well-known Banach contraction mapping principle. The paper ends with some applications of the main results to some neural network models and population growth models and numerical simulations.

Predator-prey model for the self-organization of stochastic oscillators in dual populations

NASA Astrophysics Data System (ADS)

Moradi, Sara; Anderson, Johan; Gürcan, Ozgür D.

2015-12-01

A predator-prey model of dual populations with stochastic oscillators is presented. A linear cross-coupling between the two populations is introduced following the coupling between the motions of a Wilberforce pendulum in two dimensions: one in the longitudinal and the other in torsional plain. Within each population a Kuramoto-type competition between the phases is assumed. Thus, the synchronization state of the whole system is controlled by these two types of competitions. The results of the numerical simulations show that by adding the linear cross-coupling interactions predator-prey oscillations between the two populations appear, which results in self-regulation of the system by a transfer of synchrony between the two populations. The model represents several important features of the dynamical interplay between the drift wave and zonal flow turbulence in magnetically confined plasmas, and a novel interpretation of the coupled dynamics of drift wave-zonal flow turbulence using synchronization of stochastic oscillator is discussed.

A new logistic dynamic particle swarm optimization algorithm based on random topology.

PubMed

Ni, Qingjian; Deng, Jianming

2013-01-01

Population topology of particle swarm optimization (PSO) will directly affect the dissemination of optimal information during the evolutionary process and will have a significant impact on the performance of PSO. Classic static population topologies are usually used in PSO, such as fully connected topology, ring topology, star topology, and square topology. In this paper, the performance of PSO with the proposed random topologies is analyzed, and the relationship between population topology and the performance of PSO is also explored from the perspective of graph theory characteristics in population topologies. Further, in a relatively new PSO variant which named logistic dynamic particle optimization, an extensive simulation study is presented to discuss the effectiveness of the random topology and the design strategies of population topology. Finally, the experimental data are analyzed and discussed. And about the design and use of population topology on PSO, some useful conclusions are proposed which can provide a basis for further discussion and research.

Dynamics of adaptive immunity against phage in bacterial populations

NASA Astrophysics Data System (ADS)

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

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

Integrating neuroinformatics tools in TheVirtualBrain.

PubMed

Woodman, M Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

2014-01-01

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting.

Integrating neuroinformatics tools in TheVirtualBrain

PubMed Central

Woodman, M. Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A.; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R.; Jirsa, Viktor

2014-01-01

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting. PMID:24795617

Simulated effects of recruitment variability, exploitation, and reduced habitat area on the muskellunge population in Shoepack Lake, Voyageurs National Park, Minnesota

USGS Publications Warehouse

Frohnauer, N.K.; Pierce, C.L.; Kallemeyn, L.W.

2007-01-01

The genetically unique population of muskellunge Esox masquinongy inhabiting Shoepack Lake in Voyageurs National Park, Minnesota, is potentially at risk for loss of genetic variability and long-term viability. Shoepack Lake has been subject to dramatic surface area changes from the construction of an outlet dam by beavers Castor canadensis and its subsequent failure. We simulated the long-term dynamics of this population in response to recruitment variation, increased exploitation, and reduced habitat area. We then estimated the effective population size of the simulated population and evaluated potential threats to long-term viability, based on which we recommend management actions to help preserve the long-term viability of the population. Simulations based on the population size and habitat area at the beginning of a companion study resulted in an effective population size that was generally above the threshold level for risk of loss of genetic variability, except when fishing mortality was increased. Simulations based on the reduced habitat area after the beaver dam failure and our assumption of a proportional reduction in population size resulted in an effective population size that was generally below the threshold level for risk of loss of genetic variability. Our results identified two potential threats to the long-term viability of the Shoepack Lake muskellunge population, reduction in habitat area and exploitation. Increased exploitation can be prevented through traditional fishery management approaches such as the adoption of no-kill, barbless hook, and limited entry regulations. Maintenance of the greatest possible habitat area and prevention of future habitat area reductions will require maintenance of the outlet dam built by beavers. Our study should enhance the long-term viability of the Shoepack Lake muskellunge population and illustrates a useful approach for other unique populations. ?? Copyright by the American Fisheries Society 2007.

Weighted Ensemble Simulation: Review of Methodology, Applications, and Software

PubMed Central

Zuckerman, Daniel M.; Chong, Lillian T.

2018-01-01

The weighted ensemble (WE) methodology orchestrates quasi-independent parallel simulations run with intermittent communication that can enhance sampling of rare events such as protein conformational changes, folding, and binding. The WE strategy can achieve superlinear scaling—the unbiased estimation of key observables such as rate constants and equilibrium state populations to greater precision than would be possible with ordinary parallel simulation. WE software can be used to control any dynamics engine, such as standard molecular dynamics and cell-modeling packages. This article reviews the theoretical basis of WE and goes on to describe successful applications to a number of complex biological processes—protein conformational transitions, (un)binding, and assembly processes, as well as cell-scale processes in systems biology. We furthermore discuss the challenges that need to be overcome in the next phase of WE methodological development. Overall, the combined advances in WE methodology and software have enabled the simulation of long-timescale processes that would otherwise not be practical on typical computing resources using standard simulation. PMID:28301772

Weighted Ensemble Simulation: Review of Methodology, Applications, and Software.

PubMed

Zuckerman, Daniel M; Chong, Lillian T

2017-05-22

The weighted ensemble (WE) methodology orchestrates quasi-independent parallel simulations run with intermittent communication that can enhance sampling of rare events such as protein conformational changes, folding, and binding. The WE strategy can achieve superlinear scaling-the unbiased estimation of key observables such as rate constants and equilibrium state populations to greater precision than would be possible with ordinary parallel simulation. WE software can be used to control any dynamics engine, such as standard molecular dynamics and cell-modeling packages. This article reviews the theoretical basis of WE and goes on to describe successful applications to a number of complex biological processes-protein conformational transitions, (un)binding, and assembly processes, as well as cell-scale processes in systems biology. We furthermore discuss the challenges that need to be overcome in the next phase of WE methodological development. Overall, the combined advances in WE methodology and software have enabled the simulation of long-timescale processes that would otherwise not be practical on typical computing resources using standard simulation.

Spatial structures in a simple model of population dynamics for parasite-host interactions

NASA Astrophysics Data System (ADS)

Dong, J. J.; Skinner, B.; Breecher, N.; Schmittmann, B.; Zia, R. K. P.

2015-08-01

Spatial patterning can be crucially important for understanding the behavior of interacting populations. Here we investigate a simple model of parasite and host populations in which parasites are random walkers that must come into contact with a host in order to reproduce. We focus on the spatial arrangement of parasites around a single host, and we derive using analytics and numerical simulations the necessary conditions placed on the parasite fecundity and lifetime for the population's long-term survival. We also show that the parasite population can be pushed to extinction by a large drift velocity, but, counterintuitively, a small drift velocity generally increases the parasite population.

Molecular dynamics study of the conformational properties of cyclohexadecane

NASA Astrophysics Data System (ADS)

Zhang, Renshi; Mattice, Wayne L.

1993-06-01

Molecular dynamics has been used for the first time for the study of the conformational properties of cyclohexadecane, c-C16H32. By analyzing a long molecular dynamics trajectory (14.5 ns) at 450 K, equilibrium statistics such as the relative populations of different isomeric conformers and the probability ratios, p(gt)/p(tt), p(gg)/p(tt), and p(gg)/p(gtg), of different conformational segments, have been studied. The dynamic properties including the transition modes of gauche migration and gauche-pair creation, which have been reported before in n-alkanes, and the auto- and cross-correlations of the bond dihedral angles, have also been obtained. It was possible to make direct comparisons on some of the statistics with theory and experiment. Most of the results extracted from the molecular dynamics trajectory lie in between previously reported experimental and theoretical values. Many previously predicted conformers have been confirmed by our simulations. The results of the population probability of the most populated conformer seems to suggest that an earlier discrepancy between the theoretical works and an experimental work originates from insufficient samplings in earlier theoretical works, rather than from their inaccurate force field.

Parks or Prisons?

ERIC Educational Resources Information Center

Thomson, Gareth

1998-01-01

Presents a simulation activity in which students assume the role of grizzly bears in Banff National Park. Concepts such as species diversity, fitness, natural selection, habitat loss, extinction, and population dynamics are discussed. Children learn how human activities can affect the bear's reproductive success. Lists materials, instructional…

Folding free-energy landscape of villin headpiece subdomain from molecular dynamics simulations.

PubMed

Lei, Hongxing; Wu, Chun; Liu, Haiguang; Duan, Yong

2007-03-20

High-accuracy ab initio folding has remained an elusive objective despite decades of effort. To explore the folding landscape of villin headpiece subdomain HP35, we conducted two sets of replica exchange molecular dynamics for 200 ns each and three sets of conventional microsecond-long molecular dynamics simulations, using AMBER FF03 force field and a generalized-Born solvation model. The protein folded consistently to the native state; the lowest C(alpha)-rmsd from the x-ray structure was 0.46 A, and the C(alpha)- rmsd of the center of the most populated cluster was 1.78 A at 300 K. ab initio simulations have previously not reached this level. The folding landscape of HP35 can be partitioned into the native, denatured, and two intermediate-state regions. The native state is separated from the major folding intermediate state by a small barrier, whereas a large barrier exists between the major folding intermediate and the denatured states. The melting temperature T(m) = 339 K extracted from the heat-capacity profile was in close agreement with the experimentally derived T(m) = 342 K. A comprehensive picture of the kinetics and thermodynamics of HP35 folding emerges when the results from replica exchange and conventional molecular dynamics simulations are combined.

Modification of S-Adenosyl-l-Homocysteine as Inhibitor of Nonstructural Protein 5 Methyltransferase Dengue Virus Through Molecular Docking and Molecular Dynamics Simulation

PubMed Central

Tambunan, Usman Sumo Friend; Nasution, Mochammad Arfin Fardiansyah; Azhima, Fauziah; Parikesit, Arli Aditya; Toepak, Erwin Prasetya; Idrus, Syarifuddin; Kerami, Djati

2017-01-01

Dengue fever is still a major threat worldwide, approximately threatening two-fifths of the world’s population in tropical and subtropical countries. Nonstructural protein 5 (NS5) methyltransferase enzyme plays a vital role in the process of messenger RNA capping of dengue by transferring methyl groups from S-adenosyl-l-methionine to N7 atom of the guanine bases of RNA and the RNA ribose group of 2′OH, resulting in S-adenosyl-l-homocysteine (SAH). The modification of SAH compound was screened using molecular docking and molecular dynamics simulation, along with computational ADME-Tox (absorption, distribution, metabolism, excretion, and toxicity) test. The 2 simulations were performed using Molecular Operating Environment (MOE) 2008.10 software, whereas the ADME-Tox test was performed using various software. The modification of SAH compound was done using several functional groups that possess different polarities and properties, resulting in 3460 ligands to be docked. After conducting docking simulation, we earned 3 best ligands (SAH-M331, SAH-M2696, and SAH-M1356) based on ΔGbinding and molecular interactions, which show better results than the standard ligands. Moreover, the results of molecular dynamics simulation show that the best ligands are still able to maintain the active site residue interaction with the binding site until the end of the simulation. After a series of molecular docking and molecular dynamics simulation were performed, we concluded that SAH-M1356 ligand is the most potential SAH-based compound to inhibit NS5 methyltransferase enzyme for treating dengue fever. PMID:28469408

Stochastic modelling of infectious diseases for heterogeneous populations.

PubMed

Ming, Rui-Xing; Liu, Ji-Ming; W Cheung, William K; Wan, Xiang

2016-12-22

Infectious diseases such as SARS and H1N1 can significantly impact people's lives and cause severe social and economic damages. Recent outbreaks have stressed the urgency of effective research on the dynamics of infectious disease spread. However, it is difficult to predict when and where outbreaks may emerge and how infectious diseases spread because many factors affect their transmission, and some of them may be unknown. One feasible means to promptly detect an outbreak and track the progress of disease spread is to implement surveillance systems in regional or national health and medical centres. The accumulated surveillance data, including temporal, spatial, clinical, and demographic information can provide valuable information that can be exploited to better understand and model the dynamics of infectious disease spread. The aim of this work is to develop and empirically evaluate a stochastic model that allows the investigation of transmission patterns of infectious diseases in heterogeneous populations. We test the proposed model on simulation data and apply it to the surveillance data from the 2009 H1N1 pandemic in Hong Kong. In the simulation experiment, our model achieves high accuracy in parameter estimation (less than 10.0 % mean absolute percentage error). In terms of the forward prediction of case incidence, the mean absolute percentage errors are 17.3 % for the simulation experiment and 20.0 % for the experiment on the real surveillance data. We propose a stochastic model to study the dynamics of infectious disease spread in heterogeneous populations from temporal-spatial surveillance data. The proposed model is evaluated using both simulated data and the real data from the 2009 H1N1 epidemic in Hong Kong and achieves acceptable prediction accuracy. We believe that our model can provide valuable insights for public health authorities to predict the effect of disease spread and analyse its underlying factors and to guide new control efforts.

System Dynamics based Dengue modeling environment to simulate evolution of Dengue infection under different climate scenarios

NASA Astrophysics Data System (ADS)

Anwar, R.; Khan, R.; Usmani, M.; Colwell, R. R.; Jutla, A.

2017-12-01

Vector borne infectious diseases such as Dengue, Zika and Chikungunya remain a public health threat. An estimate of the World Health Organization (WHO) suggests that about 2.5 billion people, representing ca. 40% of human population,are at increased risk of dengue; with more than 100 million infection cases every year. Vector-borne infections cannot be eradicated since disease causing pathogens survive in the environment. Over the last few decades dengue infection has been reported in more than 100 countries and is expanding geographically. Female Ae. Aegypti mosquito, the daytime active and a major vector for dengue virus, is associated with urban population density and regional climatic processes. However, mathematical quantification of relationships on abundance of vectors and climatic processes remain a challenge, particularly in regions where such data are not routinely collected. Here, using system dynamics based feedback mechanism, an algorithm integrating knowledge from entomological, meteorological and epidemiological processes is developed that has potential to provide ensemble simulations on risk of occurrence of dengue infection in human population. Using dataset from satellite remote sensing, the algorithm was calibrated and validated using actual dengue case data of Iquitos, Peru. We will show results on model capabilities in capturing initiation and peak in the observed time series. In addition, results from several simulation scenarios under different climatic conditions will be discussed.

Boundary effects on population dynamics in stochastic lattice Lotka-Volterra models

NASA Astrophysics Data System (ADS)

Heiba, Bassel; Chen, Sheng; Täuber, Uwe C.

2018-02-01

We investigate spatially inhomogeneous versions of the stochastic Lotka-Volterra model for predator-prey competition and coexistence by means of Monte Carlo simulations on a two-dimensional lattice with periodic boundary conditions. To study boundary effects for this paradigmatic population dynamics system, we employ a simulation domain split into two patches: Upon setting the predation rates at two distinct values, one half of the system resides in an absorbing state where only the prey survives, while the other half attains a stable coexistence state wherein both species remain active. At the domain boundary, we observe a marked enhancement of the predator population density. The predator correlation length displays a minimum at the boundary, before reaching its asymptotic constant value deep in the active region. The frequency of the population oscillations appears only very weakly affected by the existence of two distinct domains, in contrast to their attenuation rate, which assumes its largest value there. We also observe that boundary effects become less prominent as the system is successively divided into subdomains in a checkerboard pattern, with two different reaction rates assigned to neighboring patches. When the domain size becomes reduced to the scale of the correlation length, the mean population densities attain values that are very similar to those in a disordered system with randomly assigned reaction rates drawn from a bimodal distribution.

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

PubMed

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

2015-04-01

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

Simulation model of Skeletonema costatum population dynamics in northern San Francisco Bay, California

USGS Publications Warehouse

Cloern, J.E.; Cheng, R.T.

1981-01-01

A pseudo-two-dimensional model is developed to simulate population dynamics of one dominant phytoplankton species (Skeletonema costatum) in northern San Francisco Bay. The model is formulated around a conceptualization of this estuary as two distinct but coupled subsystems-a deep (10-20 m) central channel and lateral areas with shallow (<2 m) water and slow circulation. Algal growth rates are governed by solar irradiation, temperature and salinity, while population losses are assumed to result from grazing bycalanoid copepods. Consequences of estuarine gravitational circulation are approximated simply by reducing convective-dispersive transport in that section of the channel (null zone) where residual bottom currents are near zero, and lateral mixing is treated as a bulkexchange process between the channel and the shoals. Model output is consistent with the hypothesis that, because planktonic algae are light-limited, shallow areas are the sites of active population growth. Seasonal variation in the location of the null zone (a response to variable river discharge) is responsible for maintaining the spring bloom of neritic diatoms in the seaward reaches of the estuary (San Pablo Bay) and the summer bloom upstream (Suisun Bay). Model output suggests that these spring and summer blooms result from the same general process-establishment of populations over the shoals, where growth rates are rapid, coupled with reduced particulate transport due to estuarine gravitational circulation. It also suggests, however, that the relative importance of physical and biological processes to phytoplankton dynamics is different in San Pablo and Suisun Bays. Finally, the model has helped us determine those processes having sufficient importance to merit further refinement in the next generation of models, and it has given new direction to field studies. ?? 1981 Academic Press Inc. (London) Ltd.

A structured population model with diffusion in structure space.

PubMed

Pugliese, Andrea; Milner, Fabio

2018-05-09

A structured population model is described and analyzed, in which individual dynamics is stochastic. The model consists of a PDE of advection-diffusion type in the structure variable. The population may represent, for example, the density of infected individuals structured by pathogen density x, [Formula: see text]. The individuals with density [Formula: see text] are not infected, but rather susceptible or recovered. Their dynamics is described by an ODE with a source term that is the exact flux from the diffusion and advection as [Formula: see text]. Infection/reinfection is then modeled moving a fraction of these individuals into the infected class by distributing them in the structure variable through a probability density function. Existence of a global-in-time solution is proven, as well as a classical bifurcation result about equilibrium solutions: a net reproduction number [Formula: see text] is defined that separates the case of only the trivial equilibrium existing when [Formula: see text] from the existence of another-nontrivial-equilibrium when [Formula: see text]. Numerical simulation results are provided to show the stabilization towards the positive equilibrium when [Formula: see text] and towards the trivial one when [Formula: see text], result that is not proven analytically. Simulations are also provided to show the Allee effect that helps boost population sizes at low densities.

Heterogeneous population dynamics and scaling laws near epidemic outbreaks.

PubMed

Widder, Andreas; Kuehn, Christian

2016-10-01

In this paper, we focus on the influence of heterogeneity and stochasticity of the population on the dynamical structure of a basic susceptible-infected-susceptible (SIS) model. First we prove that, upon a suitable mathematical reformulation of the basic reproduction number, the homogeneous system and the heterogeneous system exhibit a completely analogous global behaviour. Then we consider noise terms to incorporate the fluctuation effects and the random import of the disease into the population and analyse the influence of heterogeneity on warning signs for critical transitions (or tipping points). This theory shows that one may be able to anticipate whether a bifurcation point is close before it happens. We use numerical simulations of a stochastic fast-slow heterogeneous population SIS model and show various aspects of heterogeneity have crucial influences on the scaling laws that are used as early-warning signs for the homogeneous system. Thus, although the basic structural qualitative dynamical properties are the same for both systems, the quantitative features for epidemic prediction are expected to change and care has to be taken to interpret potential warning signs for disease outbreaks correctly.

The interplay between human population dynamics and flooding in Bangladesh: a spatial analysis

NASA Astrophysics Data System (ADS)

di Baldassarre, G.; Yan, K.; Ferdous, MD. R.; Brandimarte, L.

2014-09-01

In Bangladesh, socio-economic and hydrological processes are both extremely dynamic and inter-related. Human population patterns are often explained as a response, or adaptation strategy, to physical events, e.g. flooding, salt-water intrusion, and erosion. Meanwhile, these physical processes are exacerbated, or mitigated, by diverse human interventions, e.g. river diversion, levees and polders. In this context, this paper describes an attempt to explore the complex interplay between floods and societies in Bangladeshi floodplains. In particular, we performed a spatially-distributed analysis of the interactions between the dynamics of human settlements and flood inundation patterns. To this end, we used flooding simulation results from inundation modelling, LISFLOOD-FP, as well as global datasets of population distribution data, such as the Gridded Population of the World (20 years, from 1990 to 2010) and HYDE datasets (310 years, from 1700 to 2010). The outcomes of this work highlight the behaviour of Bangladeshi floodplains as complex human-water systems and indicate the need to go beyond the traditional narratives based on one-way cause-effects, e.g. climate change leading to migrations.

The GP problem: quantifying gene-to-phenotype relationships.

PubMed

Cooper, Mark; Chapman, Scott C; Podlich, Dean W; Hammer, Graeme L

2002-01-01

In this paper we refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. However, resolving the GP problem is a fundamental requirement if we are to understand and predict phenotypes given knowledge of the genome and model dynamic properties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses we observe. We discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organization. We apply this quantitative framework to an investigation of the processes involved in genetic improvement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of environments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model. We use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to-phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improvement by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes.

Understanding African Swine Fever infection dynamics in Sardinia using a spatially explicit transmission model in domestic pig farms.

PubMed

Mur, L; Sánchez-Vizcaíno, J M; Fernández-Carrión, E; Jurado, C; Rolesu, S; Feliziani, F; Laddomada, A; Martínez-López, B

2018-02-01

African swine fever virus (ASFV) has been endemic in Sardinia since 1978, resulting in severe losses for local pig producers and creating important problems for the island's veterinary authorities. This study used a spatially explicit stochastic transmission model followed by two regression models to investigate the dynamics of ASFV spread amongst domestic pig farms, to identify geographic areas at highest risk and determine the role of different susceptible pig populations (registered domestic pigs, non-registered domestic pigs [brado] and wild boar) in ASF occurrence. We simulated transmission within and between farms using an adapted version of the previously described model known as Be-FAST. Results from the model revealed a generally low diffusion of ASF in Sardinia, with only 24% of the simulations resulting in disease spread, and for each simulated outbreak on average only four farms and 66 pigs were affected. Overall, local spread (indirect transmission between farms within a 2 km radius through fomites) was the most common route of transmission, being responsible for 98.6% of secondary cases. The risk of ASF occurrence for each domestic pig farm was estimated from the spread model results and integrated in two regression models together with available data for brado and wild boar populations. There was a significant association between the density of all three populations (domestic pigs, brado, and wild boar) and ASF occurrence in Sardinia. The most significant risk factors were the high densities of brado (OR = 2.2) and wild boar (OR = 2.1). The results of both analyses demonstrated that ASF epidemiology and infection dynamics in Sardinia create a complex and multifactorial disease situation, where all susceptible populations play an important role. To stop ASF transmission in Sardinia, three main factors (improving biosecurity on domestic pig farms, eliminating brado practices and better management of wild boars) need to be addressed. © 2017 Blackwell Verlag GmbH.

Survival of the biological control agent Candida sake CPA-1 on grapes under the influence of abiotic factors.

PubMed

Calvo-Garrido, C; Viñas, I; Usall, J; Rodríguez-Romera, M; Ramos, M C; Teixidó, N

2014-09-01

As reliability of preharvest applications of biological control agents (BCAs) to control fruit pathogens is highly dependent on the survival of the selected organism, this study aimed to describe the population dynamics of the yeast-BCA Candida sake (Saito & Ota) CPA-1 on grape berries under the effect of abiotic factors such as temperature, relative humidity, sunlight and rainfall. Candida sake (5 × 10(7) CFU ml(-1)), combined with different concentrations of the food additive Fungicover(®), was applied on grape berry clusters. Treated clusters were then exposed to abiotic factors in field or laboratory conditions, recovering populations to describe C. sake population dynamics. The addition of Fungicover significantly increased C. sake multiplication under optimal growth conditions and improved survival under fluctuating abiotic factors. After field applications, significant differences in populations on grape bunches exposed or covered by fine foliage were detected. Simulated rainfall washed off C. sake populations by 0·6-0·9 log units after 20 mm of rain volume. Allowing populations to establish for 24 h or more, prior to a rain event, persistence on grape berries significantly increased and the effect of rain intensity was not observable. Candida sake demonstrated high survival ability under unfavourable environmental conditions and persistence under intense rain. The study evidenced the importance of the first period just after application for C. sake survival on grape tissues and also the protective effect of the additive Fungicover. This research provides new information on the survival of C. sake under field conditions and its practical implications for recommending timing of spray with this antagonist. Our results could be useful for other yeast antagonists applied before harvest. This work, for the first time, defines population dynamics of a yeast BCA using simulated rainfall. © 2014 The Society for Applied Microbiology.

An agent-based approach for modeling dynamics of contagious disease spread

PubMed Central

Perez, Liliana; Dragicevic, Suzana

2009-01-01

Background The propagation of communicable diseases through a population is an inherent spatial and temporal process of great importance for modern society. For this reason a spatially explicit epidemiologic model of infectious disease is proposed for a greater understanding of the disease's spatial diffusion through a network of human contacts. Objective The objective of this study is to develop an agent-based modelling approach the integrates geographic information systems (GIS) to simulate the spread of a communicable disease in an urban environment, as a result of individuals' interactions in a geospatial context. Methods The methodology for simulating spatiotemporal dynamics of communicable disease propagation is presented and the model is implemented using measles outbreak in an urban environment as a case study. Individuals in a closed population are explicitly represented by agents associated to places where they interact with other agents. They are endowed with mobility, through a transportation network allowing them to move between places within the urban environment, in order to represent the spatial heterogeneity and the complexity involved in infectious diseases diffusion. The model is implemented on georeferenced land use dataset from Metro Vancouver and makes use of census data sets from Statistics Canada for the municipality of Burnaby, BC, Canada study site. Results The results provide insights into the application of the model to calculate ratios of susceptible/infected in specific time frames and urban environments, due to its ability to depict the disease progression based on individuals' interactions. It is demonstrated that the dynamic spatial interactions within the population lead to high numbers of exposed individuals who perform stationary activities in areas after they have finished commuting. As a result, the sick individuals are concentrated in geographical locations like schools and universities. Conclusion The GIS-agent based model designed for this study can be easily customized to study the disease spread dynamics of any other communicable disease by simply adjusting the modeled disease timeline and/or the infection model and modifying the transmission process. This type of simulations can help to improve comprehension of disease spread dynamics and to take better steps towards the prevention and control of an epidemic outbreak. PMID:19656403

Galaxy Zoo: Comparing the visual morphology of synthetic galaxies from the Illustris simulation with those in the real Universe.

NASA Astrophysics Data System (ADS)

Dickinson, Hugh; Lintott, Chris; Scarlata, Claudia; Fortson, Lucy; Bamford, Steven; Cardamone, Carolin; Keel, William C.; Kruk, Sandor; Masters, Karen; Simmons, Brooke D.; Vogelsberger, Mark; Torrey, Paul; Snyder, Gregory; Galaxy Zoo Science Team

2018-01-01

We present a comparision between the Illustris simulations and classifications from Galaxy Zoo, aiming to test the ability of modern large-scale cosmological simulations to accurately reproduce the local galaxy population. This comparison is enabled by the increasingly high spatial and temporal resolution obtained by such surveys.Using classifications that were accumulated via the Galaxy Zoo citizen science interface, we compare the visual morphologies for simulated images of Illustris galaxies with a compatible sample of images drawn from the Sloan Digital Sky Survey (SDSS) Legacy Survey.For simulated galaxies with stellar masses less than 1011 M⊙, significant differences are identified, which are most likely due to the limited resolution of the simulation, but could be revealing real differences in the dynamical evolution of populations of galaxies in the real and model universes. Above 1011 M⊙, Illustris galaxy morphologies correspond better with those of their SDSS counterparts, although even in this mass range the simulation appears to underproduce obviously disk-like galaxies. Morphologies of Illustris galaxies less massive than 1011 M⊙ should be treated with care.

Projecting pest population dynamics under global warming: the combined effect of inter- and intra-annual variations.

PubMed

Zidon, Royi; Tsueda, Hirotsugu; Morin, Efrat; Morin, Shai

2016-06-01

The typical short generation length of insects makes their population dynamics highly sensitive not only to mean annual temperatures but also to their intra-annual variations. To consider the combined effect of both thermal factors under global warming, we propose a modeling framework that links general circulation models (GCMs) with a stochastic weather generator and population dynamics models to predict species population responses to inter- and intra-annual temperature changes. This framework was utilized to explore future changes in populations of Bemisia tabaci, an invasive insect pest-species that affects multiple agricultural systems in the Mediterranean region. We considered three locations representing different pest status and climatic conditions: Montpellier (France), Seville (Spain), and Beit-Jamal (Israel). We produced ensembles of local daily temperature realizations representing current and future (mid-21st century) climatic conditions under two emission scenarios for the three locations. Our simulations predicted a significant increase in the average number of annual generations and in population size, and a significant lengthening of the growing season in all three locations. A negative effect was found only in Seville for the summer season, where future temperatures lead to a reduction in population size. High variability in population size was observed between years with similar annual mean temperatures, suggesting a strong effect of intra-annual temperature variation. Critical periods were from late spring to late summer in Montpellier and from late winter to early summer in Seville and Beit-Jamal. Although our analysis suggested that earlier seasonal activity does not necessarily lead to increased populations load unless an additional generation is produced, it is highly likely that the insect will become a significant pest of open-fields at Mediterranean latitudes above 40° during the next 50 years. Our simulations also implied that current predictions based on mean temperature anomalies are relatively conservative and it is better to apply stochastic tools to resolve complex responses to climate change while taking natural variability into account. In summary, we propose a modeling framework capable of determining distinct intra-annual temperature patterns leading to large or small population sizes, for pest risk assessment and management planning of both natural and agricultural ecosystems.

Effects of dispersal on total biomass in a patchy, heterogeneous system: Analysis and experiment.

PubMed

Zhang, Bo; Liu, Xin; DeAngelis, D L; Ni, Wei-Ming; Wang, G Geoff

2015-06-01

An intriguing recent result from mathematics is that a population diffusing at an intermediate rate in an environment in which resources vary spatially will reach a higher total equilibrium biomass than the population in an environment in which the same total resources are distributed homogeneously. We extended the current mathematical theory to apply to logistic growth and also showed that the result applies to patchy systems with dispersal among patches, both for continuous and discrete time. This allowed us to make specific predictions, through simulations, concerning the biomass dynamics, which were verified by a laboratory experiment. The experiment was a study of biomass growth of duckweed (Lemna minor Linn.), where the resources (nutrients added to water) were distributed homogeneously among a discrete series of water-filled containers in one treatment, and distributed heterogeneously in another treatment. The experimental results showed that total biomass peaked at an intermediate, relatively low, diffusion rate, higher than the total carrying capacity of the system and agreeing with the simulation model. The implications of the experiment to dynamics of source, sink, and pseudo-sink dynamics are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

Diversity-induced resonance in the response to social norms

NASA Astrophysics Data System (ADS)

Tessone, Claudio J.; Sánchez, Angel; Schweitzer, Frank

2013-02-01

In this paper we focus on diversity-induced resonance, which was recently found in bistable, excitable, and other physical systems. We study the appearance of this phenomenon in a purely economic model of cooperating and defecting agents. An agent's contribution to a public good is seen as a social norm, so defecting agents face a social pressure, which decreases if free riding becomes widespread. In this model, diversity among agents naturally appears because of the different sensitivities towards the social norm. We study the evolution of cooperation as a response to the social norm (i) for the replicator dynamics and (ii) for the logit dynamics by means of numerical simulations. Diversity-induced resonance is observed as a maximum in the response of agents to changes in the social norm as a function of the degree of heterogeneity in the population. We provide an analytical, mean-field approach for the logit dynamics and find very good agreement with the simulations. From a socioeconomic perspective, our results show that, counterintuitively, diversity in the individual sensitivity to social norms may result in a society that better follows such norms as a whole, even if part of the population is less prone to follow them.

Trait-based Modeling of Larval Dispersal in the Gulf of Maine

NASA Astrophysics Data System (ADS)

Jones, B.; Richardson, D.; Follows, M. J.; Hill, C. N.; Solow, A.; Ji, R.

2016-02-01

Population connectivity of marine species is the inter-generational movement of individuals among geographically separated subpopulations and is a crucial determinant of population dynamics, community structure, and optimal management strategies. For many marine species, population connectivity is largely determined by the dispersal patterns that emerge from a pelagic larval phase. These dispersal patterns are a result of interactions between the physical environment, adult spawning strategy, and larval ecology. Using a generalized trait-based model that represents the adult spawning strategy as a distribution of larval releases in time and space and the larval trait space with the pelagic larval duration, vertical swimming behavior, and settlement habitat preferences, we simulate dispersal patterns in the Gulf of Maine and surrounding regions. We implement this model as an individual-based simulation that tracks Lagrangian particles on a graphics processing unit as they move through hourly archived output from the Finite-Volume Community Ocean Model. The particles are released between the Hudson Canyon and Nova Scotia and the release distributions are determined using a novel method that minimizes the number of simulations required to achieve a predetermined level of precision for the connectivity matrices. The simulated larvae have a variable pelagic larval duration and exhibit multiple forms of dynamic depth-keeping behavior. We describe how these traits influence the dispersal trajectories and connectivity patterns among regions in the northwest Atlantic. Our description includes the probability of successful recruitment, patchiness of larval distributions, and the variability of these properties in time and space under a variety of larval dispersal strategies.

Quantum clustering and network analysis of MD simulation trajectories to probe the conformational ensembles of protein-ligand interactions.

PubMed

Bhattacharyya, Moitrayee; Vishveshwara, Saraswathi

2011-07-01

In this article, we present a novel application of a quantum clustering (QC) technique to objectively cluster the conformations, sampled by molecular dynamics simulations performed on different ligand bound structures of the protein. We further portray each conformational population in terms of dynamically stable network parameters which beautifully capture the ligand induced variations in the ensemble in atomistic detail. The conformational populations thus identified by the QC method and verified by network parameters are evaluated for different ligand bound states of the protein pyrrolysyl-tRNA synthetase (DhPylRS) from D. hafniense. The ligand/environment induced re-distribution of protein conformational ensembles forms the basis for understanding several important biological phenomena such as allostery and enzyme catalysis. The atomistic level characterization of each population in the conformational ensemble in terms of the re-orchestrated networks of amino acids is a challenging problem, especially when the changes are minimal at the backbone level. Here we demonstrate that the QC method is sensitive to such subtle changes and is able to cluster MD snapshots which are similar at the side-chain interaction level. Although we have applied these methods on simulation trajectories of a modest time scale (20 ns each), we emphasize that our methodology provides a general approach towards an objective clustering of large-scale MD simulation data and may be applied to probe multistate equilibria at higher time scales, and to problems related to protein folding for any protein or protein-protein/RNA/DNA complex of interest with a known structure.

Extinction phase transitions in a model of ecological and evolutionary dynamics

NASA Astrophysics Data System (ADS)

Barghathi, Hatem; Tackkett, Skye; Vojta, Thomas

2017-07-01

We study the non-equilibrium phase transition between survival and extinction of spatially extended biological populations using an agent-based model. We especially focus on the effects of global temporal fluctuations of the environmental conditions, i.e., temporal disorder. Using large-scale Monte-Carlo simulations of up to 3 × 107 organisms and 105 generations, we find the extinction transition in time-independent environments to be in the well-known directed percolation universality class. In contrast, temporal disorder leads to a highly unusual extinction transition characterized by logarithmically slow population decay and enormous fluctuations even for large populations. The simulations provide strong evidence for this transition to be of exotic infinite-noise type, as recently predicted by a renormalization group theory. The transition is accompanied by temporal Griffiths phases featuring a power-law dependence of the life time on the population size.

Integrating biology, field logistics, and simulations to optimize parameter estimation for imperiled species

USGS Publications Warehouse

Lanier, Wendy E.; Bailey, Larissa L.; Muths, Erin L.

2016-01-01

Conservation of imperiled species often requires knowledge of vital rates and population dynamics. However, these can be difficult to estimate for rare species and small populations. This problem is further exacerbated when individuals are not available for detection during some surveys due to limited access, delaying surveys and creating mismatches between the breeding behavior and survey timing. Here we use simulations to explore the impacts of this issue using four hypothetical boreal toad (Anaxyrus boreas boreas) populations, representing combinations of logistical access (accessible, inaccessible) and breeding behavior (synchronous, asynchronous). We examine the bias and precision of survival and breeding probability estimates generated by survey designs that differ in effort and timing for these populations. Our findings indicate that the logistical access of a site and mismatch between the breeding behavior and survey design can greatly limit the ability to yield accurate and precise estimates of survival and breeding probabilities. Simulations similar to what we have performed can help researchers determine an optimal survey design(s) for their system before initiating sampling efforts.

Molecular dynamics studies of the conformation of sorbitol

PubMed Central

Lerbret, A.; Mason, P.E.; Venable, R.M.; Cesàro, A.; Saboungi, M.-L.; Pastor, R.W.; Brady, J.W.

2009-01-01

Molecular dynamics simulations of a 3 m aqueous solution of D-sorbitol (also called D-glucitol) have been performed at 300 K, as well as at two elevated temperatures to promote conformational transitions. In principle, sorbitol is more flexible than glucose since it does not contain a constraining ring. However, a conformational analysis revealed that the sorbitol chain remains extended in solution, in contrast to the bent conformation found experimentally in the crystalline form. While there are 243 staggered conformations of the backbone possible for this open-chain polyol, only a very limited number were found to be stable in the simulations. Although many conformers were briefly sampled, only eight were significantly populated in the simulation. The carbon backbones of all but two of these eight conformers were completely extended, unlike the bent crystal conformation. These extended conformers were stabilized by a quite persistent intramolecular hydrogen bond between the hydroxyl groups of carbon C-2 and C-4. The conformational populations were found to be in good agreement with the limited available NMR data except for the C-2–C-3 torsion (spanned by the O-2–O-4 hydrogen bond), where the NMR data supports a more bent structure. PMID:19744646

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-05-17

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

The World According to Malthus and Volterra: The Mathematical Theory of the Struggle for Existence.

ERIC Educational Resources Information Center

Bogdanov, Constantine

1992-01-01

Discusses the mathematical model presented by Vito Volterra to describe the dynamics of population density. Discusses the predator prey relationship, presents an computer simulated model from marine life involving sharks and mackerels, and discusses ecological chaos. (MDH)

Modelling Social Learning in Monkeys

ERIC Educational Resources Information Center

Kendal, Jeremy R.

2008-01-01

The application of modelling to social learning in monkey populations has been a neglected topic. Recently, however, a number of statistical, simulation and analytical approaches have been developed to help examine social learning processes, putative traditions, the use of social learning strategies and the diffusion dynamics of socially…

Effect of temperature on the population dynamics of Aedes aegypti

NASA Astrophysics Data System (ADS)

Yusoff, Nuraini; Tokachil, Mohd Najir

2015-10-01

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

Extinction in neutrally stable stochastic Lotka-Volterra models

NASA Astrophysics Data System (ADS)

Dobrinevski, Alexander; Frey, Erwin

2012-05-01

Populations of competing biological species exhibit a fascinating interplay between the nonlinear dynamics of evolutionary selection forces and random fluctuations arising from the stochastic nature of the interactions. The processes leading to extinction of species, whose understanding is a key component in the study of evolution and biodiversity, are influenced by both of these factors. Here, we investigate a class of stochastic population dynamics models based on generalized Lotka-Volterra systems. In the case of neutral stability of the underlying deterministic model, the impact of intrinsic noise on the survival of species is dramatic: It destroys coexistence of interacting species on a time scale proportional to the population size. We introduce a new method based on stochastic averaging which allows one to understand this extinction process quantitatively by reduction to a lower-dimensional effective dynamics. This is performed analytically for two highly symmetrical models and can be generalized numerically to more complex situations. The extinction probability distributions and other quantities of interest we obtain show excellent agreement with simulations.

Extinction in neutrally stable stochastic Lotka-Volterra models.

PubMed

Dobrinevski, Alexander; Frey, Erwin

2012-05-01

Populations of competing biological species exhibit a fascinating interplay between the nonlinear dynamics of evolutionary selection forces and random fluctuations arising from the stochastic nature of the interactions. The processes leading to extinction of species, whose understanding is a key component in the study of evolution and biodiversity, are influenced by both of these factors. Here, we investigate a class of stochastic population dynamics models based on generalized Lotka-Volterra systems. In the case of neutral stability of the underlying deterministic model, the impact of intrinsic noise on the survival of species is dramatic: It destroys coexistence of interacting species on a time scale proportional to the population size. We introduce a new method based on stochastic averaging which allows one to understand this extinction process quantitatively by reduction to a lower-dimensional effective dynamics. This is performed analytically for two highly symmetrical models and can be generalized numerically to more complex situations. The extinction probability distributions and other quantities of interest we obtain show excellent agreement with simulations.

Computational Fluid Dynamics-Population Balance Model Simulation of Effects of Cell Design and Operating Parameters on Gas-Liquid Two-Phase Flows and Bubble Distribution Characteristics in Aluminum Electrolysis Cells

NASA Astrophysics Data System (ADS)

Zhan, Shuiqing; Wang, Junfeng; Wang, Zhentao; Yang, Jianhong

2018-02-01

The effects of different cell design and operating parameters on the gas-liquid two-phase flows and bubble distribution characteristics under the anode bottom regions in aluminum electrolysis cells were analyzed using a three-dimensional computational fluid dynamics-population balance model. These parameters include inter-anode channel width, anode-cathode distance (ACD), anode width and length, current density, and electrolyte depth. The simulations results show that the inter-anode channel width has no significant effect on the gas volume fraction, electrolyte velocity, and bubble size. With increasing ACD, the above values decrease and more uniform bubbles can be obtained. Different effects of the anode width and length can be concluded in different cell regions. With increasing current density, the gas volume fraction and electrolyte velocity increase, but the bubble size keeps nearly the same. Increasing electrolyte depth decreased the gas volume fraction and bubble size in particular areas and the electrolyte velocity increased.

Recombination and phenotype evolution dynamics of Helicobacter pylori in colonized hosts.

PubMed

Shafiee, Ahmad; Amini, Massoud; Emamirad, Hassan; Abadi, Amin Talebi Bezmin

2016-07-01

The ample genetic diversity and variability of Helicobater pylori, and therefore its phenotypic evolution, relate not only to frequent mutation and selection but also to intra-specific recombination. Webb and Blaser applied a mathematical model to distinguish the role of selection and mutation for Lewis antigen phenotype evolution during long-term gastric colonization in infected animal hosts (mice and gerbils). To investigate the role of recombination in Lewis antigen phenotype evolution, we have developed a prior population dynamic by adding recombination term to the model. We simulate and interpret the new model simulation's results with a comparative analysis of biological aspects. The main conclusions are as follows: (i) the models and consequently the hosts with higher recombination rate require a longer time for stabilization; and (ii) recombination and mutation have opposite effects on the size of H. pylori populations with phenotypes in the range of the most-fit ones (i.e. those that have a selective advantage) due to natural selection, although both can increase phenotypic diversity.

Modelling and Control of Robotic Leg as Assistive Device

NASA Astrophysics Data System (ADS)

Jingye, Yee; Zain, Badrul Aisham bin Md

2017-10-01

The ageing population (people older than 60 years old) is expected to constitute 21.8% of global population by year 2050. When human ages, bodily function including locomotors will deteriorate. Besides, there are hundreds of thousands of victims who suffer from multiple health conditions worldwide that leads to gait impairment. A promising solution will be the lower limb powered-exoskeleton. This study is to be a start-up platform to design a lower limb powered-exoskeleton for a normal Malaysian male, by designing and simulating the dynamic model of a 2-link robotic leg to observe its behaviour under different input conditions with and without a PID controller. Simulink in MATLAB software is used as the dynamic modelling and simulation software for this study. It is observed that the 2-links robotic leg behaved differently under different input conditions, and perform the best when it is constrained and controlled by PID controller. Simulink model is formed as a foundation for the upcoming researches and can be modified and utilised by the future researchers.

HOW POPULATION STRUCTURE SHAPES NEIGHBORHOOD SEGREGATION*

PubMed Central

Bruch, Elizabeth E.

2014-01-01

This study investigates how choices about social affiliation based on one attribute can exacerbate or attenuate segregation on another correlated attribute. The specific application is the role of racial and economic factors in generating patterns of racial residential segregation. I identify three population parameters—between-group inequality, within-group inequality, and relative group size—that determine how income inequality between race groups affects racial segregation. I use data from the Panel Study of Income Dynamics to estimate models of individual-level residential mobility, and incorporate these estimates into agent-based models. I then simulate segregation dynamics under alternative assumptions about: (1) the relative size of minority groups; and (2) the degree of correlation between race and income among individuals. I find that income inequality can have offsetting effects at the high and low ends of the income distribution. I demonstrate the empirical relevance of the simulation results using fixed-effects, metro-level regressions applied to 1980-2000 U.S. Census data. PMID:25009360

Computational Model of Population Dynamics Based on the Cell Cycle and Local Interactions

NASA Astrophysics Data System (ADS)

Oprisan, Sorinel Adrian; Oprisan, Ana

2005-03-01

Our study bridges cellular (mesoscopic) level interactions and global population (macroscopic) dynamics of carcinoma. The morphological differences and transitions between well and smooth defined benign tumors and tentacular malignat tumors suggest a theoretical analysis of tumor invasion based on the development of mathematical models exhibiting bifurcations of spatial patterns in the density of tumor cells. Our computational model views the most representative and clinically relevant features of oncogenesis as a fight between two distinct sub-systems: the immune system of the host and the neoplastic system. We implemented the neoplastic sub-system using a three-stage cell cycle: active, dormant, and necrosis. The second considered sub-system consists of cytotoxic active (effector) cells — EC, with a very broad phenotype ranging from NK cells to CTL cells, macrophages, etc. Based on extensive numerical simulations, we correlated the fractal dimensions for carcinoma, which could be obtained from tumor imaging, with the malignat stage. Our computational model was able to also simulate the effects of surgical, chemotherapeutical, and radiotherapeutical treatments.

Simulating Society Transitions: Standstill, Collapse and Growth in an Evolving Network Model

PubMed Central

Xu, Guanghua; Yang, Junjie; Li, Guoqing

2013-01-01

We developed a model society composed of various occupations that interact with each other and the environment, with the capability of simulating three widely recognized societal transition patterns: standstill, collapse and growth, which are important compositions of society evolving dynamics. Each occupation is equipped with a number of inhabitants that may randomly flow to other occupations, during which process new occupations may be created and then interact with existing ones. Total population of society is associated with productivity, which is determined by the structure and volume of the society. We ran the model under scenarios such as parasitism, environment fluctuation and invasion, which correspond to different driving forces of societal transition, and obtained reasonable simulation results. This work adds to our understanding of societal evolving dynamics as well as provides theoretical clues to sustainable development. PMID:24086530

A stochastic-field description of finite-size spiking neural networks

PubMed Central

Longtin, André

2017-01-01

Neural network dynamics are governed by the interaction of spiking neurons. Stochastic aspects of single-neuron dynamics propagate up to the network level and shape the dynamical and informational properties of the population. Mean-field models of population activity disregard the finite-size stochastic fluctuations of network dynamics and thus offer a deterministic description of the system. Here, we derive a stochastic partial differential equation (SPDE) describing the temporal evolution of the finite-size refractory density, which represents the proportion of neurons in a given refractory state at any given time. The population activity—the density of active neurons per unit time—is easily extracted from this refractory density. The SPDE includes finite-size effects through a two-dimensional Gaussian white noise that acts both in time and along the refractory dimension. For an infinite number of neurons the standard mean-field theory is recovered. A discretization of the SPDE along its characteristic curves allows direct simulations of the activity of large but finite spiking networks; this constitutes the main advantage of our approach. Linearizing the SPDE with respect to the deterministic asynchronous state allows the theoretical investigation of finite-size activity fluctuations. In particular, analytical expressions for the power spectrum and autocorrelation of activity fluctuations are obtained. Moreover, our approach can be adapted to incorporate multiple interacting populations and quasi-renewal single-neuron dynamics. PMID:28787447

The geosimulation of West Nile virus propagation: a multi-agent and climate sensitive tool for risk management in public health

PubMed Central

Bouden, Mondher; Moulin, Bernard; Gosselin, Pierre

2008-01-01

Background Since 1999, the expansion of the West Nile virus (WNV) epizooty has led public health authorities to build and operate surveillance systems in North America. These systems are very useful to collect data, but cannot be used to forecast the probable spread of the virus in coming years. Such forecasts, if proven reliable, would permit preventive measures to be put into place at the appropriate level of expected risk and at the appropriate time. It is within this context that the Multi-Agent GeoSimulation approach has been selected to develop a system that simulates the interactions of populations of mosquitoes and birds over space and time in relation to the spread and transmission of WNV. This simulation takes place in a virtual mapping environment representing a large administrative territory (e.g. province, state) and carried out under various climate scenarios in order to simulate the effects of vector control measures such as larviciding at scales of 1/20 000 or smaller. Results After setting some hypotheses, a conceptual model and system architecture were developed to describe the population dynamics and interactions of mosquitoes (genus Culex) and American crows, which were chosen as the main actors in the simulation. Based on a mathematical compartment model used to simulate the population dynamics, an operational prototype was developed for the Southern part of Quebec (Canada). The system allows users to modify the parameters of the model, to select various climate and larviciding scenarios, to visualize on a digital map the progression (on a weekly or daily basis) of the infection in and around the crows' roosts and to generate graphs showing the evolution of the populations. The basic units for visualisation are municipalities. Conclusion In all likelihood this system might be used to support short term decision-making related to WNV vector control measures, including the use of larvicides, according to climatic scenarios. Once fully calibrated in several real-life contexts, this promising approach opens the door to the study and management of other zoonotic diseases such as Lyme disease. PMID:18606008

Dynamic model for preventing mental retardation in the population: the importance of poverty and deprivation.

PubMed

McDermott, S W; Altekruse, J M

1994-01-01

A dynamic simulation model is used to answer the question, "What is the most effective child health policy initiative for the prevention of mental retardation (MR)?" The impact of medical strategies is contrasted with social interventions to see how they affect the prevalence of MR in the general population. The model is based on data from four U.S. Census and California Vital Statistics reports (1960, 1970, 1980, 1990). An interstate comparison (California and South Carolina) uses 1990 data. The results of the simulations reveal that medical interventions to improve the developmental outcome of low birth weight (LBW) infants did not cause a reduction in the rate of MR in the population after a 24-year trial period. In contrast, reducing the proportion of children living in poverty who are exposed to environmental deprivation significantly decreased (10%) MR at the end of the model's time period. This analysis supports the view that long-term reduction in MR prevalence is attainable by modifying public policies that influence children's development. Effective MR prevention calls for public policy committed to multifaceted health and educational services for both affected parents and their young children.

Bacterial population dynamics during the ensiling of Medicago sativa (alfalfa) and subsequent exposure to air.

PubMed

McGarvey, J A; Franco, R B; Palumbo, J D; Hnasko, R; Stanker, L; Mitloehner, F M

2013-06-01

To describe, at high resolution, the bacterial population dynamics and chemical transformations during the ensiling of alfalfa and subsequent exposure to air. Samples of alfalfa, ensiled alfalfa and silage exposed to air were collected and their bacterial population structures compared using 16S rRNA gene libraries containing approximately 1900 sequences each. Cultural and chemical analyses were also performed to complement the 16S gene sequence data. Sequence analysis revealed significant differences (P < 0·05) in the bacterial populations at each time point. The alfalfa-derived library contained mostly sequences associated with the Gammaproteobacteria (including the genera: Enterobacter, Erwinia and Pantoea); the ensiled material contained mostly sequences associated with the lactic acid bacteria (LAB) (including the genera: Lactobacillus, Pediococcus and Lactococcus). Exposure to air resulted in even greater percentages of LAB, especially among the genus Lactobacillus, and a significant drop in bacterial diversity. In-depth 16S rRNA gene sequence analysis revealed significant bacterial population structure changes during ensiling and again during exposure to air. This in-depth description of the bacterial population dynamics that occurred during ensiling and simulated feed out expands our knowledge of these processes. © 2013 The Society for Applied Microbiology No claim to US Government works.

Regulation of Cortical Dynamic Range by Background Synaptic Noise and Feedforward Inhibition.

PubMed

Khubieh, Ayah; Ratté, Stéphanie; Lankarany, Milad; Prescott, Steven A

2016-08-01

The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then staggered all-or-none recruitment of those neurons would be necessary for the population to achieve a broad dynamic range. Contrary to this explanation, we show here through dynamic clamp experiments in vitro and computer simulations that pyramidal neurons have a broad dynamic range under the noisy conditions that exist in the intact brain due to background synaptic input. Feedforward inhibition capitalizes on those noise effects to control neuronal gain and thereby regulates the population dynamic range. Importantly, noise allows neurons to be recruited gradually and occludes the staggered recruitment previously attributed to heterogeneous excitation. Feedforward inhibition protects spike timing against the disruptive effects of noise, meaning noise can enable the gain control required for rate coding without compromising the precise spike timing required for temporal coding. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Cannibalism in discrete-time predator-prey systems.

PubMed

Chow, Yunshyong; Jang, Sophia R-J

2012-01-01

In this study, we propose and investigate a two-stage population model with cannibalism. It is shown that cannibalism can destabilize and lower the magnitude of the interior steady state. However, it is proved that cannibalism has no effect on the persistence of the population. Based on this model, we study two systems of predator-prey interactions where the prey population is cannibalistic. A sufficient condition based on the nontrivial boundary steady state for which both populations can coexist is derived. It is found via numerical simulations that introduction of the predator population may either stabilize or destabilize the prey dynamics, depending on cannibalism coefficients and other vital parameters.

Entrainment and Control of Bacterial Populations: An in Silico Study over a Spatially Extended Agent Based Model.

PubMed

Mina, Petros; Tsaneva-Atanasova, Krasimira; Bernardo, Mario di

2016-07-15

We extend a spatially explicit agent based model (ABM) developed previously to investigate entrainment and control of the emergent behavior of a population of synchronized oscillating cells in a microfluidic chamber. Unlike most of the work in models of control of cellular systems which focus on temporal changes, we model individual cells with spatial dependencies which may contribute to certain behavioral responses. We use the model to investigate the response of both open loop and closed loop strategies, such as proportional control (P-control), proportional-integral control (PI-control) and proportional-integral-derivative control (PID-control), to heterogeinities and growth in the cell population, variations of the control parameters and spatial effects such as diffusion in the spatially explicit setting of a microfluidic chamber setup. We show that, as expected from the theory of phase locking in dynamical systems, open loop control can only entrain the cell population in a subset of forcing periods, with a wide variety of dynamical behaviors obtained outside these regions of entrainment. Closed-loop control is shown instead to guarantee entrainment in a much wider region of control parameter space although presenting limitations when the population size increases over a certain threshold. In silico tracking experiments are also performed to validate the ability of classical control approaches to achieve other reference behaviors such as a desired constant output or a linearly varying one. All simulations are carried out in BSim, an advanced agent-based simulator of microbial population which is here extended ad hoc to include the effects of control strategies acting onto the population.

Plasma dynamics on current-carrying magnetic flux tubes. II - Low potential simulation

NASA Technical Reports Server (NTRS)

Swift, Daniel W.

1992-01-01

The evolution of plasma in a current-carrying magnetic flux tube of variable cross section is investigated using a one-dimensional numerical simulation. The flux tube is narrow at the two ends and broad in the middle. The middle part of the flux tube is loaded with a hot, magnetically trapped population, and the two ends have a more dense, gravitationally bound population. A potential difference larger than the gravitational potential but less than the energy of the hot population is applied across the domain. The general result is that the potential change becomes distributed along the anode half of the domain, with negligible potential change on the cathode half. The potential is supported by the mirror force of magnetically trapped particles. The simulations show a steady depletion of plasma on the anode side of the flux tube. The current steadily decreases on a time scale of an ion transit time. The results may provide an explanation for the observed plasma depletions on auroral field lines carrying upward currents.

Dynamics of a plant-herbivore-predator system with plant-toxicity

USGS Publications Warehouse

Feng, Zhilan; Qiu, Zhipeng; Liu, Rongsong; DeAngelis, Donald L.

2011-01-01

A system of ordinary differential equations is considered that models the interactions of two plant species populations, an herbivore population, and a predator population. We use a toxin-determined functional response to describe the interactions between plant species and herbivores and use a Holling Type II functional response to model the interactions between herbivores and predators. In order to study how the predators impact the succession of vegetation, we derive invasion conditions under which a plant species can invade into an environment in which another plant species is co-existing with a herbivore population with or without a predator population. These conditions provide threshold quantities for several parameters that may play a key role in the dynamics of the system. Numerical simulations are conducted to reinforce the analytical results. This model can be applied to a boreal ecosystem trophic chain to examine the possible cascading effects of predator-control actions when plant species differ in their levels of toxic defense.

Dynamics of a plant-herbivore-predator system with plant-toxicity.

PubMed

Feng, Zhilan; Qiu, Zhipeng; Liu, Rongsong; DeAngelis, Donald L

2011-02-01

A system of ordinary differential equations is considered that models the interactions of two plant species populations, an herbivore population, and a predator population. We use a toxin-determined functional response to describe the interactions between plant species and herbivores and use a Holling Type II functional response to model the interactions between herbivores and predators. In order to study how the predators impact the succession of vegetation, we derive invasion conditions under which a plant species can invade into an environment in which another plant species is co-existing with a herbivore population with or without a predator population. These conditions provide threshold quantities for several parameters that may play a key role in the dynamics of the system. Numerical simulations are conducted to reinforce the analytical results. This model can be applied to a boreal ecosystem trophic chain to examine the possible cascading effects of predator-control actions when plant species differ in their levels of toxic defense. Published by Elsevier Inc.

Threshold Dynamics of a Temperature-Dependent Stage-Structured Mosquito Population Model with Nested Delays.

PubMed

Wang, Xiunan; Zou, Xingfu

2018-05-21

Mosquito-borne diseases remain a significant threat to public health and economics. Since mosquitoes are quite sensitive to temperature, global warming may not only worsen the disease transmission case in current endemic areas but also facilitate mosquito population together with pathogens to establish in new regions. Therefore, understanding mosquito population dynamics under the impact of temperature is considerably important for making disease control policies. In this paper, we develop a stage-structured mosquito population model in the environment of a temperature-controlled experiment. The model turns out to be a system of periodic delay differential equations with periodic delays. We show that the basic reproduction number is a threshold parameter which determines whether the mosquito population goes to extinction or remains persistent. We then estimate the parameter values for Aedes aegypti, the mosquito that transmits dengue virus. We verify the analytic result by numerical simulations with the temperature data of Colombo, Sri Lanka where a dengue outbreak occurred in 2017.

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size

PubMed Central

Gerstner, Wulfram

2017-01-01

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50–2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations. PMID:28422957

Electron-phonon thermalization in a scalable method for real-time quantum dynamics

NASA Astrophysics Data System (ADS)

Rizzi, Valerio; Todorov, Tchavdar N.; Kohanoff, Jorge J.; Correa, Alfredo A.

2016-01-01

We present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicit quantum dynamics.

System Dynamics Modeling for Public Health: Background and Opportunities

PubMed Central

Homer, Jack B.; Hirsch, Gary B.

2006-01-01

The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy. PMID:16449591

Reliable oligonucleotide conformational ensemble generation in explicit solvent for force field assessment using reservoir replica exchange molecular dynamics simulations

PubMed Central

Henriksen, Niel M.; Roe, Daniel R.; Cheatham, Thomas E.

2013-01-01

Molecular dynamics force field development and assessment requires a reliable means for obtaining a well-converged conformational ensemble of a molecule in both a time-efficient and cost-effective manner. This remains a challenge for RNA because its rugged energy landscape results in slow conformational sampling and accurate results typically require explicit solvent which increases computational cost. To address this, we performed both traditional and modified replica exchange molecular dynamics simulations on a test system (alanine dipeptide) and an RNA tetramer known to populate A-form-like conformations in solution (single-stranded rGACC). A key focus is on providing the means to demonstrate that convergence is obtained, for example by investigating replica RMSD profiles and/or detailed ensemble analysis through clustering. We found that traditional replica exchange simulations still require prohibitive time and resource expenditures, even when using GPU accelerated hardware, and our results are not well converged even at 2 microseconds of simulation time per replica. In contrast, a modified version of replica exchange, reservoir replica exchange in explicit solvent, showed much better convergence and proved to be both a cost-effective and reliable alternative to the traditional approach. We expect this method will be attractive for future research that requires quantitative conformational analysis from explicitly solvated simulations. PMID:23477537

Potential human cholesterol esterase inhibitor design: benefits from the molecular dynamics simulations and pharmacophore modeling studies.

PubMed

John, Shalini; Thangapandian, Sundarapandian; Lee, Keun Woo

2012-01-01

Human pancreatic cholesterol esterase (hCEase) is one of the lipases found to involve in the digestion of large and broad spectrum of substrates including triglycerides, phospholipids, cholesteryl esters, etc. The presence of bile salts is found to be very important for the activation of hCEase. Molecular dynamic simulations were performed for the apoform and bile salt complexed form of hCEase using the co-ordinates of two bile salts from bovine CEase. The stability of the systems throughout the simulation time was checked and two representative structures from the highly populated regions were selected using cluster analysis. These two representative structures were used in pharmacophore model generation. The generated pharmacophore models were validated and used in database screening. The screened hits were refined for their drug-like properties based on Lipinski's rule of five and ADMET properties. The drug-like compounds were further refined by molecular docking simulation using GOLD program based on the GOLD fitness score, mode of binding, and molecular interactions with the active site amino acids. Finally, three hits of novel scaffolds were selected as potential leads to be used in novel and potent hCEase inhibitor design. The stability of binding modes and molecular interactions of these final hits were re-assured by molecular dynamics simulations.

Reliable oligonucleotide conformational ensemble generation in explicit solvent for force field assessment using reservoir replica exchange molecular dynamics simulations.

PubMed

Henriksen, Niel M; Roe, Daniel R; Cheatham, Thomas E

2013-04-18

Molecular dynamics force field development and assessment requires a reliable means for obtaining a well-converged conformational ensemble of a molecule in both a time-efficient and cost-effective manner. This remains a challenge for RNA because its rugged energy landscape results in slow conformational sampling and accurate results typically require explicit solvent which increases computational cost. To address this, we performed both traditional and modified replica exchange molecular dynamics simulations on a test system (alanine dipeptide) and an RNA tetramer known to populate A-form-like conformations in solution (single-stranded rGACC). A key focus is on providing the means to demonstrate that convergence is obtained, for example, by investigating replica RMSD profiles and/or detailed ensemble analysis through clustering. We found that traditional replica exchange simulations still require prohibitive time and resource expenditures, even when using GPU accelerated hardware, and our results are not well converged even at 2 μs of simulation time per replica. In contrast, a modified version of replica exchange, reservoir replica exchange in explicit solvent, showed much better convergence and proved to be both a cost-effective and reliable alternative to the traditional approach. We expect this method will be attractive for future research that requires quantitative conformational analysis from explicitly solvated simulations.

Genetic drift and selection in many-allele range expansions.

PubMed

Weinstein, Bryan T; Lavrentovich, Maxim O; Möbius, Wolfram; Murray, Andrew W; Nelson, David R

2017-12-01

We experimentally and numerically investigate the evolutionary dynamics of four competing strains of E. coli with differing expansion velocities in radially expanding colonies. We compare experimental measurements of the average fraction, correlation functions between strains, and the relative rates of genetic domain wall annihilations and coalescences to simulations modeling the population as a one-dimensional ring of annihilating and coalescing random walkers with deterministic biases due to selection. The simulations reveal that the evolutionary dynamics can be collapsed onto master curves governed by three essential parameters: (1) an expansion length beyond which selection dominates over genetic drift; (2) a characteristic angular correlation describing the size of genetic domains; and (3) a dimensionless constant quantifying the interplay between a colony's curvature at the frontier and its selection length scale. We measure these parameters with a new technique that precisely measures small selective differences between spatially competing strains and show that our simulations accurately predict the dynamics without additional fitting. Our results suggest that the random walk model can act as a useful predictive tool for describing the evolutionary dynamics of range expansions composed of an arbitrary number of genotypes with different fitnesses.

Structural flexibility of the sulfur mustard molecule at finite temperature from Car-Parrinello molecular dynamics simulations.

PubMed

Lach, Joanna; Goclon, Jakub; Rodziewicz, Pawel

2016-04-05

Sulfur mustard (SM) is one of the most dangerous chemical compounds used against humans, mostly at war conditions but also in terrorist attacks. Even though the sulfur mustard has been synthesized over a hundred years ago, some of its molecular properties are not yet resolved. We investigate the structural flexibility of the SM molecule in the gas phase by Car-Parrinello molecular dynamics simulations. Thorough conformation analysis of 81 different SM configurations using density functional theory is performed to analyze the behavior of the system at finite temperature. The conformational diversity is analyzed with respect to the formation of intramolecular blue-shifting CH⋯S and CH⋯Cl hydrogen bonds. Molecular dynamics simulations indicate that all structural rearrangements between SM local minima are realized either in direct or non-direct way, including the intermediate structure in the last case. We study the lifetime of the SM conformers and perform the population analysis. Additionally, we provide the anharmonic dynamical finite temperature IR spectrum from the Fourier Transform of the dipole moment autocorrelation function to mimic the missing experimental IR spectrum. Copyright © 2015 Elsevier B.V. All rights reserved.

Simulating living organisms with populations of point vortices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmieder, R.W.

1995-07-01

The author has found that time-averaged images of small populations of point vortices can exhibit motions suggestive of the behavior of individual organisms. As an example, the author shows that collections of point vortices confined in a box and subjected to heating can generate patterns that are broadly similar to interspecies defense in certain sea anemones. It is speculated that other simple dynamical systems can be found to produce similar complex organism-like behavior.

Population Dynamics of Owned, Free-Roaming Dogs: Implications for Rabies Control

PubMed Central

Conan, Anne; Akerele, Oluyemisi; Simpson, Greg; Reininghaus, Bjorn; van Rooyen, Jacques; Knobel, Darryn

2015-01-01

Background Rabies is a serious yet neglected public health threat in resource-limited communities in Africa, where the virus is maintained in populations of owned, free-roaming domestic dogs. Rabies elimination can be achieved through the mass vaccination of dogs, but maintaining the critical threshold of vaccination coverage for herd immunity in these populations is hampered by their rapid turnover. Knowledge of the population dynamics of free-roaming dog populations can inform effective planning and implementation of mass dog vaccination campaigns to control rabies. Methodology/Principal Findings We implemented a health and demographic surveillance system in dogs that monitored the entire owned dog population within a defined geographic area in a community in Mpumalanga Province, South Africa. We quantified demographic rates over a 24-month period, from 1st January 2012 through 1st January 2014, and assessed their implications for rabies control by simulating the decline in vaccination coverage over time. During this period, the population declined by 10%. Annual population growth rates were +18.6% in 2012 and -24.5% in 2013. Crude annual birth rates (per 1,000 dog-years of observation) were 451 in 2012 and 313 in 2013. Crude annual death rates were 406 in 2012 and 568 in 2013. Females suffered a significantly higher mortality rate in 2013 than males (mortality rate ratio [MRR] = 1.54, 95% CI = 1.28–1.85). In the age class 0–3 months, the mortality rate of dogs vaccinated against rabies was significantly lower than that of unvaccinated dogs (2012: MRR = 0.11, 95% CI = 0.05–0.21; 2013: MRR = 0.31, 95% CI = 0.11–0.69). The results of the simulation showed that achieving a 70% vaccination coverage during annual campaigns would maintain coverage above the critical threshold for at least 12 months. Conclusions and Significance Our findings provide an evidence base for the World Health Organization’s empirically-derived target of 70% vaccination coverage during annual campaigns. Achieving this will be effective even in highly dynamic populations with extremely high growth rates and rapid turnover. This increases confidence in the feasibility of dog rabies elimination in Africa through mass vaccination. PMID:26545242

Conformational Sampling and Nucleotide-Dependent Transitions of the GroEL Subunit Probed by Unbiased Molecular Dynamics Simulations

PubMed Central

Skjaerven, Lars; Grant, Barry; Muga, Arturo; Teigen, Knut; McCammon, J. Andrew; Reuter, Nathalie; Martinez, Aurora

2011-01-01

GroEL is an ATP dependent molecular chaperone that promotes the folding of a large number of substrate proteins in E. coli. Large-scale conformational transitions occurring during the reaction cycle have been characterized from extensive crystallographic studies. However, the link between the observed conformations and the mechanisms involved in the allosteric response to ATP and the nucleotide-driven reaction cycle are not completely established. Here we describe extensive (in total long) unbiased molecular dynamics (MD) simulations that probe the response of GroEL subunits to ATP binding. We observe nucleotide dependent conformational transitions, and show with multiple 100 ns long simulations that the ligand-induced shift in the conformational populations are intrinsically coded in the structure-dynamics relationship of the protein subunit. Thus, these simulations reveal a stabilization of the equatorial domain upon nucleotide binding and a concomitant “opening” of the subunit, which reaches a conformation close to that observed in the crystal structure of the subunits within the ADP-bound oligomer. Moreover, we identify changes in a set of unique intrasubunit interactions potentially important for the conformational transition. PMID:21423709

Free-energy landscape of intrinsically disordered proteins investigated by all-atom multicanonical molecular dynamics.

PubMed

Higo, Junichi; Umezawa, Koji

2014-01-01

We introduce computational studies on intrinsically disordered proteins (IDPs). Especially, we present our multicanonical molecular dynamics (McMD) simulations of two IDP-partner systems: NRSF-mSin3 and pKID-KIX. McMD is one of enhanced conformational sampling methods useful for conformational sampling of biomolecular systems. IDP adopts a specific tertiary structure upon binding to its partner molecule, although it is unstructured in the unbound state (i.e. the free state). This IDP-specific property is called "coupled folding and binding". The McMD simulation treats the biomolecules with an all-atom model immersed in an explicit solvent. In the initial configuration of simulation, IDP and its partner molecules are set to be distant from each other, and the IDP conformation is disordered. The computationally obtained free-energy landscape for coupled folding and binding has shown that native- and non-native-complex clusters distribute complicatedly in the conformational space. The all-atom simulation suggests that both of induced-folding and population-selection are coupled complicatedly in the coupled folding and binding. Further analyses have exemplified that the conformational fluctuations (dynamical flexibility) in the bound and unbound states are essentially important to characterize IDP functioning.

Fixed points and limit cycles in the population dynamics of lysogenic viruses and their hosts

NASA Astrophysics Data System (ADS)

Wang, Zhenyu; Goldenfeld, Nigel

2010-07-01

Starting with stochastic rate equations for the fundamental interactions between microbes and their viruses, we derive a mean-field theory for the population dynamics of microbe-virus systems, including the effects of lysogeny. In the absence of lysogeny, our model is a generalization of that proposed phenomenologically by Weitz and Dushoff. In the presence of lysogeny, we analyze the possible states of the system, identifying a limit cycle, which we interpret physically. To test the robustness of our mean-field calculations to demographic fluctuations, we have compared our results with stochastic simulations using the Gillespie algorithm. Finally, we estimate the range of parameters that delineate the various steady states of our model.

HexSim - A general purpose framework for spatially-explicit, individual-based modeling

EPA Science Inventory

HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications. This talk will focus on a subset of those ap...

Altruistic aging: The evolutionary dynamics balancing longevity and evolvability.

PubMed

Herrera, Minette; Miller, Aaron; Nishimura, Joel

2017-04-01

Altruism is typically associated with traits or behaviors that benefit the population as a whole, but are costly to the individual. We propose that, when the environment is rapidly changing, senescence (age-related deterioration) can be altruistic. According to numerical simulations of an agent-based model, while long-lived individuals can outcompete their short lived peers, populations composed of long-lived individuals are more likely to go extinct during periods of rapid environmental change. Moreover, as in many situations where other cooperative behavior arises, senescence can be stabilized in a structured population.

Exploring the Dynamics of Propeller Loops in Human Telomeric DNA Quadruplexes Using Atomistic Simulations.

PubMed

Islam, Barira; Stadlbauer, Petr; Gil-Ley, Alejandro; Pérez-Hernández, Guillermo; Haider, Shozeb; Neidle, Stephen; Bussi, Giovanni; Banas, Pavel; Otyepka, Michal; Sponer, Jiri

2017-06-13

We have carried out a series of extended unbiased molecular dynamics (MD) simulations (up to 10 μs long, ∼162 μs in total) complemented by replica-exchange with the collective variable tempering (RECT) approach for several human telomeric DNA G-quadruplex (GQ) topologies with TTA propeller loops. We used different AMBER DNA force-field variants and also processed simulations by Markov State Model (MSM) analysis. The slow conformational transitions in the propeller loops took place on a scale of a few μs, emphasizing the need for long simulations in studies of GQ dynamics. The propeller loops sampled similar ensembles for all GQ topologies and for all force-field dihedral-potential variants. The outcomes of standard and RECT simulations were consistent and captured similar spectrum of loop conformations. However, the most common crystallographic loop conformation was very unstable with all force-field versions. Although the loss of canonical γ-trans state of the first propeller loop nucleotide could be related to the indispensable bsc0 α/γ dihedral potential, even supporting this particular dihedral by a bias was insufficient to populate the experimentally dominant loop conformation. In conclusion, while our simulations were capable of providing a reasonable albeit not converged sampling of the TTA propeller loop conformational space, the force-field description still remained far from satisfactory.

Exploring the Dynamics of Propeller Loops in Human Telomeric DNA Quadruplexes Using Atomistic Simulations

PubMed Central

2017-01-01

We have carried out a series of extended unbiased molecular dynamics (MD) simulations (up to 10 μs long, ∼162 μs in total) complemented by replica-exchange with the collective variable tempering (RECT) approach for several human telomeric DNA G-quadruplex (GQ) topologies with TTA propeller loops. We used different AMBER DNA force-field variants and also processed simulations by Markov State Model (MSM) analysis. The slow conformational transitions in the propeller loops took place on a scale of a few μs, emphasizing the need for long simulations in studies of GQ dynamics. The propeller loops sampled similar ensembles for all GQ topologies and for all force-field dihedral-potential variants. The outcomes of standard and RECT simulations were consistent and captured similar spectrum of loop conformations. However, the most common crystallographic loop conformation was very unstable with all force-field versions. Although the loss of canonical γ-trans state of the first propeller loop nucleotide could be related to the indispensable bsc0 α/γ dihedral potential, even supporting this particular dihedral by a bias was insufficient to populate the experimentally dominant loop conformation. In conclusion, while our simulations were capable of providing a reasonable albeit not converged sampling of the TTA propeller loop conformational space, the force-field description still remained far from satisfactory. PMID:28475322

Development of a computer-simulation model for a plant-nematode system.

PubMed

Ferris, H

1976-07-01

A computer-simulation model (MELSIM) of a Meloidogyne-grapevine system is developed. The objective is to attempt a holistic approach to the study of nematode population dynamics by using experimental data from controlled environmental conditions. A simulator with predictive ability would be useful in considering pest management alternatives and in teaching. Rates of flow and interaction between the components of the system are governed by environmental conditions. Equations for these rates are determined by fitting curves to data from controlled environment studies. Development of the model and trial simulations have revealed deficiencies in understanding of the system and identified areas where further research is necessary.

Highly Disordered Amyloid-β Monomer Probed by Single-Molecule FRET and MD Simulation.

PubMed

Meng, Fanjie; Bellaiche, Mathias M J; Kim, Jae-Yeol; Zerze, Gül H; Best, Robert B; Chung, Hoi Sung

2018-02-27

Monomers of amyloid-β (Aβ) protein are known to be disordered, but there is considerable controversy over the existence of residual or transient conformations that can potentially promote oligomerization and fibril formation. We employed single-molecule Förster resonance energy transfer (FRET) spectroscopy with site-specific dye labeling using an unnatural amino acid and molecular dynamics simulations to investigate conformations and dynamics of Aβ isoforms with 40 (Aβ40) and 42 residues (Aβ42). The FRET efficiency distributions of both proteins measured in phosphate-buffered saline at room temperature show a single peak with very similar FRET efficiencies, indicating there is apparently only one state. 2D FRET efficiency-donor lifetime analysis reveals, however, that there is a broad distribution of rapidly interconverting conformations. Using nanosecond fluorescence correlation spectroscopy, we measured the timescale of the fluctuations between these conformations to be ∼35 ns, similar to that of disordered proteins. These results suggest that both Aβ40 and Aβ42 populate an ensemble of rapidly reconfiguring unfolded states, with no long-lived conformational state distinguishable from that of the disordered ensemble. To gain molecular-level insights into these observations, we performed molecular dynamics simulations with a force field optimized to describe disordered proteins. We find, as in experiments, that both peptides populate configurations consistent with random polymer chains, with the vast majority of conformations lacking significant secondary structure, giving rise to very similar ensemble-averaged FRET efficiencies. Published by Elsevier Inc.

CFD simulation of liquid-liquid dispersions in a stirred tank bioreactor

NASA Astrophysics Data System (ADS)

Gelves, R.

2013-10-01

In this paper simulations were developed in order to allow the examinations of drop sizes in liquid-liquid dispersions (oil-water) in a stirred tank bioreactor using CFD simulations (Computational Fluid Dynamics). The effects of turbulence, rotating flow, drop breakage were simulated by using the k-e, MRF (Multiple Reference Frame) and PBM (Population Balance Model), respectively. The numerical results from different operational conditions are compared with experimental data obtained from an endoscope technique and good agreement is achieved. Motivated by these simulated and experimental results CFD simulations are qualified as a very promising tool for predicting hydrodynamics and drop sizes especially useful for liquid-liquid applications which are characterized by the challenging problem of emulsion stability due to undesired drop sizes.

Population shuffling between ground and high energy excited states

PubMed Central

Sabo, T Michael; Trent, John O; Lee, Donghan

2015-01-01

Stochastic processes powered by thermal energy lead to protein motions traversing time-scales from picoseconds to seconds. Fundamental to protein functionality is the utilization of these dynamics for tasks such as catalysis, folding, and allostery. A hierarchy of motion is hypothesized to connect and synergize fast and slow dynamics toward performing these essential activities. Population shuffling predicts a “top-down” temporal hierarchy, where slow time-scale conformational interconversion leads to a shuffling of the free energy landscape for fast time-scale events. Until now, population shuffling was only applied to interconverting ground states. Here, we extend the framework of population shuffling to be applicable for a system interconverting between low energy ground and high energy excited states, such as the SH3 domain mutants G48M and A39V/N53P/V55L from the Fyn tyrosine kinase, providing another tool for accessing the structural dynamics of high energy excited states. Our results indicate that the higher energy gauche− rotameric state for the leucine χ2 dihedral angle contributes significantly to the distribution of rotameric states in both the major and minor forms of the SH3 domain. These findings are corroborated with unrestrained molecular dynamics (MD) simulations on both the major and minor states of the SH3 domain demonstrating high correlations between experimental and back-calculated leucine χ2 rotameric populations. Taken together, we demonstrate how fast time-scale rotameric side-chain population distributions can be extracted from slow time-scale conformational exchange data further extending the scope and the applicability of the population shuffling model. PMID:26316263

Population shuffling between ground and high energy excited states.

PubMed

Sabo, T Michael; Trent, John O; Lee, Donghan

2015-11-01

Stochastic processes powered by thermal energy lead to protein motions traversing time-scales from picoseconds to seconds. Fundamental to protein functionality is the utilization of these dynamics for tasks such as catalysis, folding, and allostery. A hierarchy of motion is hypothesized to connect and synergize fast and slow dynamics toward performing these essential activities. Population shuffling predicts a "top-down" temporal hierarchy, where slow time-scale conformational interconversion leads to a shuffling of the free energy landscape for fast time-scale events. Until now, population shuffling was only applied to interconverting ground states. Here, we extend the framework of population shuffling to be applicable for a system interconverting between low energy ground and high energy excited states, such as the SH3 domain mutants G48M and A39V/N53P/V55L from the Fyn tyrosine kinase, providing another tool for accessing the structural dynamics of high energy excited states. Our results indicate that the higher energy gauche - rotameric state for the leucine χ2 dihedral angle contributes significantly to the distribution of rotameric states in both the major and minor forms of the SH3 domain. These findings are corroborated with unrestrained molecular dynamics (MD) simulations on both the major and minor states of the SH3 domain demonstrating high correlations between experimental and back-calculated leucine χ2 rotameric populations. Taken together, we demonstrate how fast time-scale rotameric side-chain population distributions can be extracted from slow time-scale conformational exchange data further extending the scope and the applicability of the population shuffling model. © 2015 The Protein Society.

The Dynamics of HPV Infection and Cervical Cancer Cells.

PubMed

Asih, Tri Sri Noor; Lenhart, Suzanne; Wise, Steven; Aryati, Lina; Adi-Kusumo, F; Hardianti, Mardiah S; Forde, Jonathan

2016-01-01

The development of cervical cells from normal cells infected by human papillomavirus into invasive cancer cells can be modeled using population dynamics of the cells and free virus. The cell populations are separated into four compartments: susceptible cells, infected cells, precancerous cells and cancer cells. The model system of differential equations also has a free virus compartment in the system, which infect normal cells. We analyze the local stability of the equilibrium points of the model and investigate the parameters, which play an important role in the progression toward invasive cancer. By simulation, we investigate the boundary between initial conditions of solutions, which tend to stable equilibrium point, representing controlled infection, and those which tend to unbounded growth of the cancer cell population. Parameters affected by drug treatment are varied, and their effect on the risk of cancer progression is explored.

The effect of climatic forcing on population synchrony and genetic structuring of the Canadian lynx

PubMed Central

Stenseth, Nils Chr.; Ehrich, Dorothee; Rueness, Eli Knispel; Lingjærde, Ole Chr.; Chan, Kung-Sik; Boutin, Stan; O'Donoghue, Mark; Robinson, David A.; Viljugrein, Hildegunn; Jakobsen, Kjetill S.

2004-01-01

The abundance of Canadian lynx follows 10-year density fluctuations across the Canadian subcontinent. These cyclic fluctuations have earlier been shown to be geographically structured into three climatic regions: the Atlantic, Continental, and Pacific zones. Recent genetic evidence revealed an essentially similar spatial structuring. Introducing a new population model, the “climate forcing of ecological and evolutionary patterns” model, we link the observed ecological and evolutionary patterns. Specifically, we demonstrate that there is greater phase synchrony within climatic zones than between them and show that external climatic forcing may act as a synchronizer. We simulated genetic drift by using data on population dynamics generated by the climate forcing of ecological and evolutionary patterns model, and we demonstrate that the observed genetic structuring can be seen as an emerging property of the spatiotemporal ecological dynamics. PMID:15067131

Disturbance frequency and vertical distribution of seeds affect long-term population dynamics: a mechanistic seed bank model.

PubMed

Eager, Eric Alan; Haridas, Chirakkal V; Pilson, Diana; Rebarber, Richard; Tenhumberg, Brigitte

2013-08-01

Seed banks are critically important for disturbance specialist plants because seeds of these species germinate only in disturbed soil. Disturbance and seed depth affect the survival and germination probability of seeds in the seed bank, which in turn affect population dynamics. We develop a density-dependent stochastic integral projection model to evaluate the effect of stochastic soil disturbances on plant population dynamics with an emphasis on mimicking how disturbances vertically redistribute seeds within the seed bank. We perform a simulation analysis of the effect of the frequency and mean depth of disturbances on the population's quasi-extinction probability, as well as the long-term mean and variance of the total density of seeds in the seed bank. We show that increasing the frequency of disturbances increases the long-term viability of the population, but the relationship between the mean depth of disturbance and the long-term viability of the population are not necessarily monotonic for all parameter combinations. Specifically, an increase in the probability of disturbance increases the long-term viability of the total seed bank population. However, if the probability of disturbance is too low, a shallower mean depth of disturbance can increase long-term viability, a relationship that switches as the probability of disturbance increases. However, a shallow disturbance depth is beneficial only in scenarios with low survival in the seed bank.

Simulated Seasonal Spatio-Temporal Patterns of Soil Moisture, Temperature, and Net Radiation in a Deciduous Forest

NASA Technical Reports Server (NTRS)

Ballard, Jerrell R., Jr.; Howington, Stacy E.; Cinnella, Pasquale; Smith, James A.

2011-01-01

The temperature and moisture regimes in a forest are key components in the forest ecosystem dynamics. Observations and studies indicate that the internal temperature distribution and moisture content of the tree influence not only growth and development, but onset and cessation of cambial activity [1], resistance to insect predation[2], and even affect the population dynamics of the insects [3]. Moreover, temperature directly affects the uptake and metabolism of population from the soil into the tree tissue [4]. Additional studies show that soil and atmospheric temperatures are significant parameters that limit the growth of trees and impose treeline elevation limitation [5]. Directional thermal infrared radiance effects have long been observed in natural backgrounds [6]. In earlier work, we illustrated the use of physically-based models to simulate directional effects in thermal imaging [7-8]. In this paper, we illustrated the use of physically-based models to simulate directional effects in thermal, and net radiation in a adeciduous forest using our recently developed three-dimensional, macro-scale computational tool that simulates the heat and mass transfer interaction in a soil-root-stem systems (SRSS). The SRSS model includes the coupling of existing heat and mass transport tools to stimulate the diurnal internal and external temperatures, internal fluid flow and moisture distribution, and heat flow in the system.

Efficient evaluation of sampling quality of molecular dynamics simulations by clustering of dihedral torsion angles and Sammon mapping.

PubMed

Frickenhaus, Stephan; Kannan, Srinivasaraghavan; Zacharias, Martin

2009-02-01

A direct conformational clustering and mapping approach for peptide conformations based on backbone dihedral angles has been developed and applied to compare conformational sampling of Met-enkephalin using two molecular dynamics (MD) methods. Efficient clustering in dihedrals has been achieved by evaluating all combinations resulting from independent clustering of each dihedral angle distribution, thus resolving all conformational substates. In contrast, Cartesian clustering was unable to accurately distinguish between all substates. Projection of clusters on dihedral principal component (PCA) subspaces did not result in efficient separation of highly populated clusters. However, representation in a nonlinear metric by Sammon mapping was able to separate well the 48 highest populated clusters in just two dimensions. In addition, this approach also allowed us to visualize the transition frequencies between clusters efficiently. Significantly, higher transition frequencies between more distinct conformational substates were found for a recently developed biasing-potential replica exchange MD simulation method allowing faster sampling of possible substates compared to conventional MD simulations. Although the number of theoretically possible clusters grows exponentially with peptide length, in practice, the number of clusters is only limited by the sampling size (typically much smaller), and therefore the method is well suited also for large systems. The approach could be useful to rapidly and accurately evaluate conformational sampling during MD simulations, to compare different sampling strategies and eventually to detect kinetic bottlenecks in folding pathways.

An Agent-Based Epidemic Simulation of Social Behaviors Affecting HIV Transmission among Taiwanese Homosexuals

PubMed Central

2015-01-01

Computational simulations are currently used to identify epidemic dynamics, to test potential prevention and intervention strategies, and to study the effects of social behaviors on HIV transmission. The author describes an agent-based epidemic simulation model of a network of individuals who participate in high-risk sexual practices, using number of partners, condom usage, and relationship length to distinguish between high- and low-risk populations. Two new concepts—free links and fixed links—are used to indicate tendencies among individuals who either have large numbers of short-term partners or stay in long-term monogamous relationships. An attempt was made to reproduce epidemic curves of reported HIV cases among male homosexuals in Taiwan prior to using the agent-based model to determine the effects of various policies on epidemic dynamics. Results suggest that when suitable adjustments are made based on available social survey statistics, the model accurately simulates real-world behaviors on a large scale. PMID:25815047

Diploid male dynamics under different numbers of sexual alleles and male dispersal abilities.

PubMed

Faria, Luiz R R; Soares, Elaine Della Giustina; Carmo, Eduardo do; Oliveira, Paulo Murilo Castro de

2016-09-01

Insects in the order Hymenoptera (bees, wasps and ants) present an haplodiploid system of sexual determination in which fertilized eggs become females and unfertilized eggs males. Under single locus complementary sex-determination (sl-CSD) system, the sex of a specimen depends on the alleles at a single locus: when diploid, an individual will be a female if heterozygous and male if homozygous. Significant diploid male (DM) production may drive a population to an extinction scenario called "diploid male vortex". We aimed at studying the dynamics of populations of a sl-CSD organism under several combinations of two parameters: male flight abilities and number of sexual alleles. In these simulations, we evaluated the frequency of DM and a genetic diversity measure over 10,000 generations. The number of sexual alleles varied from 10 to 100 and, at each generation, a male offspring might fly to another random site within a varying radius R. Two main results emerge from our simulations: (i) the number of DM depends more on male flight radius than on the number of alleles; (ii) in large geographic regions, the effect of males flight radius on the allelic diversity turns out much less pronounced than in small regions. In other words, small regions where inbreeding normally appears recover genetic diversity due to large flight radii. These results may be particularly relevant when considering the population dynamics of species with increasingly limited dispersal ability (e.g., forest-dependent species of euglossine bees in fragmented landscapes).

Population dynamics, information transfer, and spatial organization in a chemical reaction network under spatial confinement and crowding conditions

NASA Astrophysics Data System (ADS)

Bellesia, Giovanni; Bales, Benjamin B.

2016-10-01

We investigate, via Brownian dynamics simulations, the reaction dynamics of a generic, nonlinear chemical network under spatial confinement and crowding conditions. In detail, the Willamowski-Rossler chemical reaction system has been "extended" and considered as a prototype reaction-diffusion system. Our results are potentially relevant to a number of open problems in biophysics and biochemistry, such as the synthesis of primitive cellular units (protocells) and the definition of their role in the chemical origin of life and the characterization of vesicle-mediated drug delivery processes. More generally, the computational approach presented in this work makes the case for the use of spatial stochastic simulation methods for the study of biochemical networks in vivo where the "well-mixed" approximation is invalid and both thermal and intrinsic fluctuations linked to the possible presence of molecular species in low number copies cannot be averaged out.

Effects of payoff functions and preference distributions in an adaptive population

NASA Astrophysics Data System (ADS)

Yang, H. M.; Ting, Y. S.; Wong, K. Y. Michael

2008-03-01

Adaptive populations such as those in financial markets and distributed control can be modeled by the Minority Game. We consider how their dynamics depends on the agents’ initial preferences of strategies, when the agents use linear or quadratic payoff functions to evaluate their strategies. We find that the fluctuations of the population making certain decisions (the volatility) depends on the diversity of the distribution of the initial preferences of strategies. When the diversity decreases, more agents tend to adapt their strategies together. In systems with linear payoffs, this results in dynamical transitions from vanishing volatility to a nonvanishing one. For low signal dimensions, the dynamical transitions for the different signals do not take place at the same critical diversity. Rather, a cascade of dynamical transitions takes place when the diversity is reduced. In contrast, no phase transitions are found in systems with the quadratic payoffs. Instead, a basin boundary of attraction separates two groups of samples in the space of the agents’ decisions. Initial states inside this boundary converge to small volatility, while those outside diverge to a large one. Furthermore, when the preference distribution becomes more polarized, the dynamics becomes more erratic. All the above results are supported by good agreement between simulations and theory.

Simulating the Interactions Among Land Use, Transportation, and Economy to Inform Light Rail Transit Decisions

EPA Science Inventory

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic a...

Simulating the Interactions Among Land Use, Transportation, and Economy to Inform Light Rail Transit Decisions (proceedings)

EPA Science Inventory

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic a...

Continuous and discrete extreme climatic events affecting the dynamics of a high-arctic reindeer population.

PubMed

Chan, Kung-Sik; Mysterud, Atle; Øritsland, Nils Are; Severinsen, Torbjørn; Stenseth, Nils Chr

2005-10-01

Climate at northern latitudes are currently changing both with regard to the mean and the temporal variability at any given site, increasing the frequency of extreme events such as cold and warm spells. Here we use a conceptually new modelling approach with two different dynamic terms of the climatic effects on a Svalbard reindeer population (the Brøggerhalvøya population) which underwent an extreme icing event ("locked pastures") with 80% reduction in population size during one winter (1993/94). One term captures the continuous and linear effect depending upon the Arctic Oscillation and another the discrete (rare) "event" process. The introduction of an "event" parameter describing the discrete extreme winter resulted in a more parsimonious model. Such an approach may be useful in strongly age-structured ungulate populations, with young and very old individuals being particularly prone to mortality factors during adverse conditions (resulting in a population structure that differs before and after extreme climatic events). A simulation study demonstrates that our approach is able to properly detect the ecological effects of such extreme climate events.

Detecting population–environmental interactions with mismatched time series data

PubMed Central

Ferguson, Jake M.; Reichert, Brian E.; Fletcher, Robert J.; Jager, Henriëtte I.

2017-01-01

Time series analysis is an essential method for decomposing the influences of density and exogenous factors such as weather and climate on population regulation. However, there has been little work focused on understanding how well commonly collected data can reconstruct the effects of environmental factors on population dynamics. We show that, analogous to similar scale issues in spatial data analysis, coarsely sampled temporal data can fail to detect covariate effects when interactions occur on timescales that are fast relative to the survey period. We propose a method for modeling mismatched time series data that couples high-resolution environmental data to low-resolution abundance data. We illustrate our approach with simulations and by applying it to Florida’s southern Snail kite population. Our simulation results show that our method can reliably detect linear environmental effects and that detecting nonlinear effects requires high-resolution covariate data even when the population turnover rate is slow. In the Snail kite analysis, our approach performed among the best in a suite of previously used environmental covariates explaining Snail kite dynamics and was able to detect a potential phenological shift in the environmental dependence of Snail kites. Our work provides a statistical framework for reliably detecting population–environment interactions from coarsely surveyed time series. An important implication of this work is that the low predictability of animal population growth by weather variables found in previous studies may be due, in part, to how these data are utilized as covariates. PMID:28759123

Individual-Based Spatially-Explicit Model of an Herbivore and Its Resource: The Effect of Habitat Reduction and Fragmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostova, T; Carlsen, T; Kercher, J

2002-06-17

We present an individual-based, spatially-explicit model of the dynamics of a small mammal and its resource. The life histories of each individual animal are modeled separately. The individuals can have the status of residents or wanderers and belong to behaviorally differing groups of juveniles or adults and males or females. Their territory defending and monogamous behavior is taken into consideration. The resource, green vegetation, grows depending on seasonal climatic characteristics and is diminished due to the herbivore's grazing. Other specifics such as a varying personal energetic level due to feeding and starvation of the individuals, mating preferences, avoidance of competitors,more » dispersal of juveniles, as a result of site overgrazing, etc. are included in the model. We determined model parameters from real data for the species Microtus ochrogaster (prairie vole). The simulations are done for a case of an enclosed habitat without predators or other species competitors. The goal of the study is to find the relation between size of habitat and population persistence. The experiments with the model show the populations go extinct due to severe overgrazing, but that the length of population persistence depends on the area of the habitat as well as on the presence of fragmentation. Additionally, the total population size of the vole population obtained during the simulations exhibits yearly fluctuations as well as multi-yearly peaks of fluctuations. This dynamics is similar to the one observed in prairie vole field studies.« less

Antagonistic interactions are sufficient to explain self-assemblage of bacterial communities in a homogeneous environment: a computational modeling approach

PubMed Central

Zapién-Campos, Román; Olmedo-Álvarez, Gabriela; Santillán, Moisés

2015-01-01

Most of the studies in Ecology have been devoted to analyzing the effects the environment has on individuals, populations, and communities, thus neglecting the effects of biotic interactions on the system dynamics. In the present work we study the structure of bacterial communities in the oligotrophic shallow water system of Churince, Cuatro Cienegas, Mexico. Since the physicochemical conditions of this water system are homogeneous and quite stable in time, it is an excellent candidate to study how biotic factors influence the structure of bacterial communities. In a previous study, the binary antagonistic interactions of 78 bacterial strains, isolated from Churince, were experimentally determined. We employ these data to develop a computer algorithm to simulate growth experiments in a cellular grid representing the pond. Remarkably, in our model, the dynamics of all the simulated bacterial populations is determined solely by antagonistic interactions. Our results indicate that all bacterial strains (even those that are antagonized by many other bacteria) survive in the long term, and that the underlying mechanism is the formation of bacterial community patches. Patches corresponding to less antagonistic and highly susceptible strains are consistently isolated from the highly-antagonistic bacterial colonies by patches of neutral strains. These results concur with the observed features of the bacterial community structure previously reported. Finally, we study how our findings depend on factors like initial population size, differential population growth rates, homogeneous population death rates, and enhanced bacterial diffusion. PMID:26052318

Ultrafast semi-metallic layer formation in detonating nitromethane

NASA Astrophysics Data System (ADS)

Reed, Evan; Manaa, M. Riad; Fried, Laurence; Glaesemann, Kurt; Joannopoulos, John

2008-03-01

We present the first quantum molecular dynamics simulations behind a detonation front (up to 0.2 ns) of the explosive nitromethane (CH3NO2) represented by the density-functional-based tight-binding method (DFTB). This simulation is enabled by our recently developed multi-scale shock wave molecular dynamics technique (MSST) that opens the door to longer duration simulations by several orders of magnitude. The electronic density of states around the Fermi energy initially increases as metastable material states are produced but then later decreases, perhaps unexpectedly. These changes indicate that the shock front is characterized by an increase in optical thickness and conductivity followed by a reduction around 100 picoseconds behind the front. We find that a significant population of intermediate metastable molecules are charged and charged species play an important role in the density of states evolution. The transient transformation to a semi-metallic state can be understood within the Anderson picture of metallization.

A semi-metallic layer in detonating nitromethane

NASA Astrophysics Data System (ADS)

Reed, Evan; Manaa, Riad; Fried, Laurence; Glaesemann, Kurt; Joannopoulos, John

2007-06-01

We present the first ever glimpse behind a detonation front in a chemically reactive quantum molecular dynamics simulation (up to 0.2 ns) of the explosive nitromethane (CH3NO2) represented by the density-functional-based tight-binding method (DFTB). This simulation is enabled by our recently developed multi-scale shock wave molecular dynamics technique (MSST) that opens the door to longer duration simulations by several orders of magnitude. The electronic DOS around the Fermi energy initially increases as metastable material states are produced but then later decreases, perhaps unexpectedly. These changes indicate that the shock front is characterized by an increase in optical thickness followed by a reduction in optical thickness hundreds of picoseconds behind the front, explaining recent experimental observations. We find that a significant population of intermediate metastable molecules are charged and charged species play an important role in the density of states evolution and a possible Mott metal-insulator transition.

Forecasting the use of elderly care: a static micro-simulation model.

PubMed

Eggink, Evelien; Woittiez, Isolde; Ras, Michiel

2016-07-01

This paper describes a model suitable for forecasting the use of publicly funded long-term elderly care, taking into account both ageing and changes in the health status of the population. In addition, the impact of socioeconomic factors on care use is included in the forecasts. The model is also suitable for the simulation of possible implications of some specific policy measures. The model is a static micro-simulation model, consisting of an explanatory model and a population model. The explanatory model statistically relates care use to individual characteristics. The population model mimics the composition of the population at future points in time. The forecasts of care use are driven by changes in the composition of the population in terms of relevant characteristics instead of dynamics at the individual level. The results show that a further 37 % increase in the use of elderly care (from 7 to 9 % of the Dutch 30-plus population) between 2008 and 2030 can be expected due to a further ageing of the population. However, the use of care is expected to increase less than if it were based on the increasing number of elderly only (+70 %), due to decreasing disability levels and increasing levels of education. As an application of the model, we simulated the effects of restricting access to residential care to elderly people with severe physical disabilities. The result was a lower growth of residential care use (32 % instead of 57 %), but a somewhat faster growth in the use of home care (35 % instead of 32 %).

Gaussian process-based Bayesian nonparametric inference of population size trajectories from gene genealogies.

PubMed

Palacios, Julia A; Minin, Vladimir N

2013-03-01

Changes in population size influence genetic diversity of the population and, as a result, leave a signature of these changes in individual genomes in the population. We are interested in the inverse problem of reconstructing past population dynamics from genomic data. We start with a standard framework based on the coalescent, a stochastic process that generates genealogies connecting randomly sampled individuals from the population of interest. These genealogies serve as a glue between the population demographic history and genomic sequences. It turns out that only the times of genealogical lineage coalescences contain information about population size dynamics. Viewing these coalescent times as a point process, estimating population size trajectories is equivalent to estimating a conditional intensity of this point process. Therefore, our inverse problem is similar to estimating an inhomogeneous Poisson process intensity function. We demonstrate how recent advances in Gaussian process-based nonparametric inference for Poisson processes can be extended to Bayesian nonparametric estimation of population size dynamics under the coalescent. We compare our Gaussian process (GP) approach to one of the state-of-the-art Gaussian Markov random field (GMRF) methods for estimating population trajectories. Using simulated data, we demonstrate that our method has better accuracy and precision. Next, we analyze two genealogies reconstructed from real sequences of hepatitis C and human Influenza A viruses. In both cases, we recover more believed aspects of the viral demographic histories than the GMRF approach. We also find that our GP method produces more reasonable uncertainty estimates than the GMRF method. Copyright © 2013, The International Biometric Society.

Spontaneous quaternary and tertiary T-R transitions of human hemoglobin in molecular dynamics simulation.

PubMed

Hub, Jochen S; Kubitzki, Marcus B; de Groot, Bert L

2010-05-06

We present molecular dynamics simulations of unliganded human hemoglobin (Hb) A under physiological conditions, starting from the R, R2, and T state. The simulations were carried out with protonated and deprotonated HC3 histidines His(beta)146, and they sum up to a total length of 5.6 micros. We observe spontaneous and reproducible T-->R quaternary transitions of the Hb tetramer and tertiary transitions of the alpha and beta subunits, as detected from principal component projections, from an RMSD measure, and from rigid body rotation analysis. The simulations reveal a marked asymmetry between the alpha and beta subunits. Using the mutual information as correlation measure, we find that the beta subunits are substantially more strongly linked to the quaternary transition than the alpha subunits. In addition, the tertiary populations of the alpha and beta subunits differ substantially, with the beta subunits showing a tendency towards R, and the alpha subunits showing a tendency towards T. Based on the simulation results, we present a transition pathway for coupled quaternary and tertiary transitions between the R and T conformations of Hb.

Spontaneous Quaternary and Tertiary T-R Transitions of Human Hemoglobin in Molecular Dynamics Simulation

PubMed Central

de Groot, Bert L.

2010-01-01

We present molecular dynamics simulations of unliganded human hemoglobin (Hb) A under physiological conditions, starting from the R, R2, and T state. The simulations were carried out with protonated and deprotonated HC3 histidines His(β)146, and they sum up to a total length of 5.6µs. We observe spontaneous and reproducible T→R quaternary transitions of the Hb tetramer and tertiary transitions of the α and β subunits, as detected from principal component projections, from an RMSD measure, and from rigid body rotation analysis. The simulations reveal a marked asymmetry between the α and β subunits. Using the mutual information as correlation measure, we find that the β subunits are substantially more strongly linked to the quaternary transition than the α subunits. In addition, the tertiary populations of the α and β subunits differ substantially, with the β subunits showing a tendency towards R, and the α subunits showing a tendency towards T. Based on the simulation results, we present a transition pathway for coupled quaternary and tertiary transitions between the R and T conformations of Hb. PMID:20463873

Refining Markov state models for conformational dynamics using ensemble-averaged data and time-series trajectories

NASA Astrophysics Data System (ADS)

Matsunaga, Y.; Sugita, Y.

2018-06-01

A data-driven modeling scheme is proposed for conformational dynamics of biomolecules based on molecular dynamics (MD) simulations and experimental measurements. In this scheme, an initial Markov State Model (MSM) is constructed from MD simulation trajectories, and then, the MSM parameters are refined using experimental measurements through machine learning techniques. The second step can reduce the bias of MD simulation results due to inaccurate force-field parameters. Either time-series trajectories or ensemble-averaged data are available as a training data set in the scheme. Using a coarse-grained model of a dye-labeled polyproline-20, we compare the performance of machine learning estimations from the two types of training data sets. Machine learning from time-series data could provide the equilibrium populations of conformational states as well as their transition probabilities. It estimates hidden conformational states in more robust ways compared to that from ensemble-averaged data although there are limitations in estimating the transition probabilities between minor states. We discuss how to use the machine learning scheme for various experimental measurements including single-molecule time-series trajectories.

Exact Hybrid Particle/Population Simulation of Rule-Based Models of Biochemical Systems

PubMed Central

Stover, Lori J.; Nair, Niketh S.; Faeder, James R.

2014-01-01

Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This “network-free” approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of “partial network expansion” into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility. PMID:24699269

Exact hybrid particle/population simulation of rule-based models of biochemical systems.

PubMed

Hogg, Justin S; Harris, Leonard A; Stover, Lori J; Nair, Niketh S; Faeder, James R

2014-04-01

Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This "network-free" approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of "partial network expansion" into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility.

Spatial dynamics of invasion: the geometry of introduced species.

PubMed

Korniss, Gyorgy; Caraco, Thomas

2005-03-07

Many exotic species combine low probability of establishment at each introduction with rapid population growth once introduction does succeed. To analyse this phenomenon, we note that invaders often cluster spatially when rare, and consequently an introduced exotic's population dynamics should depend on locally structured interactions. Ecological theory for spatially structured invasion relies on deterministic approximations, and determinism does not address the observed uncertainty of the exotic-introduction process. We take a new approach to the population dynamics of invasion and, by extension, to the general question of invasibility in any spatial ecology. We apply the physical theory for nucleation of spatial systems to a lattice-based model of competition between plant species, a resident and an invader, and the analysis reaches conclusions that differ qualitatively from the standard ecological theories. Nucleation theory distinguishes between dynamics of single- and multi-cluster invasion. Low introduction rates and small system size produce single-cluster dynamics, where success or failure of introduction is inherently stochastic. Single-cluster invasion occurs only if the cluster reaches a critical size, typically preceded by a number of failed attempts. For this case, we identify the functional form of the probability distribution of time elapsing until invasion succeeds. Although multi-cluster invasion for sufficiently large systems exhibits spatial averaging and almost-deterministic dynamics of the global densities, an analytical approximation from nucleation theory, known as Avrami's law, describes our simulation results far better than standard ecological approximations.

Dynamic complexities in a pest control model with birth pulse and harvesting

NASA Astrophysics Data System (ADS)

Goel, A.; Gakkhar, S.

2016-04-01

In this paper, an impulsive model is discussed for an integrated pest management approach comprising of chemical and mechanical controls. The pesticides and harvesting are used to control the stage-structured pest population. The mature pest give birth to immature pest in pulses at regular intervals. The pest is controlled by spraying chemical pesticides affecting immature as well as mature pest. The harvesting of both immature and mature pest further reduce the pest population. The discrete dynamical system obtained from stroboscopic map is analyzed. The threshold conditions for stability of pest-free state as well as non-trivial period-1 solution is obtained. The effect of pesticide spray timing and harvesting on immature as well as mature pest are shown. Finally, by numerical simulation with MATLAB, the dynamical behaviors of the model is found to be complex. Above the threshold level there is a characteristic sequence of bifurcations leading to chaotic dynamics. Route to chaos is found to be period-doubling. Period halving bifurcations are also observed.

Dynamic analysis of a parasite population model.

PubMed

Sibona, G J; Condat, C A

2002-03-01

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

Dynamic analysis of a parasite population model

NASA Astrophysics Data System (ADS)

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

2002-03-01

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

Early animal farming and zoonotic disease dynamics: modelling brucellosis transmission in Neolithic goat populations.

PubMed

Fournié, Guillaume; Pfeiffer, Dirk U; Bendrey, Robin

2017-02-01

Zoonotic pathogens are frequently hypothesized as emerging with the origins of farming, but evidence of this is elusive in the archaeological records. To explore the potential impact of animal domestication on zoonotic disease dynamics and human infection risk, we developed a model simulating the transmission of Brucella melitensis within early domestic goat populations. The model was informed by archaeological data describing goat populations in Neolithic settlements in the Fertile Crescent, and used to assess the potential of these populations to sustain the circulation of Brucella . Results show that the pathogen could have been sustained even at low levels of transmission within these domestic goat populations. This resulted from the creation of dense populations and major changes in demographic characteristics. The selective harvesting of young male goats, likely aimed at improving the efficiency of food production, modified the age and sex structure of these populations, increasing the transmission potential of the pathogen within these populations. Probable interactions between Neolithic settlements would have further promoted pathogen maintenance. By fostering conditions suitable for allowing domestic goats to become reservoirs of Brucella melitensis , the early stages of agricultural development were likely to promote the exposure of humans to this pathogen.

Early animal farming and zoonotic disease dynamics: modelling brucellosis transmission in Neolithic goat populations

PubMed Central

Pfeiffer, Dirk U.; Bendrey, Robin

2017-01-01

Zoonotic pathogens are frequently hypothesized as emerging with the origins of farming, but evidence of this is elusive in the archaeological records. To explore the potential impact of animal domestication on zoonotic disease dynamics and human infection risk, we developed a model simulating the transmission of Brucella melitensis within early domestic goat populations. The model was informed by archaeological data describing goat populations in Neolithic settlements in the Fertile Crescent, and used to assess the potential of these populations to sustain the circulation of Brucella. Results show that the pathogen could have been sustained even at low levels of transmission within these domestic goat populations. This resulted from the creation of dense populations and major changes in demographic characteristics. The selective harvesting of young male goats, likely aimed at improving the efficiency of food production, modified the age and sex structure of these populations, increasing the transmission potential of the pathogen within these populations. Probable interactions between Neolithic settlements would have further promoted pathogen maintenance. By fostering conditions suitable for allowing domestic goats to become reservoirs of Brucella melitensis, the early stages of agricultural development were likely to promote the exposure of humans to this pathogen. PMID:28386446

Hierarchy of forward-backward stochastic Schrödinger equation

NASA Astrophysics Data System (ADS)

Ke, Yaling; Zhao, Yi

2016-07-01

Driven by the impetus to simulate quantum dynamics in photosynthetic complexes or even larger molecular aggregates, we have established a hierarchy of forward-backward stochastic Schrödinger equation in the light of stochastic unravelling of the symmetric part of the influence functional in the path-integral formalism of reduced density operator. The method is numerically exact and is suited for Debye-Drude spectral density, Ohmic spectral density with an algebraic or exponential cutoff, as well as discrete vibrational modes. The power of this method is verified by performing the calculations of time-dependent population differences in the valuable spin-boson model from zero to high temperatures. By simulating excitation energy transfer dynamics of the realistic full FMO trimer, some important features are revealed.

Application of a computer simulation model to migrating white-fronted geese in the Klamath Basin

USGS Publications Warehouse

Frederick, R.B.; Clark, William R.; Takekawa, John Y.; McCullough, Dale R.; Barrett, R.H.

1992-01-01

The Pacific greater white-fronted goose (Anser albifrons) population has declined precipitously over the past 20 years. Loss of wetland habitat in California wintering areas has had a significant effect on the population, so recovery of the population may depend on innovative management of the few remaining wetlands. A computer simulation model, REFMOD, was applied to greater white-fronted geese in the Klamath Basin, northern California, to investigate the importance of food availability and hunting disturbance to migrating and wintering populations. Time spent flying and feeding was simulated during fall and early winter, and the resulting energy expenditure was compared with energy consumed to calculate an overall energy balance. This energy balance and the ease with which waterfowl acquired needed food affected emigration rate, and thus, the waterfowl population level was directly tied to availability and distribution of food. The model validly described distances moved by geese from their Tule Lake Refuge roosting site (core) to feeding sites within the surrounding Klamath Basin arena, and exhibited a capability to simulate observed time spent feeding. Based on 25 stochastic simulations, greater white-fronted goose population dynamics were validly simulated over the fall and early-winter (P>0.8). When food was removed from the Tule Lake Refuge, simulated geese had to fly farther (P<0.0001) to find food, hastening emigration and resulting in a decline (P<0.05) in use of the Klamath Basin by geese. Although barley is normally abundant in the basin and is extensively used by geese, simulated elimination of barley in the arena did not cause a reduction in goose numbers (P>0.05). The elimination did cause an increase in the distance traveled to feed (P<0.05), but the availability of other foods in the basin (e.g., potatoes) was evidently sufficient to support the population. The elimination of hunting in the Klamath Basin, and the related decrease in disturbance of feeding birds, had little effect (P>0.05) on the distance traveled to feed or on goose numbers. A 10-fold increase in disturbance hastened emigration and reduced population levels (P<0.0001) during the season by about 30%; a 100-fold increase in disturbance reduced population levels (P<0.0001) by 85%. When goose immigration was increased to simulate an average peak population of approximately 500 000 geese, population levels remained high throughout the fall, indicating the Klamath Basin can sustain a population much larger than currently exists. This suggests food availability and disturbance levels in the Klamath Basin are not responsible for observed population declines during the last 2 decades. REFMOD can easily be used to evaluate the effects of other scenarios related to hunting regimes and food distribution and availability.

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

NASA Astrophysics Data System (ADS)

Worman, Stacey; Furbish, David; Fathel, Siobhan

2014-05-01

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.

Evolutionary dynamics of public goods games with diverse contributions in finite populations

NASA Astrophysics Data System (ADS)

Wang, Jing; Wu, Bin; Chen, Xiaojie; Wang, Long

2010-05-01

The public goods game is a powerful metaphor for exploring the maintenance of social cooperative behavior in a group of interactional selfish players. Here we study the emergence of cooperation in the public goods games with diverse contributions in finite populations. The theory of stochastic process is innovatively adopted to investigate the evolutionary dynamics of the public goods games involving a diversity of contributions. In the limit of rare mutations, the general stationary distribution of this stochastic process can be analytically approximated by means of diffusion theory. Moreover, we demonstrate that increasing the diversity of contributions greatly reduces the probability of finding the population in a homogeneous state full of defectors. This increase also raises the expectation of the total contribution in the entire population and thus promotes social cooperation. Furthermore, by investigating the evolutionary dynamics of optional public goods games with diverse contributions, we find that nonparticipation can assist players who contribute more in resisting invasion and taking over individuals who contribute less. In addition, numerical simulations are performed to confirm our analytical results. Our results may provide insight into the effect of diverse contributions on cooperative behaviors in the real world.

Accidental release of chlorine in Chicago: Coupling of an exposure model with a Computational Fluid Dynamics model

NASA Astrophysics Data System (ADS)

Sanchez, E. Y.; Colman Lerner, J. E.; Porta, A.; Jacovkis, P. M.

2013-01-01

The adverse health effects of the release of hazardous substances into the atmosphere continue being a matter of concern, especially in densely populated urban regions. Emergency responders need to have estimates of these adverse health effects in the local population to aid planning, emergency response, and recovery efforts. For this purpose, models that predict the transport and dispersion of hazardous materials are as necessary as those that estimate the adverse health effects in the population. In this paper, we present the results obtained by coupling a Computational Fluid Dynamics model, FLACS (FLame ACceleration Simulator), with an exposure model, DDC (Damage Differential Coupling). This coupled model system is applied to a scenario of hypothetical release of chlorine with obstacles, such as buildings, and the results show how it is capable of predicting the atmospheric dispersion of hazardous chemicals, and the adverse health effects in the exposed population, to support decision makers both in charge of emergency planning and in charge of real-time response. The results obtained show how knowing the influence of obstacles in the trajectory of the toxic cloud and in the diffusion of the pollutants transported, and obtaining dynamic information of the potentially affected population and of associated symptoms, contribute to improve the planning of the protection and response measures.

Quasispecies in population of compositional assemblies.

PubMed

Gross, Renan; Fouxon, Itzhak; Lancet, Doron; Markovitch, Omer

2014-12-30

The quasispecies model refers to information carriers that undergo self-replication with errors. A quasispecies is a steady-state population of biopolymer sequence variants generated by mutations from a master sequence. A quasispecies error threshold is a minimal replication accuracy below which the population structure breaks down. Theory and experimentation of this model often refer to biopolymers, e.g. RNA molecules or viral genomes, while its prebiotic context is often associated with an RNA world scenario. Here, we study the possibility that compositional entities which code for compositional information, intrinsically different from biopolymers coding for sequential information, could show quasispecies dynamics. We employed a chemistry-based model, graded autocatalysis replication domain (GARD), which simulates the network dynamics within compositional molecular assemblies. In GARD, a compotype represents a population of similar assemblies that constitute a quasi-stationary state in compositional space. A compotype's center-of-mass is found to be analogous to a master sequence for a sequential quasispecies. Using single-cycle GARD dynamics, we measured the quasispecies transition matrix (Q) for the probabilities of transition from one center-of-mass Euclidean distance to another. Similarly, the quasispecies' growth rate vector (A) was obtained. This allowed computing a steady state distribution of distances to the center of mass, as derived from the quasispecies equation. In parallel, a steady state distribution was obtained via the GARD equation kinetics. Rewardingly, a significant correlation was observed between the distributions obtained by these two methods. This was only seen for distances to the compotype center-of-mass, and not to randomly selected compositions. A similar correspondence was found when comparing the quasispecies time dependent dynamics towards steady state. Further, changing the error rate by modifying basal assembly joining rate of GARD kinetics was found to display an error catastrophe, similar to the standard quasispecies model. Additional augmentation of compositional mutations leads to the complete disappearance of the master-like composition. Our results show that compositional assemblies, as simulated by the GARD formalism, portray significant attributes of quasispecies dynamics. This expands the applicability of the quasispecies model beyond sequence-based entities, and potentially enhances validity of GARD as a model for prebiotic evolution.

Electron-phonon thermalization in a scalable method for real-time quantum dynamics

DOE PAGES

Rizzi, Valerio; Todorov, Tchavdar N.; Kohanoff, Jorge J.; ...

2016-01-27

Here, we present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicitmore » quantum dynamics.« less

Dispersal leads to spatial autocorrelation in species distributions: A simulation model

USGS Publications Warehouse

Bahn, V.; Krohn, W.B.; O'Connor, R.J.

2008-01-01

Compared to population growth regulated by local conditions, dispersal has been underappreciated as a central process shaping the spatial distribution of populations. This paper asks: (a) which conditions increase the importance of dispersers relative to local recruits in determining population sizes? and (b) how does dispersal influence the spatial distribution patterns of abundances among connected populations? We approached these questions with a simulation model of populations on a coupled lattice with cells of continuously varying habitat quality expressed as carrying capacities. Each cell contained a population with the basic dynamics of density-regulated growth, and was connected to other populations by immigration and emigration. The degree to which dispersal influenced the distribution of population sizes depended most strongly on the absolute amount of dispersal, and then on the potential population growth rate. Dispersal decaying in intensity with distance left close neighbours more alike in population size than distant populations, leading to an increase in spatial autocorrelation. The spatial distribution of species with low potential growth rates is more dependent on dispersal than that of species with high growth rates; therefore, distribution modelling for species with low growth rates requires particular attention to autocorrelation, and conservation management of these species requires attention to factors curtailing dispersal, such as fragmentation and dispersal barriers. ?? 2007 Elsevier B.V. All rights reserved.

Toolbox for Urban Mobility Simulation: High Resolution Population Dynamics for Global Cities

NASA Astrophysics Data System (ADS)

Bhaduri, B. L.; Lu, W.; Liu, C.; Thakur, G.; Karthik, R.

2015-12-01

In this rapidly urbanizing world, unprecedented rate of population growth is not only mirrored by increasing demand for energy, food, water, and other natural resources, but has detrimental impacts on environmental and human security. Transportation simulations are frequently used for mobility assessment in urban planning, traffic operation, and emergency management. Previous research, involving purely analytical techniques to simulations capturing behavior, has investigated questions and scenarios regarding the relationships among energy, emissions, air quality, and transportation. Primary limitations of past attempts have been availability of input data, useful "energy and behavior focused" models, validation data, and adequate computational capability that allows adequate understanding of the interdependencies of our transportation system. With increasing availability and quality of traditional and crowdsourced data, we have utilized the OpenStreetMap roads network, and has integrated high resolution population data with traffic simulation to create a Toolbox for Urban Mobility Simulations (TUMS) at global scale. TUMS consists of three major components: data processing, traffic simulation models, and Internet-based visualizations. It integrates OpenStreetMap, LandScanTM population, and other open data (Census Transportation Planning Products, National household Travel Survey, etc.) to generate both normal traffic operation and emergency evacuation scenarios. TUMS integrates TRANSIMS and MITSIM as traffic simulation engines, which are open-source and widely-accepted for scalable traffic simulations. Consistent data and simulation platform allows quick adaption to various geographic areas that has been demonstrated for multiple cities across the world. We are combining the strengths of geospatial data sciences, high performance simulations, transportation planning, and emissions, vehicle and energy technology development to design and develop a simulation framework to assist decision makers at all levels - local, state, regional, and federal. Using Cleveland, Tennessee as an example, in this presentation, we illustrate how emerging cities could easily assess future land use scenario driven impacts on energy and environment utilizing such a capability.

Forces Generated by Vastus Lateralis and Vastus Medialis Decrease with Increasing Stair Descent Speed.

PubMed

Caruthers, Elena J; Oxendale, Kassandra K; Lewis, Jacqueline M; Chaudhari, Ajit M W; Schmitt, Laura C; Best, Thomas M; Siston, Robert A

2018-04-01

Stair descent (SD) is a common, difficult task for populations who are elderly or have orthopaedic pathologies. Joint torques of young, healthy populations during SD increase at the hip and ankle with increasing speed but not at the knee, contrasting torque patterns during gait. To better understand the sources of the knee torque pattern, we used dynamic simulations to estimate knee muscle forces and how they modulate center of mass (COM) acceleration across SD speeds (slow, self-selected, and fast) in young, healthy adults. The vastus lateralis and vastus medialis forces decreased from slow to self-selected speeds as the individual lowered to the next step. Since the vasti are primary contributors to vertical support during SD, they produced lower forces at faster speeds due to the lower need for vertical COM support observed at faster speeds. In contrast, the semimembranosus and rectus femoris forces increased across successive speeds, allowing the semimembranosus to increase acceleration downward and forward and the rectus femoris to provide more vertical support and resistance to forward progression as SD speed increased. These results demonstrate the utility of dynamic simulations to extend beyond traditional inverse dynamics analyses to gain further insight into muscle mechanisms during tasks like SD.

Emergence and dynamics of self-producing information niches as a step towards pre-evolutionary organization

PubMed Central

Carter, Richard J.; Wiesner, Karoline

2018-01-01

As a step towards understanding pre-evolutionary organization in non-genetic systems, we develop a model to investigate the emergence and dynamics of proto-autopoietic networks in an interacting population of simple information processing entities (automata). Our simulations indicate that dynamically stable strongly connected networks of mutually producing communication channels emerge under specific environmental conditions. We refer to these distinct organizational steady states as information niches. In each case, we measure the information content by the Shannon entropy, and determine the fitness landscape, robustness and transition pathways for information niches subjected to intermittent environmental perturbations under non-evolutionary conditions. By determining the information required to generate each niche, we show that niche transitions are only allowed if accompanied by an equal or increased level of information production that arises internally or via environmental perturbations that serve as an exogenous source of population diversification. Overall, our simulations show how proto-autopoietic networks of basic information processors form and compete, and under what conditions they persist over time or go extinct. These findings may be relevant to understanding how inanimate systems such as chemically communicating protocells can initiate the transition to living matter prior to the onset of contemporary evolutionary and genetic mechanisms. PMID:29343630

The role of host sex in parasite dynamics: individual based model simulations of host-parasite interactions in a semi-enclosed embayment.

NASA Astrophysics Data System (ADS)

Velo Suarez, L.; Arancio, M.; Sourisseau, M.

2016-02-01

Parasitic dinoflagellates of the genus Amoebophrya infect free-living dinoflagellates, some of which can cause harmful algal blooms (HABs). During a field study in Salt Pond (MA, USA), we found a significant influence of Amoebophrya spp. on populations of Alexandrium fundyense. Parasitism appeared to exhibit a significant top down influence on A. fundyense populations and a dramatic life-cycle transition from vegetative division to sexual fusion was recorded. Despite our intensive sampling in Salt Pond, host-parasite interactions were undersampled owing to the very short time scales relevant to host-Amoebophrya spp. dynamics. In the present work, we explored the role of sexual reproduction and excystment/encystment processes using an Individual Based Model (IBM). The model was parameterized using published data and laboratory experiments carried out to analyze Amoebophrya spp. functional response. Observed-simulated differences in host-parasite dynamics support the hypothesis of parasite-host simultaneous dormancy, and further excystment months later to propagate both species. Results suggest that coexistence of A. fundyense and Amoebophrya spp. and their annual persistence in Salt Pond might rely on a sexual response/encystment. Understanding host-parasite interactions and coexistence strategies will improve our knowledge of Alexandrium spp. blooms and assess the impact of parasites on natural plankton assemblages in coastal systems.

Numerical modeling of mosquito population dynamics of Aedes aegypti.

PubMed

Yamashita, William M S; Das, Shyam S; Chapiro, Grigori

2018-04-16

The global incidences of dengue virus have increased the interest in studying and understanding the mosquito population dynamics. It is predominantly spread by Aedes aegypti in the tropical and sub-tropical countries in the world. Understanding these dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. For this reason, a new model has been proposed to investigate the population dynamics of mosquitoes in a city. The present paper discusses the numerical modeling of population dynamics of Ae. aegypti mosquitoes in an urban neighborhood of a city using the finite volume method. The model describes how populations spread through the city assisted by the wind. This model allows incorporating external factors (wind and chemical insecticides) and topography data (streets, building blocks, parks, forests and beach). The proposed model has been successfully tested in examples involving two Brazilian cities (City center, Juiz de Fora and Copacabana Beach, Rio de Janeiro). Invasion phenomena of Ae. aegypti mosquitoes have been observed in each of the simulations. It was observed that, inside the blocks, the growth of the population for both winged and aquatic phase causes an infestation of Ae. aegypti in a short time. Within the blocks the mosquito population was concentrated and diffused slowly. In the streets, there was a long-distance spread, which was influenced by wind and diffusion with a low concentration of mosquito population. The model was also tested taking into account chemical insecticides spread in two different configurations. It has been observed that the insecticides have a significant effect on the mosquito population for both winged and aquatic phases when the chemical insecticides spread more uniformly along all the streets in a neighborhood of a city. The presented methodology can be employed to evaluate and to understand the epidemic risks in a specific region of the city. Moreover the model allows an increase in efficiency of the existing mosquito population control techniques and to theoretically test new methods before involving the human population.

Modeling sandhill crane population dynamics

USGS Publications Warehouse

Johnson, D.H.

1979-01-01

The impact of sport hunting on the Central Flyway population of sandhill cranes (Grus canadensis) has been a subject of controversy for several years. A recent study (Buller 1979) presented new and important information on sandhill crane population dynamics. The present report is intended to incorporate that and other information into a mathematical model for the purpose of assessing the long-range impact of hunting on the population of sandhill cranes.The model is a simple deterministic system that embodies density-dependent rates of survival and recruitment. The model employs four kinds of data: (1) spring population size of sandhill cranes, estimated from aerial surveys to be between 250,000 and 400,000 birds; (2) age composition in fall, estimated for 1974-76 to be 11.3% young; (3) annual harvest of cranes, estimated from a variety of sources to be about 5 to 7% of the spring population; and (4) age composition of harvested cranes, which was difficult to estimate but suggests that immatures were 2 to 4 times as vulnerable to hunting as adults.Because the true nature of sandhill crane population dynamics remains so poorly understood, it was necessary to try numerous (768 in all) combinations of survival and recruitment functions, and focus on the relatively few (37) that yielded population sizes and age structures comparable to those extant in the real population. Hunting was then applied to those simulated populations. In all combinations, hunting resulted in a lower asymptotic crane population, the decline ranging from 5 to 54%. The median decline was 22%, which suggests that a hunted sandhill crane population might be about three-fourths as large as it would be if left unhunted. Results apply to the aggregate of the three subspecies in the Central Flyway; individual subspecies or populations could be affected to a greater or lesser degree.

Evolutionary dynamics for persistent cooperation in structured populations

NASA Astrophysics Data System (ADS)

Li, Yan; Liu, Xinsheng; Claussen, Jens Christian; Guo, Wanlin

2015-06-01

The emergence and maintenance of cooperative behavior is a fascinating topic in evolutionary biology and social science. The public goods game (PGG) is a paradigm for exploring cooperative behavior. In PGG, the total resulting payoff is divided equally among all participants. This feature still leads to the dominance of defection without substantially magnifying the public good by a multiplying factor. Much effort has been made to explain the evolution of cooperative strategies, including a recent model in which only a portion of the total benefit is shared by all the players through introducing a new strategy named persistent cooperation. A persistent cooperator is a contributor who is willing to pay a second cost to retrieve the remaining portion of the payoff contributed by themselves. In a previous study, this model was analyzed in the framework of well-mixed populations. This paper focuses on discussing the persistent cooperation in lattice-structured populations. The evolutionary dynamics of the structured populations consisting of three types of competing players (pure cooperators, defectors, and persistent cooperators) are revealed by theoretical analysis and numerical simulations. In particular, the approximate expressions of fixation probabilities for strategies are derived on one-dimensional lattices. The phase diagrams of stationary states, and the evolution of frequencies and spatial patterns for strategies are illustrated on both one-dimensional and square lattices by simulations. Our results are consistent with the general observation that, at least in most situations, a structured population facilitates the evolution of cooperation. Specifically, here we find that the existence of persistent cooperators greatly suppresses the spreading of defectors under more relaxed conditions in structured populations compared to that obtained in well-mixed populations.

A model of population dynamics of TB in a prison system and application to South Africa.

PubMed

Witbooi, Peter; Vyambwera, Sibaliwe Maku

2017-11-29

Tuberculosis (TB) continues to spread in South African prisons in particular, as prisons are over-capacitated and have poor ventilation. The awaiting trial detainees are not screened on admission and are at high risk of getting infected with TB. We propose a compartmental model to describe the population dynamics of TB disease in prisons. Our model considers the inflow of susceptible, exposed and TB infectives into the prison population. Removal of individuals out of the prison population can be either by death or by being released from prison, as compared to a general population in which removal is only by death. We describe conditions, including non-inflow of infectives into the prison, which will ensure that TB can be eradicated from the prison population. The model is calibrated for the South African prison system, by using data in existing literature. The model can be used to make quantitative projections of TB prevalence and to measure the effect of interventions. Illustrative simulations in this regard are presented. The model can be used for other prison populations too, if data is available to calculate the model parameters. Various simulations generated with our model serve to illustrate how it can be utilized in making future projections of the levels of prevalence of TB, and to quantify the effect of interventions such as screening, treatment or reduction of transmission parameter values through improved living conditions for inmates. This makes it particularly useful as there are various targets set by the World Health Organization and by governments, for reduction of TB prevalence and ultimately its eradication. Towards eradication of TB from a prison system, the theorem on global stability of the disease-free state is a useful indicator.

Non-equilibrium hydrogen ionization in 2D simulations of the solar atmosphere

NASA Astrophysics Data System (ADS)

Leenaarts, J.; Carlsson, M.; Hansteen, V.; Rutten, R. J.

2007-10-01

Context: The ionization of hydrogen in the solar chromosphere and transition region does not obey LTE or instantaneous statistical equilibrium because the timescale is long compared with important hydrodynamical timescales, especially of magneto-acoustic shocks. Since the pressure, temperature, and electron density depend sensitively on hydrogen ionization, numerical simulation of the solar atmosphere requires non-equilibrium treatment of all pertinent hydrogen transitions. The same holds for any diagnostic application employing hydrogen lines. Aims: To demonstrate the importance and to quantify the effects of non-equilibrium hydrogen ionization, both on the dynamical structure of the solar atmosphere and on hydrogen line formation, in particular Hα. Methods: We implement an algorithm to compute non-equilibrium hydrogen ionization and its coupling into the MHD equations within an existing radiation MHD code, and perform a two-dimensional simulation of the solar atmosphere from the convection zone to the corona. Results: Analysis of the simulation results and comparison to a companion simulation assuming LTE shows that: a) non-equilibrium computation delivers much smaller variations of the chromospheric hydrogen ionization than for LTE. The ionization is smaller within shocks but subsequently remains high in the cool intershock phases. As a result, the chromospheric temperature variations are much larger than for LTE because in non-equilibrium, hydrogen ionization is a less effective internal energy buffer. The actual shock temperatures are therefore higher and the intershock temperatures lower. b) The chromospheric populations of the hydrogen n = 2 level, which governs the opacity of Hα, are coupled to the ion populations. They are set by the high temperature in shocks and subsequently remain high in the cool intershock phases. c) The temperature structure and the hydrogen level populations differ much between the chromosphere above photospheric magnetic elements and above quiet internetwork. d) The hydrogen n = 2 population and column density are persistently high in dynamic fibrils, suggesting that these obtain their visibility from being optically thick in Hα also at low temperature. Movie and Appendix A are only available in electronic form at http://www.aanda.org

The role of climate and vegetation on woolly mammoth extinction on St. Paul Island, Alaska and megafauna extinction in North America in the late Quaternary

NASA Astrophysics Data System (ADS)

Wang, Y.; Porter, W.; Miller, P. A.; Graham, R. W.; Williams, J. W.

2016-12-01

Estimate of megafauna behaviors dynamically under associated environmental factors is important to understand the mechanisms and causes of the late Quaternary megafaunal extinctions. On St. Paul Island, an isolated remnant of the Bering Land Bridge, a late-surviving population of woolly mammoth (Mammuthus primigenius) persisted until 5,600 cal BP, while 37 out of 54 megafauna species in the continent of North America, all herbivores, went extinct at the end of Pleistocene between 13,800 and 11,500 cal BP. Proposed natural drivers of the extinction events include abrupt temperature changes, food resource loss and freshwater shortage. Here we tested these three hypothesized mechanisms, using a physiological model (Niche Mapper) to estimate individual megafauna behaviors from the perspectives of metabolic rate, individual vegetation and freshwater requirement under simulated climates from Community Climate System Model version 3 (CCSM3), vegetation reconstructions based on dynamic LPJ-GUESS model and woolly mammoth and megafauna species trait data reconstructed based on mammal fossils. Preliminary simulations of woolly mammoth on St. Paul Island point to the importance of net vegetation primary productivity and freshwater availability as limits on the carrying capacity of St. Paul for mammoth populations, with a low carrying capacity in the middle Holocene making this population highly vulnerable to extinction. Results also indicate that the abrupt warming based around 14,000 cal BP in Bering land bridge on CCSM3 simulations causes woolly mammoth extinction, by driving metabolic rate high up beyond the active basic metabolic rate. Analysis suggests a positive relationship between temperature and metabolic rate, and woolly mammoth would go extinct when summer temperature is up to 12 °C or higher. However the temperature reconstructed based on regional proxies is relatively stable compared to CCSM3 simulations, and leads to stable metabolic rate of woolly mammoth and no extinction events. Proposed simulations of megafauna species in North America indicate the role of ice sheets in limiting habitats. This work helps resolve the drivers of extinction for a small island surviving woolly mammoth population and worldwide megafauna extinctions in the late Quaternary.

Atomistic simulations of dislocation pileup: Grain boundaries interaction

DOE PAGES

Wang, Jian

2015-05-27

Here, using molecular dynamics (MD) simulations, we studied the dislocation pileup–grain boundary (GB) interactions. Two Σ11 asymmetrical tilt grain boundaries in Al are studied to explore the influence of orientation relationship and interface structure on dislocation activities at grain boundaries. To mimic the reality of a dislocation pileup in a coarse-grained polycrystalline, we optimized the dislocation population in MD simulations and developed a predict-correct method to create a dislocation pileup in MD simulations. MD simulations explored several kinetic processes of dislocations–GB reactions: grain boundary sliding, grain boundary migration, slip transmission, dislocation reflection, reconstruction of grain boundary, and the correlation ofmore » these kinetic processes with the available slip systems across the GB and atomic structures of the GB.« less

Spatio-temporal transitions in the dynamics of bacterial populations

NASA Astrophysics Data System (ADS)

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

2001-03-01

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

Investigation of Kibble-Zurek Quench Dynamics in a Spin-1 Ferromagnetic BEC

NASA Astrophysics Data System (ADS)

Anquez, Martin; Robbins, Bryce; Hoang, Thai; Yang, Xiaoyun; Land, Benjamin; Hamley, Christopher; Chapman, Michael

2014-05-01

We study the temporal evolution of spin populations in small spin-1 87Rb condensates following a slow quench. A ferromagnetic spin-1 BEC exhibits a second-order gapless (quantum) phase transition due to a competition between the magnetic and collisional spin interaction energies. The dynamics of slow quenches through the critical point are predicted to exhibit universal power-law scaling as a function of quench speed. In spatially extended condensates, these excitations are revealed as spatial spin domains. In small condensates, the excitations are manifest in the temporal evolution of the spin populations, illustrating a Kibble-Zurek type scaling. We will present the results of our investigation and compare them to full quantum simulations of the system.

Simulation of aerosolized oil droplets capture in a range hood exhaust using coupled CFD-population balance method

NASA Astrophysics Data System (ADS)

Liu, Shuyuan; Zhang, Yong; Feng, Yu; Shi, Changbin; Cao, Yong; Yuan, Wei

2018-02-01

A coupled population balance sectional method (PBSM) coupled with computational fluid dynamics (CFD) is presented to simulate the capture of aerosolized oil droplets (AODs) in a range hood exhaust. The homogeneous nucleation and coagulation processes are modeled and simulated with this CFD-PBSM method. With the design angle, α of the range hood exhaust varying from 60° to 30°, the AODs capture increases meanwhile the pressure drop between the inlet and the outlet of the range hood also increases from 8.38Pa to 175.75Pa. The increasing inlet flow velocities also result in less AODs capture although the total suction increases due to higher flow rates to the range hood. Therefore, the CFD-PBSM method provides an insight into the formation and capture of AODs as well as their impact on the operation and design of the range hood exhaust.

A model for the interaction of frog population dynamics with Batrachochytrium dendrobaties, Janthinobacterium lividium and temperature and its implication for chytridiomycosis management

USGS Publications Warehouse

Ackleh, Azmy S.; Carter, Jacoby; Chellamuthu, Vinodh K.; Ma, Baoling

2016-01-01

Chytridiomycosis is an emerging disease caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd) that poses a serious threat to frog populations worldwide. Several studies have shown that inoculation of bacterial species Janthinobacterium lividum (Jl) can mitigate the impact of the disease. However, there are many questions regarding this interaction. A mathematical model of a frog population infected with chytridiomycosis is developed to investigate how the inoculation of Jl could reduce the impact of Bd disease on frogs. The model also illustrates the important role of temperature in disease dynamics. The model simulation results suggest possible control strategies for Jl to limit the impact of Bd in various scenarios. However, a better knowledge of Jl life cycle is needed to fully understand the interaction of Jl, Bd, temperature and frogs.

Stability and Bifurcation of a Fishery Model with Crowley-Martin Functional Response

NASA Astrophysics Data System (ADS)

Maiti, Atasi Patra; Dubey, B.

To understand the dynamics of a fishery system, a nonlinear mathematical model is proposed and analyzed. In an aquatic environment, we considered two populations: one is prey and another is predator. Here both the fish populations grow logistically and interaction between them is of Crowley-Martin type functional response. It is assumed that both the populations are harvested and the harvesting effort is assumed to be dynamical variable and tax is considered as a control variable. The existence of equilibrium points and their local stability are examined. The existence of Hopf-bifurcation, stability and direction of Hopf-bifurcation are also analyzed with the help of Center Manifold theorem and normal form theory. The global stability behavior of the positive equilibrium point is also discussed. In order to find the value of optimal tax, the optimal harvesting policy is used. To verify our analytical findings, an extensive numerical simulation is carried out for this model system.

Chaotic Dynamics of Trans-Neptunian Objects Perturbed by Planet Nine

NASA Astrophysics Data System (ADS)

Hadden, Sam; Li, Gongjie; Payne, Matthew J.; Holman, Matthew J.

2018-06-01

Observations of clustering among the orbits of the most distant trans-Neptunian objects (TNOs) has inspired interest in the possibility of an undiscovered ninth planet lurking in the outskirts of the solar system. Numerical simulations by a number of authors have demonstrated that, with appropriate choices of planet mass and orbit, such a planet can maintain clustering in the orbital elements of the population of distant TNOs, similar to the observed sample. However, many aspects of the rich underlying dynamical processes induced by such a distant eccentric perturber have not been fully explored. We report the results of our investigation of the dynamics of coplanar test-particles that interact with a massive body on an circular orbit (Neptune) and a massive body on a more distant, highly eccentric orbit (the putative Planet Nine). We find that a detailed examination of our idealized simulations affords tremendous insight into the rich test-particle dynamics that are possible. In particular, we find that chaos and resonance overlap plays an important role in particles’ dynamical evolution. We develop a simple mapping model that allows us to understand, in detail, the web of overlapped mean-motion resonances explored by chaotically evolving particles. We also demonstrate that gravitational interactions with Neptune can have profound effects on the orbital evolution of particles. Our results serve as a starting point for a better understanding of the dynamical behavior observed in more complicated simulations that can be used to constrain the mass and orbit of Planet Nine.

Dynamic partitioning for hybrid simulation of the bistable HIV-1 transactivation network.

PubMed

Griffith, Mark; Courtney, Tod; Peccoud, Jean; Sanders, William H

2006-11-15

The stochastic kinetics of a well-mixed chemical system, governed by the chemical Master equation, can be simulated using the exact methods of Gillespie. However, these methods do not scale well as systems become more complex and larger models are built to include reactions with widely varying rates, since the computational burden of simulation increases with the number of reaction events. Continuous models may provide an approximate solution and are computationally less costly, but they fail to capture the stochastic behavior of small populations of macromolecules. In this article we present a hybrid simulation algorithm that dynamically partitions the system into subsets of continuous and discrete reactions, approximates the continuous reactions deterministically as a system of ordinary differential equations (ODE) and uses a Monte Carlo method for generating discrete reaction events according to a time-dependent propensity. Our approach to partitioning is improved such that we dynamically partition the system of reactions, based on a threshold relative to the distribution of propensities in the discrete subset. We have implemented the hybrid algorithm in an extensible framework, utilizing two rigorous ODE solvers to approximate the continuous reactions, and use an example model to illustrate the accuracy and potential speedup of the algorithm when compared with exact stochastic simulation. Software and benchmark models used for this publication can be made available upon request from the authors.

Spatial patterns and biodiversity in off-lattice simulations of a cyclic three-species Lotka-Volterra model

NASA Astrophysics Data System (ADS)

Avelino, P. P.; Bazeia, D.; Losano, L.; Menezes, J.; de Oliveira, B. F.

2018-02-01

Stochastic simulations of cyclic three-species spatial predator-prey models are usually performed in square lattices with nearest-neighbour interactions starting from random initial conditions. In this letter we describe the results of off-lattice Lotka-Volterra stochastic simulations, showing that the emergence of spiral patterns does occur for sufficiently high values of the (conserved) total density of individuals. We also investigate the dynamics in our simulations, finding an empirical relation characterizing the dependence of the characteristic peak frequency and amplitude on the total density. Finally, we study the impact of the total density on the extinction probability, showing how a low population density may jeopardize biodiversity.

Protein free energy landscapes from long equilibrium simulations

NASA Astrophysics Data System (ADS)

Piana-Agostinetti, Stefano

Many computational techniques based on molecular dynamics (MD) simulation can be used to generate data to aid in the construction of protein free energy landscapes with atomistic detail. Unbiased, long, equilibrium MD simulations--although computationally very expensive--are particularly appealing, as they can provide direct kinetic and thermodynamic information on the transitions between the states that populate a protein free energy surface. It can be challenging to know how to analyze and interpret even results generated by this direct technique, however. I will discuss approaches we have employed, using equilibrium MD simulation data, to obtain descriptions of the free energy landscapes of proteins ranging in size from tens to thousands of amino acids.

Dynamic social networks based on movement

USGS Publications Warehouse

Scharf, Henry; Hooten, Mevin B.; Fosdick, Bailey K.; Johnson, Devin S.; London, Joshua M.; Durban, John W.

2016-01-01

Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.

Conformational dynamics of dry lamellar crystals of sugar based lipids: an atomistic simulation study.

PubMed

ManickamAchari, Vijayan; Bryce, Richard A; Hashim, Rauzah

2014-01-01

The rational design of a glycolipid application (e.g. drug delivery) with a tailored property depends on the detailed understanding of its structure and dynamics. Because of the complexity of sugar stereochemistry, we have undertaken a simulation study on the conformational dynamics of a set of synthetic glycosides with different sugar groups and chain design, namely dodecyl β-maltoside, dodecyl β-cellobioside, dodecyl β-isomaltoside and a C12C10 branched β-maltoside under anhydrous conditions. We examined the chain structure in detail, including the chain packing, gauche/trans conformations and chain tilting. In addition, we also investigated the rotational dynamics of the headgroup and alkyl chains. Monoalkylated glycosides possess a small amount of gauche conformers (∼20%) in the hydrophobic region of the lamellar crystal (LC) phase. In contrast, the branched chain glycolipid in the fluid Lα phase has a high gauche population of up to ∼40%. Rotational diffusion analysis reveals that the carbons closest to the headgroup have the highest correlation times. Furthermore, its value depends on sugar type, where the rotational dynamics of an isomaltose was found to be 11-15% and more restrained near the sugar, possibly due to the chain disorder and partial inter-digitation compared to the other monoalkylated lipids. Intriguingly, the present simulation demonstrates the chain from the branched glycolipid bilayer has the ability to enter into the hydrophilic region. This interesting feature of the anhydrous glycolipid bilayer simulation appears to arise from a combination of lipid crowding and the amphoteric nature of the sugar headgroups.

Effects of the distant population density on spatial patterns of demographic dynamics

NASA Astrophysics Data System (ADS)

Tamura, Kohei; Masuda, Naoki

2017-08-01

Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500 m) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km.

Effects of the distant population density on spatial patterns of demographic dynamics.

PubMed

Tamura, Kohei; Masuda, Naoki

2017-08-01

Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500  m ) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km.

Effects of the distant population density on spatial patterns of demographic dynamics

PubMed Central

2017-01-01

Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500 m) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km. PMID:28878987

Re-evaluation of Yellowstone grizzly bear population dynamics not supported by empirical data: response to Doak & Cutler

USGS Publications Warehouse

van Manen, Frank T.; Ebinger, Michael R.; Haroldson, Mark A.; Harris, Richard B.; Higgs, Megan D.; Cherry, Steve; White, Gary C.; Schwartz, Charles C.

2014-01-01

Doak and Cutler critiqued methods used by the Interagency Grizzly Bear Study Team (IGBST) to estimate grizzly bear population size and trend in the Greater Yellowstone Ecosystem. Here, we focus on the premise, implementation, and interpretation of simulations they used to support their arguments. They argued that population increases documented by IGBST based on females with cubs-of-the-year were an artifact of increased search effort. However, we demonstrate their simulations were neither reflective of the true observation process nor did their results provide statistical support for their conclusion. They further argued that survival and reproductive senescence should be incorporated into population projections, but we demonstrate their choice of extreme mortality risk beyond age 20 and incompatible baseline fecundity led to erroneous conclusions. The conclusions of Doak and Cutler are unsubstantiated when placed within the context of a thorough understanding of the data, study system, and previous research findings and publications.

[A Cellular Automata Model for a Community Comprising Two Plant Species of Different Growth Forms].

PubMed

Frolov, P V; Zubkova, E V; Komarov, A S

2015-01-01

A cellular automata computer model for the interactions between two plant species of different growth forms--the lime hairgrass Deschampsia caespitosa (L.) P. Beauv., a sod cereal, and the moneywort Lysimachia nummularia L., a ground creeping perennial herb--is considered. Computer experiments on the self-maintenance of the populations of each species against the background of a gradual increase in the share of randomly eliminated individuals, coexistence of the populations of two species, and the effect of the phytogenous field have been conducted. As has been shown, all the studied factors determine the number of individuals and self-sustainability of the simulated populations by the degree of their impact. The limits of action have been determined for individual factors; within these limits, the specific features in plant reproduction and dispersal provide sustainable coexistence of the simulated populations. It has been demonstrated that the constructed model allows for studying the long-term developmental dynamics of the plants belonging to the selected growth forms.

Population dynamics and angler exploitation of the unique muskellunge population in Shoepack Lake, Voyageurs National Park, Minnesota

USGS Publications Warehouse

Frohnauer, N.K.; Pierce, C.L.; Kallemeyn, L.W.

2007-01-01

A unique population of muskellunge Esox masquinongy inhabits Shoepack Lake in Voyageurs National Park, Minnesota. Little is known about its status, dynamics, and angler exploitation, and there is concern for the long-term viability of this population. We used intensive sampling and mark-recapture methods to quantify abundance, survival, growth, condition, age at maturity and fecundity and angler surveys to quantify angler pressure, catch rates, and exploitation. During our study, heavy rain washed out a dam constructed by beavers Castor canadensis which regulates the water level at the lake outlet, resulting in a nearly 50% reduction in surface area. We estimated a population size of 1,120 adult fish at the beginning of the study. No immediate reduction in population size was detected in response to the loss of lake area, although there was a gradual, but significant, decline in population size over the 2-year study. Adults grew less than 50 mm per year, and relative weight (W r) averaged roughly 80. Anglers were successful in catching, on average, two fish during a full day of angling, but harvest was negligible. Shoepack Lake muskellunge exhibit much slower growth rates and lower condition, but much higher densities and angler catch per unit effort (CPUE), than other muskellunge populations. The unique nature, limited distribution, and location of this population in a national park require special consideration for management. The results of this study provide the basis for assessing the long-term viability of the Shoepack Lake muskellunge population through simulations of long-term population dynamics and genetically effective population size. ?? Copyright by the American Fisheries Society 2007.

THE STELLAR SPHEROID, THE DISK, AND THE DYNAMICS OF THE COSMIC WEB

DOE Office of Scientific and Technical Information (OSTI.GOV)

Domínguez-Tenreiro, R.; Obreja, A.; Brook, C. B.

Models of the advanced stages of gravitational instability predict that baryons that form the stellar populations of current galaxies at z = 0 displayed a web-like structure at high z, as part of the cosmic web (CW). We explore details of these predictions using cosmological hydrodynamical simulations. When the stellar populations of the spheroid and disk components of simulated late-type galaxies are traced back separately to high zs we found CW-like structures where spheroid progenitors are more evolved than disk progenitors. The distinction between the corresponding stellar populations, as driven by their specific angular momentum content j, can be explainedmore » in terms of the CW evolution, extended to two processes occurring at lower z. First, the spheroid progenitors strongly lose j at collapse, which contrasts with the insignificant j loss of the disk progenitors. The second is related to the lack of alignment, at assembly, between the spheroid-to-be material and the already settled proto-disk, in contrast to the alignment of disk-to-be material, in some cases resulting from circumgalactic, disk-induced gravitational torques. The different final outcomes of these low-z processes have their origins in the different initial conditions driven by the CW dynamics.« less

A malaria transmission-directed model of mosquito life cycle and ecology

PubMed Central

2011-01-01

Background Malaria is a major public health issue in much of the world, and the mosquito vectors which drive transmission are key targets for interventions. Mathematical models for planning malaria eradication benefit from detailed representations of local mosquito populations, their natural dynamics and their response to campaign pressures. Methods A new model is presented for mosquito population dynamics, effects of weather, and impacts of multiple simultaneous interventions. This model is then embedded in a large-scale individual-based simulation and results for local elimination of malaria are discussed. Mosquito population behaviours, such as anthropophily and indoor feeding, are included to study their effect upon the efficacy of vector control-based elimination campaigns. Results Results for vector control tools, such as bed nets, indoor spraying, larval control and space spraying, both alone and in combination, are displayed for a single-location simulation with vector species and seasonality characteristic of central Tanzania, varying baseline transmission intensity and vector bionomics. The sensitivities to habitat type, anthropophily, indoor feeding, and baseline transmission intensity are explored. Conclusions The ability to model a spectrum of local vector species with different ecologies and behaviours allows local customization of packages of interventions and exploration of the effect of proposed new tools. PMID:21999664

Stochastic simulation of multiscale complex systems with PISKaS: A rule-based approach.

PubMed

Perez-Acle, Tomas; Fuenzalida, Ignacio; Martin, Alberto J M; Santibañez, Rodrigo; Avaria, Rodrigo; Bernardin, Alejandro; Bustos, Alvaro M; Garrido, Daniel; Dushoff, Jonathan; Liu, James H

2018-03-29

Computational simulation is a widely employed methodology to study the dynamic behavior of complex systems. Although common approaches are based either on ordinary differential equations or stochastic differential equations, these techniques make several assumptions which, when it comes to biological processes, could often lead to unrealistic models. Among others, model approaches based on differential equations entangle kinetics and causality, failing when complexity increases, separating knowledge from models, and assuming that the average behavior of the population encompasses any individual deviation. To overcome these limitations, simulations based on the Stochastic Simulation Algorithm (SSA) appear as a suitable approach to model complex biological systems. In this work, we review three different models executed in PISKaS: a rule-based framework to produce multiscale stochastic simulations of complex systems. These models span multiple time and spatial scales ranging from gene regulation up to Game Theory. In the first example, we describe a model of the core regulatory network of gene expression in Escherichia coli highlighting the continuous model improvement capacities of PISKaS. The second example describes a hypothetical outbreak of the Ebola virus occurring in a compartmentalized environment resembling cities and highways. Finally, in the last example, we illustrate a stochastic model for the prisoner's dilemma; a common approach from social sciences describing complex interactions involving trust within human populations. As whole, these models demonstrate the capabilities of PISKaS providing fertile scenarios where to explore the dynamics of complex systems. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Fundamental limits on dynamic inference from single-cell snapshots

PubMed Central

Weinreb, Caleb; Tusi, Betsabeh K.; Socolovsky, Merav

2018-01-01

Single-cell expression profiling reveals the molecular states of individual cells with unprecedented detail. Because these methods destroy cells in the process of analysis, they cannot measure how gene expression changes over time. However, some information on dynamics is present in the data: the continuum of molecular states in the population can reflect the trajectory of a typical cell. Many methods for extracting single-cell dynamics from population data have been proposed. However, all such attempts face a common limitation: for any measured distribution of cell states, there are multiple dynamics that could give rise to it, and by extension, multiple possibilities for underlying mechanisms of gene regulation. Here, we describe the aspects of gene expression dynamics that cannot be inferred from a static snapshot alone and identify assumptions necessary to constrain a unique solution for cell dynamics from static snapshots. We translate these constraints into a practical algorithmic approach, population balance analysis (PBA), which makes use of a method from spectral graph theory to solve a class of high-dimensional differential equations. We use simulations to show the strengths and limitations of PBA, and then apply it to single-cell profiles of hematopoietic progenitor cells (HPCs). Cell state predictions from this analysis agree with HPC fate assays reported in several papers over the past two decades. By highlighting the fundamental limits on dynamic inference faced by any method, our framework provides a rigorous basis for dynamic interpretation of a gene expression continuum and clarifies best experimental designs for trajectory reconstruction from static snapshot measurements. PMID:29463712

Climate change, shifting seasons, and the ecohydrology of Devils Hole, Death Valley National Park

NASA Astrophysics Data System (ADS)

Hausner, M. B.; Wilson, K. P.; Gaines, D. B.; Suarez, F. I.; Tyler, S. W.

2011-12-01

Devils Hole, a water-filled fracture in the carbonate aquifer of the Death Valley Regional Flow System, comprises an ecosystem that can serve as a bellwether of climate change. This 50 square meter pool of unknown depth is home to the only extant population of the endangered Devils Hole pupfish (Cyprinodon diabolis). A shallow shelf in the system provides the most suitable habitat for spawning, and the past pupfish population counts have been correlated to the water level in the system. Recently, however, population declines unrelated to water level have been observed. The 33° C waters of Devils Hole are near the upper threshold for most Cyprinodon species, and the shallow shelf experiences the greatest diurnal and seasonal temperature variability. The extremely limited habitat, small population (the spring, 2011 population survey counted approximately 100 individuals), and precarious nature of populations near survival thresholds combine to make the system exceptionally susceptible to the impacts of climate change. A hydrodynamic model of the shallow shelf was developed to simulate thermal convection in response to a number of energy fluxes, including climatic drivers such as air temperature and solar radiation. Simulations of current conditions demonstrate seasonal and diurnal changes in the temperature of the water and the substrate in which adult pupfish spawn, eggs hatch, and larvae develop. The simulated convection patterns also influence the oxygen dynamics, nutrient cycling, and the food web of the ecosystem. Simulations of future conditions using a delta change methodology point towards changes in the seasonal cycles, which may limit or shift the reproductive season of the species.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glaser, D.; Connolly, J.; Berghoffen, A.

The resident bald eagles of the lower Columbia River have lower productivity and higher contaminant levels than other bald eagles of the Pacific Northwest. The primary population stressors are believed to be habitat loss, human disturbance, p,p{prime}DDE, PCBs, dioxins and furans. The primary effect of habitat loss is to reduce the carrying capacity of the region for nesting sites, and the primary effects of human disturbance and contamination by organic compounds are to reduce productivity. The purpose of this study was to quantitatively evaluate the effects of all of, these potential stressors on the bald eagle population dynamics. A modelmore » of the population dynamics was developed. The model structure includes a physiologically-based toxicokinetic (PBTK) submodel to estimate the degree of contamination, which is linked via a toxicology submodel to a population dynamics submodel. The PBTK submodel is time-variable, incorporating species-specific bioenergetics, as well as contaminant assimilation and excretion rates for each compound of interest. Calculated body burdens and egg concentrations for each compound account for spatial and temporal variations in feeding habits and prey contaminant levels. The population submodel includes fecundity and survival information, as well as a limit to the number of breeding pairs (carrying capacity) and a population of non-breeding subadults and adults (floaters). Model simulations are performed in a Monte Carlo framework. Results include estimates of the persistence, resistance and resilience of the population: the probability of extinction, the relationship between magnitude of stress and change in population size, and the time course of recovery of a population following a reduction in stress.« less

A diffusion based study of population dynamics: Prehistoric migrations into South Asia

PubMed Central

Vahia, Mayank N.; Yadav, Nisha; Ladiwala, Uma; Mathur, Deepak

2017-01-01

A diffusion equation has been used to study migration of early humans into the South Asian subcontinent. The diffusion equation is tempered by a set of parameters that account for geographical features like proximity to water resources, altitude, and flatness of land. The ensuing diffusion of populations is followed in time-dependent computer simulations carried out over a period of 10,000 YBP. The geographical parameters are determined from readily-available satellite data. The results of our computer simulations are compared to recent genetic data so as to better correlate the migratory patterns of various populations; they suggest that the initial populations started to coalesce around 4,000 YBP before the commencement of a period of relative geographical isolation of each population group. The period during which coalescence of populations occurred appears consistent with the established timeline associated with the Harappan civilization and also, with genetic admixing that recent genetic mapping data reveal. Our results may contribute to providing a timeline for the movement of prehistoric people. Most significantly, our results appear to suggest that the Ancestral Austro-Asiatic population entered the subcontinent through an easterly direction, potentially resolving a hitherto-contentious issue. PMID:28493906

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostova, T; Carlsen, T

We present a study, based on simulations with SERDYCA, a spatially-explicit individual-based model of rodent dynamics, on the relation between population persistence and the presence of numerous isolated disturbances in the habitat. We are specifically interested in the effect of disturbances that do not fragment the environment on population persistence. Our results suggest that the presence of disturbances in the absence of fragmentation can actually increase the average time to extinction of the modeled population. The presence of disturbances decreases population density but can increase the chance for mating in monogamous species and consequently, the ratio of juveniles in themore » population. It thus provides a better chance for the population to restore itself after a severe period with critically low population density. We call this the ''disturbance-forced localization effect''.« less

Dynamical evolution and spatial mixing of multiple population globular clusters

NASA Astrophysics Data System (ADS)

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

2013-03-01

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

Incorporating the effects of humidity in a mechanistic model of Anopheles gambiae mosquito population dynamics in the Sahel region of Africa

PubMed Central

2013-01-01

Background Low levels of relative humidity are known to decrease the lifespan of mosquitoes. However, most current models of malaria transmission do not account for the effects of relative humidity on mosquito survival. In the Sahel, where relative humidity drops to levels <20% for several months of the year, we expect relative humidity to play a significant role in shaping the seasonal profile of mosquito populations. Here, we present a new formulation for Anopheles gambiae sensu lato (s.l.) mosquito survival as a function of temperature and relative humidity and investigate the effect of humidity on simulated mosquito populations. Methods Using existing observations on relationships between temperature, relative humidity and mosquito longevity, we developed a new equation for mosquito survival as a function of temperature and relative humidity. We collected simultaneous field observations on temperature, wind, relative humidity, and anopheline mosquito populations for two villages from the Sahel region of Africa, which are presented in this paper. We apply this equation to the environmental data and conduct numerical simulations of mosquito populations using the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS). Results Relative humidity drops to levels that are uncomfortable for mosquitoes at the end of the rainy season. In one village, Banizoumbou, water pools dried up and interrupted mosquito breeding shortly after the end of the rainy season. In this case, relative humidity had little effect on the mosquito population. However, in the other village, Zindarou, the relatively shallow water table led to water pools that persisted several months beyond the end of the rainy season. In this case, the decrease in mosquito survival due to relative humidity improved the model’s ability to reproduce the seasonal pattern of observed mosquito abundance. Conclusions We proposed a new equation to describe Anopheles gambiae s.l. mosquito survival as a function of temperature and relative humidity. We demonstrated that relative humidity can play a significant role in mosquito population and malaria transmission dynamics. Future modeling work should account for these effects of relative humidity. PMID:23938022

The simcyp population based simulator: architecture, implementation, and quality assurance.

PubMed

Jamei, Masoud; Marciniak, Steve; Edwards, Duncan; Wragg, Kris; Feng, Kairui; Barnett, Adrian; Rostami-Hodjegan, Amin

2013-01-01

Developing a user-friendly platform that can handle a vast number of complex physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models both for conventional small molecules and larger biologic drugs is a substantial challenge. Over the last decade the Simcyp Population Based Simulator has gained popularity in major pharmaceutical companies (70% of top 40 - in term of R&D spending). Under the Simcyp Consortium guidance, it has evolved from a simple drug-drug interaction tool to a sophisticated and comprehensive Model Based Drug Development (MBDD) platform that covers a broad range of applications spanning from early drug discovery to late drug development. This article provides an update on the latest architectural and implementation developments within the Simulator. Interconnection between peripheral modules, the dynamic model building process and compound and population data handling are all described. The Simcyp Data Management (SDM) system, which contains the system and drug databases, can help with implementing quality standards by seamless integration and tracking of any changes. This also helps with internal approval procedures, validation and auto-testing of the new implemented models and algorithms, an area of high interest to regulatory bodies.

Influence of Climate Variability on Brown Planthopper Population Dynamics and Development Time

NASA Astrophysics Data System (ADS)

Romadhon, S.; Koesmaryono, Y.; Hidayati, R.

2017-03-01

Brown planthopper or Nilaparvata lugens (BPH) is one of the rice major pest in Indonesia. BPH can cause extensive damage and almost always appear in each planting season, frequent explosions attack (outbreaks) resulting in very high economic losses. Outbreaks of BPH were often occurred in paddy fields in Indramayu regency and several endemic regency in Java island, where rice is cultivated twice to three times a year both in the rainy and dry cropping seasons. The output of simulation shows the BPH population starts increasing from December to February (rainy season) and from June to August (dry season). The result relatively had same pattern with light trap observation data, but overestimate to predict BPH population. Therefore, the output of simulation had adequately close pattern if it is compares to BPH attacked area observation data. The development time taken by different stages of BPH varied at different temperatures. BPH development time at eggs and adults stage from the simulation output is suitable with BPH real lifestage, but at nymphs stage the result is different with the concept of development time.

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

USGS Publications Warehouse

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

2014-01-01

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

Consumer-Resource Dynamics: Quantity, Quality, and Allocation

PubMed Central

Getz, Wayne M.; Owen-Smith, Norman

2011-01-01

Background The dominant paradigm for modeling the complexities of interacting populations and food webs is a system of coupled ordinary differential equations in which the state of each species, population, or functional trophic group is represented by an aggregated numbers-density or biomass-density variable. Here, using the metaphysiological approach to model consumer-resource interactions, we formulate a two-state paradigm that represents each population or group in a food web in terms of both its quantity and quality. Methodology and Principal Findings The formulation includes an allocation function controlling the relative proportion of extracted resources to increasing quantity versus elevating quality. Since lower quality individuals senesce more rapidly than higher quality individuals, an optimal allocation proportion exists and we derive an expression for how this proportion depends on population parameters that determine the senescence rate, the per-capita mortality rate, and the effects of these rates on the dynamics of the quality variable. We demonstrate that oscillations do not arise in our model from quantity-quality interactions alone, but require consumer-resource interactions across trophic levels that can be stabilized through judicious resource allocation strategies. Analysis and simulations provide compelling arguments for the necessity of populations to evolve quality-related dynamics in the form of maternal effects, storage or other appropriate structures. They also indicate that resource allocation switching between investments in abundance versus quality provide a powerful mechanism for promoting the stability of consumer-resource interactions in seasonally forcing environments. Conclusions/Significance Our simulations show that physiological inefficiencies associated with this switching can be favored by selection due to the diminished exposure of inefficient consumers to strong oscillations associated with the well-known paradox of enrichment. Also our results demonstrate how allocation switching can explain observed growth patterns in experimental microbial cultures and discuss how our formulation can address questions that cannot be answered using the quantity-only paradigms that currently predominate. PMID:21283752

Post-transition state dynamics and product energy partitioning following thermal excitation of the F∙∙∙HCH 2 CN transition state: Disagreement with experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pratihar, Subha; Ma, Xinyou; Xie, Jing

Born-Oppenheimer direct dynamics simulations were performed to study atomistic details of the F + CH 3CN → HF + CH 2CN H-atom abstraction reaction. The simulation trajectories were calculated with a combined M06-2X/MP2 algorithm utilizing the 6-311++G** basis set. In accord with experiment and assuming the accuracy of transition state theory (TST), the trajectories were initiated at the F-HCH 2CN abstraction TS with a 300 K Boltzmann distribution of energy and directed towards products. Recrossing of the TS was negligible, confirming the accuracy of TST for the simulation. HF formation was rapid, occurring within 0.014 ps of the trajectory initiation.more » The intrinsic reaction coordinate (IRC) for reaction involves rotation of HF about CH 2CN and then trapping in the CH 2CN-HF post-reaction potential energy well of ~10 kcal/mol with respect to the HF + CH 2CN products. In contrast to this IRC, five different trajectory types were observed, with the majority involving direct dissociation and only 11% approximately following the IRC. The HF vibrational and rotational quantum numbers, n and J, were calculated when HF was initially formed and they increase as potential energy is released in forming the HF + CH 2CN products. The population of the HF product vibrational states is only in qualitative agreement with experiment, with the simulations showing depressed and enhanced populations of the n = 1 and 2 states as compared to experiment. From the simulations and with an anharmonic zero-point energy constraint, the percentage partitioning of the product energy to relative translation, HF rotation, HF vibration, CH 2CN rotation and CH 2CN vibration is 5, 11, 60, 7, and 16%, respectively. In contrast the experimental energy partitioning percentages to HF rotation and vibration are 6 and 41%. Comparisons are made between the current simulation and those for other F + H-atom abstraction reactions. The simulation product energy partitioning and HF vibrational population for F + CH 3CN → HF + CH 2CN are similar to those for these other reactions. A detailed discussion is given of possible origins of the difference between the simulation and experimental energy partitioning dynamics for the F + CH 3CN → HF + CH 2CN reaction. The F + CH 3CN reaction also forms the CH 3C(F)N intermediate, in which the F-atom adds to the C≡N bond. However, this intermediate and the F---CH 3CN and CH 3CN-F van der Waals complexes are not expected to affect the F + CH 3CN → HF + CH 2CN product energy partitioning.« less

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

PubMed

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity.

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity

PubMed Central

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity. PMID:28060865

Mathematical modeling of transmission co-infection tuberculosis in HIV community

NASA Astrophysics Data System (ADS)

Lusiana, V.; Putra, P. S.; Nuraini, N.; Soewono, E.

2017-03-01

TB and HIV infection have the effect of deeply on assault the immune system, since they can afford to weaken host immune respone through a mechanism that has not been fully understood. HIV co-infection is the stongest risk factor for progression of M. tuberculosis to active TB disease in HIV individuals, as well as TB has been accelerated to progression HIV infection. In this paper we create a model of transmission co-infection TB in HIV community, dynamic system with ten compartments built in here. Dynamic analysis in this paper mentioned ranging from disease free equilibrium conditions, endemic equilibrium conditions, basic reproduction ratio, stability analysis and numerical simulation. Basic reproductive ratio were obtained from spectral radius the next generation matrix of the model. Numerical simulations are built to justify the results of the analysis and to see the changes in the dynamics of the population in each compartment. The sensitivity analysis indicates that the parameters affecting the population dynamics of TB in people with HIV infection is parameters rate of progression of individuals from the exposed TB class to the active TB, treatment rate of exposed TB individuals, treatment rate of infectious (active TB) individuals and probability of transmission of TB infection from an infective to a susceptible per contact per unit time. We can conclude that growing number of infections carried by infectious TB in people with HIV infection can lead to increased spread of disease or increase in endemic conditions.

Invasion complexity at large spatial scales is an emergent property of interactions among landscape characteristics and invader traits

PubMed Central

Jordan, Nicholas R.; Forester, James D.

2018-01-01

Invasion potential should be part of the evaluation of candidate species for any species introduction. However, estimating invasion risks remains a challenging problem, particularly in complex landscapes. Certain plant traits are generally considered to increase invasive potential and there is an understanding that landscapes influence invasions dynamics, but little research has been done to explore how those drivers of invasions interact. We evaluate the relative roles of, and potential interactions between, plant invasiveness traits and landscape characteristics on invasions with a case study using a model parameterized for the potentially invasive biomass crop, Miscanthus × giganteus. Using that model we simulate invasions on 1000 real landscapes to evaluate how landscape characteristics, including both composition and spatial structure, affect invasion outcomes. We conducted replicate simulations with differing strengths of plant invasiveness traits (dispersal ability, establishment ability, population growth rate, and the ability to utilize dispersal corridors) to evaluate how the importance of landscape characteristics for predicting invasion patterns changes depending on the invader details. Analysis of simulations showed that the presence of highly suitable habitat (e.g., grasslands) is generally the strongest determinant of invasion dynamics but that there are also more subtle interactions between landscapes and invader traits. These effects can also vary between different aspects of invasion dynamics (short vs. long time scales and population size vs. spatial extent). These results illustrate that invasions are complex emergent processes with multiple drivers and effective management needs to reflect the ecology of the species of interest and the particular goals or risks for which efforts need to be optimized. PMID:29771923

Potential effects of maternal contribution on egg and larva population dynamics of striped bass: Integrated individual-based model and directed field sampling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cowan, J.H., Jr.; Rose, K.A.

1991-01-01

We have used a bioenergetically-driven, individual-based model (IBM) of striped bass as a framework for synthesizing available information on population biology and quantifying, in a relative sense, factors that potentially affect year class success. The IBM has been configured to simulate environmental conditions experienced by several striped bass populations; i.e., in the Potomac River, MD; in Hudson River, NY; in the Santee-Cooper River System, SC, and; in the San Joaquin-Sacramento River System CA. These sites represent extremes in the geographic distribution and thus, environmental variability of striped bass spawning. At each location, data describing the physio-chemical and biological characteristics ofmore » the spawning population and nursery area are being collected and synthesized by means of a prioritized, directed field sampling program that is organized by the individual-based recruitment model. Here, we employ the striped bass IBM configured for the Potomac River, MD from spawning into the larval period to evaluate the potential for maternal contribution to affect larva survival and growth. Model simulations in which the size distribution and spawning day of females are altered indicate that larva survival is enhanced (3.3-fold increase) when a high fraction of females in the spawning population are large. Larva stage duration also is less ({bar X} = 18.4 d and 22.2 d) when large and small females, respectively, are mothers in simulations. Although inconclusive, these preliminary results for Potomac River striped bass suggest that the effects of female size, timing of spawning nad maternal contribution on recruitment dynamics potentially are important and illustrate our approach to the study of recruitment in striped bass. We hope to use the model, field collections and management alternatives that vary from site to site, in an iterative manner for some time to come. 54 refs., 4 figs., 1 tab.« less

Meteorologically Driven Simulations of Dengue Epidemics in San Juan, PR

PubMed Central

Morin, Cory W.; Monaghan, Andrew J.; Hayden, Mary H.; Barrera, Roberto; Ernst, Kacey

2015-01-01

Meteorological factors influence dengue virus ecology by modulating vector mosquito population dynamics, viral replication, and transmission. Dynamic modeling techniques can be used to examine how interactions among meteorological variables, vectors and the dengue virus influence transmission. We developed a dengue fever simulation model by coupling a dynamic simulation model for Aedes aegypti, the primary mosquito vector for dengue, with a basic epidemiological Susceptible-Exposed-Infectious-Recovered (SEIR) model. Employing a Monte Carlo approach, we simulated dengue transmission during the period of 2010–2013 in San Juan, PR, where dengue fever is endemic. The results of 9600 simulations using varied model parameters were evaluated by statistical comparison (r2) with surveillance data of dengue cases reported to the Centers for Disease Control and Prevention. To identify the most influential parameters associated with dengue virus transmission for each period the top 1% of best-fit model simulations were retained and compared. Using the top simulations, dengue cases were simulated well for 2010 (r2 = 0.90, p = 0.03), 2011 (r2 = 0.83, p = 0.05), and 2012 (r2 = 0.94, p = 0.01); however, simulations were weaker for 2013 (r2 = 0.25, p = 0.25) and the entire four-year period (r2 = 0.44, p = 0.002). Analysis of parameter values from retained simulations revealed that rain dependent container habitats were more prevalent in best-fitting simulations during the wetter 2010 and 2011 years, while human managed (i.e. manually filled) container habitats were more prevalent in best-fitting simulations during the drier 2012 and 2013 years. The simulations further indicate that rainfall strongly modulates the timing of dengue (e.g., epidemics occurred earlier during rainy years) while temperature modulates the annual number of dengue fever cases. Our results suggest that meteorological factors have a time-variable influence on dengue transmission relative to other important environmental and human factors. PMID:26275146

Trade-offs between maintenance of ecosystem services and socio-economic development in rural mountainous communities in southern Spain: a dynamic simulation approach.

PubMed

Vidal-Legaz, Beatriz; Martínez-Fernández, Julia; Picón, Andrés Sánchez; Pugnaire, Francisco I

2013-12-15

Mountainous rural communities have traditionally managed their land extensively, resulting in land uses that provide important ecosystem services for both rural and urban areas. Over recent decades, these communities have undergone drastic changes in economic structure, population size and land use. Our understanding of the exact mechanisms that drive these changes is limited, and there is also a lack of integrative approaches to enable decision makers to steer rural development towards a more sustainable path. In this study, we build a dynamic simulation model to calculate the trade-offs between the provisions of two ecosystem services - landscape aesthetic value and water supply for human use - and the economic development associated with different land use changes. The study area for the simulation comprises two rural communities located in southern Spain. Our results show trade-offs between economic development and the provision of the selected ecosystem services in the selected study area. Land use intensification results in economic development but is not enough to prevent population loss and has a negative impact on both the water supply and on aesthetic services. We conclude that more proactive management policies are needed to mitigate a loss in ecosystem services. Simulation models like ours may facilitate the choice of these policies, as they could test the result of land use planning policies contributing therefore, to a more integrative and sustainable management of rural communities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Recent progress in simulating galaxy formation from the largest to the smallest scales

NASA Astrophysics Data System (ADS)

Faucher-Giguère, Claude-André

2018-05-01

Galaxy formation simulations are an essential part of the modern toolkit of astrophysicists and cosmologists alike. Astrophysicists use the simulations to study the emergence of galaxy populations from the Big Bang, as well as the formation of stars and supermassive black holes. For cosmologists, galaxy formation simulations are needed to understand how baryonic processes affect measurements of dark matter and dark energy. Owing to the extreme dynamic range of galaxy formation, advances are driven by novel approaches using simulations with different tradeoffs between volume and resolution. Large-volume but low-resolution simulations provide the best statistics, while higher-resolution simulations of smaller cosmic volumes can be evolved with self-consistent physics and reveal important emergent phenomena. I summarize recent progress in galaxy formation simulations, including major developments in the past five years, and highlight some key areas likely to drive further advances over the next decade.

Conformation and Dynamics of Human Urotensin II and Urotensin Related Peptide in Aqueous Solution.

PubMed

Haensele, Elke; Mele, Nawel; Miljak, Marija; Read, Christopher M; Whitley, David C; Banting, Lee; Delépée, Carla; Sopkova-de Oliveira Santos, Jana; Lepailleur, Alban; Bureau, Ronan; Essex, Jonathan W; Clark, Timothy

2017-02-27

Conformation and dynamics of the vasoconstrictive peptides human urotensin II (UII) and urotensin related peptide (URP) have been investigated by both unrestrained and enhanced-sampling molecular-dynamics (MD) simulations and NMR spectroscopy. These peptides are natural ligands of the G-protein coupled urotensin II receptor (UTR) and have been linked to mammalian pathophysiology. UII and URP cannot be characterized by a single structure but exist as an equilibrium of two main classes of ring conformations, open and folded, with rapidly interchanging subtypes. The open states are characterized by turns of various types centered at K 8 Y 9 or F 6 W 7 predominantly with no or only sparsely populated transannular hydrogen bonds. The folded conformations show multiple turns stabilized by highly populated transannular hydrogen bonds comprising centers F 6 W 7 K 8 or W 7 K 8 Y 9 . Some of these conformations have not been characterized previously. The equilibrium populations that are experimentally difficult to access were estimated by replica-exchange MD simulations and validated by comparison of experimental NMR data with chemical shifts calculated with density-functional theory. UII exhibits approximately 72% open:28% folded conformations in aqueous solution. URP shows very similar ring conformations as UII but differs in an open:folded equilibrium shifted further toward open conformations (86:14) possibly arising from the absence of folded N-terminal tail-ring interaction. The results suggest that the different biological effects of UII and URP are not caused by differences in ring conformations but rather by different interactions with UTR.

An agent-based model of tsetse fly response to seasonal climatic drivers: Assessing the impact on sleeping sickness transmission rates.

PubMed

Alderton, Simon; Macleod, Ewan T; Anderson, Neil E; Palmer, Gwen; Machila, Noreen; Simuunza, Martin; Welburn, Susan C; Atkinson, Peter M

2018-02-01

This paper presents the development of an agent-based model (ABM) to incorporate climatic drivers which affect tsetse fly (G. m. morsitans) population dynamics, and ultimately disease transmission. The model was used to gain a greater understanding of how tsetse populations fluctuate seasonally, and investigate any response observed in Trypanosoma brucei rhodesiense human African trypanosomiasis (rHAT) disease transmission, with a view to gaining a greater understanding of disease dynamics. Such an understanding is essential for the development of appropriate, well-targeted mitigation strategies in the future. The ABM was developed to model rHAT incidence at a fine spatial scale along a 75 km transect in the Luangwa Valley, Zambia. The model incorporates climatic factors that affect pupal mortality, pupal development, birth rate, and death rate. In combination with fine scale demographic data such as ethnicity, age and gender for the human population in the region, as well as an animal census and a sample of daily routines, we create a detailed, plausible simulation model to explore tsetse population and disease transmission dynamics. The seasonally-driven model suggests that the number of infections reported annually in the simulation is likely to be a reasonable representation of reality, taking into account the high levels of under-detection observed. Similar infection rates were observed in human (0.355 per 1000 person-years (SE = 0.013)), and cattle (0.281 per 1000 cattle-years (SE = 0.025)) populations, likely due to the sparsity of cattle close to the tsetse interface. The model suggests that immigrant tribes and school children are at greatest risk of infection, a result that derives from the bottom-up nature of the ABM and conditioning on multiple constraints. This result could not be inferred using alternative population-level modelling approaches. In producing a model which models the tsetse population at a very fine resolution, we were able to analyse and evaluate specific elements of the output, such as pupal development and the progression of the teneral population, allowing the development of our understanding of the tsetse population as a whole. This is an important step in the production of a more accurate transmission model for rHAT which can, in turn, help us to gain a greater understanding of the transmission system as a whole.

Nasal airflow simulations suggest convergent adaptation in Neanderthals and modern humans.

PubMed

de Azevedo, S; González, M F; Cintas, C; Ramallo, V; Quinto-Sánchez, M; Márquez, F; Hünemeier, T; Paschetta, C; Ruderman, A; Navarro, P; Pazos, B A; Silva de Cerqueira, C C; Velan, O; Ramírez-Rozzi, F; Calvo, N; Castro, H G; Paz, R R; González-José, R

2017-11-21

Both modern humans (MHs) and Neanderthals successfully settled across western Eurasian cold-climate landscapes. Among the many adaptations considered as essential to survival in such landscapes, changes in the nasal morphology and/or function aimed to humidify and warm the air before it reaches the lungs are of key importance. Unfortunately, the lack of soft-tissue evidence in the fossil record turns difficult any comparative study of respiratory performance. Here, we reconstruct the internal nasal cavity of a Neanderthal plus two representatives of climatically divergent MH populations (southwestern Europeans and northeastern Asians). The reconstruction includes mucosa distribution enabling a realistic simulation of the breathing cycle in different climatic conditions via computational fluid dynamics. Striking across-specimens differences in fluid residence times affecting humidification and warming performance at the anterior tract were found under cold/dry climate simulations. Specifically, the Asian model achieves a rapid air conditioning, followed by the Neanderthals, whereas the European model attains a proper conditioning only around the medium-posterior tract. In addition, quantitative-genetic evolutionary analyses of nasal morphology provided signals of stabilizing selection for MH populations, with the removal of Arctic populations turning covariation patterns compatible with evolution by genetic drift. Both results indicate that, departing from important craniofacial differences existing among Neanderthals and MHs, an advantageous species-specific respiratory performance in cold climates may have occurred in both species. Fluid dynamics and evolutionary biology independently provided evidence of nasal evolution, suggesting that adaptive explanations regarding complex functional phenotypes require interdisciplinary approaches aimed to quantify both performance and evolutionary signals on covariation patterns.

Emergent dynamic structures and statistical law in spherical lattice gas automata.

PubMed

Yao, Zhenwei

2017-12-01

Various lattice gas automata have been proposed in the past decades to simulate physics and address a host of problems on collective dynamics arising in diverse fields. In this work, we employ the lattice gas model defined on the sphere to investigate the curvature-driven dynamic structures and analyze the statistical behaviors in equilibrium. Under the simple propagation and collision rules, we show that the uniform collective movement of the particles on the sphere is geometrically frustrated, leading to several nonequilibrium dynamic structures not found in the planar lattice, such as the emergent bubble and vortex structures. With the accumulation of the collision effect, the system ultimately reaches equilibrium in the sense that the distribution of the coarse-grained speed approaches the two-dimensional Maxwell-Boltzmann distribution despite the population fluctuations in the coarse-grained cells. The emergent regularity in the statistical behavior of the system is rationalized by mapping our system to a generalized random walk model. This work demonstrates the capability of the spherical lattice gas automaton in revealing the lattice-guided dynamic structures and simulating the equilibrium physics. It suggests the promising possibility of using lattice gas automata defined on various curved surfaces to explore geometrically driven nonequilibrium physics.

Emergent dynamic structures and statistical law in spherical lattice gas automata

NASA Astrophysics Data System (ADS)

Yao, Zhenwei

2017-12-01

Various lattice gas automata have been proposed in the past decades to simulate physics and address a host of problems on collective dynamics arising in diverse fields. In this work, we employ the lattice gas model defined on the sphere to investigate the curvature-driven dynamic structures and analyze the statistical behaviors in equilibrium. Under the simple propagation and collision rules, we show that the uniform collective movement of the particles on the sphere is geometrically frustrated, leading to several nonequilibrium dynamic structures not found in the planar lattice, such as the emergent bubble and vortex structures. With the accumulation of the collision effect, the system ultimately reaches equilibrium in the sense that the distribution of the coarse-grained speed approaches the two-dimensional Maxwell-Boltzmann distribution despite the population fluctuations in the coarse-grained cells. The emergent regularity in the statistical behavior of the system is rationalized by mapping our system to a generalized random walk model. This work demonstrates the capability of the spherical lattice gas automaton in revealing the lattice-guided dynamic structures and simulating the equilibrium physics. It suggests the promising possibility of using lattice gas automata defined on various curved surfaces to explore geometrically driven nonequilibrium physics.

Evaluation of unrestrained replica-exchange simulations using dynamic walkers in temperature space for protein structure refinement.

PubMed

Olson, Mark A; Lee, Michael S

2014-01-01

A central problem of computational structural biology is the refinement of modeled protein structures taken from either comparative modeling or knowledge-based methods. Simulations are commonly used to achieve higher resolution of the structures at the all-atom level, yet methodologies that consistently yield accurate results remain elusive. In this work, we provide an assessment of an adaptive temperature-based replica exchange simulation method where the temperature clients dynamically walk in temperature space to enrich their population and exchanges near steep energetic barriers. This approach is compared to earlier work of applying the conventional method of static temperature clients to refine a dataset of conformational decoys. Our results show that, while an adaptive method has many theoretical advantages over a static distribution of client temperatures, only limited improvement was gained from this strategy in excursions of the downhill refinement regime leading to an increase in the fraction of native contacts. To illustrate the sampling differences between the two simulation methods, energy landscapes are presented along with their temperature client profiles.

Budget impact analysis of switching to digital mammography in a population-based breast cancer screening program: a discrete event simulation model.

PubMed

Comas, Mercè; Arrospide, Arantzazu; Mar, Javier; Sala, Maria; Vilaprinyó, Ester; Hernández, Cristina; Cots, Francesc; Martínez, Juan; Castells, Xavier

2014-01-01

To assess the budgetary impact of switching from screen-film mammography to full-field digital mammography in a population-based breast cancer screening program. A discrete-event simulation model was built to reproduce the breast cancer screening process (biennial mammographic screening of women aged 50 to 69 years) combined with the natural history of breast cancer. The simulation started with 100,000 women and, during a 20-year simulation horizon, new women were dynamically entered according to the aging of the Spanish population. Data on screening were obtained from Spanish breast cancer screening programs. Data on the natural history of breast cancer were based on US data adapted to our population. A budget impact analysis comparing digital with screen-film screening mammography was performed in a sample of 2,000 simulation runs. A sensitivity analysis was performed for crucial screening-related parameters. Distinct scenarios for recall and detection rates were compared. Statistically significant savings were found for overall costs, treatment costs and the costs of additional tests in the long term. The overall cost saving was 1,115,857€ (95%CI from 932,147 to 1,299,567) in the 10th year and 2,866,124€ (95%CI from 2,492,610 to 3,239,638) in the 20th year, representing 4.5% and 8.1% of the overall cost associated with screen-film mammography. The sensitivity analysis showed net savings in the long term. Switching to digital mammography in a population-based breast cancer screening program saves long-term budget expense, in addition to providing technical advantages. Our results were consistent across distinct scenarios representing the different results obtained in European breast cancer screening programs.

Budget Impact Analysis of Switching to Digital Mammography in a Population-Based Breast Cancer Screening Program: A Discrete Event Simulation Model

PubMed Central

Comas, Mercè; Arrospide, Arantzazu; Mar, Javier; Sala, Maria; Vilaprinyó, Ester; Hernández, Cristina; Cots, Francesc; Martínez, Juan; Castells, Xavier

2014-01-01

Objective To assess the budgetary impact of switching from screen-film mammography to full-field digital mammography in a population-based breast cancer screening program. Methods A discrete-event simulation model was built to reproduce the breast cancer screening process (biennial mammographic screening of women aged 50 to 69 years) combined with the natural history of breast cancer. The simulation started with 100,000 women and, during a 20-year simulation horizon, new women were dynamically entered according to the aging of the Spanish population. Data on screening were obtained from Spanish breast cancer screening programs. Data on the natural history of breast cancer were based on US data adapted to our population. A budget impact analysis comparing digital with screen-film screening mammography was performed in a sample of 2,000 simulation runs. A sensitivity analysis was performed for crucial screening-related parameters. Distinct scenarios for recall and detection rates were compared. Results Statistically significant savings were found for overall costs, treatment costs and the costs of additional tests in the long term. The overall cost saving was 1,115,857€ (95%CI from 932,147 to 1,299,567) in the 10th year and 2,866,124€ (95%CI from 2,492,610 to 3,239,638) in the 20th year, representing 4.5% and 8.1% of the overall cost associated with screen-film mammography. The sensitivity analysis showed net savings in the long term. Conclusions Switching to digital mammography in a population-based breast cancer screening program saves long-term budget expense, in addition to providing technical advantages. Our results were consistent across distinct scenarios representing the different results obtained in European breast cancer screening programs. PMID:24832200

Predator-prey model for the self-organization of stochastic oscillators in dual populations

NASA Astrophysics Data System (ADS)

Moradi, Sara; Anderson, Johan; Gürcan, Ozgur D.

A predator-prey model of dual populations with stochastic oscillators is presented. A linear cross-coupling between the two populations is introduced that follows the coupling between the motions of a Wilberforce pendulum in two dimensions: one in the longitudinal and the other in torsional plain. Within each population a Kuramoto type competition between the phases is assumed. Thus, the synchronization state of the whole system is controlled by these two types of competitions. The results of the numerical simulations show that by adding the linear cross-coupling interactions predator-prey oscillations between the two populations appear which results in self-regulation of the system by a transfer of synchrony between the two populations. The model represents several important features of the dynamical interplay between the drift wave and zonal flow turbulence in magnetically confined plasmas, and a novel interpretation of the coupled dynamics of drift wave-zonal flow turbulence using synchronization of stochastic oscillator is discussed. Sara Moradi has benefited from a mobility grant funded by the Belgian Federal Science Policy Office and the MSCA of the European Commission (FP7-PEOPLE-COFUND-2008 nº 246540).

Global dynamics of avian influenza epidemic models with psychological effect.

PubMed

Liu, Sanhong; Pang, Liuyong; Ruan, Shigui; Zhang, Xinan

2015-01-01

Cross-sectional surveys conducted in Thailand and China after the outbreaks of the avian influenza A H5N1 and H7N9 viruses show a high degree of awareness of human avian influenza in both urban and rural populations, a higher level of proper hygienic practice among urban residents, and in particular a dramatically reduced number of visits to live markets in urban population after the influenza A H7N9 outbreak in China in 2013. In this paper, taking into account the psychological effect toward avian influenza in the human population, a bird-to-human transmission model in which the avian population exhibits saturation effect is constructed. The dynamical behavior of the model is studied by using the basic reproduction number. The results demonstrate that the saturation effect within avian population and the psychological effect in human population cannot change the stability of equilibria but can affect the number of infected humans if the disease is prevalent. Numerical simulations are given to support the theoretical results and sensitivity analyses of the basic reproduction number in terms of model parameters that are performed to seek for effective control measures for avian influenza.

Detecting black bear source–sink dynamics using individual-based genetic graphs

PubMed Central

Draheim, Hope M.; Moore, Jennifer A.; Etter, Dwayne; Winterstein, Scott R.; Scribner, Kim T.

2016-01-01

Source–sink dynamics affects population connectivity, spatial genetic structure and population viability for many species. We introduce a novel approach that uses individual-based genetic graphs to identify source–sink areas within a continuously distributed population of black bears (Ursus americanus) in the northern lower peninsula (NLP) of Michigan, USA. Black bear harvest samples (n = 569, from 2002, 2006 and 2010) were genotyped at 12 microsatellite loci and locations were compared across years to identify areas of consistent occupancy over time. We compared graph metrics estimated for a genetic model with metrics from 10 ecological models to identify ecological factors that were associated with sources and sinks. We identified 62 source nodes, 16 of which represent important source areas (net flux > 0.7) and 79 sink nodes. Source strength was significantly correlated with bear local harvest density (a proxy for bear density) and habitat suitability. Additionally, resampling simulations showed our approach is robust to potential sampling bias from uneven sample dispersion. Findings demonstrate black bears in the NLP exhibit asymmetric gene flow, and individual-based genetic graphs can characterize source–sink dynamics in continuously distributed species in the absence of discrete habitat patches. Our findings warrant consideration of undetected source–sink dynamics and their implications on harvest management of game species. PMID:27440668

Theory of time-averaged neutral dynamics with environmental stochasticity

NASA Astrophysics Data System (ADS)

Danino, Matan; Shnerb, Nadav M.

2018-04-01

Competition is the main driver of population dynamics, which shapes the genetic composition of populations and the assembly of ecological communities. Neutral models assume that all the individuals are equivalent and that the dynamics is governed by demographic (shot) noise, with a steady state species abundance distribution (SAD) that reflects a mutation-extinction equilibrium. Recently, many empirical and theoretical studies emphasized the importance of environmental variations that affect coherently the relative fitness of entire populations. Here we consider two generic time-averaged neutral models; in both the relative fitness of each species fluctuates independently in time but its mean is zero. The first (model A) describes a system with local competition and linear fitness dependence of the birth-death rates, while in the second (model B) the competition is global and the fitness dependence is nonlinear. Due to this nonlinearity, model B admits a noise-induced stabilization mechanism that facilitates the invasion of new mutants. A self-consistent mean-field approach is used to reduce the multispecies problem to two-species dynamics, and the large-N asymptotics of the emerging set of Fokker-Planck equations is presented and solved. Our analytic expressions are shown to fit the SADs obtained from extensive Monte Carlo simulations and from numerical solutions of the corresponding master equations.

Detecting black bear source-sink dynamics using individual-based genetic graphs.

PubMed

Draheim, Hope M; Moore, Jennifer A; Etter, Dwayne; Winterstein, Scott R; Scribner, Kim T

2016-07-27

Source-sink dynamics affects population connectivity, spatial genetic structure and population viability for many species. We introduce a novel approach that uses individual-based genetic graphs to identify source-sink areas within a continuously distributed population of black bears (Ursus americanus) in the northern lower peninsula (NLP) of Michigan, USA. Black bear harvest samples (n = 569, from 2002, 2006 and 2010) were genotyped at 12 microsatellite loci and locations were compared across years to identify areas of consistent occupancy over time. We compared graph metrics estimated for a genetic model with metrics from 10 ecological models to identify ecological factors that were associated with sources and sinks. We identified 62 source nodes, 16 of which represent important source areas (net flux > 0.7) and 79 sink nodes. Source strength was significantly correlated with bear local harvest density (a proxy for bear density) and habitat suitability. Additionally, resampling simulations showed our approach is robust to potential sampling bias from uneven sample dispersion. Findings demonstrate black bears in the NLP exhibit asymmetric gene flow, and individual-based genetic graphs can characterize source-sink dynamics in continuously distributed species in the absence of discrete habitat patches. Our findings warrant consideration of undetected source-sink dynamics and their implications on harvest management of game species. © 2016 The Author(s).

Dynamics of the double-crested cormorant population on Lake Ontario

USGS Publications Warehouse

Blackwell, Bradley F.; Stapanian, Martin A.; Weseloh, D.V. Chip

2002-01-01

After nearly 30 years of recolonization and expansion across North America, the double-crested cormorant (Phalacrocorax auritus) occupies the role of a perceived and, in some situations, realized threat to fish stocks and other resources. However, population data necessary to plan, defend, and implement management of this species are few. Our purpose was to gain insight into the relative contribution of various population parameters to the overall rate of population growth and identify data needs critical to improving our understanding of the dynamics of double-crested cormorant populations. We demonstrated the construction of a biologically reasonable representation of cormorant population growth on Lake Ontario (1979-2000) by referencing literature values for fertility, age at first breeding, and survival. These parameters were incorporated into a deterministic stage-classified matrix model. By calculating the elasticity of matrix elements (i.e., statgspecific fertility and survival), we found that cormorant population growth on Lake Ontario was most sensitive to survival of birds about to turn age 3 and older. Finally, we demonstrated how this information could be used to evaluate management scenarios and direct future research by simulating potential environmental effects on fertility and survival, as well as a 5-year egg-oiling program. We also demonstrated that survival of older birds exerts more effective population control than changes in fertility.

Development of an establishment scheme for a DGVM

NASA Astrophysics Data System (ADS)

Song, Xiang; Zeng, Xiaodong; Zhu, Jiawen; Shao, Pu

2016-07-01

Environmental changes are expected to shift the distribution and abundance of vegetation by determining seedling establishment and success. However, most current ecosystem models only focus on the impacts of abiotic factors on biogeophysics (e.g., global distribution, etc.), ignoring their roles in the population dynamics (e.g., seedling establishment rate, mortality rate, etc.) of ecological communities. Such neglect may lead to biases in ecosystem population dynamics (such as changes in population density for woody species in forest ecosystems) and characteristics. In the present study, a new establishment scheme for introducing soil water as a function rather than a threshold was developed and validated, using version 1.0 of the IAP-DGVM as a test bed. The results showed that soil water in the establishment scheme had a remarkable influence on forest transition zones. Compared with the original scheme, the new scheme significantly improved simulations of tree population density, especially in the peripheral areas of forests and transition zones. Consequently, biases in forest fractional coverage were reduced in approximately 78.8% of the global grid cells. The global simulated areas of tree, shrub, grass and bare soil performed better, where the relative biases were reduced from 34.3% to 4.8%, from 27.6% to 13.1%, from 55.2% to 9.2%, and from 37.6% to 3.6%, respectively. Furthermore, the new scheme had more reasonable dependencies of plant functional types (PFTs) on mean annual precipitation, and described the correct dominant PFTs in the tropical rainforest peripheral areas of the Amazon and central Africa.

Testing an online, dynamic consent portal for large population biobank research.

PubMed

Thiel, Daniel B; Platt, Jodyn; Platt, Tevah; King, Susan B; Fisher, Nicole; Shelton, Robert; Kardia, Sharon L R

2015-01-01

Michigan's BioTrust for Health, a public health research biobank comprised of residual dried bloodspot (DBS) cards from newborn screening contains over 4 million samples collected without written consent. Participant-centric initiatives are IT tools that hold great promise to address the consent challenges in biobank research. Working with Private Access Inc., a pioneer in patient-centric web solutions, we created and pilot tested a dynamic informed consent simulation, paired with an educational website, focusing on consent for research utilizing DBSs in Michigan's BioTrust for Health. Out of 187 pilot testers recruited in 2 groups, 137 completed the consent simulation and exit survey. Over 50% indicated their willingness to set up an account if the simulation went live and to recommend it to others. Participants raised concerns about the process of identity verification and appeared to have little experience with sharing health information online. Applying online, dynamic approaches to address the consent challenges raised by biobanks with legacy sample collections should be explored, given the positive reaction to our pilot test and the strong preference for active consent. Balancing security and privacy with accessibility and ease of use will continue to be a challenge. © 2014 S. Karger AG, Basel.

Pattern does not equal process: what does patch occupancy really tell us about metapopulation dynamics?

PubMed

Clinchy, Michael; Haydon, Daniel T; Smith, Andrew T

2002-04-01

Patch occupancy surveys are commonly used to parameterize metapopulation models. If isolation predicts patch occupancy, this is generally attributed to a balance between distance-dependent recolonization and spatially independent extinctions. We investigated whether similar patterns could also be generated by a process of spatially correlated extinctions following a unique colonization event (analogous to nonequilibrium processes in island biogeography). We simulated effects of spatially correlated extinctions on patterns of patch occupancy among pikas (Ochotona princeps) at Bodie, California, using randomly located extinction disks to represent the likely effects of predation. Our simulations produced similar patterns to those cited as evidence of balanced metapopulation dynamics. Simulations using a variety of disk sizes and patch configurations confirmed that our results are potentially applicable to a broad range of species and sites. Analyses of the observed patterns of patch occupancy at Bodie revealed little evidence of rescue effects and strong evidence that most recolonizations are ephemeral in nature. Persistence will be overestimated if static or declining patterns of patch occupancy are mistakenly attributed to dynamically stable metapopulation processes. Consequently, simple patch occupancy surveys should not be considered as substitutes for detailed experimental tests of hypothesized population processes, particularly when conservation concerns are involved.

Modelling the effect of an alternative host population on the spread of citrus Huanglongbing

NASA Astrophysics Data System (ADS)

d'A. Vilamiu, Raphael G.; Ternes, Sonia; Laranjeira, Francisco F.; de C. Santos, Tâmara T.

2013-10-01

The objective of this work was to model the spread of citrus Huanglongbing (HLB) considering the presence of a population of alternative hosts (Murraya paniculata). We developed a compartmental deterministic mathematical model for representing the dynamics of HLB disease in a citrus orchard, including delays in the latency and incubation phases of the disease in the plants and a delay period on the nymphal stage of Diaphorina citri, the insect vector of HLB in Brazil. The results of numerical simulations indicate that alternative hosts should not play a crucial role on HLB dynamics considering a typical scenario for the Recôncavo Baiano region in Brazil . Also, the current policy of removing symptomatic plants every three months should not be expected to significantly hinder HLB spread.

[Mathematical models and epidemiological analysis].

PubMed

Gerasimov, A N

2010-01-01

The limited use of mathematical simulation in epidemiology is due not only to the difficulty of monitoring the epidemic process and identifying its parameters but also to the application of oversimplified models. It is shown that realistic reproduction of actual morbidity dynamics requires taking into account heterogeneity and finiteness of the population and seasonal character of pathogen transmission mechanism.

Simulations of population dynamics of hemlock woolly adelgid and potential impact of biological control agents

Treesearch

Joseph S. Elkinton; Robert T. Trotter; Ann F. Paradis

2011-01-01

The hemlock woolly adelgid (Adelges tsugae) is a small invasive Hemipteran herbivore that threatens the continued presence and abundance of hemlock in eastern North America. Efforts to control the adelgid have focused on the introduction of classical biological control agents. These biological controls include six different species of predatory...

The utility of covariances: a response to Ranta et al

Treesearch

J.E. Houlahan; K. Cottenie; G.S. Cumming; D.J. Currie; C.S. Findlay; U. Gaedke; P. Legendre; J.J. Magnuson; B.H. McArdle; R.D. Stevens; I.P. Woiwod; S.M. Wondzell

2008-01-01

In an earlier publication (Houlahan et al. 2007) we reviewed trends in population covariances within communities across a range of long-term empirical data sets. We used these results to argue that compensatory dynamics are rare in natural communities. Ranta et al. (2008) explored interspecific interactions in a simulated environment and showed that 'negative...

Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago

PubMed Central

Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E.

2018-01-01

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns. PMID:29657753

Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago.

PubMed

Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E; Pellissier, Loïc

2018-03-01

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns.

Bipartite graphs as models of population structures in evolutionary multiplayer games.

PubMed

Peña, Jorge; Rochat, Yannick

2012-01-01

By combining evolutionary game theory and graph theory, "games on graphs" study the evolutionary dynamics of frequency-dependent selection in population structures modeled as geographical or social networks. Networks are usually represented by means of unipartite graphs, and social interactions by two-person games such as the famous prisoner's dilemma. Unipartite graphs have also been used for modeling interactions going beyond pairwise interactions. In this paper, we argue that bipartite graphs are a better alternative to unipartite graphs for describing population structures in evolutionary multiplayer games. To illustrate this point, we make use of bipartite graphs to investigate, by means of computer simulations, the evolution of cooperation under the conventional and the distributed N-person prisoner's dilemma. We show that several implicit assumptions arising from the standard approach based on unipartite graphs (such as the definition of replacement neighborhoods, the intertwining of individual and group diversity, and the large overlap of interaction neighborhoods) can have a large impact on the resulting evolutionary dynamics. Our work provides a clear example of the importance of construction procedures in games on graphs, of the suitability of bigraphs and hypergraphs for computational modeling, and of the importance of concepts from social network analysis such as centrality, centralization and bipartite clustering for the understanding of dynamical processes occurring on networked population structures.

A quantitative evaluation of a qualitative risk assessment framework: Examining the assumptions and predictions of the Productivity Susceptibility Analysis (PSA)

PubMed Central

2018-01-01

Qualitative risk assessment frameworks, such as the Productivity Susceptibility Analysis (PSA), have been developed to rapidly evaluate the risks of fishing to marine populations and prioritize management and research among species. Despite being applied to over 1,000 fish populations, and an ongoing debate about the most appropriate method to convert biological and fishery characteristics into an overall measure of risk, the assumptions and predictive capacity of these approaches have not been evaluated. Several interpretations of the PSA were mapped to a conventional age-structured fisheries dynamics model to evaluate the performance of the approach under a range of assumptions regarding exploitation rates and measures of biological risk. The results demonstrate that the underlying assumptions of these qualitative risk-based approaches are inappropriate, and the expected performance is poor for a wide range of conditions. The information required to score a fishery using a PSA-type approach is comparable to that required to populate an operating model and evaluating the population dynamics within a simulation framework. In addition to providing a more credible characterization of complex system dynamics, the operating model approach is transparent, reproducible and can evaluate alternative management strategies over a range of plausible hypotheses for the system. PMID:29856869